基于群智能和布谷鸟搜索的微电网能量调度系统

Priyadarshini Balasubramanyam, Vijay K. Sood
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引用次数: 0

摘要

由分布式能源组成的并网或孤岛微电网,需要一个电力管理/调度系统来控制电力调度并满足系统的负荷需求。在典型的微电网三级控制中,采用最优调度机制对本地der发电、从电网获取的能量和负荷消耗的能量进行管理。提出了一种新的智能电网日前调度混合优化技术。利用群体智能和布谷鸟搜索实现混合反馈PSO-MCS算法,以提高微电网产消者的性能并获得经济有效的解决方案。将混合反馈PSO-MCS (HFPSOMCS)算法与PSO和改进的CS (MCS)算法进行了比较。在MATLAB/Simulink和Python IDE平台上执行性能最好的算法,比较执行时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Hybrid Swarm Intelligence and Cuckoo Search Based Microgrid EMS for Optimal Energy Scheduling
A grid-connected or islanded microgrid made up of distributed energy sources (DERs), requires a power management/dispatch system to control the power dispatch and meet the load demand in the system. At the tertiary control level in a typical microgrid, an optimal scheduling mechanism is used to manage the power generated from the local DERs, energy drawn from the grid and energy consumption by the load. This paper proposes a novel hybrid optimization technique for day-ahead scheduling in a smart-grid. A Hybrid Feedback PSO-MCS algorithm is implemented using swarm intelligence and cuckoo search to enhance the performance and obtain a cost-effective solution for a microgrid prosumer. A comparison has been made of the Hybrid Feedback PSO-MCS (HFPSOMCS) algorithm with PSO and modified CS (MCS) algorithm. The best performing algorithm among the three is executed in MATLAB/Simulink and Python IDE platforms to compare the execution time.
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