基于智能体建模的新型电力系统下火电企业市场交易策略

Market Trading Strategy for Thermal Power Enterprise in New Power System Based on Agent Modeling

高比例新能源渗透情景下火电企业竞价策略研究对保障火电企业运营和推进新型电力系统建设具有重要意义。基于智能体建模框架,建立电力现货市场仿真模型和机组自学习决策模型。其中,环境模块建立了考虑源荷双侧不确定性的风光火储多方参与的电力现货市场出清模型;智能体模块将火电机组投标决策过程刻画为部分观测马尔科夫决策过程,采用深度确定性策略梯度算法求解。以HRP-38节点系统为例进行仿真分析,明晰高比例新能源下火电企业市场交易策略。结果表明:在不考虑火电机组提供辅助服务的前提下,随着新能源渗透率的提高,仍有部分位置独特且具有成本优势的火电机组拥有竞争力;预测误差增大将使大容量火电机组投标策略趋于保守,而小容量机组投标策略相反;火电机组在各类场景下均具有隐性共谋倾向,即彼此隐藏信息时仍同时提高报价。

It is of great significance to study the bidding strategy of thermal power enterprises under the scenario of high proportion of new energy penetration for guaranteeing the normal operation of thermal power enterprises and promoting the construction of new power system.Based on the multi-agent modeling framework,this paper establishes a power spot market simulation model and an unit self-learning decision model.In the environment module,a spot market clearing model with multiple participation of wind-solar-fire-storage is established considering the uncertainty of both sources and loads.The bidding decision-making process of thermal power units is described as a partially observed Markov decision-making process in the agent module and solved by improved Deep Deterministic Policy Gradient algorithm.Finally,a HRP-38 node system is simulated to clarify the market trading strategy for thermal power enterprises under a high proportion of new energy.The results show that,when the auxiliary services provided by thermal power units are not considered,with the increase of new energy penetration,some thermal power units with unique locations and cost advantages are still competitive;the increase of prediction error will make the bidding strategy of large-capacity thermal power units tend to be conservative,while the bidding strategy of small-capacity units is opposite;the thermal power units have implicit collusion tendency in all kinds of scenarios,that is,they will increase the quotation at the same time while hiding information from each other.