典型住宅离网可再生能源系统的最优能源调度

Hayder O. Alwan, Hamidreza Sadeghian, S. Abdelwahed
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引用次数: 2

摘要

需求侧管理(DSM)是一种传统的负荷调度方法,旨在使电力成本最小化。本文旨在提出一种针对一组住宅的需求侧管理方法,该方法可以用于响应日前电价信号,并最大限度地利用所产生的电力。这项工作是一个双场景的案例研究,四个家庭参与了一个单一馈线上的DSM项目。在第一种情况下,四户家庭都有本地光伏发电。在第二种情况下,光伏发电仅由同一供电网上的其他非参与家庭提供。仿真结果验证了所提出的调度算法能够有效地反映和影响用户的能耗行为,实现最优用电时间。出于实际考虑,我们还考虑了光伏发电对总电力成本的影响。分析表明,采用较高的惩罚因子可以显著提高光伏发电的利用效率,同时减少整个系统电压分布的波动。本文还研究了采用DSM算法对馈线总功率损耗的影响。该方案基于克隆选择算法(CSA)实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Energy scheduling of an off-grid renewable system used for typical residential households
Demand side management (DSM) is the conventional load scheduling method aimed at minimizing electricity costs This paper aims to present an approach for demand side management for a group of residential homes which can be used in response to day-ahead electricity price signal, and to maximize the usage of the power generated. This work is a dual-scenario case study of four households that are participants in a DSM program on a single feeder line. In the first scenario, each of the four households has local PV generation. In the second scenario, PV generation is provided only by other non-participant households on the same feeder. Simulation results confirm that the proposed scheduling algorithm can effectively reflect and affect user’s energy consumption behavior and achieve the optimal time of electricity usage. For practical consideration, we have also taken into consideration the impact of PV generation on the total electricity cost. Analysis shows that application of higher penalty factors can significantly improve the PV utilization efficiency while reducing fluctuations in the voltage profile for the entire system. The impact of applying a DSM algorithm on the total power losses of the feeder is also studied in this paper. The proposed solution is implemented based on the Clonal Selection Algorithm (CSA).
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