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考虑综合经济性的风光配电网储能优化配置

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在配电网中配置储能系统可以有效缓解风光接入对配电网产生的影响,提升对风光的消纳能力、减少电压偏差等,而储能接入的位置和容量不同会对配电网产生不同的影响.首先分析储能建设过程中的主要费用,考虑基于分时电价下的网损成本和峰谷差收益,以年综合成本、配电网的日节点电压偏差和最小为目标,建立配电网储能选址定容模型,采用改进多目标遗传二代算法(improved multi-objective nondominated sorting genetic Ⅱ algorithm,INSGA-Ⅱ)对模型进行求解,利用改进理想点决策法(improved ideal point based decision,IIPBD)来选取最优配置方案,最后在IEEE-33节点模型中对方案进行验证.仿真结果表明:使用INSGA-Ⅱ算法进行求解时最终决策出的储能配置方案实现了成本最小,并且显著提升了电压的稳定性,验证了改进后算法的优良性和所提出的储能优化配置方案的有效性.
Consider the Optimal Configuration of Energy Storage in Wind-solar Distribution Networks with Comprehensive Economy
Configuration of energy storage system in the distribution network can effectively alleviate the impact of wind access on the distribution network,enhance the ability to consume wind,reduce voltage deviation,etc.,and different locations and capacities of energy storage access will have different impacts on the distribution network.Firstly,the main costs in the process of energy storage construction was analyzed,the cost of network loss and peak-valley difference revenue were considered based on time-sharing tariff,taking the annual comprehensive cost,the daily node voltage deviation of the distribution network and the minimum as the goal,the distribution network energy storage siting and capacity model was established,and the improved multi-objective genetic second generation Ⅱ algorithm(INSGA-Ⅱ)was adopted to solve the model,improved ideal point based decision(IIPBD)was used to select the optimal configuration scheme.Finally,the scheme was verified in the IEEE-33 node model.The simulation results show that the final decision-making energy storage configuration scheme using the INSGA-Ⅱ algorithm minimizes the cost and significantly improves the voltage stability,which verifies the improved algorithm and the proposed energy storage model.The improved algorithm and the effectiveness of the proposed optimized energy storage configuration scheme are verified.

distribution networkenergy storage accesstime-sharing tariffimproved multi-objective genetic second generation Ⅱ algorithm(INSGA-Ⅱ)improved ideal point based decision(IIPBD)

闫群民、李召、马永翔、张芮华、张翔

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陕西理工大学电气工程学院,汉中 723000

配电网 储能系统 分时电价 改进多目标遗传二代算法(INSGA-Ⅱ) 改进理想点决策法(IIPBD)

国家自然科学基金一般面上项目陕西省教育厅重点科学研究项目

6217614620JS018

2024

10.12404/j.issn.1671-1815.2304820

科学技术与工程
中国技术经济学会

科学技术与工程

CSTPCD北大核心
影响因子：0.338
ISSN：1671-1815
年,卷(期)：2024.24(12)
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