Relevant bibliographies by topics / Optimal Power Flow (OPF)

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Academic literature on the topic 'Optimal Power Flow (OPF)'

Author: Grafiati
Published: 4 June 2021
Last updated: 5 February 2022

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Journal articles on the topic "Optimal Power Flow (OPF)"

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Oh, HyungSeon. "Distributed optimal power flow." PLOS ONE 16, no. 6 (June 18, 2021): e0251948. http://dx.doi.org/10.1371/journal.pone.0251948.

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Objective The objectives of this paper are to 1) construct a new network model compatible with distributed computation, 2) construct the full optimal power flow (OPF) in a distributed fashion so that an effective, non-inferior solution can be found, and 3) develop a scalable algorithm that guarantees the convergence to a local minimum. Existing challenges Due to the nonconvexity of the problem, the search for a solution to OPF problems is not scalable, which makes the OPF highly limited for the system operation of large-scale real-world power grids—“the curse of dimensionality”. The recent attempts at distributed computation aim for a scalable and efficient algorithm by reducing the computational cost per iteration in exchange of increased communication costs. Motivation A new network model allows for efficient computation without increasing communication costs. With the network model, recent advancements in distributed computation make it possible to develop an efficient and scalable algorithm suitable for large-scale OPF optimizations. Methods We propose a new network model in which all nodes are directly connected to the center node to keep the communication costs manageable. Based on the network model, we suggest a nodal distributed algorithm and direct communication to all nodes through the center node. We demonstrate that the suggested algorithm converges to a local minimum rather than a point, satisfying the first optimality condition. Results The proposed algorithm identifies solutions to OPF problems in various IEEE model systems. The solutions are identical to those using a centrally optimized and heuristic approach. The computation time at each node does not depend on the system size, and Niter does not increase significantly with the system size. Conclusion Our proposed network model is a star network for maintaining the shortest node-to-node distances to allow a linear information exchange. The proposed algorithm guarantees the convergence to a local minimum rather than a maximum or a saddle point, and it maintains computational efficiency for a large-scale OPF, scalable algorithm.
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Lakdja, Fatiha, Fatima Zohra Gherbi, Redouane Berber, and Houari Boudjella. "Optimal TCSC placement for optimal power flow." Journal of Electrical Engineering 63, no. 5 (November 1, 2012): 316–21. http://dx.doi.org/10.2478/v10187-012-0046-2.

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Very few publications have been focused on the mathematical modeling of Flexible Alternating Current Transmission Systems (FACTS) -devices in optimal power flow analysis. A Thyristor Controlled Series Capacitors (TCSC) model has been proposed, and the model has been implemented in a successive QP. The mathematical models for TCSC have been established, and the Optimal Power Flow (OPF) problem with these FACTS-devices is solved by Newtons method. This article employs the Newton- based OPF-TCSC solver of MATLAB Simulator, thus it is essential to understand the development of OPF and the suitability of Newton-based algorithms for solving OPF-TCSC problem. The proposed concept was tested and validated with TCSC in twenty six-bus test system. Result shows that, when TCSC is used to relieve congestion in the system and the investment on TCSC can be recovered, with a new and original idea of integration.
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Mohagheghi, Erfan, Mansour Alramlawi, Aouss Gabash, and Pu Li. "A Survey of Real-Time Optimal Power Flow." Energies 11, no. 11 (November 13, 2018): 3142. http://dx.doi.org/10.3390/en11113142.

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There has been a strong increase of penetration of renewable energies into power systems. However, the renewables pose new challenges for the operation of the networks. Particularly, wind power is intermittently fluctuating, and, therefore, the network operator has to fast update the operations correspondingly. This task should be performed by an online optimization. Therefore, real-time optimal power flow (RT-OPF) has become an attractive topic in recent years. This paper presents an overview of recent studies on RT-OPF under wind energy penetration, offering a critical review of the major advancements in RT-OPF. It describes the challenges in the realization of the RT-OPF and presents available approaches to address these challenges. The paper focuses on a number of topics which are reviewed in chronological order of appearance: offline energy management systems (EMSs) (deterministic and stochastic approaches) and real-time EMSs (constraint satisfaction-based and OPF-based methods). The particular challenges associated with the incorporation of battery storage systems in the networks are explored, and it is concluded that the current research on RT-OPF is not sufficient, and new solution approaches are needed.
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Zheng, Xinhu, Dongliang Duan, Liuqing Yang, and Haonan Wang. "Decomposed Iterative Optimal Power Flow with Automatic Regionalization." Energies 13, no. 18 (September 22, 2020): 4987. http://dx.doi.org/10.3390/en13184987.

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The optimal power flow (OPF) problem plays an important role in power system operation and control. The problem is nonconvex and NP-hard, hence global optimality is not guaranteed and the complexity grows exponentially with the size of the system. Therefore, centralized optimization techniques are not suitable for large-scale systems and an efficient decomposed implementation of OPF is highly demanded. In this paper, we propose a novel and efficient method to decompose the entire system into multiple sub-systems based on automatic regionalization and acquire the OPF solution across sub-systems via a modified MATPOWER solver. The proposed method is implemented in a modified solver and tested on several IEEE Power System Test Cases. The performance is shown to be more appealing compared with the original solver.
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Radosavljevic, Jordan, Miroljub Jevtic, Dardan Klimenta, and Nebojsa Arsic. "Optimal power flow for distribution networks with distributed generation." Serbian Journal of Electrical Engineering 12, no. 2 (2015): 145–70. http://dx.doi.org/10.2298/sjee1502145r.

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This paper presents a genetic algorithm (GA) based approach for the solution of the optimal power flow (OPF) in distribution networks with distributed generation (DG) units, including fuel cells, micro turbines, diesel generators, photovoltaic systems and wind turbines. The OPF is formulated as a nonlinear multi-objective optimization problem with equality and inequality constraints. Due to the stochastic nature of energy produced from renewable sources, i.e. wind turbines and photovoltaic systems, as well as load uncertainties, a probabilisticalgorithm is introduced in the OPF analysis. The Weibull and normal distributions are employed to model the input random variables, namely the wind speed, solar irradiance and load power. The 2m+1 point estimate method and the Gram Charlier expansion theory are used to obtain the statistical moments and the probability density functions (PDFs) of the OPF results. The proposed approach is examined and tested on a modified IEEE 34 node test feeder with integrated five different DG units. The obtained results prove the efficiency of the proposed approach to solve both deterministic and probabilistic OPF problems for different forms of the multi-objective function. As such, it can serve as a useful decision-making supporting tool for distribution network operators.
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He, Xuan Hu, Wei Wang, Ying Nan Wang, Jun Kong, Jing Geng, and Sheng Bin Fan. "Fuzzy Optimal Power Flow with Multi-Objective Based on Artificial Bee Colony Algorithm in Power System." Applied Mechanics and Materials 448-453 (October 2013): 2473–77. http://dx.doi.org/10.4028/www.scientific.net/amm.448-453.2473.

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According to the problem of optimal power flow (OPF), the optimization objectives including minimization of total fuel cost for generating units, minimization of emission for atmospheric pollutants, minimization of active power losses and minimization of voltages deviations are established. The paper uses fuzzy membership functions instead of multi-objective functions to form fuzzy optimal power flow in the optimal power flow calculation process. The novel artificial bee colony (ABC) algorithm is proposed to solve OPF problem with multi-objective. The proposed approach is applied to the OPF problem on IEEE30 test systems. And the simulation results verify the effectiveness of the proposed method.
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Rugthaicharoencheep, Nattachote, Manat Boonthienthong, and Aroon Charlangsut. "Optimal Reactive Power Control in Power System with Particle Swarm Optimization Technique." Applied Mechanics and Materials 891 (May 2019): 246–52. http://dx.doi.org/10.4028/www.scientific.net/amm.891.246.

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This paper considers an application of Newton's optimal power flow to the solution of the secondary voltage/reactive power control in power system. This procedure is based on the sensitivity theory applied to the determination of zones for the secondary voltage/ reactive power control and corresponding reduced set of regulating sources, whose reactive outputs represent control variables in the optimal power flow program. PSO is applied to solve the OPF problem for optimal power flow the optimal power flow program output becomes a schedule to be used by operators in the process of OPF-PSO (Optimal Power Flow - Particle swarm optimization) PSO applied to optimal reactive power dispatch is evaluated on an IEEE 30-bus power system. The optimization strategy is general and can be used to solve other power system optimization problems as well.
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Kubba, Hassan Abdullah, and Mounir Thamer Esmieel. "Flexible Genetic Algorithm Based Optimal Power Flow of Power Systems." Journal of Engineering 24, no. 3 (March 1, 2018): 84. http://dx.doi.org/10.31026/j.eng.2018.03.07.

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Nowadays, the power plant is changing the power industry from a centralized and vertically integrated form into regional, competitive and functionally separate units. This is done with the future aims of increasing efficiency by better management and better employment of existing equipment and lower price of electricity to all types of customers while retaining a reliable system. This research is aimed to solve the optimal power flow (OPF) problem. The OPF is used to minimize the total generations fuel cost function. Optimal power flow may be single objective or multi objective function. In this thesis, an attempt is made to minimize the objective function with keeping the voltages magnitudes of all load buses, real output power of each generator bus and reactive power of each generator bus within their limits. The proposed method in this thesis is the Flexible Continuous Genetic Algorithm or in other words the Flexible Real-Coded Genetic Algorithm (RCGA) using the efficient GA's operators such as Rank Assignment (Weighted) Roulette Wheel Selection, Blending Method Recombination operator and Mutation Operator as well as Multi-Objective Minimization technique (MOM). This method has been tested and checked on the IEEE 30 buses test system and implemented on the 35-bus Super Iraqi National Grid (SING) system (400 KV). The results of OPF problem using IEEE 30 buses typical system has been compared with other researches.
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Srikun, Isaree. "Multi-Objective Optimal Power Flow Solutions Using Differential Search Algorithm." Advanced Materials Research 1077 (December 2014): 241–45. http://dx.doi.org/10.4028/www.scientific.net/amr.1077.241.

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This paper presents a Differential Search Algorithm for solving a multi-objective Optimal Power Flow (OPF) in support of power system operation and control . The multi-objective OPF was formulated for tackling with total generation cost and environmental impacts simultaneously. The proposed method was applied to the standard IEEE 30-bus test system. The results show that solving the multi-objective OPF problem by the Differential Search Algorithm is more effective than other swarm intelligence methods in the literature.
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Ji, Cong, Zhi Nong Wei, Guo Qiang Sun, and Yong Hui Sun. "AC-DC Decoupling Algorithm of Optimal Power Flow with HVDC System." Applied Mechanics and Materials 457-458 (October 2013): 1107–12. http://dx.doi.org/10.4028/www.scientific.net/amm.457-458.1107.

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To calculate optimal power flow (OPF) with high voltage direct current (HVDC) system, AC-DC system variables are used to be optimized together. Since there are many HVDC variables, more formula derivation and coding of Jacobi matrix and Hessian Matrix are needed in the calculation. Considering DC system characteristic of OPF with HVDC system, a method of alternative iteration of AC-DC system is presented in this paper, which could take advantage of the existing AC system OPF program and extend to calculate OPF with HVDC system. Simulation and comparison results indicate that, the OPF calculating method of alternative iteration of AC-DC system presented in this paper has good convergence, strong adaptability and high accuracy
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Dissertations / Theses on the topic "Optimal Power Flow (OPF)"

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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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Books on the topic "Optimal Power Flow (OPF)"

1

Gonzalez, Jose I. Barrada. The optimal power flow problem. Manchester: UMIST, 1998.

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Veerapraditsin, Chanchai. Identification of reactive power margin using optimal power flow. Manchester: UMIST, 1998.

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Load Flow Optimization and Optimal Power Flow. Taylor & Francis Group, 2017.

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Load Flow Optimization and Optimal Power Flow. CRC Press, 2017. http://dx.doi.org/10.1201/9781351228299.

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Angelidis, George Angelo *. Newton optimal power-flow solution for electric power systems. 1988.

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Kumar, L. Ashok, and K. Mohana Sundaram. Optimal Power Flow Using FACTS Devices: Soft Computing Techniques. Taylor & Francis Group, 2020.

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Kumar, L. Ashok, and K. Mohana Sundaram. Optimal Power Flow Using FACTS Devices: Soft Computing Techniques. Taylor & Francis Group, 2020.

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Kumar, L. Ashok, and K. Mohana Sundaram. Optimal Power Flow Using FACTS Devices: Soft Computing Techniques. Taylor & Francis Group, 2020.

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Optimal Power Flow Using FACTS Devices: Soft Computing Techniques. Taylor & Francis Group, 2020.

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Angelidis, George Angelos. Hydro-thermal optimal power flow solution for large-scale electric power systems. 1992.

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Book chapters on the topic "Optimal Power Flow (OPF)"

1

Ranganathan, Prakash, and Kendall E. Nygard. "Unbiased Optimal Power Flow (OPF) for Power Systems with Wind-Power Generation." In Power Electronics and Power Systems, 137–43. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52617-1_11.

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Papalexopoulos, A. "Optimal Power Flow Packages Requirements and Experiences." In Optimization in Planning and Operation of Electric Power Systems, 309–47. Heidelberg: Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-662-12646-2_10.

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Jabr, Rabih A. "Recent Developments in Optimal Power Flow Modeling Techniques." In Handbook of Power Systems II, 3–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12686-4_1.

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Ullah, Zia, M. R. Elkadeem, Shaorong Wang, Muhammad Azam, Khdija Shaheen, Mehmood Hussain, and Muhammad Rizwan. "A Mini-review: Conventional and Metaheuristic Optimization Methods for the Solution of Optimal Power Flow (OPF) Problem." In Advanced Information Networking and Applications, 308–19. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44041-1_29.

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Kato, K. "Cost/Benefits Analysis of the Optimal Power Flow." In Optimization in Planning and Operation of Electric Power Systems, 349–65. Heidelberg: Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-662-12646-2_11.

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Bacher, Rainer. "Power System Models, Objectives and Constraints in Optimal Power Flow Calculations." In Optimization in Planning and Operation of Electric Power Systems, 217–63. Heidelberg: Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-662-12646-2_8.

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Fioretto, Ferdinando, and Pascal Van Hentenryck. "Constrained-Based Differential Privacy: Releasing Optimal Power Flow Benchmarks Privately." In Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 215–31. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93031-2_15.

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Alipour, Manijeh, Kazem Zare, and Heresh Seyedi. "Joint Electricity and Heat Optimal Power Flow of Energy Hubs." In Operation, Planning, and Analysis of Energy Storage Systems in Smart Energy Hubs, 391–409. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75097-2_16.

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Siano, P., P. Chen, Z. Chen, and A. Piccolo. "Optimal Allocation of Wind Turbines in Active Distribution Networks by Using Multi-Period Optimal Power Flow and Genetic Algorithms." In Modeling and Control of Sustainable Power Systems, 249–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-22904-6_9.

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Hutterer, Stephan, Michael Affenzeller, and Franz Auinger. "Evolutionary Algorithm Based Control Policies for Flexible Optimal Power Flow over Time." In Applications of Evolutionary Computation, 152–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37192-9_16.

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Conference papers on the topic "Optimal Power Flow (OPF)"

1

Strbac, G. "Benders decomposition applied to OPF problems." In IEE Colloquium on Optimal Power Flow - Invaluable Tool or Expensive Toy? IEE, 1997. http://dx.doi.org/10.1049/ic:19970571.

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Ristanovic, Petar. "The OPF algorithm for real-time and study mode." In IEE Colloquium on Optimal Power Flow - Invaluable Tool or Expensive Toy? IEE, 1997. http://dx.doi.org/10.1049/ic:19970572.

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Low, Steven, Dennice Gayme, and Ufuk Topcu. "Convexifying optimal power flow: Recent advances in OPF solution methods." In 2013 American Control Conference (ACC). IEEE, 2013. http://dx.doi.org/10.1109/acc.2013.6580654.

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Lee, M. "Compact based decoupled OPF for the reactive management problem in NGC." In IEE Colloquium on Optimal Power Flow - Invaluable Tool or Expensive Toy? IEE, 1997. http://dx.doi.org/10.1049/ic:19970577.

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Jha, Rahul Ranjan, and Anamika Dubey. "Exact Distribution Optimal Power Flow (D-OPF) Model using Convex Iteration Technique." In 2019 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2019. http://dx.doi.org/10.1109/pesgm40551.2019.8974080.

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Li, Peijie, Guangyu He, Bin Li, and Hua Wei. "Interface Design of On-Line Optimal Power Flow (OPF) Based on XML and IEEE Format." In 2010 Asia-Pacific Power and Energy Engineering Conference. IEEE, 2010. http://dx.doi.org/10.1109/appeec.2010.5448917.

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Chowdhury, Md Mahmud-Ul-Tarik, and Sukumar Kamalasadan. "An Angle Included Optimal Power Flow (OPF) Model for Power Distribution Network Using Second Order Cone Programming (SOCP)." In 2020 IEEE Industry Applications Society Annual Meeting. IEEE, 2020. http://dx.doi.org/10.1109/ias44978.2020.9334785.

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Frolov, Vladimir, Line Roald, and Michael Chertkov. "Cloud-AC-OPF: Model Reduction Technique for Multi-Scenario Optimal Power Flow via Chance-Constrained Optimization." In 2019 IEEE Milan PowerTech. IEEE, 2019. http://dx.doi.org/10.1109/ptc.2019.8810870.

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Sharif, S. S., and J. H. Taylor. "Dynamic optimal reactive power flow." In Proceedings of the 1998 American Control Conference (ACC). IEEE, 1998. http://dx.doi.org/10.1109/acc.1998.703223.

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Ji Wang. "Reliability constrained optimal power flow." In 3rd IEE International Conference on Reliability of Transmission and Distribution Networks (RTDN 2005). IEE, 2005. http://dx.doi.org/10.1049/cp:20050036.

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Reports on the topic "Optimal Power Flow (OPF)"

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Girigoudar, Kshitij. Linearized three-phase optimal power flow models for distribution grids. Office of Scientific and Technical Information (OSTI), August 2021. http://dx.doi.org/10.2172/1813820.

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Bienstock, Daniel, Michael Chertkov, and Sean Harnett. Chance Constrained Optimal Power Flow: Risk-Aware Network Control under Uncertainty. Office of Scientific and Technical Information (OSTI), September 2012. http://dx.doi.org/10.2172/1052351.

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Wang, Jing, and Marissa Hummon. Real Time - Optimal Power Flow Based Distributed Energy Resources Management System (DERMS) (CRADA Number CRD-20-16909 Final Report). Office of Scientific and Technical Information (OSTI), May 2021. http://dx.doi.org/10.2172/1785461.

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