2,926 research outputs found

    Spring search algorithm for simultaneous placement of distributed generation and capacitors

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    Purpose. In this paper, for simultaneous placement of distributed generation (DG) and capacitors, a new approach based on Spring Search Algorithm (SSA), is presented. This method is contained two stages using two sensitive index Sv and Ss. Sv and Ss are calculated according to nominal voltageand network losses. In the first stage, candidate buses are determined for installation DG and capacitors according to Sv and Ss. Then in the second stage, placement and sizing of distributed generation and capacitors are specified using SSA. The spring search algorithm is among the optimization algorithms developed by the idea of laws of nature and the search factors are a set of objects. The proposed algorithm is tested on 33-bus and 69-bus radial distribution networks. The test results indicate good performance of the proposed methodЦель. В статье для одновременного размещения распределенной генерации и конденсаторов представлен новый подход, основанный на "пружинном" алгоритме поиска (Spring Search Algorithm, SSA). Данный метод состоит из двух этапов с использованием двух показателей чувствительности Sv и Ss. Показатели чувствительности Sv и Ss рассчитываются в соответствии с номинальным напряжением и потерями в сети. На первом этапе определяются шины-кандидаты для установки распределенной генерации и конденсаторов согласно Sv и Ss. Затем, на втором этапе размещение и калибровка распределенной генерации и конденсаторов выполняются с использованием алгоритма SSA. "Пружинный" алгоритм поиска входит в число алгоритмов оптимизации, разработанных на основе идей законов природы, а факторы поиска представляют собой набор объектов. Предлагаемый алгоритм тестируется на радиальных распределительных сетях с 33 и 69 шинами. Результаты тестирования показывают хорошую эффективность предложенного метода

    Risk-Based Capacitor Placement in Distribution Networks

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    In this paper, the problem of sizing and placement of constant and switching capacitors in electrical distribution systems is modelled considering the load uncertainty. This model is formu- lated as a multicriteria mathematical problem. The risk of voltage violation is calculated, and the stability index is modelled using fuzzy logic and fuzzy equations. The instability risk is introduced as the deviation of our fuzzy-based stability index with respect to the stability margin. The capacitor placement objectives in our paper include: (i) minimizing investment and installation costs as well as loss cost; (ii) reducing the risk of voltage violation; and (iii) reducing the instability risk. The proposed mathematical model is solved using a multi-objective version of a genetic algorithm. The model is implemented on a distribution network, and the results of the experiment are discussed. The impacts of constant and switching capacitors are assessed separately and concurrently. Moreo- ver, the impact of uncertainty on the multi-objectives is determined based on a sensitivity analysis. It is demonstrated that the more the uncertainty is, the higher the system cost, the voltage risk and the instability risk are

    Optimal control of switched capacitor banks in Vietnam distribution network using integer genetic algorithm

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    In distribution network, power and energy losses can be reduced by using switched capacitor banks. The capacitor banks can be switched on or off based on voltage profile or power factor or using timers. Due to variation of load, it is necessary to control the capacitor banks switching in function of load curve. This paper presents the application of an integer genetic algorithm to determine the optimal number of banks corresponding with hourly load to minimize total active power losses of distribution feeders. The problem constraints include voltage profile and heat conditions which are taken into account to the objective function by a penalty function. In this application, the structure of chromosomes is a set of numbers of the capacitor banks hourly connected to the grid. The proposed formulation is validated by a feeder. The result shows that in some cases, the active power losses at maximum compensation are greater than the ones of optimal control compensation, and the voltage reaches a higher level than the maximum voltage limit. The optimal control of switched capacitor banks can reduce power and energy losses as well as ensure maximum voltage profile within the limit

    Reduction of Power Losses in the Distribution System by Controlling Tap Changing Transformer using the PSO Algorithm

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    Energy is an essential commodity for everyone, with electrical energy being the most preferred form. Unfortunately, non-renewable energy resources are gradually depleting, and renewable energy sources take several years to establish. To mitigate this problem, technology has shifted from non-renewable energy sources to electrical devices and machines, including household appliances like washing machines and air conditioners. However, the generation of electricity is still inadequate to meet the growing demand. This leads to two critical issues: Excessive power loss and inadequate voltage stability, making it difficult for power distribution companies to ensure a consistent and reliable power supply. The objective of this study is to tackle the issue of reduction and minimization of power dissipation By employing the PSO technique, adjusting the transformer tap settings. The proposed approach uses the 14-bus system as a reference and calculates losses for this system using the backward-forward sweeping technique

    Reactive optimization of transmission and distribution networks

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    Some of the challenges associated with the multi-objective optimization on a modern power system were addressed in this work. Optimization of reactive resources was performed in order to simultaneously optimize several criteria: transmission losses, distribution losses, voltage stability, etc. The optimization was performed simultaneously on the entire power system; transmission and distribution subsystems included. The inherent physical complexity of modeling together transmission and distribution systems was considered first. After considering all pros and cons for such a task, a model of the entire power system was successfully developed. The inherent mathematical complexity of high-dimensional optimization space was handled by introducing the decoupling principle. System is first decoupled in several independent models and optimizations were performed on each part of the system. An algorithm is developed that properly combines the independent solutions to reach the overall system optima. The principle of algorithm synthesis is used to reduce the size of the solution space. Deterministic algorithms are used to locate the local optima which are subsequently refined by probabilistic algorithm. The algorithm is applied on a "real-life" test system and it is shown that the obtained solutions outperform the solution obtained with the conventional algorithms.Ph.D.Committee Chair: Begovic, Miroslav; Committee Member: Divan, Deepakraj; Committee Member: Dorsey, John; Committee Member: Ferri, Bonnie; Committee Member: Lambert, Fran

    Dual techniques of load shedding and capacitor placement considering load models for optimal distribution system

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    Voltage stability represents one of the main issues in electrical power system. Under voltage load shedding (UVLS) has long been regarded as one of the most successful techniques to prevent the voltage collapse. However, the ordinary load shedding schemes do not consider the different load models and decreasing in the ‎economic cost that resulted from load disconnection, so the dual techniques of load shedding with reactive compensation are needed. Usually loads being modeled as constant power, while in fact of load flow the various load models are utilized. An investigation of optimal dual load shedding with reactive compensation for distribution system based on direct backward forward sweep method (DBFSM) load flow along with a comparison among the other load models are presented in this paper. The teaching learning-based optimization (TLBO) algorithm is executed in order to reduce power losses and enhance the voltage profile. This algorithm is tested and applied to IEEE-16 bus distribution test system to find the optimal superior capacitor size and placement while minimizing load shading for the network. Five different load shedding sequences are considered and the optimization performance of load models demonstrated the comparison through MATLAB program

    Optimization of the Thyristor Controlled Phase Shifting Transformer using PSO Algorithm

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    The increase of power system demand leads to the change in voltage profile, reliability requirement and system robustness against disturbance. The voltage profile can be improved by providing a source of reactive power through the addition of new power plants, capacitor banks, or implementation of Flexible AC Transmission System (FACTS) devices such as Static VAR Compensator (SVC), Unified Power Flow Control (UPFC), Thyristor Controlled Series Capacitor (TCSC), Thyristor Controlled Phase Shifting Transformer (TCPST), and many others. Determination of optimal location and sizing of device injection is paramount to produce the best improvement of voltage profile and power losses reduction. In this paper, optimization of the combined advantages of TCPST and TCSC has been investigated using Particle Swarm Optimization (PSO) algorithm, being applied to the 30-bus system IEEE standard. The effectiveness of the placement and sizing of TCPST-TCSC combination has been compared to the implementation of capacitor banks. The result showed that the combination of TCPST-TCSC resulted in more effective improvement of system power losses condition than the implementation of capacitor banks.  The power losses reduction of 46.47% and 42.03% have been obtained using of TCPST-TCSC combination and capacitor banks respectively. The TCPST-TCSC and Capacitor Bank implementations by using PSO algorithm have also been compared with the implementation of Static VAR Compensator (SVC) using Artificial Bee Colony (ABC) Algorithm. The implementation of the TCSC-TCPST compensation with PSO algorithm have gave a better result than using the capacitor bank with PSO algorithm and SVC with the ABC algorithm
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