基于MILP和NSGA-Ⅱ的多类型储能协同调度优化

冯春贤; 王文学; 王一峰; 张飞飞; 袁龙; 范志昊; 陈衡

doi:10.19666/j.rlfd.202508008

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基于MILP和NSGA-Ⅱ的多类型储能协同调度优化

Thermal Power Generation Vol. 55, Issue 2, Pages: 180-192(2026)

更新时间：2026-08-07

- 基于MILP和NSGA-Ⅱ的多类型储能协同调度优化
- 作者机构：
  
  1. 国网河北省电力有限公司
  2. 华北电力大学能源动力与机械工程学院
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.202508008
  CLC： TM73
- Published：2026
- 稿件说明：
移动端阅览
[1]冯春贤,王文学,王一峰,等.基于MILP和NSGA-Ⅱ的多类型储能协同调度优化[J].热力发电,2026,55(02):180-192.
[1]冯春贤,王文学,王一峰,等.基于MILP和NSGA-Ⅱ的多类型储能协同调度优化[J].热力发电,2026,55(02):180-192. DOI： 10.19666/j.rlfd.202508008.

DOI：10.19666/j.rlfd.202508008.

摘要

【目的】为应对高比例新能源接入电网对灵活性与经济性的需求，提出一种面向峰谷电价与新能源波动的多类型储能协同调度优化模型及调度策略。【方法】基于混合整数线性规划算法（MILP）与非支配排序多目标遗传算法（NSGA-II），构建以系统总成本最低和新能源消纳率最高为双目标的优化调度模型，并通过河北地区不同季节典型日的负荷与风光出力数据验证模型的经济性与消纳效果。【结果】结果表明：该模型具有较好的鲁棒性，能够适应风光与负荷波动；春季最佳储能出力为3 000 MW，夏季、秋季、冬季均为2 000 MW，各季节特征日风光消纳率均保持在85%以上，系统总成本控制在15 000元水平。【结论】研究通过融合多季节场景、多类型储能及多目标优化，实现了经济性与新能源消纳水平的协同提升，有效增强了电网灵活性并降低了弃风弃光率。

Abstract

[Objective] To address the demand for flexibility and economy in power grids with high penetration of renewable energy

this paper proposes a coordinated dispatch optimization model and scheduling strategy for multitype energy storage systems considering peak-valley electricity prices and renewable energy fluctuations. [Methods] Based on mixed integer linear programming(MILP) and the non-dominated sorting genetic algorithm II(NSGAII)

a dual-objective optimization dispatch model is constructed

aiming to minimize system costs and maximize renewable energy utilization rate. The model is validated using typical daily load and wind-solar power output data from different seasons in Hebei region to evaluate its economic performance and renewable energy accommodation effectiveness. [Results] The results show that the model demonstrates good robustness and can adapt to fluctuations in wind-solar power and load. The optimal energy storage output is 3 000 MW in spring and 2 000 MW in summer

autumn

and winter. The renewable energy utilization rate remains above 85% in all seasons

and the total system cost is controlled at around 15 000 yuan. [Conclusion] By integrating multi-season scenarios

multi-type energy storage

and multi-objective optimization

this study achieves coordinated improvement in both economic performance and renewable energy accommodation

effectively enhancing grid flexibility and reducing the curtailment rate of wind and photovoltaic power.

关键词

Keywords

references

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