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Pajic, Slobodan. "Power System State Estimation and Contingency Constrained Optimal Power Flow - A Numerically Robust Implementation." Digital WPI, 2007. https://digitalcommons.wpi.edu/etd-dissertations/240.
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The research conducted in this dissertation is divided into two main parts. The first part provides further improvements in power system state estimation and the second part implements Contingency Constrained Optimal Power Flow (CCOPF) in a stochastic multiple contingency framework. As a real-time application in modern power systems, the existing Newton-QR state estimation algorithms are too slow and too fragile numerically. This dissertation presents a new and more robust method that is based on trust region techniques. A faster method was found among the class of Krylov subspace iterative methods, a robust implementation of the conjugate gradient method, called the LSQR method. Both algorithms have been tested against the widely used Newton-QR state estimator on the standard IEEE test networks. The trust region method-based state estimator was found to be very reliable under severe conditions (bad data, topological and parameter errors). This enhanced reliability justifies the additional time and computational effort required for its execution. The numerical simulations indicate that the iterative Newton-LSQR method is competitive in robustness with classical direct Newton-QR. The gain in computational efficiency has not come at the cost of solution reliability. The second part of the dissertation combines Sequential Quadratic Programming (SQP)-based CCOPF with Monte Carlo importance sampling to estimate the operating cost of multiple contingencies. We also developed an LP-based formulation for the CCOPF that can efficiently calculate Locational Marginal Prices (LMPs) under multiple contingencies. Based on Monte Carlo importance sampling idea, the proposed algorithm can stochastically assess the impact of multiple contingencies on LMP-congestion prices.
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Wang, Xing. "Market-based transmission congestion management using extended optimal power flow techniques." Thesis, Brunel University, 2001. http://bura.brunel.ac.uk/handle/2438/4804.
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This thesis describes research into the problem of transmission congestion management. The causes, remedies, pricing methods, and other issues of transmission congestion are briefly reviewed. This research is to develop market-based approaches to cope with transmission congestion in real-time, short-run and long-run efficiently, economically and fairly. Extended OPF techniques have been playing key roles in many aspects of electricity markets. The Primal-Dual Interior Point Linear Programming and Quadratic Programming are applied to solve various optimization problems of congestion management proposed in the thesis. A coordinated real-time optimal dispatch method for unbundled electricity markets is proposed for system balancing and congestion management. With this method, almost all the possible resources in different electricity markets, including operating reserves and bilateral transactions, can be used to eliminate the real-time congestion according to their bids into the balancing market. Spot pricing theory is applied to real-time congestion pricing. Under the same framework, a Lagrangian Relaxation based region decomposition OPF algorithm is presented to deal with the problems of real-time active power congestion management across multiple regions. The inter/intra-regional congestion can be relieved without exchanging any information between regional ISOs but the Lagrangian Multipliers. In day-ahead spot market, a new optimal dispatch method is proposed for congestion and price risk management, particularly for bilateral transaction curtailment. Individual revenue adequacy constraints, which include payments from financial instruments, are involved in the original dispatch problem. An iterative procedure is applied to solve this special optimization problem with both primal and dual variables involved in its constraints. An optimal Financial Transmission Rights (FTR) auction model is presented as an approach to the long-term congestion management. Two types of series F ACTS devices are incorporated into this auction problem using the Power Injection Model to maximize the auction revenue. Some new treatment has been done on TCSC's operating limits to keep the auction problem linear.
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Nair, Nirmal-Kumar. "Incorporating voltage security into the planning, operation and monitoring of restructured electric energy markets." Texas A&M University, 2004. http://hdl.handle.net/1969.1/3199.
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As open access market principles are applied to power systems, significant changes
are happening in their planning, operation and control. In the emerging marketplace,
systems are operating under higher loading conditions as markets focus greater attention
to operating costs than stability and security margins. Since operating stability is a basic
requirement for any power system, there is need for newer tools to ensure stability and
security margins being strictly enforced in the competitive marketplace. This dissertation
investigates issues associated with incorporating voltage security into the unbundled
operating environment of electricity markets. It includes addressing voltage security in
the monitoring, operational and planning horizons of restructured power system.
This dissertation presents a new decomposition procedure to estimate voltage
security usage by transactions. The procedure follows physical law and uses an index
that can be monitored knowing the state of the system. The expression derived is based
on composite market coordination models that have both PoolCo and OpCo transactions,
in a shared stressed transmission grid. Our procedure is able to equitably distinguish the
impacts of individual transactions on voltage stability, at load buses, in a simple and fast
manner.
This dissertation formulates a new voltage stability constrained optimal power flow
(VSCOPF) using a simple voltage security index. In modern planning, composite power
system reliability analysis that encompasses both adequacy and security issues is being
developed. We have illustrated the applicability of our VSCOPF into composite
reliability analysis.
This dissertation also delves into the various applications of voltage security index.
Increasingly, FACT devices are being used in restructured markets to mitigate a variety
of operational problems. Their control effects on voltage security would be
demonstrated using our VSCOPF procedure. Further, this dissertation investigates the
application of steady state voltage stability index to detect potential dynamic voltage
collapse.
Finally, this dissertation examines developments in representation, standardization,
communication and exchange of power system data. Power system data is the key input
to all analytical engines for system operation, monitoring and control. Data exchange
and dissemination could impact voltage security evaluation and therefore needs to be
critically examined.
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Kreikebaum, Frank Karl. "Control of transmission system power flows." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50392.
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Power flow (PF) control can increase the utilization of the transmission system and connect lower cost generation with load. While PF controllers have demonstrated the ability to realize dynamic PF control for more than 25 years, PF control has been sparsely implemented.
This research re-examines PF control in light of the recent development of fractionally-rated PF controllers and the incremental power flow (IPF) control concept. IPF control is the transfer of an incremental quantity of power from a specified source bus to specified destination bus along a specified path without influencing power flows on circuits outside of the path.
The objectives of the research are to develop power system operation and planning methods compatible with IPF control, test the technical viability of IPF control, develop transmission planning frameworks leveraging PF and IPF control, develop power system operation and planning tools compatible with PF control, and quantify the impacts of PF and IPF control on multi-decade transmission planning.
The results suggest that planning and operation of the power system are feasible with PF controllers and may lead to cost savings. The proposed planning frameworks may incent transmission investment and be compatible with the existing transmission planning process. If the results of the planning tool demonstration scale to the national level, the annual savings in electricity expenditures would be $13 billion per year (2010$). The proposed incremental packetized energy concept may facilitate a reduction in the environmental impact of energy consumption and lead to additional cost savings.
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Nasri, Amin. "On the Dynamics and Statics of Power System Operation : Optimal Utilization of FACTS Devicesand Management of Wind Power Uncertainty." Doctoral thesis, KTH, Elektriska energisystem, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-154576.
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Nowadays, power systems are dealing with some new challenges raisedby the major changes that have been taken place since 80’s, e.g., deregu-lation in electricity markets, significant increase of electricity demands andmore recently large-scale integration of renewable energy resources such aswind power. Therefore, system operators must make some adjustments toaccommodate these changes into the future of power systems.One of the main challenges is maintaining the system stability since theextra stress caused by the above changes reduces the stability margin, andmay lead to rise of many undesirable phenomena. The other important chal-lenge is to cope with uncertainty and variability of renewable energy sourceswhich make power systems to become more stochastic in nature, and lesscontrollable.Flexible AC Transmission Systems (FACTS) have emerged as a solutionto help power systems with these new challenges. This thesis aims to ap-propriately utilize such devices in order to increase the transmission capacityand flexibility, improve the dynamic behavior of power systems and integratemore renewable energy into the system. To this end, the most appropriatelocations and settings of these controllable devices need to be determined.This thesis mainly looks at (i) rotor angle stability, i.e., small signal andtransient stability (ii) system operation under wind uncertainty. In the firstpart of this thesis, trajectory sensitivity analysis is used to determine themost suitable placement of FACTS devices for improving rotor angle sta-bility, while in the second part, optimal settings of such devices are foundto maximize the level of wind power integration. As a general conclusion,it was demonstrated that FACTS devices, installed in proper locations andtuned appropriately, are effective means to enhance the system stability andto handle wind uncertainty.The last objective of this thesis work is to propose an efficient solutionapproach based on Benders’ decomposition to solve a network-constrained acunit commitment problem in a wind-integrated power system. The numericalresults show validity, accuracy and efficiency of the proposed approach.The Doctoral Degrees issued upon completion of the programme are issued by Comillas Pontifical University, Delft University of Technology and KTH Royal Institute of Technology. The invested degrees are official in Spain, the Netherlands and Sweden, respectively.QC 20141028
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Gutierrez, Lagos Luis Daniel. "Advanced voltage control for energy conservation in distribution networks." Thesis, University of Manchester, 2018. https://www.research.manchester.ac.uk/portal/en/theses/advanced-voltage-control-for-energy-conservation-in-distribution-networks(2718dcf1-f5db-45df-84e2-4890956ba8b1).html.
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The increasing awareness on the effect of carbon emissions in our planet has led to several countries to adopt targets for their reduction. One way of contributing to this aim is to use and distribute electricity more efficiently. In this context, Conservation Voltage Reduction (CVR), a well-known technique that takes advantage of the positive correlation between voltage and demand to reduce energy consumption, is gaining renewed interest. This technique saves energy by only reducing customer voltages, without relying on customer actions and, therefore, can be controlled by the Distribution Network Operator (DNO). CVR not only brings benefits to the electricity system by reducing generation requirements (fewer fossil fuel burning and carbon emissions), but also to customers, as energy bill reductions. The extent to which CVR can bring benefits mainly depends on the customers load composition and their voltages. While the former dictates the voltage-demand correlation, the latter constraints the voltage reduction that can be applied without violating statutory limits. Although CVR has been studied for many years, most of the studies neglect the time-varying voltage-demand characteristic of loads and/or do not assess end customer voltages. While these simplifications could be used to estimate CVR benefits for fixed and limited voltage reductions, realistic load and network models are needed to assess the performance of active CVR schemes, where voltages are actively managed to be close to the minimum limit. Moreover, distribution networks have been traditionally designed with limited monitoring and controllability. Therefore, CVR has been typically implemented by adopting conservative voltage reductions from primary substations, for both American and European-style networks. However, as new infrastructure is deployed in European-style LV networks (focus of this work), such as monitoring and on-load tap changers (OLTCs), the opportunity arises to actively manage voltages closer to end customer (unlocking further energy savings). Although these technologies have shown to effectively control voltages in LV networks, their potential for CVR has not been assessed before. Additionally, most CVR studies were performed in a context where distributed generation (DG) was not common. However, this has changed in many countries, with residential photovoltaic (PV) systems becoming popular. As this is likely to continue, the interactions of residential PV and CVR need to be studied. This thesis contributes to address the aforementioned literature gaps by: (i) proposing a simulation framework to characterise the time-varying voltage-demand correlation of individual end customers; (ii) developing a process to model real distribution networks (MV and LV) from DNO data; (iii) adopting a Monte Carlo-based quantification process to cater for the uncertainties related to individual customer demand; (iv) assessing the CVR benefits that can be unlocked with new LV infrastructure and different PV conditions. To accomplish (iv), first, a simple yet effective rule-based scheme is proposed to actively control voltages in OLTC-enabled LV networks without PV and using limited monitoring. It is demonstrated that by controlling voltages closer to customers, annual energy savings can increase significantly, compared to primary substation voltage reductions. Also, to understand the effect of PV on CVR, a centralized, three-phase AC OPF-based CVR scheme is proposed. This control, using monitoring, OLTCs and capacitors across MV and LV networks, actively manages voltages to minimize energy consumption in high PV penetration scenarios whilst considering MV-LV constraints. Results demonstrate that without CVR, PV systems lead to higher energy imports for customers without PV, due to higher voltages. Conversely, the OPF-based CVR scheme can effectively manage voltages throughout the day, minimising energy imports for all customers. Moreover, if OLTCs at secondary substations are available (and managed in coordination with the primary substation OLTC), these tend to regulate customer voltages close to the minimum statutory limit (lower tap positions), while the primary OLTC delivers higher voltages to the MV network to also reduce MV energy losses.
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Alnaser, Sahban Wa'el Saeed. "Control of distributed generation and storage : operation and planning perspectives." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/control-of-distributed-generation-and-storage-operation-and-planning-perspectives(a937e071-4e6b-4a07-a196-031c3b23655f).html.
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Transition towards low-carbon energy systems requires an increase in the volume of renewable Distributed Generation (DG), particularly wind and photovoltaic, connected to distribution networks. To facilitate the connection of renewable DG without the need for expensive and time-consuming network reinforcements, distribution networks should move from passive to active methods of operation, whereby technical network constraints are actively managed in real time. This requires the deployment of control solutions that manage network constraints and, crucially, ensure adequate levels of energy curtailment from DG plants by using other controllable elements to solve network issues rather than resorting to generation curtailment only. This thesis proposes a deterministic distribution Network Management System (NMS) to facilitate the connections of renewable DG plants (specifically wind) by actively managing network voltages and congestion in real time through the optimal control of on-load tap changers (OLTCs), DG power factor and, then, generation curtailment as a last resort. The set points for the controllable elements are found using an AC Optimal Power Flow (OPF). The proposed NMS considers the realistic modelling of control by adopting one-minute resolution time-series data. To decrease the volumes of control actions from DG plants and OLTCs, the proposed approach departs from multi-second control cycles to multi-minute control cycles. To achieve this, the decision-making algorithm is further improved into a risk-based one to handle the uncertainties in wind power throughout the multi-minute control cycles. The performance of the deterministic and the risk-based NMS are compared using a 33 kV UK distribution network for different control cycles. The results show that the risk-based approach can effectively manage network constraints better than the deterministic approach, particularly for multi-minute control cycles, reducing also the number of control actions but at the expense of higher levels of curtailment. This thesis also proposes energy storage sizing framework to find the minimum power rating and energy capacity of multiple storage facilities to reduce curtailment from DG plants. A two-stage iterative process is adopted in this framework. The first stage uses a multi-period AC OPF across the studied horizon to obtain initial storage sizes considering hourly wind and load profiles. The second stage adopts a high granularity minute-by-minute control driven by a mono-period bi-level AC OPF to tune the first-stage storage sizes according to the actual curtailment. The application of the proposed planning framework to a 33 kV UK distribution network demonstrates the importance of embedding real-time control aspects into the planning framework so as to accurately size storage facilities. By using reactive power capabilities of storage facilities it is possible to reduce storage sizes. The combined active management of OLTCs and power factor of DG plants resulted in the most significant benefits in terms of the required storage sizes.
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Salamat, Sharif Saied. "Optimal reactive power flow problem." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0013/NQ38355.pdf.
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Zhang, Shouming. "Security optimised optimal power flow." Thesis, Brunel University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320858.
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Tao, Ye. "Optimal power flow via quadratic modeling." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/45766.
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Optimal power flow (OPF) is the choice tool for determining the optimal operating status of the power system by managing controllable devices. The importance of the OPF approach has increased due to increasing energy prices and availability of more control devices. Existing OPF approaches exhibit shortcomings. Current OPF algorithms can be classified into (a) nonlinear programming, (b) intelligent search methods, and (c) sequential algorithms. Nonlinear programming algorithms focus on the solution of the Kuhn-Tucker conditions; they require a starting feasible solution and the model includes all constraints; these characteristics limit the robustness and efficiency of these methods. Intelligent search methods are first-order methods and are totally inefficient for large-scale systems. Traditional sequential algorithms require a starting feasible solution, a requirement that limits their robustness. Present implementations of sequential algorithms use traditional modeling that result in inefficient algorithms.
The research described in this thesis has overcome the shortcomings by developing a robust and highly efficient algorithm. Robustness is defined as the ability to provide a solution for any system; the proposed approach achieves robustness by operating on suboptimal points and moving toward feasible, it stops at a suboptimal solution if an optimum does not exist. Efficiency is achieved by (a) converting the nonlinear OPF problem to a quadratic problem (b) and limiting the size of the model; the quadratic model enables fast convergence and the algorithm that identifies the active constraints, limits the size of the model by only including the active constraints.
A concise description of the method is as follows: The proposed method starts from an arbitrary state which may be infeasible; model equations and system constraints are satisfied by introducing artificial mismatch variables at each bus. Mathematically this is an optimal but infeasible point. At each iteration, the artificial mismatches are reduced while the solution point maintains optimality. When mismatches reach zero, the solution becomes feasible and the optimum has been found; otherwise, the mismatch residuals are converted to load shedding and the algorithm provides a suboptimal but feasible solution. Therefore, the algorithm operates on infeasible but optimal points and moves towards feasibility.
The proposed algorithm maximizes efficiency with two innovations: (a) quadratization that converts the nonlinear model to quadratic with excellent convergence properties and (b) minimization of model size by identifying active constraints, which are the only constraints included in the model. Finally sparsity technique is utilized that provide the best computational efficiency for large systems.
This dissertation work demonstrates the proposed OPF algorithm using various systems up to three hundred buses and compares it with several well-known OPF software packages. The results show that the proposed algorithm converges fast and its runtime is competitive.
Furthermore, the proposed method is extended to a three-phase OPF (TOPF) algorithm for unbalanced networks using the quadratized three-phase power system model. An example application of the TOPF is presented. Specifically, TOPF is utilized to address the problem of fault induced delayed voltage recovery (FIDVR) phenomena, which lead to unwanted relay operations, stalling of motors and load disruptions. This thesis presents a methodology that will optimally enhance the distribution system to mitigate/eliminate the onset of FIDVR. The time domain simulation method has been integrated with a TOPF model and a dynamic programming optimization algorithm to provide the optimal reinforcing strategy for the circuits.
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De, Almeida Katia Campos. "A general parametric optimal power flow." Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=28660.
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The objective of an Optimal Power Flow (OPF) algorithm is to find the steady-state operation point of a generation-transmission system which minimizes a pre-specified cost function and meets a set of operational and/or security constraints. OPF algorithms are among the tools present in many Energy Management Systems and their usefulness is increasingly being recognized by power utilities.This thesis presents an algorithm which uses the parameters existing in the OPF problem to find its solution. These parameters can be in the objective function or the equality or inequality constraints. This algorithm is applied to a parameterized OPF model built according to the following criteria: (i) when all parameters present in the model are relaxed from their given levels, a solution can be trivially found for this parameterized problem and (ii) when all parameters are returned to their original values, the parameterized model is equal to the original OPF. As the initially relaxed parameters are returned to their original values, they define a sequence of OPF problems which converge to the original one. The algorithm is designed to track the optimal solutions of these intermediate problems until the optimum of the original OPF. This tracking is made in a systematic manner. By using a binary search or a linear prediction method, the algorithm finds the maximum increment of the parameters which allow only one inequality to be fixed at its limit or to be released. The parameters are then adjusted to their new values, defining a new OPF problem with known optimal active feasible set. As a consequence, the optimal solution of this new problem can be easily found by solving the first order optimality conditions by Newton's method. In this way, the optimum is tracked from one active feasible set to the next until the parameters reach their original values.
The parameterization permits the solution of the OPF problem for a fixed and variable load using the same mechanism described in the previous paragraph. As a result of this systematic tracking, the method is robust and able to provide a very good insight about the behaviour of the OPF solutions. In addition, the main difficulties encountered in solving the OPF problem are easily visualized and, in particular, the approach permits the differentiation of the potential causes for the failure of the tracking process, including the identification of unsolvable cases. The sensitivities of the optimal solution as a function of the parameters are also by-products of the method; including the Bus Incremental Costs and the System Incremental Cost as functions of the loads. The approach is also flexible enough to permit the simulation of line contingencies and of Flexible AC Transmission Systems (FACTS devices). The algorithm developed was tested in numerous networks with different objective functions and initializations and the results demonstrated the potential of this technique.
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Gnanam, Gnanaprabhu. "Optimal power flow including voltage stability." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/mq25844.pdf.
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Huang, Shan. "On Accuracy of Conic Optimal Power Flow." Thesis, KTH, Elektriska energisystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-170829.
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Nowadays, with the increasing need for security and economic operation of power systems, the optimal power flow (OPF) has been an essential and predominant tool for economic and operation planning of power systems. A developed conic formulation for OPF has been proposed [1]. This model is bases on the line based flow equations and can be transformed into the form of second order cone programming (SOCP). The SOCP formulation of OPF problem can be solved using interior point methods (IPMs) [2]. In this thesis, a study on the performance of this developed conic formulation for OPF is carried out. Firstly, the accuracy of SOCP formulation is studied. A more accurate model is developed. The model is obtained by modifying the phase angle constrains of SOCP formulation. The modified model can be solved using sequential conic programming method. A comparison of results from these two models is made on different test systems. Secondly, the SOCP formulation is applied to both small and large test systems. The results of SOCP formulation is compared with the results from PSS/EOPF. The performance of SOCP formulation has shown the accurate and effectiveness for solving OPF problems.
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Kuan, Jenn-Huei Jeffrey. "Optimal power flow with price-elastic demand." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/10644.
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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (leaves 66-68).
by Jenn-Huei Jeffrey.
M.S.
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Cedeño-Maldonado, José R. "Differential evolution based optimal power flow algorithm /." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1486402288260595.
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Chao, Xingyong H. "Nondivergent and optimal power flow : a unified approach." Diss., Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/15499.
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Tiako, Remy. "Optimal design of power system stabilizer (PPS) using multi-power flow conditions." Master's thesis, University of Cape Town, 2007. http://hdl.handle.net/11427/5096.
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Fidai, Muhammad Hassan. "Implementation of DC Supervisory Control : Optimal Power Flow Calculator." Thesis, KTH, Industriella informations- och styrsystem, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-155824.
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Integration of renewable resources such as remote solar or wind farms and electricpower trading between neighbouring countries lead to new requirements on the development of thetransmission grids. Since AC grid expansion is limited by e.g. legislations issues, High VoltageDirect Current (HVDC) technology with its diverse benets compared to AC is being considered asappropriate alternative solution. The developed HVDC grid can be either embedded inside one ACgrid or connects several AC areas. In both architectures, the separate DC supervisory control can beproposed to control the HVDC grids using the interfacing information from AC Supervisory ControlAnd Data Acquisition (SCADA). The supervisory control is supposed to calculate the optimal power ow (OPF) in order to run the system in the most optimal situation. Based on the architecture, therequired information, boundary of the system and also objective function can vary. The aim of the thesis is to present the ndings of a feasibility study to implement a supervisorycontrol for bipolar Voltage Source Converter (VSC) HVDC grids in possible real time platforms. DCsupervisory control has a network topology manager to identify the grid conguration and employsan OPF calculator based on interior point optimization method to determine the set-point valuesfor all HVDC stations in a grid. OPF calculator takes into account the DC voltage, converter andDC line constraints.ii
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Pajic, Slobodan. "Sequential quadratic programming-based contingency constrained optimal power flow." Link to electronic thesis, 2003. http://www.wpi.edu/Pubs/ETD/Available/etd-0430103-152758.
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Salgado, Roberto de Souza. "Optimal power flow solutions using the gradient projection method." reponame:Repositório Institucional da UFSC, 1989. http://repositorio.ufsc.br/xmlui/handle/123456789/75577.
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Jamalzadeh, Reza. "Microgrid Optimal Power Flow Based On Generalized Benders Decomposition." Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1512743611060712.
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Kane, Laura. "An assessment of power system principles of access for wind power using optimal power flow." Thesis, University of Strathclyde, 2015. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=24925.
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The growth of renewable generation (and wind generation in particular) in distribution networks is leading to the development of Active Network Management (ANM) strategies and solutions. ANM systems aim to increase the capacity of renewable and distributed generation that can connect to power networks. One such ANM strategy is generation curtailment where distributed generation is given a non-firm connection under which the network operator instructs the generator to reduce its power output under specified conditions and this is practically achieved through the implementation of automatic controls in the ANM system. The rules which define the method of curtailment are often referred to as Principles of Access (PoA). The UK is currently at the forefront of ANM research and there are a number of full scale trials in Orkney [1], Shetland [2] and Cambridgeshire [3]. All of these schemes will apply PoA for curtailment of wind generators. There has been little research undertaken to date on alternative PoA for non-firm wind generation other than those implemented in these trial schemes. This research performs a qualitative analysis of PoA using industry recognised assessment criteria, and a quantitative analysis of PoA using an Optimal Power Flow (OPF) method. Business models present a means of recovering the costs of ANM and compares this to the cost of traditional methods of network reinforcement. Alternative PoA can have a significant impact on the capacity factor of generators and a PoA which implements a market system is found to deliver the best result for both network and generator. Alternatively, PoA which distribute curtailment more evenly across generators such as Pro Rata provide an increase in capacity factor for generators lower in the priority stack under a LIFO arrangement.
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Zhang, Fan. "Solving Large Security-Constrained Optimal Power Flow for Power Grid Planning and Operations." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1592567584117811.
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Schmidt, Oliver T., Seyed M. Hosseini, Ulrich Rist, Ardeshir Hanifi, and Dan Henningson. "Optimal initial perturbations in streamwise corner-flow." KTH, Stabilitet, Transition, Kontroll, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-123194.
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Localised optimal initial perturbations are studied to gain an understanding of the global stability properties of streamwise corner-flow. A self-similar and a modified base-flow are considered. The latter mimics a characteristic deviation from the self-similar solution, commonly observed in experiment. Poweriterations in terms of subsequent direct and adjoint linearised Navier-Stokes solution sweeps are employed to converge optimal solutions for two optimisation times. The optimal response manifests as a wave packet that initially gains energy through the Orr mechanism and continues growing exponentially thereafter. The study at hand represents the first global stability analysis of streamwise corner-flow and confirms key observations made in theoretical and/or experimental work on the subject. Namely, the presence of an inviscid instability mechanism in the near-corner region and a destabilising effect of the characteristic mean-flow deformation found in experiment.QC 20130604
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Olofsson, Magnus. "Optimal Operation of the Swedish Railway Electrical system : An Application of Optimal power Flow." Doctoral thesis, KTH, Elkraftteknik, 1996. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187380.
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Torres, Geraldo L. "Nonlinear optimal power flow by interior and noninterior point methods." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0010/NQ38274.pdf.
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Maust, Reid S. "Optimal power flow using a genetic algorithm and linear algebra." Morgantown, W. Va. : [West Virginia University Libraries], 1999. http://etd.wvu.edu/templates/showETD.cfm?recnum=1163.
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Thesis (Ph. D.)--West Virginia University, 1999.Title from document title page. Document formatted into pages; contains vi, 91 p. : ill. Vita. Includes abstract. Includes bibliographical references (p. 41-42).
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ALMEIDA, JOSE ANTONIO FERREIRA DE. "INCLUSION OF REACTIVE VOLTAGE CONSTRAINTS IN LINEARIZED OPTIMAL POWER FLOW." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1991. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=14574@1.
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O sistema elétrico é planejado para operar na condição mais confiável possível de atendimento, sem que sejam violadas as restrições operativas a que está sujeito. Para a busca da região segura de operação utilizam-se vários programas de otimização e simulação.
O Fluxo de Potência Ótimo (FPO) é uma ferramenta muito útil para a busca do ponto de operação seguro. Mas, devido a sua complexidade computacional para solução das restrições não-lineares, possui resposta relativamente lenta, impossibilitando a sua utilização em diversos casos práticos, tanto em tempo real, onde existe a necessidade de rapidez de resposta, como no planejamento da operação, quando é necessário um grande número de execuções do FPO.
Em contrapartida, o Fluxo de Potência Ótimo Linearizado (FPO DC), devido a sua simplicidade computacional, possui grande rapidez de resposta. Mas, nas suas aproximações não são consideradas as restrições reativas, o que pode levar a uma solução em que estas sejam violadas.
Este trabalho apresenta uma metodologia que incorpora ao Fluxo de Potência Ótimo Linearizado restrições reativas em função da potência ativa do geradores, de tal forma que a solução fornecida por este modelo leve em consideração as restrições de tensão e potência reativa.The electrical network is planned to stay in the most reliable operation conditions, without any violated operation constraints. Many optimization and simulation models are used to define the safe operation region. The Optimal Power Flow (OPF) is a useful tool for the search of the best safe operation point. However, the computational complexity associated to its non-linear constraints implies in a heavy computation time and makes it difficult to be used whenever a fast response is required, as in on-line oporation or even most operation planning problems. On the other hand, the Linearized Optimal Power Flow (LOPF), due to its simplicity, is a very fast tool. However, it does not consider reactive (voltage) constraints, and is not able to detect any violation. This work presents a model to incorporate voltage constraints in the Linearized Power Flow.
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Laury, John. "Optimal Power Flow for an HVDC Feeder Solution for AC Railways." Thesis, KTH, Elektrisk energiomvandling, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-104655.
Full textAbstract:
With today’s increasing railway traffic, the demand for electrical power has increased. However, several railway systems are weak and are not being controlled optimally. Thus, transmission losses are high and the voltage can be significantly lower than the nominal level. One proposal, instead of using an extra HVAC power supply system, is to implement a HVDC supply system. A HVDC supply line would be installed in parallel to the current railway catenary system and power can be exchanged between the HVDC grid and the catenary through converters. This thesis investigates different properties and behaviours of a proposed HVDC feeder solution. An AC/DC unified Optimal Power Flow (OPF) model is developed and presented. Decision variables are utilized to obtain proper control of the converters. The used power flow equations and converter loss function, which are non linear, and the use of binary variables for the unit commitment leads to an optimization problem, that requires Mixed Integer Non-Linear Programing (MINLP) for solving. The optimization problem is formulated in the software GAMS, and is solved by BONMIN. In each case investigated, the objective is to minimize the total active power losses. The results of the investigated cases presented in this thesis, show that the proposed OPF-controlled HVDC solution reduces the losses and provides better voltage profile at the catenary, compared with today’s supply systems.
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Singh, Manish K. "Optimal Operation of Water and Power Distribution Networks." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/86860.
Full textAbstract:
Under the envisioned smart city paradigm, there is an increasing demand for the coordinated operation of our infrastructure networks. In this context, this thesis puts forth a comprehensive toolbox for the optimization of electric power and water distribution networks. On the analytical front, the toolbox consists of novel mixed-integer (non)-linear program (MINLP) formulations; convex relaxations with optimality guarantees; and the powerful technique of McCormick linearization. On the application side, the developed tools support the operation of each of the infrastructure networks independently, but also towards their joint operation. Starting with water distribution networks, the main difficulty in solving any (optimal-) water flow problem stems from a piecewise quadratic pressure drop law. To efficiently handle these constraints, we have first formulated a novel MINLP, and then proposed a relaxation of the pressure drop constraints to yield a mixed-integer second-order cone program. Further, a novel penalty term is appended to the cost that guarantees optimality and exactness under pre-defined network conditions. This contribution can be used to solve the WF problem; the OWF task of minimizing the pumping cost satisfying operational constraints; and the task of scheduling the operation of tanks to maximize the water service time in an area experiencing electric power outage. Regarding electric power systems, a novel MILP formulation for distribution restoration using binary indicator vectors on graph properties alongside exact McCormick linearization is proposed. This can be used to minimize the restoration time of an electric system under critical operational constraints, and to enable a coordinated response with the water utilities during outages.Master of Science
The advent of smart cities has promoted research towards interdependent operation of utilities such as water and power systems. While power system analysis is significantly developed due to decades of focused research, water networks have been relying on relatively less sophisticated tools. In this context, this thesis develops Advanced efficient computational tools for the analysis and optimization for water distribution networks. Given the consumer demands, an optimal water flow (OWF) problem for minimizing the pump operation cost is formulated. Developing a rigorous analytical framework, the proposed formulation provides significant computational improvements without compromising on the accuracy. Explicit network conditions are provided that guarantee the optimality and feasibility of the obtained OWF solution. The developed formulation is next used to solve two practical problems: the water flow problem, that solves the complex physical equations yielding nodal pressures and pipeline flows given the demands/injections; and an OWF problem that finds the best operational strategy for water utilities during power outages. The latter helps the water utility to maximize their service time during power outages, and helps power utilities better plan their restoration strategy. While the increased instrumentation and automation has enabled power utilities to better manage restoration during outages, finding an optimal strategy remains a difficult problem. The operational and coordination requirements for the upcoming distributed resources and microgrids further complicate the problem. This thesis develops a computationally fast and reasonably accurate power distribution restoration scheme enabling optimal coordination of different generators with optimal islanding. Numerical tests are conducted on benchmark water and power networks to corroborate the claims of the developed formulations.
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Mosca, Umberto. "A Novel Distributed Approach for Optimal Power Flow Problem in Smart Grids." Thesis, KTH, Reglerteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-117697.
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In this thesis we study a classical problem of the electrical field; the optimal power flow (OPF) in an electrical network. Given a power grid, the problem is to find the optimal production of generators respecting all the constraints imposed by physics, like Kirchhoff’ equations and power bounds on each part of network. The goal of a power flow problem is to obtain complete voltage angle and magnitude information for each bus in a power system for operating conditions.Solving this problem in a centralized manner for a very large networks becomes difficult due to computational limitations and become undesirable due to safety reasons. The development of computational ability in each component of the network has opened new horizons, linking the electrical and ICT engineering. With the rapid development of smart grid infrastructures, the OPF problem is becoming very important.Scalability and the fast convergent properties of the associated solution methods are highly desirable in a practical point of view. One of the main challenge in the OPF problem is the decoupling of the constraints enforced by the Kirchhoff’ laws. Our contribution has been to propose a new formulation of the problem so that the bigger problem can be decomposable into a number of subproblems (one for each node), which relies on only the local information available. As a result, our proposed protocols are scalable. Moreover, we adopt the state-ofthe-art alternating direction method of multipliers (ADMM), which blends fast convergent properties into the proposed protocol. We also propose a partially distributed protocol based on ADMM, which relies on an intelligent central controller to handle the associated constraints of the OPF problem. In this case, the computational burden at nodes are very small, thus, the nodes can be unintelligent. Finally, we provide numerical experiments to illustrate the behavior of proposed algorithms.
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Yan, Xihui. "Infeasible primal-dual interior point algorithms for solving optimal power flow problems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq21399.pdf.
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Chiang, Naiyuan. "Structure-exploiting interior point methods for security constrained optimal power flow problems." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/8281.
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The aim of this research is to demonstrate some more efficient approaches to solve the n-1 security constrained optimal power flow (SCOPF) problems by using structure-exploiting primal-dual interior point methods (IPM). Firstly, we consider a DC-SCOPF model, which is a linearized version of AC-SCOPF. One new reformulation of the DC-SCOPF model is suggested, in which most matrices that need to be factorized are constant. Consequently, most numerical factorizations and a large number of back-solve operations only need to be performed once throughout the entire IPM process. In the framework of the structure-exploiting IPM implementation, one of the major computational efforts consists of forming the Schur complement matrix, which is very computationally expensive if no further measure is applied. One remedy is to apply a preconditioned iterative method to solve the corresponding linear systems which appear in assembling the Schur complement matrix. We suggest two main schemes to pick a good and robust preconditioner for SCOPF problems based on combining different “active” contingency scenarios. The numerical results show that our new approaches are much faster than the default structure-exploiting method in OOPS, and also that it requires less memory. The second part of this thesis goes to the standard AC-SCOPF problem, which is a nonlinear and nonconvex optimization problem. We present a new contingency generation algorithm: it starts with solving the basic OPF problem, which is a much smaller problem of the same structure, and then generates contingency scenarios dynamically when needed. Some theoretical analysis of this algorithm is shown for the linear case, while the numerical results are exciting, as this new algorithm works for both AC and DC cases. It can find all the active scenarios and significantly reduce the number of scenarios one needs to contain in the model. As a result, it speeds up the solving process and may require less IPM iterations. Also, some heuristic algorithms are designed and presented to predict the active contingencies for the standard AC-SCOPF, based on the use of AC-OPF or DC-SCOPF. We test our heuristic algorithms on the modified IEEE 24-bus system, and also present their corresponding numerical results in the thesis.
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Abuella, Mohamed A. "STUDY OF PARTICLE SWARM FOR OPTIMAL POWER FLOW IN IEEE BENCHMARK SYSTEMS INCLUDING WIND POWER GENERATORS." OpenSIUC, 2012. https://opensiuc.lib.siu.edu/theses/991.
Full textAbstract:
AN ABSTRACT OF THE THESIS OF Mohamed A. Abuella, for the Master of Science degree in Electrical and Computer Engineering, presented on May 10, 2012, at Southern Illinois University Carbondale. TITLE:STUDY OF PARTICLE SWARM FOR OPTIMAL POWER FLOW IN IEEE BENCHMARK SYSTEMS INCLUDING WIND POWER GENERATORS MAJOR PROFESSOR: Dr. C. Hatziadoniu, The aim of this thesis is the optimal economic dispatch of real power in systems that include wind power. The economic dispatch of wind power units is quite different of conventional thermal units. In addition, the consideration should take the intermittency nature of wind speed and operating constraints as well. Therefore, this thesis uses a model that considers the aforementioned considerations in addition to whether the utility owns wind turbines or not. The optimal power flow (OPF) is solved by using one of the modern optimization algorithms: the particle swarm optimization algorithm (PSO). IEEE 30-bus test system has been adapted to study the implementation PSO algorithm in OPF of conventional-thermal generators. A small and simple 6-bus system has been used to study OPF of a system that includes wind-powered generators besides to thermal generators. The analysis of investigations on power systems is presented in tabulated and illustrative methods to lead to clear conclusions.
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Zamani, Iman. "Optimal distributed generation planning based on NSGA-II and MATPOWER." Thesis, Brunel University, 2015. http://bura.brunel.ac.uk/handle/2438/11483.
Full textAbstract:
The UK and the world are moving away from central energy resource to distributed generation (DG) in order to lower carbon emissions. Renewable energy resources comprise a big percentage of DGs and their optimal integration to the grid is the main attempt of planning/developing projects with in electricity network. Feasibility and thorough conceptual design studies are required in the planning/development process as most of the electricity networks are designed in a few decades ago, not considering the challenges imposed by DGs. As an example, the issue of voltage rise during steady state condition becomes problematic when large amount of dispersed generation is connected to a distribution network. The efficient transfer of power out or toward the network is not currently an efficient solution due to phase angle difference of each network supplied by DGs. Therefore optimisation algorithms have been developed over the last decade in order to do the planning purpose optimally to alleviate the unwanted effects of DGs. Robustness of proposed algorithms in the literature has been only partially addressed due to challenges of power system problems such multi-objective nature of them. In this work, the contribution provides a novel platform for optimum integration of distributed generations in power grid in terms of their site and size. The work provides a modified non-sorting genetic algorithm (NSGA) based on MATPOWER (for power flow calculation) in order to find a fast and reliable solution to optimum planning. The proposed multi-objective planning tool, presents a fast convergence method for the case studies, incorporating the economic and technical aspects of DG planning from the planner‟s perspective. The proposed method is novel in terms of power flow constraints handling and can be applied to other energy planning problems.
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Mohammadi, Javad. "Distributed Computational Methods for Energy Management in Smart Grids." Research Showcase @ CMU, 2016. http://repository.cmu.edu/dissertations/710.
Full textAbstract:
It is expected that the grid of the future differs from the current system by the increased integration of distributed generation, distributed storage, demand response, power electronics, and communications and sensing technologies. The consequence is that the physical structure of the system becomes significantly more distributed. The existing centralized control structure is not suitable any more to operate such a highly distributed system. This thesis is dedicated to providing a promising solution to a class of energy management problems in power systems with a high penetration of distributed resources. This class includes optimal dispatch problems such as optimal power flow, security constrained optimal dispatch, optimal power flow control and coordinated plug-in electric vehicles charging. Our fully distributed algorithm not only handles the computational complexity of the problem, but also provides a more practical solution for these problems in the emerging smart grid environment. This distributed framework is based on iteratively solving in a distributed fashion the first order optimality conditions associated with the optimization formulations. A multi-agent viewpoint of the power system is adopted, in which at each iteration, every network agent updates a few local variables through simple computations, and exchanges information with neighboring agents. Our proposed distributed solution is based on the consensus+innovations framework, in which the consensus term enforces agreement among agents while the innovations updates ensure that local constraints are satisfied.
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Dolloff, Paul A. "Optimization in electrical distribution systems : Discrete Ascent Optimal Programming /." Diss., This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-06062008-151439/.
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Ratul, Saiful A. "Optimal DG Placement: A Multimethod Analysis." ScholarWorks@UNO, 2016. http://scholarworks.uno.edu/td/2269.
Full textAbstract:
With Power System being restructured in the vision of Smart Grid, it is important now more than ever to find suitable locations to place Distributed Generators (DG). Distributed generators, which may be renewable, are not limited to specific locations as in the case of conventional generators. Several papers have been published that make suggestions on where the optimal location of DG should be in a system. Objectives ranging from loss minimization to total cost minimization have been the factor for such studies. In this study, a new method is introduced that hopes to improve a current system in three ways by maximizing load, minimizing the locational marginal price and improving line contingency scenarios. The proposed methodology is simulated using MATPOWER’s Optimal Power Flow on the IEEE 14 bus test system.
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Ponrajah, Ranendra Anthony. "The minimum cost optimal power flow problem solved via the restart homotopy continuation method /." Thesis, McGill University, 1987. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=75455.
Full textAbstract:
This thesis is the result of an investigation to assess the potential of the continuation method to solve the minimum cost optimal power flow problem. For this purpose, a restart homotopy continuation method algorithm is developed, which contains in essence two phases.The pertinent steps of the first phase are as follows: (1) Create a sub-problem of the complete optimal power flow problem by relaxing boundary limits on all functional variables, namely voltages at load buses, line flows and reactive generations. (2) Parameterize a subset of the whole set of controls which comprises initially of tap-changers, phase-shifters, shunt controllers, and the voltages at generation buses. (3) Optimize the resulting problem.
The solution in step (3) is used as an initial starting point in a continuation process, designed to track this solution to the optimal solution of the sub-problem defined in step (1). The tracking is accomplished via a predictor-corrector path following algorithm embodying certain special features, such that the solution accuracy can be improved to any desired degree through a flexible restart feature developed in this study. Within the tracking process only a subset (identified in step 2 above) of the whole set of controls require specific monitoring for break-points. This feature greatly reduces the computational burden. Termination of the first phase marks an operating point in which all controls are strictly feasible.
If, following the termination of the first phase, functional variables previously ignored prove to be within their respective bounds, the solution to the sub-problem becomes the solution to the complete optimal power flow problem. However, should functional variables violate their bounds the second phase of the algorithm is invoked, which in essence creates a new sub-problem by changing the roles of the control and violated dependent variables, such that the newly modified sub-problem maintains the same basic structure as its predecessor.
Phase I is invoked again at this juncture to solve the modified sub-problem. This process is repeated in cycles until the Kuhn-Tucker optimality conditions are satisfied. Simulations suggest that convergence is usually achieved within two or three Phase I/II cycles.
This being a method unique to the minimum cost optimal power flow problem, numerous examples (up to 118 buses) have been tested and compared against the commercial code MINOS. The newly proposed algorithm appears to be faster and more reliable.
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Huneault, Maurice. "An investigation of the solution to the optimal power flow problem incorporating continuation methods /." Thesis, McGill University, 1988. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=75853.
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This thesis analyzes and tests some new solution techniques for the optimal power flow problem. This new methodology exploits a parametric technique, called the continuation method, which is applied to different tasks in the solution procedure. In a first application, the continuation method solves the quadratic subproblems generated sequentially by the optimal power flow's nonlinear program. It first creates a simple subproblem, which is easy to solve, and then links it to the subproblem we wish to solve. Starting at the solution of the simple problem, it generates optimal solution trajectories for the intermediate problems, leading to the desired optimal solution. In a second application, the algorithm tracks optimal solutions trajectories of the nonlinear problem when the load is slowly varied. This constitutes an example of "incremental loading", a technique already used for real power dispatch, but in this case a complete network model is used. The flexibility of the algorithm at various levels allows for some excellent computation times in this load-tracking mode: we have observed reductions in computation times for new solutions of the order of 70%, compared to the computation time of the initial load.This thesis first presents an analysis of the various structures used in optimal power flow algorithms. Then, having chosen and presented the structure of our algorithm, we analyze the quadratic subproblems generated by this algorithm for some of its more important tasks: minimum cost, minimum losses and load shedding. New rules are proposed to link the solutions of successive subproblems to ensure the convergence of the nonlinear problem. Then, as a final contribution to the theory, some extensions are suggested for the subproblems: among them are ramp constraints, bus incremental costs, and provisions for redispatching.
Numerical simulations of the proposed optimal power flow algorithm using the minimum fuel cost task were performed on four test systems, with sizes ranging from 6 to 118 buses. The results are documented in detail, and results for the 30 bus test are compared to those reported by other authors. All in all, our results demonstrate quite well the potential of this technique. (Abstract shortened with permission of author.)
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Robertson, James George. "New optimal power flow techniques to improve integration of distributed generation in responsive distribution networks." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/10528.
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Climate change has brought about legally-binding targets for Scotland, the U.K. and the E.U. to reduce greenhouse gas emissions and source a share of overall energy consumption from renewable energy resources by 2020. With severe limitations in the transport and heating sectors the onus is on the electricity sector to provide a significant reduction in greenhouse gas emissions and introduce a substantial increase in renewable energy production. The most attractive renewable energy resources are located in the geographic extremes of the country, far from the large population densities and high voltage, high capacity transmission networks. This means that the majority of renewable generation technologies will need to connect to the conventionally passive, lower voltage distribution networks. The integration of Distributed Generation (DG) is severely restricted by the technical limitations of the passively managed lower voltage infrastructure. Long lead times and the capital expenditure of traditional electricity network reinforcement can significantly delay or make the economics of some renewable generation schemes unviable. To be able to quickly and cost-effectively integrate significant levels of DG, the conventional fit-and-forget approach will have to be evolved into a ‘connect-and-manage’ system using active network management (ANM) techniques. ANM considers the real-time variation in generation and demand levels and schedules electricity network control settings to alleviate system constraints and increase connectable capacity of DG. This thesis explores the extent to which real time adjustments to DG and network asset controller set-points could allow existing networks to accommodate more DG. This thesis investigates the use of a full AC OPF technique to operate and schedule in real time variables of ANM control in distribution networks. These include; DG real and reactive power output and on-load-tap-changing transformer set-points. New formulations of the full AC OPF problem including multi-objective functions, penalising unnecessary deviation of variable control settings, and a Receding-Horizon formulation are assessed. This thesis also presents a methodology and modelling environment to explore the new and innovative formulations of OPF and to assess the interactions of various control practices in real time. Continuous time sequential, single scenario, OPF analyses at a very short control cycle can lead to the discontinuous and unnecessary switching of network control set-points, particularly during the less onerous network operating conditions. Furthermore, residual current flow and voltage variation can also gave rise to undesirable network effects including over and under voltage excursion and thermal overloading of network components. For the majority of instances, the magnitude of constraint violation was not significant but the levels of occurrence gave occasional cause for concern. The new formulations of the OPF problem were successful in deterring any extreme and unsatisfactory effects. Results have shown significant improvements in the energy yield from non-firm renewable energy resources. Initial testing of the real time OPF techniques in a simple demonstration network where voltage rise restricted the headroom for installed DG capacity and energy yield, showed that the energy yield for a single DG increased by 200% from the fit-and-forget scenario. Extrapolation of the OPF technique to a network with multiple DGs from different types of renewable energy resources showed an increase of 216% from the fit-and-forget energy yield. In a much larger network case study, where thermal loading limits constrained further DG capacity and energy yield, the increase in energy yield was more modest with an average increase of 45% over the fit-and-forget approach. In the large network where thermal overloading prevailed there was no immediate alternative to real power curtailment. This work has demonstrated that the proposed ANM OPF schemes can provide an intelligent, more cost effective and quicker alternative to network upgrades. As a result, DNOs can have a better knowledge and understanding of the capabilities and technical limitations of their networks to absorb DG safely and securely, without the expense of conventional network reinforcement.
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Xie, Kai. "Nonlinear interior point methods for optimal power flow and their applications to spot pricing of electricity." Thesis, Brunel University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.311243.
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Anthony, Ikenna O., Geev Mokryani, Rana H. A. Zubo, and O. A. Ezechukwu. "Distribution Network Reconfiguration Considering Security-Constraint and Multi-DG Configurations." IEEE, 2020. http://hdl.handle.net/10454/18492.
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YesThis paper proposes a novel method for distribution network reconfiguration considering security-constraints and multi-configuration of renewable distributed generators (DG). The objective of the proposed method is to minimize the total operational cost using security constrained optimal power flow (SCOPF). The impact of multi-configuration of renewable DGs in a meshed network is investigated. In this work, lines were added to the radial distribution network to analyse the network power flow in different network configurations. The added lines were connected to the closest generator bus which offered least operating cost. A 16-bus UK generic distribution system (UKGDS) was used to model the efficiency of the proposed method. The obtained results in multi-DG configuration ensure the security of the network in N-1 contingency criteria.
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Bahrami, Shahab. "Algorithm design for optimal power flow, security-constrained unit commitment, and demand response in energy systems." Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/62754.
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Energy management is of prime importance for power system operators to enhance the use of the existing and new facilities, while maintaining a high level of reliability. In this thesis, we develop analytical models and efficient algorithms for energy management programs in transmission and distribution networks. First, we study the optimal power flow (OPF) in ac-dc grids, which is a non-convex optimization problem. We use convex relaxation techniques and transform the problem into a semidefinite program (SDP). We derive the sufficient conditions for zero relaxation gap and design an algorithm to obtain the global optimal solution. Subsequently, we study the security-constrained unit commitment (SCUC) problem in ac-dc grids with generation and load uncertainty. We introduce the concept of conditional value-at risk to limit the net power supply shortage. The SCUC is a nonlinear mixed-integer optimization problem. We use ℓ₁-norm approximation and convex relaxation techniques to transform the problem into an SDP. We develop an algorithm to determine a near-optimal solution. Next, we target the role of end-users in energy management activities. We study demand response programs for residential users and data centers. For residential users, we capture their coupled decision making in a demand response program with real-time pricing as a partially observable stochastic game. To make the problem tractable, we approximate the optimal scheduling policy of the residential users by the Markov perfect equilibrium (MPE) of a fully observable stochastic game with incomplete information. We develop an online load scheduling learning algorithm to determine the users’ MPE policy. Last but not least, we focus on the demand response program for data centers in deregulated electricity markets, where each data center can choose a utility company from multiple available suppliers. We model the data centers’ coupled decisions of utility company choices and workload scheduling as a many-to-one matching game with externalities. We characterize the stable outcome of the game, where no data center has an incentive to unilaterally change its strategy. We develop a distributed algorithm that is guaranteed to converge to a stable outcome.Applied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
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Bukhsh, Waqquas Ahmed. "Islanding model for preventing wide-area blackouts and the issue of local solutions of the optimal power flow problem." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/9671.
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Optimization plays a central role in the control and operation of electricity power networks. In this thesis we focus on two very important optimization problems in power systems. The first is the optimal power flow problem (OPF). This is an old and well-known nonconvex optimization problem in power system. The existence of local solutions of OPF has been a question of interest for decades. Both local and global solution techniques have been put forward to solve OPF problem but without any documented cases of local solutions. We have produced test cases of power networks with local solutions and have collected these test cases in a publicly available online archive (http://www.maths.ed.ac.uk/optenergy/LocalOpt/), which can be used now by researchers and practitioners to test the robustness of their solution techniques. Also a new nonlinear relaxation of OPF is presented and it is shown that this relaxation in practice gives tight lower bounds of the global solution of OPF. The second problem considered is how to split a network into islands so as to prevent cascading blackouts over wide areas. A mixed integer linear programming (MILP) model for islanding of power system is presented. In recent years, islanding of power networks is attracting attention, because of the increasing occurrence and risk of blackouts. Our proposed approach is quite flexible and incorporates line switching and load shedding. We also give the motivation behind the islanding operation and test our model on variety of test cases. The islanding model uses DC model of power flow equations. We give some of the shortcomings of this model and later improve this model by using piecewise linear approximation of nonlinear terms. The improved model yields good feasible results very quickly and numerical results on large networks show the promising performance of this model.
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Min, Liang. "Decomposition algorithms for multi-area power system analysis." Texas A&M University, 2003. http://hdl.handle.net/1969.1/5919.
Full textAbstract:
A power system with multiple interconnected areas needs to be operated coordinately
for the purposes of the system reliability and economic operation, although
each area has its own ISO under the market environment. In consolidation of different
areas under a common grid coordinator, analysis of a power system becomes more
computationally demanding. Furthermore, the analysis becomes more challenging
because each area cannot obtain the network operating or economic data of other
areas.
This dissertation investigates decomposition algorithms for multi-area power system
transfer capability analysis and economic dispatch analysis. All of the proposed
algorithms assume that areas do not share their network operating and economic
information among themselves, while they are willing to cooperate via a central coordinator
for system wide analyses.
The first proposed algorithm is based on power transfer distribution factors
(PTDFs). A quadratic approximation, developed for the nonlinear PTDFs, is used to
update tie-line power flows calculated by Repeated Power Flow (RPF). These tie-line
power flows are then treated as injections in the TTC calculation of each area, as
the central entity coordinates these results to determine the final system-wide TTC
value.
The second proposed algorithm is based on REI-type network equivalents. It uses
the Continuation Power Flow (CPF) as the computational tool and, thus, the problem of voltage stability is considered in TTC studies. Each area uses REI equivalents of
external areas to compute its TTC via the CPF. The choice and updating procedure
for the continuation parameter employed by the CPF is implemented in a distributed
but coordinated manner.
The third proposed algorithm is based on inexact penalty functions. The traditional
OPF is treated as the optimization problems with global variables. Quadratic
penalty functions are used to relax the compatible constraints between the global
variables and the local variables. The solution is proposed to be implemented by
using a two-level computational architecture.
All of the proposed algorithms are verified by numerical comparisons between the
integrated and proposed decomposition algorithms. The proposed algorithms lead to
potential gains in the computational efficiency with limited data exchanges among
areas.
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Hamon, Camille. "Probabilistic security management for power system operations with large amounts of wind power." Doctoral thesis, KTH, Elektriska energisystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166398.
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Power systems are critical infrastructures for the society. They are therefore planned and operated to provide a reliable eletricity delivery. The set of tools and methods to do so are gathered under security management and are designed to ensure that all operating constraints are fulfilled at all times. During the past decade, raising awareness about issues such as climate change, depletion of fossil fuels and energy security has triggered large investments in wind power. The limited predictability of wind power, in the form of forecast errors, pose a number of challenges for integrating wind power in power systems. This limited predictability increases the uncertainty already existing in power systems in the form of random occurrences of contingencies and load forecast errors. It is widely acknowledged that this added uncertainty due to wind power and other variable renewable energy sources will require new tools for security management as the penetration levels of these energy sources become significant. In this thesis, a set of tools for security management under uncertainty is developed. The key novelty in the proposed tools is that they build upon probabilistic descriptions, in terms of distribution functions, of the uncertainty. By considering the distribution functions of the uncertainty, the proposed tools can consider all possible future operating conditions captured in the probabilistic forecasts, as well as the likeliness of these operating conditions. By contrast, today's tools are based on the deterministic N-1 criterion that only considers one future operating condition and disregards its likelihood. Given a list of contingencies selected by the system operator and probabilitistic forecasts for the load and wind power, an operating risk is defined in this thesis as the sum of the probabilities of the pre- and post-contingency violations of the operating constraints, weighted by the probability of occurrence of the contingencies. For security assessment, this thesis proposes efficient Monte-Carlo methods to estimate the operating risk. Importance sampling is used to substantially reduce the computational time. In addition, sample-free analytical approximations are developed to quickly estimate the operating risk. For security enhancement, the analytical approximations are further embedded in an optimization problem that aims at obtaining the cheapest generation re-dispatch that ensures that the operating risk remains below a certain threshold. The proposed tools build upon approximations, developed in this thesis, of the stable feasible domain where all operating constraints are fulfilled.QC 20150508
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Macfie, Peter. "Large-scale security constrained optimal reactive power flow for operational loss management on the GB electricity transmission network." Thesis, Brunel University, 2010. http://bura.brunel.ac.uk/handle/2438/5073.
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The transmission of power across the GB transmission system, as operated by National Grid, results in inevitable loss of electrical power. Operationally these power losses cannot be eliminated, but they can be reduced by adjustment of the system voltage profile. At present the minimisation of active power losses relies upon a lengthy manually based iterative adjustment process. Therefore the system operator requires the development of advanced optimisation tools to cope with the challenges faced over the next decade, such as achieving the stringent greenhouse gas emission targets laid down by the UK government, while continue to provide an economical, secure and efficient service. To meet these challenges the research presented in this thesis has developed optimisation techniques that can assist control centre engineers by automatically setting up voltage studies that are low loss and low cost. The proposed voltage optimisation techniques have been shown to produce solutions that are secured against 800 credible contingency cases. A prototype voltage optimisation tool has been deployed, which required the development of a series of novel approaches to extend the functionality of an existing optimisation program. This research has lead to the development of novel methods for handling multi-objectives, contradictory shunt switching configurations and selecting all credible contingencies. Studies indicate that a theoretical loss saving of 1.9% is achievable, equivalent to an annual emissions saving of approximately 64,000 tonnes of carbon dioxide. A novel security constrained mixed integer non-linear optimisation technique has also been developed. The proposed method has been shown to be superior to several conventional methods on a wide range of IEEE standard network models and also on a range of large-scale GB network models. The proposed method manages to further reduce active power losses and also satisfies all security constraints.
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Hotz, Matthias [Verfasser], Wolfgang [Akademischer Betreuer] Utschick, Mario [Gutachter] Paolone, and Wolfgang [Gutachter] Utschick. "Optimal Power Flow in Hybrid AC/DC Power Systems : Modeling, Methods, and Design Implications / Matthias Hotz ; Gutachter: Mario Paolone, Wolfgang Utschick ; Betreuer: Wolfgang Utschick." München : Universitätsbibliothek der TU München, 2021. http://d-nb.info/123143452X/34.
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Alharbi, Mohammad. "Development of simplified power grid models in EU project Spine." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-285503.
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The electric power system is among the biggest and most complex man-made physical network worldwide. The increase of electricity demand, the integration of ICT technologies for the modernization of the electric grid and the introduction of intermittent renewable generation has resulted in further increasing the complexity of operating and planning the grid optimally. For this reason the analysis of large-scale power systems considering all state variables is a very complicated procedure. Thus, it is necessary to explore methods that represent the original network with smaller equivalent networks in order to simplify power system studies. The equivalent network should provide an accurate and efficient estimation of the behavior of the original power system network without considering the full analytical modelling of the grid infrastructure. This thesis investigates partitioning methods and reduction methodologies in order to develop a proper reduction model. The K-means and K-medoids clustering algorithms are employed to partition the network into numerous clusters of buses. In this thesis the Radial, Equivalent, and Independent (REI) method is further developed, implemented, and evaluated for obtaining a reduced, equivalent circuit of each cluster of the original power system. The basic idea of REI method is to aggregate the power injections of the eliminated buses to two fictitious buses through the zero power balance network. The method is implemented using Julia language and the PowerModels.jl package. The reduction methodology is evaluated using the IEEE 5-bus, 30-bus, and 118-bus systems, by comparing a series of accuracy and performance indices. Factors examined in the comparison include the chosen number of clusters, different assumptions for the slack bus as well as the effect of the imposed voltage limits on the fictitious REI buses.Elsystemet är ett av de största och mest komplexa människotillverkade fysiskanätverken i världen. Ökad elförbrukning, integration av informationsteknik föratt modernisera elnäten samt införandet av varierande förnybar elproduktion harresulterat i ytterligare ökad komplexitet för att driva nätet optimalt. Därför ärdet mycket komplicerat att analysera storskaliga elsystem samtidigt som man tarhänsyn till alla tillståndsvariabler. Det är således nödvändigt att utforska metoderför att modellera det ursprungliga nätverket med ett mindre ekvivalent nätverk föratt underlätta studier av elsystem. Det ekvivalenta nätverket ska ge en noggrann ocheffektiv uppskattning av det ursprungliga systemets egenskaper utan att inkludera enkompletta analytisk modell av nätverkets stuktur.Den här rapporten undersöker metoder för att dela upp och reducera ett nätverkför att få fram en lämplig ekvivalent modell. Klusteranalysalgotmerna K-meansoch K-medoids används för att dela in nätverket i ett antal kluster av noder. Irapporten vidareutvecklas, implementeras och utvärderas REI-metoden för att ta framreducerade ekvivalenta nätverk för varje kluster i det ursprungliga systemet. Dengrundläggande idén med REI-metoden är att den aggregerar elproduktionen i deelminerade noderna i två fiktiva noder genom ett nolleffektbalansnätverk.Metoden är implementerad i programspråket Julia och programpaketetPowerModels.jl. Reduceringsmetoderna utvärderas på IEEE:s system med 5 noder,30 noder respektive 118 noder, genom att jämföra ett antal index för noggrannhetoch prestanda. De faktorer som undersäks i jämförelsen inkluderar det valda antaletkluster, olika antagande om slacknoden samt följderna av spänningsgränserna för defiktiva REI-noderna.v