Scenario-Driven Optimization Strategy for Energy Storage Configuration in High-Proportion Renewable Energy Power Systems

Author:

Yang Hui1,Liu Qine1,Xiao Kang1,Guo Long1,Yang Lucheng1,Zou Hongbo2

Affiliation:

1. State Grid Hubei Electric Power Co., Ltd., Xiangyang Power Supply Company, Xiangyang 441000, China

2. College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China

Abstract

The output of renewable energy sources is characterized by random fluctuations, and considering scenarios with a stochastic renewable energy output is of great significance for energy storage planning. Existing scenario generation methods based on random sampling fail to account for the volatility and temporal characteristics of renewable energy output. To enhance photovoltaic (PV) absorption capacity and reduce the cost of planning distributed PV and energy storage systems, a scenario-driven optimization configuration strategy for energy storage in high-proportion renewable energy power systems is proposed, incorporating demand-side response and bidirectional dynamic reconfiguration strategies into the planning model. Firstly, this paper designs a time series scenario generation method for renewable energy output based on a Deep Belief Network (DBN) to fully explore the characteristics of renewable energy output. Then, considering various cost factors of PV and energy storage, a capacity determination model is established by analyzing the relationship between annual planning costs, PV connection capacity, energy storage installation capacity, and power. Case studies are conducted on the IEEE-33 node system to compare and analyze the impact of active distribution network strategies on the planning results of PV and energy storage equipment under different scenarios. The results show that by incorporating demand-side response and bidirectional dynamic reconfiguration strategies into the active distribution network, the selection and sizing of PV energy storage can significantly improve the PV absorption capacity, achieve the lowest planning cost, and address the issue of low voltage levels during periods of excess PV output due to bidirectional reconfiguration. This improves the economic efficiency and reliability of the operation of power distribution networks with a high proportion of PV, providing a solution for energy storage planning that considers the randomness of renewable energy output.

Funder

State Grid Hubei Electric Power Co., Ltd. Technology Project

Publisher

MDPI AG

Reference28 articles.

1. Photovoltaics and Energy Storage Integrated Flexible Direct Current Distribution Systems of Buildings: Definition, Technology Review, and Application;Liu;CSEE J. Power Energy Syst.,2023

2. Coordination for Multienergy Microgrids Using Multiagent Reinforcement Learning;Qiu;IEEE Trans. Ind. Inform.,2023

3. Han, J., Ji, X., Feng, J., Zhang, C., Dehghanian, P., and Yang, D. (2023, January 15–17). Optimized Dispatch of Integrated Energy System with Hydrogen Energy and Carbon Capture Under Demand Side Response Mechanisms. Proceedings of the 2023 3rd International Conference on Energy, Power and Electrical Engineering (EPEE), Wuhan, China.

4. Expected Benefits of Coordinated Energy Storage Operation in Stochastic Unit Commitment with Enhanced Deliverability of Reserves;Park;IEEE Access,2024

5. Multi-Objective Sizing of Solar-Wind-Hydro Hybrid Power System with Doubled Energy Storages Under Optimal Coordinated Operational Strategy;Guo;CSEE J. Power Energy Syst.,2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3