Relevant bibliographies by topics / Electric distribution network optimization

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Electric distribution network optimization'

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Published: 4 June 2021
Last updated: 10 February 2022

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Journal articles on the topic "Electric distribution network optimization"

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Xie, Chuan Sheng, Cheng Ying Zhou, and Chen Chen Zhao. "Electric Vehicle Battery Distribution Network Optimization." Applied Mechanics and Materials 404 (September 2013): 408–14. http://dx.doi.org/10.4028/www.scientific.net/amm.404.408.

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Along with the wide spread of electric vehicles in China, the popularity of related facilities are popularizing and improving gradually, and in the meantime, requirements for the efficiency and effectiveness of the facilities arises. This article focuses on problems concerning the efficient electric vehicle battery distribution network, and obtains the feasible distribution programs by optimal model of cost; then evaluates feasible programs by fuzzy comprehensive evaluation method to determine the optimal layout of the distribution network. Numerical results show that the model is flexible, scientific and rational.
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Pirouzi, Sasan, and Jamshid Aghaei. "Mathematical modeling of electric vehicles contributions in voltage security of smart distribution networks." SIMULATION 95, no. 5 (June 6, 2018): 429–39. http://dx.doi.org/10.1177/0037549718778766.

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This paper evaluates the voltage security of the distribution networks in the presence of electric vehicles in the optimization framework. Accordingly, the main objective functions of this optimization problem include maximization of voltage security margin and minimization of operational cost. Also, it is supposed that the electric vehicles are equipped with bidirectional chargers to control active and reactive power in smart distribution networks, simultaneously. The objective functions are subject to the constraints of power flow equations, system operating limits and electric vehicle constraints. The proposed model is implemented on the 33-bus distribution network to evaluate the performance of the proposed optimization scheme for the management of the smart distribution networks in the presence of electric vehicles. The results show that the operational cost and network voltage security margin are reduced in the case of the higher electric vehicle penetration rate when electric vehicles are used for charging active power and reactive power control capability, with respect to the case that does not include electric vehicles.
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Srećković, Nevena, Miran Rošer, and Gorazd Štumberger. "Utilization of Active Distribution Network Elements for Optimization of a Distribution Network Operation." Energies 14, no. 12 (June 12, 2021): 3494. http://dx.doi.org/10.3390/en14123494.

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Electricity Distributions Networks (DNs) are changing from a once passive to an active electric power system element. This change, driven by several European Commission Directives and Regulations in the energy sector prompts the proliferated integration of new network elements, which can actively participate in network operations if adequately utilized. This paper addresses the possibility of using these active DN elements for optimization of a time-discrete network operation in terms of minimization of power losses while ensuring other operational constraints (i.e., voltage profiles and line currents). The active elements considered within the proposed optimization procedure are distributed generation units, capable of reactive power provision; remotely controlled switches for changing the network configuration; and an on-load tap changer-equipped substation, supplying the network. The proposed procedure was tested on a model of an actual medium voltage DN. The results showed that simultaneous consideration of these active elements could reduce power losses at a considered point of operation while keeping the voltage profiles within the permitted interval. Furthermore, by performing a series of consecutive optimization procedures at a given time interval, an optimization of network operations for extended periods (e.g., days, months, or years) could also be achieved.
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Wang, Guan, Chao Qin, Yan Li Huang, and Zhong Fu Tan. "Coal Transportation Network Optimization Model Based on Power Source Distribution." Applied Mechanics and Materials 740 (March 2015): 918–21. http://dx.doi.org/10.4028/www.scientific.net/amm.740.918.

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Coal is the important fuel and industrial raw materials in my country, and it accounts for 70% of total energy production and consumption in our country, and power plants’ coal consumption accounts for more than half of national total coal consumption. The research of electric-coal supply chain related to coal production place, coal transit place and consumption place (power plant). Due to there are many nodes like these three kinds coal transportation in the market, so the project that integrates every nodes into unified transportation optimization network has the function of reducing coal consumption and saving transportation costs. The paper constructs coal transportation analysis model, electric-coal supply and transportation path dynamic optimization model based on electric-coal transportation network analysis, and make effective analysis for choosing electric-coal transportation path. The paper also puts forward electric-coal supply chain optimization measures from electric-coal supply chain integration and ports building.
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Nguyen, Thuan Thanh, Ngoc Thiem Nguyen, and Trung Dung Nguyen. "Optimal electric distribution network configuration using adaptive sunflower optimization." Bulletin of Electrical Engineering and Informatics 10, no. 4 (August 1, 2021): 1777–84. http://dx.doi.org/10.11591/eei.v10i4.2588.

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Network reconfiguration (NR) is a powerful approach for power loss reduction in the distribution system. This paper presents a method of network reconfiguration using adaptive sunflower optimization (ASFO) to minimize power loss of the distribution system. ASFO is developed based on the original sunflower optimization (SFO) that is inspired from moving of sunflower to the sun. In ASFO, the mechanisms including pollination, survival and mortality mechanisms have been adjusted compared to the original SFO to fit with the network reconfiguration problem. The numerical results on the 14-node and 33-node systems have shown that ASFO outperforms to SFO for finding the optimal network configuration with greater success rate and better obtained solution quality. The comparison results with other previous approaches also indicate that ASFO has better performance than other methods in term of optimal network configuration. Thus, ASFO is a powerful method for the NR.
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Fan, Ai Long, Da Lu Guan, and Ping Hao. "Reconfiguration of Electric Distribution Networks Based on SR-ACA." Advanced Materials Research 403-408 (November 2011): 2874–77. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.2874.

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Distribution network reconfiguration is a non-linear combinatorial optimization problem. It is defined as altering the topological structures of the power system by changing the open/closed states of the sectionalizing and tie switches.The aim is to reduce the power loss, and eliminate the overload of the lines, and improve the power quality, and restore the power supply to non-fault area in the distribution network and so on. Combined with distribution networks, The paper proposed an improved ant colony algorithm under the normal operating conditions to solve the distribution network reconfiguration problem. To demonstrate the validity and effectiveness of the proposed method, an example system is studied.The results on IEEE 71-bus distribution networks are also given,which reveal that the proposed method is feasible and effective.
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Yang, Wanhao, Hong Wang, Zhijie Wang, Xiaolin Fu, Pengchi Ma, Zhengchen Deng, and Zihao Yang. "Optimization Strategy of Electric Vehicles Charging Path Based on “Traffic-Price-Distribution” Mode." Energies 13, no. 12 (June 20, 2020): 3208. http://dx.doi.org/10.3390/en13123208.

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According to the current optimization problem of electric vehicle charging path planning, a charging path optimization strategy for electric vehicles is proposed, which is under the “traffic-price-distribution” mode. Moreover, this strategy builds an electric vehicle charging and navigation system on the basis of the road traffic network model, real-time electricity price model and distribution network model. Based on the Dijkstra shortest path algorithm and Monte Carlo time-space prediction method, it gets the optimal charging path navigation with the goal of minimizing the charging cost of electric vehicles. The simulation results in MATLAB and MATPOWER (MATLAB R2018a, MATPOWER3.1b2, PSERC, Cannell University) show that the electric vehicle charging path optimization strategy can solve the local traffic congestion problem better and improve the safety and stability of the distribution network because of the fully considering the convenience of electric vehicle charging.
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Ahmadian, Ali, Ali Elkamel, and Abdelkader Mazouz. "An Improved Hybrid Particle Swarm Optimization and Tabu Search Algorithm for Expansion Planning of Large Dimension Electric Distribution Network." Energies 12, no. 16 (August 8, 2019): 3052. http://dx.doi.org/10.3390/en12163052.

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Optimal expansion of medium-voltage power networks is a common issue in electrical distribution planning. Minimizing the total cost of the objective function with technical constraints make it a combinatorial problem which should be solved by powerful optimization algorithms. In this paper, a new improved hybrid Tabu search/particle swarm optimization algorithm is proposed to optimize the electric expansion planning. The proposed method is analyzed both mathematically and experimentally and it is applied to three different electric distribution networks as case studies. Numerical results and comparisons are presented and show the efficiency of the proposed algorithm. As a result, the proposed algorithm is more powerful than the other algorithms, especially in larger dimension networks.
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Li, Fenglei, Chunxia Dou, and Shiyun Xu. "Optimal Scheduling Strategy of Distribution Network Based on Electric Vehicle Forecasting." Electronics 8, no. 7 (July 22, 2019): 816. http://dx.doi.org/10.3390/electronics8070816.

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Based on the Monte Carlo method, this paper simulates, predicts the load, and considers the travel chain of electric vehicles and different charging methods to establish a predictive model. Based on the results of electric vehicle simulation prediction, an optimal scheduling model of the distribution network considering the demand response side load is established. The firefly optimization algorithm is used to solve the optimal scheduling problem. The results show that the prediction model proposed in this paper has a certain reference value for the prediction of an electric vehicle load. The electric vehicle is placed in the optimal scheduling resource of the distribution network, which increases the dimension of the scheduling resources of the network and improves the economics of the distribution network operation.
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Zhao, Jian, Jianhui Wang, Zhao Xu, Cheng Wang, Can Wan, and Chen Chen. "Distribution Network Electric Vehicle Hosting Capacity Maximization: A Chargeable Region Optimization Model." IEEE Transactions on Power Systems 32, no. 5 (September 2017): 4119–30. http://dx.doi.org/10.1109/tpwrs.2017.2652485.

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Dissertations / Theses on the topic "Electric distribution network optimization"

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Radibratovic, Branislav. "Reactive optimization of transmission and distribution networks." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/28264.

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Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Begovic, Miroslav; Committee Member: Divan, Deepakraj; Committee Member: Dorsey, John; Committee Member: Ferri, Bonnie; Committee Member: Lambert, Frank.
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Neimane, Viktoria. "On Development Planning of Electricity Distribution Networks." Doctoral thesis, KTH, Electrical Systems, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3253.

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Future development of electric power systems must pursue anumber of different goals. The power system should beeconomically efficient, it should provide reliable energysupply and should not damage the environment. At the same time,operation and development of the system is influenced by avariety of uncertain and random factors. The planner attemptsto find the best strategy from a large number of possiblealternatives. Thus, the complexity of the problems related topower systems planning is mainly caused by presence of multipleobjectives, uncertain information and large number ofvariables. This dissertation is devoted to consideration of themethods for development planning of a certain subsystem, i.e.the distribution network.

The dissertation first tries to formulate the networkplanning problem in general form in terms of Bayesian DecisionTheory. However, the difficulties associated with formulationof the utility functions make it almost impossible to apply theBayesian approach directly. Moreover, when approaching theproblem applying different methods it is important to considerthe concave character of the utility function. Thisconsideration directly leads to the multi-criteria formulationof the problem, since the decision is motivated not only by theexpected value of revenues (or losses), but also by theassociated risks. The conclusion is made that the difficultiescaused by the tremendous complexity of the problem can beovercome either by introducing a number of simplifications,leading to the considerable loss in precision or applyingmethods based on modifications of Monte-Carlo or fuzzyarithmetic and Genetic Algorithms (GA), or Dynamic Programming(DP).

In presence of uncertainty the planner aims at findingrobust and flexible plans to reducethe risk of considerablelosses. Several measures of risk are discussed. It is shownthat measuring risk by regret may lead to risky solutions,therefore an alternative measure - Expected Maximum Value - issuggested. The general future model, called fuzzy-probabilistictree of futures, integrates all classes of uncertain parameters(probabilistic, fuzzy and truly uncertain).

The suggested network planning software incorporates threeefficient applications of GA. The first algorithm searchessimultaneously for the whole set of Pareto optimal solutions.The hybrid GA/DP approach benefits from the global optimizationproperties of GA and local search by DP resulting in originalalgorithm with improved convergence properties. Finally, theStochastic GA can cope with noisy objective functions.

Finally, two real distribution network planning projectsdealing with primary distribution network in the large city andsecondary network in the rural area are studied.

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Rong, Du. "Wireless Sensor Networks in Smart Cities : The Monitoring of Water Distribution Networks Case." Licentiate thesis, KTH, Reglerteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-185453.

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The development of wireless sensor networks (WSNs) is making it possible to monitor our cities. Due to the small size of the sensor nodes, and their capabilities of transmitting data remotely, they can be deployed at locations that are not easy or impossible to access, such as the pipelines of water distribution networks (WDNs), which plays an important role in protecting environment and securing public health.   The design of WSNs for WDNs faces major challenges. Generally, WSNs are resource-limited because most of the sensor nodes are battery powered. Thus, their resource allocation has to be carefully controlled. The thesis considers two prominent problems that occur when designing WSNs for WDNs: scheduling the sensing of the nodes of static WSNs, and sensor placement for mobile WSNs. These studies are reported in the thesis from three published or submitted papers. In the first paper, the scheduling of sleep/sensing for each sensor node is considered to maximize the whole WSNs lifetime while guaranteeing a monitoring performance constraint. The problem is transformed into an energy balancing problem, and solved by a dynamic programming based algorithm. It is proved that this algorithm finds one of the optimal solutions for the energy balancing problem. In the second paper, the question of how the energy balancing problem approximates the original scheduling problem is addressed. It is shown that even though these two problems are not equivalent, the gap of them is small enough. Thus, the proposed algorithm for the energy balancing problem can find a good approximation solution for the original scheduling problem. The second part of the thesis considers the use of mobile sensor nodes. Here, the limited resource is the number of available such mobile nodes. To maximize the monitoring coverage in terms of population, an optimization problem for determining the releasing locations for the mobile sensor nodes is formulated. An approximate solution algorithm based on submodular maximization is proposed and its performance is investigated. Beside WDNs, WSN applications for smart cities share a common characteristic: the area to monitor usually has a network structure. Therefore, the studies of this thesis can be potentially generalized for several IoT scenarios.

QC 20160419

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Yuan, Wei. "Reliable Power System Planning and Operations through Robust Optimization." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5807.

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In this dissertation, we introduce and study robust optimization models and decomposition algorithms in order to deal with the uncertainties such as terrorist attacks, natural disasters, and uncertain demand that are becoming more and more signicant in power systems operation and planning. An optimal power grid hardening problem is presented as a defender-attacker-defender (DAD) sequential game and solved by an exact decomposition algorithm. Network topology control, which is an eective corrective measure in power systems, is then incorporated into the defender-attacker-defender model as a recourse operation for the power system operator after a terrorist attack. Computational results validate the cost-eectiveness of the novel model. In addition, a resilient distribution network planning problem (RDNP) is proposed in order to coordinate the hardening and distributed generation resource placement with the objective of minimizing the distribution system damage under uncertain natural disaster events. A multi-stage and multi-zone based uncertainty set is designed to capture the spatial and temporal dynamics of a natural disaster as an extension to the N-K worst-case network interdiction approach. Finally, a power market day-ahead generation scheduling problem, i.e., robust unit commitment (RUC) problem, that takes account of uncertain demand is analyzed. Improvements have been made in achieving a fast
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Belpiede, Danilo. "Aplicação de algoritmos e evolutivos para a otimização do fluxo de potência em sistemas de subtransmissão de energia elétrica." Universidade de São Paulo, 2006. http://www.teses.usp.br/teses/disponiveis/3/3143/tde-22042007-200433/.

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Esta dissertação apresenta uma metodologia de otimização do fluxo de potência em sistemas elétricos de subtransmissão utilizando duas técnicas da Computação Evolutiva, os Algoritmos Genéticos e as Estratégias Evolutivas. A metodologia decompõe o problema em duas partes e o trata seqüencialmente. A primeira parte procede com a otimização do fluxo de potência ativa e a segunda com a otimização do fluxo de potência reativa. São apresentadas as características e estruturas básicas dos Algoritmos Genéticos e das Estratégias Evolutivas. A técnica dos Algoritmos Genéticos é implementada no modelo de otimização do fluxo de potência ativa e a técnica das Estratégias Evolutivas no modelo de otimização do fluxo de potência reativa. As variáveis de controle dos modelos desenvolvidos são, respectivamente, os estados dos dispositivos de seccionamento e os níveis de tensão dos barramentos dos pontos de fronteira, associadas ao sistema analisado. Analisam-se os sistemas elétricos de subtransmissão que contêm múltiplos pontos de fronteira (conexão) com a Rede Básica e diversas possibilidades de configuração operativa. A metodologia proposta é aplicada a um sistema elétrico de subtransmissão real a fim de minimizar o custo dos encargos de uso dos sistemas de transmissão. Os resultados obtidos mostram a eficácia dos algoritmos desenvolvidos na busca das soluções desejadas.
This dissertation presents a power flow optimization methodology on subtransmission electric systems using two techniques of Evolutionary Computation, namely the Genetic Algorithms and the Evolution Strategies. The methodology splits the problem into two parts and treats it separately. On the first step it proceeds to optimize the active power flow and on the second step to optimize the reactive power flow. Characteristics and basic structures of the Genetic Algorithms and the Evolution Strategies are shown. The Genetic Algorithms technique is implemented on the active power flow optimization model and the Evolution Strategies technique on the reactive power flow optimization model. The control variables of developed models are, respectively, the switch states and the border point bar voltage levels, associated to the analyzed system. The subtransmission electric systems that have multiple border (connection) points to the Basic Network and many operative configuration possibilities are analyzed. The proposed methodology is applied to a real subtransmission electric system in order to minimizes the transmission system use duty costs. The obtained results show the efficacy of the developed algorithms in the search of desired solutions.
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Yang, Yi. "Power line sensor networks for enhancing power line reliability and utilization." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41087.

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Over the last several decades, electricity consumption and generation have continually grown. Investment in the Transmission and Distribution (T&D) infrastructure has been minimal and it has become increasingly difficult and expensive to permit and build new power lines. At the same time, a growing increase in the penetration of renewable energy resources is causing an unprecedented level of dynamics on the grid. Consequently, the power grid is congested and under stress. To compound the situation, the utilities do not possess detailed information on the status and operating margins on their assets in order to use them optimally. The task of monitoring asset status and optimizing asset utilization for the electric power industry seems particularly challenging, given millions of assets and hundreds of thousands of miles of power lines distributed geographically over millions of square miles. The lack of situational awareness compromises system reliability, and raises the possibility of power outages and even cascading blackouts. To address this problem, a conceptual Power Line Sensor Network (PLSN) is proposed in this research. The main objective of this research is to develop a distributed PLSN to provide continuous on-line monitoring of the geographically dispersed power grid by using hundreds of thousands of low-cost, autonomous, smart, and communication-enabled Power Line Sensor (PLS) modules thus to improve the utilization and reliability of the existing power system. The proposed PLSN specifically targets the use of passive sensing techniques, focusing on monitoring the real-time dynamic capacity of a specific span of a power line under present weather conditions by using computational intelligence technologies. An ancillary function is to detect the presence of incipient failures along overhead power lines via monitoring and characterizing the electromagnetic fields around overhead conductors. This research integrates detailed modeling of the power lines and the physical manifestations of the parameters being sensed, with pattern recognition technologies. Key issues of this research also include design of a prototype PLS module with integrated sensing, power and communication functions, and validation of the Wireless Sensor Network (WSN) technology integrated to this proposed PLSN.
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Guimarães, Marcos Antonio do Nascimento. "Reconfiguração de sistemas de distribuição de energia eletrica utilizando algoritmos de busca Tabu." [s.n.], 2005. http://repositorio.unicamp.br/jspui/handle/REPOSIP/261716.

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Orientador: Carlos Alberto de Castro Junior
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação
Made available in DSpace on 2018-08-06T10:50:00Z (GMT). No. of bitstreams: 1 Guimaraes_MarcosAntoniodoNascimento_M.pdf: 908712 bytes, checksum: d5cf1733a05a1a20b87eb0c7abf094fb (MD5) Previous issue date: 2005
Resumo: A reconfiguração de sistemas de distribuição consiste na alteração da topologia da rede através do fechamento e abertura de chaves instaladas em pontos estratégicos da rede. Normalmente o procedimento é utilizado para fins de isolamento de faltas, minimização de perdas de potência ativa e balanceamento de cargas entre os alimentadores. Esse problema é de difícil resolução devido ao grande número de variáveis envolvidas e das restrições impostas, sendo a restrição de radialidade a de mais difícil representação matemática. O problema pode ser classificado como um problema de programação não linear inteiro misto (PNLIM) e apresenta o fenômeno de explosão combinatorial. Este trabalho tem como principal objetivo o desenvolvimento de um algoritmo de Busca Tabu para a reconfiguração de sistemas de distribuição de energia elétrica tendo como objetivo a maximização da margem de segurança com relação à estabilidade de tensão (ou margem de carregamento). São apresentados resultados para sistemas de 14 barras, 32 barras, 69 barras, 84 barras e os sistemas reais de 135 barras e 202 barras
Abstract: The network reconfiguration consists in modifying the topology of the network through the closing and opening of switches installed in strategical points. The reconfiguration of distribution systems is usually done to isolate faults, minimize real power losses, or to balance the load among feeders. This problem is difficult due to the great number of variables involved and the imposed constraints, being the constraint of radial structure of more difficult mathematical representation. The problem can be classified as nonlinear mixed integer programming problems with combinatorial explosion. The main objective of this work is to develop a Tabu Search algorithm for the reconfiguration of distribution systems for voltage stability margin enhancement. Results for the systems: 14 buses, 32 buses, 69 buses, 84 buses and the real systems 135 bus and 202 bus are presented and discussed.
Mestrado
Sistemas de Energia Eletrica
Mestre em Engenharia Elétrica
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Vinot, Benoît. "Conception d'un système d'information distribué pour la conduite des flexibilités dans un réseau de distribution électrique : modélisation, simulation et implémentation." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAM043/document.

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Le secteur industriel de l'énergie, et les réseaux électriques en particulier, rendent à nos sociétés modernes d'immenses services dont nous ne pouvons plus nous passer. Ils présentent aussi, hélas, un certain nombre de graves inconvénients, notamment en matière d'impact environnemental. Ces inconvénients apparaissent aujourd'hui comme inacceptables; le secteur de l'énergie s'efforce donc actuellement de les amoindrir autant que possible, dans le cadre de ce qu'on appelle la transition énergétique.Outre d'indispensables efforts en matière de sobriété et d'efficacité énergétique, deux grands axes d'amélioration se dessinent: d'une part, le remplacement progressif de certains moyens de production d'électricité conventionnels par des moyens de production renouvelables; et d'autre part, le transfert de certains usages aujourd'hui non-électriques vers l'électricité --- en particulier en matière de mobilité.L'intégration au réseau électrique de ces nouveaux types de dispositifs pose cependant des difficultés techniques considérables, qui motivent depuis le début des années 2000 de nombreux travaux sur le thème de ce que l'on appelle aujourd'hui les "smart grids": des réseaux électriques compatibles avec les exigences de la transition énergétique, c'est-à-dire capables d'accueillir massivement les nouveaux types d'usages comme la production photovoltaïque et les bornes de recharge des véhicules électriques, ceci notamment grâce à l'utilisation accrue des nouvelles technologies de l'information et de la communication. Parmi les difficultés susmentionnées, qui limitent la capacité d'accueil du réseau, figurent les congestions, c'est-à-dire les limites physiques à la puissance que l'on peut faire transiter d'un point à un autre sur une infrastructure donnée. C'est à la gestion des congestions que nos travaux sont consacrés. À ce sujet, la question fondamentale est de déterminer par quel enchaînement de mesures, de calcul, de communications et in fine d'actions, on peut passer d'une situation de contrainte sur un réseau de distribution d'électricité, à une situation où cette contrainte a été éliminée par l'action des flexibilités environnantes; autrement dit, en augmentant ou en réduisant judicieusement la production et/ou la consommation locales, et éventuellement en jouant sur d'autres types de leviers.L'objet de cette thèse est de participer à l'élaboration des outils conceptuels et informatiques qui nous permettront de répondre à la question fondamentale ci-dessus. Nos travaux portent ainsi sur la question de la modélisation des réseaux de distribution d'électricité "flexibles", et sur l'implémentation concrète des modèles retenus sous forme d'un logiciel de simulation ad hoc, parfaitement adapté à l'étude de ce type de réseaux
The energy sector and the electrical networks in particular, provide great and indispensable services to our modern societies. Unfortunately, they also bring some serious drawbacks, especially with regard to the environment. These drawbacks are becoming more and more unacceptable; that is why the energy sector is trying to reduce them as much as possible, in the framework of the so-called energy transition.In addition to mandatory efforts in terms of energy efficiency and sobriety, two major directions of improvement have been identified: on the one hand, the progressive replacement of some conventional power plants with renewable production units; and on the other hand, the transfer of several non-electrical usages towards electricity --- in particular in the area of mobility.The integration of these new devices into electrical networks raise new technical challenges which, since the early 2000s, have been driving a lot of work about so-called "smart grids": electrical networks compatible with the requirements of the energy transition, ie. able to host new devices like photovoltaic solar panels and charging stations for electric vehicles, notably through the increasing usage of new information and communications technologies.Among the difficulties mentioned above, which limit the hosting capacity of the network, there are congestions ie. physical constraints limiting the amount of power that may be transmitted through a given infrastructure. Our work is devoted to the management of congestions. The fundamental issue thereon is to define a sequence of decisions, computations, communications and in fine actionsthat allows to move from a constrained situation on the electrical distribution network, to a situation in which the action of local flexibilities has lifted the constraint; in other words, to a situation where increasing or decreasing local generation and/or consumption, or taking some other control action, relieved the network.The aim of this thesis is to contribute to the development of conceptual and computing tools that will allow us to answer the fundamental aforementioned issue. Our work thus deals with the modelling of flexible electrical distribution networks, and with the tangible implementation of selected models in the form of ad hoc simulation software, specifically designed for the study of such networks
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Bettoni, Luiz Marcelo Michelotti. "Modelos plim para otimização de circuitos da rede de distribuição secundária de energia elétrica." Universidade Tecnológica Federal do Paraná, 2011. http://repositorio.utfpr.edu.br/jspui/handle/1/373.

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ANEEL
Em sistemas de distribuição de energia elétrica é comum o desenvolvimento de projetos que busquem a melhoria dos índices de equilíbrio de cargas, carregamento de transformadores e quedas de tensão ao longo dos circuitos da rede secundária. O presente trabalho apresenta modelos matemáticos de Programação Linear Inteira Mista (PLIM) para quatro das intervenções técnicas usualmente praticadas com vistas a estas melhorias: balanceamento de carga, troca de condutor, divisão de circuito e remanejamento de carga. Os modelos respeitam aspectos técnicos, elétricos e considerações operacionais dos especialistas na busca de soluções que minimizem o investimento necessário para restabelecimento destes índices. Um método linear simplificado para o cálculo elétrico, baseado no Backward-Forward Sweep (BFS), é proposto a fim de incluir restrições sobre níveis de tensão diretamente nos modelos. A realização conjunta das intervenções é sugerida em uma proposta de integração de modelos por encadeamento de soluções. Para desenvolvimento dos modelos PLIM criou-se o ambiente de modelagem Gusek, interface para o solver livre GLPK. Os modelos foram implementados em uma ferramenta de apoio à tomada de decisão para projetos de melhoria de rede. Resultados são apresentados através de estudos de caso com dados de circuitos reais.
In eletric power distribution systems it is common to develop projects to improve the levels of load balancing, transformer loading and voltage drops along secondary network circuits. This paper presents Mixed Integer Linear Programming (MILP) mathematical models for adressing four technical interventions usually undertaken to achieve these improvements: load balancing, conductor changing, circuit split, and load relocation. These models comply with technical and electrical aspects and satisfy operational considerations from specialists in finding solutions that minimize the required investment for restoration of circuit levels. A simplified linear power flow method, based on the Backward-Forward Sweep (BFS), is proposed to include voltage levels constraints into the models. The combination of interventions is suggested in a proposal for integration of models by chaining solutions. To develop the MILP models the GUSEK modeling environment was created as an interface for the GLPK free solver. The models were implemented in a decision-making support tool for network improvement projects. Results are presented through case studies with data from real circuits.
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Correa, Juan R. (Juan Roza). "Optimization of a fast-response distribution network." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/39596.

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Abstract:
Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2007.
Includes bibliographical references (p. 69).
Inditex is one of the world's largest fashion distributors, operating 3,100 stores in 64 countries; its brands currently include Zara, Pull and Bear, Massimo Dutti, Bershka, Stradivarius, Oysho, Zara Home and Kiddy's Class. The group's flagship company is Zara, which is the world's largest "fast fashion" company: through unique and carefully integrated design, manufacturing and distribution processes, Zara routinely achieves design-to-shelf leadtimes of 6 weeks against an industry average of 6 months, and introduces 11,000 references per season against an industry average of 3,000. Throughout the season, Zara currently ships every new incoming product to all 950 stores comprising its distribution network at the same time. Its operations group has recognized a large opportunity in customizing the assortment of products offered in each store based on local sales, and staggering shipments to stores of each new reference in order to acquire more accurate sales forecast and enable better subsequent inventory allocation decisions. My thesis will detail the development and implementation of new optimization models for dynamically allocating inventory across Zara's distribution network.
(cont.) It will build upon and expand an ongoing collaboration between Zara and a team of two faculty at MIT (Pr. Jeremie Gallien) and UCLA (Pr. Felipe Caro). In addition, it will also explore five of the most used fabrics in manufacturing in order to satisfy the "fast fashion" model. It will describe the preferred fabric properties and any manufacturing issues that arise as a result of the fabric choices. Specifically, it will detail how changes in the structure of the fabric affect its final properties.
by Juan R. Correa.
S.M.
M.B.A.
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Books on the topic "Electric distribution network optimization"

1

Chakrabortty, Aranya. Control and optimization methods for electric smart grids. Edited by Ilic Marija D. 1951-. New York: Springer, 2012.

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Soong, Kim Che, Melikov Agassi, and SpringerLink (Online service), eds. Performance Analysis and Optimization of Multi-Traffic on Communication Networks. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.

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Shahnia, Farhad, Ali Arefi, and Gerard Ledwich, eds. Electric Distribution Network Planning. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7056-3.

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Arefi, Ali, Farhad Shahnia, and Gerard Ledwich, eds. Electric Distribution Network Management and Control. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7001-3.

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1928-, Holmes E. J., and Institution of Electrical Engineers, eds. Electricity distribution network design. 2nd ed. London: Peter Peregrinus Ltd., on behalf of the Institution of Electrical Engineers, 2003.

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Lakervi, E. Electricity distribution network design. London: P. Peregrinus on behalf of the Institution of Electrical Engineers, 1989.

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Resener, Mariana, Steffen Rebennack, Panos M. Pardalos, and Sérgio Haffner, eds. Handbook of Optimization in Electric Power Distribution Systems. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36115-0.

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Lauronen, Jari. Spare part management of an electricity distribution network. Lappeenranta, Finland: Lappeenranta University of Technology, 1998.

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Transforming the grid: Electricity system governance and network integration of distributed generation. Baden-Baden, Germany: Nomos, 2012.

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Myllyntaus, Timo. Phases of a network: From a breakthrough to a national system. [Helsinki]: Fingrid Oyj, 1999.

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Book chapters on the topic "Electric distribution network optimization"

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Sabillón, Carlos F., John F. Franco, Marcos J. Rider, and Rubén Romero. "Mathematical Optimization of Unbalanced Networks with Smart Grid Devices." In Electric Distribution Network Planning, 65–114. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7056-3_3.

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Mahdavi, Meisam, Pierluigi Siano, and Hassan Haes Alhelou. "Optimization Techniques for Reconfiguration of Energy Distribution Systems." In Flexibility in Electric Power Distribution Networks, 299–345. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003122326-13.

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Carvalho, Pedro M. S., and Luis A. F. M. Ferreira. "Large-Scale Network Optimization with Evolutionary Hybrid Algorithms: Ten Years’ Experience with the Electric Power Distribution Industry." In Computational Intelligence in Expensive Optimization Problems, 325–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-10701-6_13.

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Jiang, Ping, Xin Wang, Lixue Li, Yihui Zheng, Lidan Zhou, and Zhongbao Zhang. "Reactive Power Optimization for Distribution Network Based on Chaos Guide Particle Swarm Optimization Algorithm with Gold Criterion." In Lecture Notes in Electrical Engineering, 287–93. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-4981-2_31.

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Zaheeruddin, Aruna Pathak, and Manoj Kumar Tiwari. "Prolonging the Lifetime of Wireless Sensor Network by Exponential Node Distribution and Ant-colony Optimization Routing." In Lecture Notes in Electrical Engineering, 709–18. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6154-8_69.

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Cheng, Shan, Min-You Chen, Peter J. Fleming, and Xia Li. "Optimal Allocation of Distributed Generators in a Distribution Network Using Adaptive Multi-Objective Particle Swarm Optimization." In Electrical, Information Engineering and Mechatronics 2011, 1707–15. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2467-2_203.

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Huang, Xucheng, and Xuzheng Chai. "A New Method of Power Distribution Network Planning for Obstacle Bypass Based on Ant Colony Optimization Algorithm." In Lecture Notes in Electrical Engineering, 445–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25905-0_58.

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Aziz, Asnaf, Razaullah, and Iftikhar Hussain. "Design and Optimization of a Multi-echelon Supply Chain Network for Product Distribution with Cross-Route Costs and Traffic Factor Values." In Lecture Notes in Electrical Engineering, 381–91. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1059-1_36.

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Muñoz-Delgado, Gregorio, Javier Contreras, and José M. Arroyo. "Distribution System Expansion Planning." In Electric Distribution Network Planning, 1–39. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7056-3_1.

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Dahalan, Wardiah Mohd, and Hazlie Mokhlis. "Simultaneous Network Reconfiguration and Sizing of Distributed Generation." In Electric Distribution Network Planning, 279–98. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7056-3_10.

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Conference papers on the topic "Electric distribution network optimization"

1

Fan, Vivienne Hui, Ke Meng, and Zhaoyang Dong. "Stochastic Electric Vehicle Charging Optimization in Distribution Network." In 2021 6th Asia Conference on Power and Electrical Engineering (ACPEE). IEEE, 2021. http://dx.doi.org/10.1109/acpee51499.2021.9437062.

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Yang, Wenhai, Jing Li, Jianpeng Liu, and Yajing Gao. "The optimization research of electric car batteries on distribution network." In 2013 2nd International Symposium on Instrumentation & Measurement, Sensor Network and Automation (IMSNA). IEEE, 2013. http://dx.doi.org/10.1109/imsna.2013.6743295.

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Rashid, Numan, and Andrew Lapthorn. "Evaluation and optimization of network capacity utilization for electric distribution." In 2016 IEEE International Conference on Power System Technology (POWERCON). IEEE, 2016. http://dx.doi.org/10.1109/powercon.2016.7753983.

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Li, Chao-qun, Chun-lei Mao, and Zhi-qiang Yuan. "Research on the optimization configuration of electric secondary system of power distribution network." In 2012 China International Conference on Electricity Distribution (CICED). IEEE, 2012. http://dx.doi.org/10.1109/ciced.2012.6508548.

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He, Jie, Dong Liu, Guangsheng Yan, and Jun Yong. "Hierarchical optimization control strategy for electric vehicle in active distribution network." In 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2017. http://dx.doi.org/10.1109/ei2.2017.8245718.

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Singh, Sanjeev, Shailendra Kumar, Ujjwal K. Kalla, A. Chandra, and M. Saad. "Optimization of Rooftop PV System Deployment for LV Distribution Network." In 2021 International Conference on Sustainable Energy and Future Electric Transportation (SEFET). IEEE, 2021. http://dx.doi.org/10.1109/sefet48154.2021.9375688.

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Moya, Cristian Vera, and Jorge Mendoza Baeza. "Optimization of centralized charging strategy for electric vehicles in power distribution network." In 2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON). IEEE, 2017. http://dx.doi.org/10.1109/chilecon.2017.8229546.

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Li, Xin, Yanping Liu, Yi Liang, Shunqi Zeng, and Mingqi Li. "Evaluation and optimization of Electric Vehicle Load Acceptance Capacity of Distribution Network." In 2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2020. http://dx.doi.org/10.1109/ei250167.2020.9346622.

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Zhou, Kunpeng, Haixia Tang, Tian Liu, Feng Xiong, and Lei Wang. "Reactive power optimization in smart distribution network under power market." In 2015 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT). IEEE, 2015. http://dx.doi.org/10.1109/drpt.2015.7432310.

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Patel, Avani G., and Chintan Patel. "Distribution network reconfiguration for loss reduction." In 2016 International Conference on Electrical, Electronics and Optimization Techniques (ICEEOT). IEEE, 2016. http://dx.doi.org/10.1109/iceeot.2016.7755453.

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