考虑连续双向拍卖机制的楼宇群日前优化调度

Day-ahead optimal scheduling of buildings considering continuous double auction trading mechanism

作为城市能耗的主体,智能楼宇低碳高效运行对实现“双碳”目标有着重要意义。为了增强楼宇经济性并提升楼宇能源共享和分布式能源消纳,提出了一种考虑楼宇特性、电能交易的楼宇群分布式优化调度模型。在楼宇优化层面,建立了以经济性和温度舒适性需求为目标的楼宇多目标运行优化模型;在楼宇群能源共享层面,建立了端对端(peer to peer,P2P)楼宇交易市场,并提出了结合楼宇优化结果和市场风险的新型连续双向拍卖交易机制。通过将市场交易结果反馈至各楼宇优化层面,实现楼宇运行的迭代优化和楼宇群内能源的互动共享,利用鲁棒优化检验该模型在各类不确定场景中的有效性。仿真结果表明,在多场景中,所提的楼宇群分布式优化调度模型均能在优化楼宇经济性的同时,提升楼宇群能源互补和分布式能源消纳的能力。

As the main consumers of urban energy,the low carbon and efficient operation of intelligent buildings is crucial for achieving the goals of“peak carbon dioxide emissions and carbon neutrality”.To enhance building economics while improving energy sharing and the consumption of distributed energy resources,a distributed optimal scheduling model for buildings taking into account building characteristics and energy trading was proposed.At the building optimization level,a multi-objective building operation optimization model considering economic and temperature comfort requirements was established.At the energy sharing level,a peer-to-peer buildings trading market was set up,and a new continuous double auction trading mechanism combining building optimization results and market risks was proposed.This mechanism feeds back the results of market transactions to the optimization level of each building,achieving iterative optimization and energy sharing within buildings.Robust optimization was used to test the effectiveness of the model in various uncertainty scenarios.Simulation results show that the distributed optimal scheduling model can optimize building economics while enhancing energy complementarity and the consumption of distributed energy resources in various scenarios.