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Scheduling of Distributed Energy Resources in Active Distribution Networks Considering Combination of Techno-Economic and Environmental Objectives

机译:考虑技术经济目标与环境目标相结合的主动配电网分布式能源调度

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The use of the potential capacity of Electric Vehicles' (EVs) is regarded as one of the feasible solutions to boost the integration of Renewable Energy Sources (RES) into power systems. The incorporation of EVs' potential in smart distribution systems entails effective management of their power exchange with the grid in charging/discharging modes. The present study delves into a multi-objective optimization problem seeking for an optimum operation schedule of the grid, including EVs and Distributed Generation (DG) in the smart grid. The objective function is comprised of minimization of operation cost along with the reduction of emission. The Beta distribution and Weibull distribution approaches are employed to deal with the uncertainties of renewable resources in the model. The Cuckoo bird Optimization Algorithm (COA) is also employed to solve the problem. In addition, the fuzzy method is applied to the model to find the best solution to the multi-objective optimization problem. In order to evaluate and assess the performance of the proposed method, it is tested on a 33-bus distribution system for a 24-hour interval subject to satisfy the operational constraints of the power system, DG, and EVs. The obtained results convey the high performance of the proposed method in resource planning and improvement of distribution system efficiency through the optimal operation of EVs and DGs.
机译:利用电动汽车的潜在容量被认为是促进将可再生能源(RES)集成到电力系统中的可行解决方案之一。将电动汽车的潜力纳入智能配电系统中,需要在充电/放电模式下有效管理其与电网的电力交换。本研究深入研究了多目标优化问题,以寻求电网的最佳运行计划,包括智能电网中的EV和分布式发电(DG)。目标功能包括最小化运营成本以及减少排放。使用Beta分布和Weibull分布方法来处理模型中可再生资源的不确定性。杜鹃鸟优化算法(COA)也用于解决该问题。另外,将模糊方法应用于模型,以找到多目标优化问题的最佳解决方案。为了评估和评估所提出方法的性能,该方法在33总线配电系统上测试了24小时,以满足电力系统,DG和EV的运行约束。通过EV和DG的优化运行,所获得的结果传达了该方法在资源规划和提高配电系统效率方面的高性能。

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