Optimal Dispatch Strategy for a Distribution Network Containing High-Density Photovoltaic Power Generation and Energy Storage under Multiple Scenarios

IF 2.1 Q2 ENGINEERING, MULTIDISCIPLINARY
Langbo Hou, Heng Chen, Jinjun Wang, Shichao Qiao, Gang Xu, Honggang Chen, Tao Liu
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引用次数: 0

Abstract

To better consume high-density photovoltaics, in this article, the application of energy storage devices in the distribution network not only realizes the peak shaving and valley filling of the electricity load but also relieves the pressure on the grid voltage generated by the distributed photovoltaic access. At the same time, photovoltaic power generation and energy storage cooperate and have an impact on the tidal distribution of the distribution network. Since photovoltaic output has uncertainty, the maximum photovoltaic output in each scenario is determined by the clustering algorithm, while the storage scheduling strategy is reasonably selected so the distribution network operates efficiently and stably. The tidal optimization of the distribution network is carried out with the objectives of minimizing network losses and voltage deviations, two objectives that are assigned comprehensive weights, and the optimization model is constructed by using a particle swarm algorithm to derive the optimal dispatching strategy of the distribution network with the cooperation of photovoltaic and energy storage. Finally, a model with 30 buses is simulated and the system is optimally dispatched under multiple scenarios to demonstrate the necessity of conducting coordinated optimal dispatch of photovoltaics and energy storage.
多场景下包含高密度光伏发电和储能的配电网最优调度策略
为了更好地消纳高密度光伏,在本文中,储能装置在配电网中的应用不仅实现了电力负荷的调峰填谷,而且缓解了分布式光伏接入对电网电压的压力。同时,光伏发电与储能相互配合,对配电网的潮汐分布产生影响。由于光伏输出具有不确定性,通过聚类算法确定各场景下的最大光伏输出,同时合理选择储能调度策略,使配电网高效稳定运行。以网损最小和电压偏差最小为目标,对配电网进行潮汐优化,并赋予综合权重,利用粒子群算法构建优化模型,推导出光伏与储能协同下配电网的最优调度策略。最后,对30辆公交车的模型进行了仿真,并在多种场景下对系统进行了优化调度,论证了光伏与储能协同优化调度的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Inventions
Inventions Engineering-Engineering (all)
CiteScore
4.80
自引率
11.80%
发文量
91
审稿时长
12 weeks
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