基于混合机器学习的新型电力系统电力电量平衡风险评估方法OA
Risk assessment method for power and energy balance of novel power system baseon integrating machine learning
为了解决极端情况对电力系统电力电量平衡的冲击问题,提出了一种基于混合机器学习的新型电力系统电力电量平衡风险评估方法.建立了新型电力系统的运行模型,其中包含新能源出力模型、储能模型、发电机组和线路潮流模型,考虑以极端天气为主的极端情况,对极端天气场景进行定义,提出新型电力系统面对极端情况下的电力电量不平衡指标,提出了一种混合机器学习优化(integrating machine learning optimi-zation,ILO)方法求解电力电量不平衡.两阶段 ILO 法包括用于精确策略初始化的模仿学习(imitative learn-ing,IL)阶段和用于高效微调的强化学习(reinforcement learning,RL)阶段.基于 PJM5 节点系统和改进的IEEE118 节点系统的算例仿真结果表明,所提方法可以对电力电量不平衡进行量化定义,并且提高了电力电量平衡风险评估的效率和稳定性.
To address the impact of extreme situations on the power and energy balance of the novel power system,a risk assessment method for power and energy balance of the novel power system based on integrating machine learning is proposed.An operation model of the novel power system is established,which includes the output model of new energy sources,the energy storage model,the generator set and the power flow model of transmission lines.Considering extreme situations mainly dominated by extreme weather,the extreme weather scenarios are defined,and the power and energy imbalance indicators of the novel power system under extreme situations are proposed.Anintegrating machine learning optimization(ILO)method is proposed to solve the power and energy imbalance.The two-stage ILO method includes an imitative learning(IL)stage for accurate strategy initialization and a rein-forcement learning(RL)stage for efficient fine-tuning.The simulation results based on the PJM5-bus system and the improved IEEE118-bus system show that the proposed method can quantitatively define the power and energy imbalance,and improve the efficiency and stability of the risk assessment of power and energy balance.
张琳娜;李强;荆永明;梁燕;刘红丽;王凯凯;乐健
国网山西省电力公司,太原 030021国网山西省电力公司经济技术研究院,太原 030021国网山西省电力公司经济技术研究院,太原 030021国网山西省电力公司经济技术研究院,太原 030021国网山西省电力公司经济技术研究院,太原 030021国网山西省电力公司经济技术研究院,太原 030021武汉大学 电气与自动化学院,武汉 430072
信息技术与安全科学
新型电力系统电力电量平衡风险评估混合机器学习
novel power systempower and energy balancerisk assessmentintegrating machine learning
《电测与仪表》 2026 (6)
31-40,10
国网山西省电力有限公司科技项目(52053324000B)
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