基于双碳目标的主动配电网优化调度方法研究

肖龙海; 刘继文; 袁国珍; 俞海良; 樊卡

肖龙海,刘继文,袁国珍,俞海良,樊卡.基于双碳目标的主动配电网优化调度方法研究[J].电测与仪表,2026,63(2):45-53.
XIAO Longhai,LIU Jiwen,YUAN Guozhen,YU Hailiang,FAN Ka.Research on active distribution network optimal and scheduling method based on carbon peaking and carbon neutrality goal[J].Electrical Measurement & Instrumentation,2026,63(2):45-53.

基于双碳目标的主动配电网优化调度方法研究

Research on active distribution network optimal and scheduling method based on carbon peaking and carbon neutrality goal

DOI：10.19753/j.issn1001-1390.2026.02.005

中文关键词: 双碳目标分布式电源配电网智能调度日前-日内调度 NSGA-III算法

英文关键词:carbon peaking and carbon neutrality goal, distributed power supply, distribution network, intelligent scheduling, day-ahead and intra-day scheduling, NSGA-III algorithm

基金项目:国家电网科技项目：（5400-202219152A-1-1-ZN）

作者中文名	作者英文名	单位
肖龙海	XIAO Longhai	国网浙江海宁市供电有限公司
刘继文	LIU Jiwen	国网浙江海宁市供电有限公司
袁国珍	YUAN Guozhen	国网浙江海宁市供电有限公司
俞海良	YU Hailiang	国网浙江海宁市供电有限公司
樊卡	FAN Ka	国网浙江海宁市供电有限公司

摘要点击次数: 483

中文摘要:

新的电力系统和双碳目标推动了主动配电网智能调度方法的发展。针对现有主动配电网智能调度方法存在的经济性和低碳型差等问题，提出了一种基于日前-日内调度的主动配电网智能调度方法。日前配电网调度模型采用双层结构，上层以主网购电、网损、储能、运维、碳排放和峰谷惩罚等成本综合最优构建。下层采用峰谷罚款、碳排放和电动汽车充电等成本的综合最优构建。日内配电网优化调度模型通过日前上层模型目标和可中断负荷补偿等成本综合最优构建。通过改进的非支配排序遗传算法III (non-dominated sorting genetic algorithm-III, NSGA-III)求解模型。通过算例对所提方法的优越性进行验证。结果表明，所提方法兼顾了经济性和低碳性。通过日前和日内联合调度，有效解决光伏出力波动问题，优化配电网运行性能。总求解时间412.11 s，总成本50 665.60元，碳排放成本1 583.50元。可为双碳目标实现提供一定的助力。

英文摘要:

The novel power system and dual carbon goals have driven the development of intelligent scheduling methods for active distribution network. Aiming at the economic and low-carbon shortcomings of existing intelligent scheduling methods for active distribution network, a proactive intelligent scheduling method for distribution network based on day-ahead and intra-day scheduling has been proposed. The current distribution network scheduling model adopts a double-layer structure, with the upper layer being constructed based on the comprehensive optimization of costs such as main network electricity purchase, network loss, energy storage, operation and maintenance, carbon emissions, and peak valley penalties. The lower layer adopts a comprehensive optimal construction of peak valley fines, carbon emissions, and electric vehicle charging costs. The optimal scheduling model of intra-day distribution network is constructed by means of day-ahead upper level model objectives and interruptible load compensation costs. The model is solved through an improved non-dominated sorting genetic algorithm-III（NSGA-III）. The superiority of the proposed method is verified through numerical examples. The results indicate that, the proposed method takes into account both economic and low-carbon aspects. Through joint day-ahead and intra-day scheduling, the problem of photovoltaic output fluctuations has been effectively solved, and the operational performance of the distribution network has been optimized. The total solution time is 412.11 seconds, the total cost is CNY 50 665.60, and the carbon emission cost is CNY 1 583.50. It can provide certain assistance for achieving the dual carbon goal.

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