兼顾经济性与可靠性的新能源基地储能优化配置与模糊决策方法研究

曹茜; 王晓斌; 魏明宇; 李忠政; 李昌陵; 周红莲

曹茜,王晓斌,魏明宇,李忠政,李昌陵,周红莲.兼顾经济性与可靠性的新能源基地储能优化配置与模糊决策方法研究[J].电测与仪表,2026,63(2):102-110.
CAO Qian,WANG Xiaobin,WEI Mingyu,LI Zhongzheng,LI Changling,ZHOU Honglian.Research on the optimal allocation and fuzzy decision method of energy storage in the new energy base with both economy and reliability[J].Electrical Measurement & Instrumentation,2026,63(2):102-110.

兼顾经济性与可靠性的新能源基地储能优化配置与模糊决策方法研究

Research on the optimal allocation and fuzzy decision method of energy storage in the new energy base with both economy and reliability

DOI：10.19753/j.issn1001-1390.2026.02.011

中文关键词: 新能源基地储能配置外送多目标粒子群（MOPSO）模糊评价

英文关键词:new energy base, energy storage allocation, outbound delivery, MOPSO, fuzzy evaluation

基金项目:国家电网有限公司科技项目（SGXJJJ00NYJS2310023）

作者中文名	作者英文名	单位
曹茜	CAO Qian	国网新疆电力有限公司经济技术研究院
王晓斌	WANG Xiaobin	国网新疆电力有限公司经济技术研究院
魏明宇	WEI Mingyu	东北电力大学电气工程学院
李忠政	LI Zhongzheng	国网新疆电力有限公司经济技术研究院
李昌陵	LI Changling	国网新疆电力有限公司经济技术研究院
周红莲	ZHOU Honglian	国网新疆电力有限公司经济技术研究院

摘要点击次数: 440

中文摘要:

新能源基地合理配置储能对于提高输电走廊利用率、保障新能源电力高效、平稳外送具有重要意义。文章首先构建了新能源电源、有源调节电源及储能系统的有功输出模型，进而结合内需与外送电力周期特性，实现了新能源基地的时序生产模拟，在此基础上建立了以系统运行成本最小和外送电力保证率最大为目标，兼顾内需与外送的新能源基地储能优化配置模型，并采用多目标粒子群优化(multi-objective particle swarm optimization, MOPSO)算法对模型进行求解，获取最优Pareto解集。以模糊隶属度为基础，构建了储能配置满意度评价指标，并以此为依据实现了从最优Pareto解集到折衷储能配置方案的决策。以我国北方某新能源基地规划年场景为例，利用文章提出的优化配置与决策方法实现了兼顾经济性与供电可靠性的新能源基地的储能配置，结果表明文章算法配置得到的储能容量不仅能够在满足内需与外送的前提下显著降低系统运行成本，外送通道的供电保证率也进一步提高。

英文摘要:

The reasonable allocation of energy storage in new energy base is of great significance for improving the utilization rate of power transmission corridor and ensuring the efficient and stable outbound delivery of renewable energy electricity. This paper first constructs an active output model for new energy power sources, active regulation power sources, and energy storage system. Then, combined with the cyclical characteristics of local consumption and outbound delivery power, it achieves the time-series production simulation of the renewable energy base. On this basis, it establishes an energy storage optimization configuration model for renewable energy bases with the goal of minimizing system operating costs while maximizing both local consumption and power outbound delivery. A multi-objective particle swarm optimization (MOPSO) is used to solve the model to obtain the optimal Pareto solution set. Based on fuzzy membership degree, an energy storage satisfaction evaluation index is constructed, and decision-making from optimal Pareto solution set to compromise energy storage configuration is achieved. Taking the annual planning scenario of a new energy base in China as an example, the optimization configuration and decision-making method proposed in this paper is used to achieve energy storage configuration for the new energy base that balances economics and power supply reliability. The results show that the energy storage capacity obtained by the algorithm in this paper not only significantly reduces system operating costs while meeting domestic and export requirements, but also further increases the power supply guarantee rate of the export channel.

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