arXiv:2505.05511cs.NEcs.LG2025-05

用随机森林与遗传算法优化园区储能配置,降本增效。

Economic Analysis and Optimization of Energy Storage Configuration for Park Power Systems Based on Random Forest and Genetic Algorithm

  • 用随机森林分析无储能时成本影响因素,发现购电成本关联最大。
  • 部署50kW/100kWh储能后,弃风弃光减少,运营成本降低。
  • 遗传算法优化配置与运行策略,三园区经济性均提升。

本研究针对不同条件下园区的经济性能展开分析,重点关注储能系统部署前后运营成本及负荷平衡变化。首先,基于随机森林模型分析无储能情况下的园区经济表现,以园区A为例,发现购电成本相关性最高,其次为光伏出力,表明风光发电是影响经济性的关键因素。随后,对配置50kW/100kWh储能系统的园区进行仿真,计算总成本与储能运行策略。结果表明,部署储能后各园区弃风弃光量下降,运营成本显著降低。最后,采用遗传算法优化各园区储能配置,通过适应度函数、交叉与变异操作优化运行策略。优化后,园区A、B、C的经济指标均得到提升。研究结果表明,通过优化储能配置,可有效降低园区成本,提升经济效益,推动电力系统可持续发展。

原文摘要 · Abstract (English)

This study aims to analyze the economic performance of various parks under different conditions, particularly focusing on the operational costs and power load balancing before and after the deployment of energy storage systems. Firstly, the economic performance of the parks without energy storage was analyzed using a random forest model. Taking Park A as an example, it was found that the cost had the greatest correlation with electricity purchase, followed by photovoltaic output, indicating that solar and wind power output are key factors affecting economic performance. Subsequently, the operation of the parks after the configuration of a 50kW/100kWh energy storage system was simulated, and the total cost and operation strategy of the energy storage system were calculated. The results showed that after the deployment of energy storage, the amount of wind and solar power curtailment in each park decreased, and the operational costs were reduced. Finally, a genetic algorithm was used to optimize the energy storage configuration of each park. The energy storage operation strategy was optimized through fitness functions, crossover operations, and mutation operations. After optimization, the economic indicators of Parks A, B, and C all improved. The research results indicate that by optimizing energy storage configuration, each park can reduce costs, enhance economic benefits, and achieve sustainable development of the power system.

储能优化随机森林遗传算法园区能源

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