Optimal Sizing of hybrid grid-connected energy system with demand side scheduling

Majdi Saidi, Zhongliang Li, S. B. Elghali, R. Outbib
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引用次数: 1

Abstract

With the accelerated development of the renewable energy and smart grid technologies, more and more electricity consumers are planning integrating local renewable systems for economical and ecological reasons. To be efficient, the system has to be sized optimally in consideration of both energy generation and consumption. Meanwhile, the demand side management subject to consume energy more flexibly has been drawing more and more attention. In this study, an optimal sizing strategy is proposed for grid-connected PV/WT hybrid system with demand side scheduling. To do this, the energy consumption related to different load types are modeled for scheduling. A bi-level optimization framework is then proposed to realize load scheduling within the optimal sizing. In the framework, down-level is for load scheduling and achieved by genetic algorithm, while the up-level is dedicated to optimal sizing and realized by efficient global optimization algorithm. The proposed framework is verified through a case study for an industrial company, whose objective is to size one PV/WT system to compensate the local energy consumption. The obtained results show the benefits of combining system sizing with load scheduling.
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考虑需求侧调度的混合并网能源系统最优规模
随着可再生能源和智能电网技术的加速发展,越来越多的电力用户出于经济和生态的考虑,计划将当地的可再生能源系统整合起来。为了提高效率,系统的大小必须考虑到能源的产生和消耗。同时,以灵活消费能源为主体的需求侧管理也越来越受到重视。本文研究了具有需求侧调度的并网PV/WT混合系统的最优规模策略。为此,对与不同负载类型相关的能耗进行建模以进行调度。在此基础上,提出了一种双层优化框架来实现最优规模下的负载调度。其中,下一级用于负载调度,采用遗传算法实现;上一级用于优化规模,采用高效的全局优化算法实现。通过对一家工业公司的案例研究验证了所提出的框架,该公司的目标是确定一个PV/WT系统的规模,以补偿当地的能源消耗。得到的结果表明,将系统分级与负载调度相结合的好处。
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