
1.宁夏大学 电子与电气工程学院,银川 750021
2.宁夏电力能源安全重点实验室,银川 750004
Received:15 April 2025,
Revised:2025-07-11,
Published Online:17 September 2025,
Published:25 September 2025
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张元曦,杨国华,马龙腾等.基于改进DE算法的园区微电网风光储优化配置[J].综合智慧能源,2025,47(09):71-79.
ZHANG Yuanxi,YANG Guohua,MA Longteng,et al.Optimized wind-solar-storage configuration of industrial park microgrids based on improved differential evolution algorithm[J].BLASTING,2025,47(09):71-79.
张元曦,杨国华,马龙腾等.基于改进DE算法的园区微电网风光储优化配置[J].综合智慧能源,2025,47(09):71-79. DOI: 10.3969/j.issn.2097-0706.2025.09.008.
ZHANG Yuanxi,YANG Guohua,MA Longteng,et al.Optimized wind-solar-storage configuration of industrial park microgrids based on improved differential evolution algorithm[J].BLASTING,2025,47(09):71-79. DOI: 10.3969/j.issn.2097-0706.2025.09.008.
针对传统差分进化(DE)算法在多园区微电网风光储系统优化配置中易陷入局部最优、物理可解释性弱的局限,提出了改进DE算法与物理机理融合的优化框架。构建以日供电成本最小化为目标的风光储配置模型,嵌入储能充放电效率及荷电状态约束;设计三重自适应改进DE算法:采用双阶段线性衰减机制调节缩放因子和交叉概率,融合精英历史经验复用策略提升收敛速度,引入双模振荡扰动增强多样性;从源荷适配的物理本质出发,剖析储能配置与风光负荷曲线的内在规律。算例表明:改进DE算法较传统DE、粒子群和遗传算法效果更好,联合运行成本降至15 424.06元;联合运行的供电成本较独立运行总和的供电成本降低6.11%,储能总功率与容量分别节省30.77%和50.00%,弃风弃光量归零;储能配置具有最大单时段弃电量决定功率、最大连续弃电总量决定容量的普适规律,基于此的B园区物理估算方案成本为5 065.43元,较优化算法结果(5 066.22元)更低。通过算法改进与物理规律挖掘,为风光储系统优化配置提供了高精度、强可解释性的解决方案。
To address the limitations of traditional differential evolution (DE) algorithms—susceptibility to local optima and weak physical interpretability—in the optimal configuration of wind-solar-storage systems in multi-park microgrids, an optimization framework integrating an improved DE algorithm with physical mechanisms was proposed. A wind-solar-storage configuration model was established with the objective of minimizing daily power supply costs, incorporating constraints on energy storage charging/discharging efficiency and state of charge. A triple-adaptive improved DE algorithm was designed: a dual-phase linear decay mechanism was used to adjust the scaling factor and crossover probability, an elite historical experience reuse strategy was integrated to enhance convergence speed, and a dual-mode oscillatory disturbance was introduced to increase population diversity. From the physical essence of source-load matching, the intrinsic patterns between energy storage configuration and wind-solar load curves were analyzed. Case studies showed that: the improved DE algorithm outperformed traditional DE, particle swarm optimization, and genetic algorithms, reducing the joint operating costs to 15 424.06 yuan; the joint operation reduced the power supply cost by 6.11% compared to the sum of independent operations and saved 30.77% of total energy storage power and 50.00% of capacity, with wind and solar curtailment reduced to zero; energy storage configuration followed a universal pattern that the power rating was determined by the maximum single-interval curtailment, and the capacity was determined by the maximum consecutive curtailment. Based on this, the physical estimation scheme for Park B reduced the coet to 5 065.43 yuan, which was lower than the result obtained by the optimization algorithm (5 066.22 yuan). By combining algorithm improvement with the exploration of physical patterns, a high-precision and strongly interpretable solution for the optimal configuration of wind-solar-storage systems is provided.
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