MPSO based energy dispatch strategy for microgrid considering TOU demand response

Ting-Yen Hsieh, Tsai-Hsiang Chen, K. Lian, C. Kuo, Jia-Sing Kang, P. Chen, Yung-Ruei Chang, Y. Ho
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引用次数: 1

Abstract

This paper introduces an effective and accurate method for scheduling the energy dispatch for a microgrid system. In contrast with previous work, the probabilistic models based on the famous Weibull probability density function have been utilized to calculate the intermittent power generation, especially for a microgrid system with high penetration of renewable generation. The modified particle swarm optimization (MPSO) was adopted to solve the optimization problem. All the case studies presented in the paper are based on the operational microgrid system, developed by the Institute of Nuclear Energy Research (INER) in Taiwan. The purchasing electric rate for renewable energy and the time of use (TOU) electricity prices, regulated by the Taiwan Power Company (TPC) have been included in the cost function in order to obtain the most economic solution. All outcomes are helpful to lower system operation cost and enhance the application of high penetration of renewable energy resources both on islanded and grid-connected modes.
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考虑分时电价需求响应的基于MPSO的微电网能量调度策略
本文介绍了一种有效而准确的微电网系统能量调度调度方法。与以往的研究不同,本文采用基于著名的威布尔概率密度函数的概率模型来计算间歇性发电,特别是对于可再生能源发电渗透率较高的微电网系统。采用改进粒子群算法(MPSO)求解优化问题。本文所介绍的所有案例都是基于台湾核能研究所(INER)开发的可运行微电网系统。为了获得最经济的解决方案,将台湾电力公司(TPC)管制的可再生能源购电费率与分时电价纳入成本函数。这些结果都有助于降低系统运行成本,提高可再生能源在孤岛和并网模式下的高渗透率应用。
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