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Multi-objective stochastic model for joint optimal allocation of DG units and network reconfiguration from DG owner's and DisCo's perspectives

机译:从DG所有者和DisCo的角度考虑DG单元的最优分配和网络重新配置的多目标随机模型

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Optimal distribution system reconfiguration (DSR) and distribution generation (DG) allocation are viable solutions for improvement of technical and economic aspects of distribution systems. This paper proposes a stochastic multi-objective DSR (SMO-DSR) model, aims to maximize the DG owner's profit and minimizes the distribution company's (DisCo's) costs. The uncertainties of wind power generation, electricity price, and demand are handled via scenario based approach. The proposed SMO-DSR model is solved via epsilon-constraint method and the best compromise solution is selected by fuzzy satisfying criterion. The model is a mixed integer non-linear programing (MINLP) problem which is implemented on IEEE 33 bus distribution system in General Algebraic Modeling System (GAMS) environment. To show the effectiveness of the proposed SMO-DSR approach, it is studied in different cases. A sensitivity analysis is also performed to show the effect of contract price of wind energy on the objectives of DisCo and DG owner. The obtained results substantiate the interaction between the DSR and DG allocation problems. Also, it is shown that the contract price of wind energy considerably influences both DG owner and DisCo schedules. Besides, when a compromise is made between the DG owner's profit and DisCo's cost, the power losses of the network is reduced. (C) 2018 Elsevier Ltd. All rights reserved.
机译:最佳配电系统重新配置(DSR)和配电生成(DG)分配是改善配电系统技术和经济方面的可行解决方案。本文提出了一种随机多目标DSR(SMO-DSR)模型,旨在最大化DG所有者的利润,并最小化配电公司(DisCo)的成本。风力发电,电价和需求的不确定性通过基于情景的方法来处理。通过ε约束方法对提出的SMO-DSR模型进行求解,并通过模糊满足准则选择最佳折衷方案。该模型是混合整数非线性编程(MINLP)问题,该问题在通用代数建模系统(GAMS)环境中的IEEE 33总线分配系统上实现。为了显示所提出的SMO-DSR方法的有效性,在不同情况下进行了研究。还进行了敏感性分析,以显示风能合同价格对DisCo和DG所有者的目标的影响。获得的结果证实了DSR和DG分配问题之间的相互作用。此外,还表明,风能的合同价格对DG所有者和DisCo时间表都有很大影响。此外,当在DG所有者的利润和DisCo的成本之间做出折衷时,可以减少网络的功率损耗。 (C)2018 Elsevier Ltd.保留所有权利。

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