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Investigation in economic analysis of microgrids based on renewable energy uncertainty and demand response in the electricity market

机译:基于可再生能源不确定性和电力市场需求响应的微电网经济分析研究

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Owing to the increasing utilization of renewable resources such as wind turbines (WT), photovoltaic (PV) into a microgrid (MG), optimal planning has become important to satisfy the energy demand due to inherent uncertainties. This paper proposes a new model of planning based on renewable energy uncertainty and demand response and electric vehicles (EVs) in order to minimize the electricity market & rsquo;s total cost. Considering uncertainty challenges, energy storage system (ESS) and demand response programs based on time-of-use (TOU) are employed as a solution for managing the power flow in MG to warranty the essential load supporting and voltage stability and satisfy electrical and heat demands. Moreover, in this paper, the influence of price-based demand response (DR) for industrial, commercial, and residential loads is taken into account. Finally, the proposed problem is modeled as an optimization problem while the related decision variables are adjusted by a modified version of virus colony search (VCS) algorithm based on chaos theory in order to increase the exploitation and exploration terms. The proposed approach is tested on an MG system with several scenarios through analyzing the effect of DR programs based on the total cost reduction. As shown in the simulation results, DR highly reduced total cost (20e26% related to the case without DR), in which voltage dip (maximum 1.4%) and power deviation (maximum 1.2%) were enhanced.(c) 2021 Elsevier Ltd. All rights reserved.
机译:由于诸如风力涡轮机(WT)等可再生资源的利用率增加,光伏(PV)进入微电网(MG),最佳规划使由于固有的不确定性来满足能源需求变得重要。本文提出了一种基于可再生能源不确定性和需求响应和电动汽车(EVS)的新规划模式,以最大限度地减少电力市场和rsquo;总费用。考虑到不确定性挑战,能量存储系统(ESS)和基于使用时间(TOU)的需求响应程序是用于管理MG中的功率流量的解决方案,以保证基本负载支撑和电压稳定性,满足电气和热量需要。此外,在本文中,考虑了基于基于价格的需求响应(DR)对工业,商业和住宅负荷的影响。最后,提出的问题被建模为优化问题,而基于混沌理论的病毒群搜索(VCS)算法的修改版本调整相关决策变量,以增加剥削和探索术语。通过根据总成本降低分析DR程序的效果,在MG系统上测试所提出的方法。如模拟结果所示,DR高度降低总成本(与案例有关的20E26%而无DR),其中增强了电压浸(最大1.4%)和功率偏差(最大1.2%)。(c)2021 Elsevier Ltd.版权所有。

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