计及多能灵活性的含光热电站综合能源系统多目标分布鲁棒优化调度  

Multi-Objective Distributionally Robust Optimal Scheduling of Integrated Energy System with Concentrated Solar Power Plant Considering Multi-Energy Flexibility

作　　者：吴中孚 邓丽君 覃智君 WU Zhongfu;DENG Lijun;QIN Zhijun(Guangxi Key Laboratory of Power System Optimization and Energy Technology(Guangxi University),Nanning 530004,China;School of Electrical Engineering,Guangxi University,Nanning 530004,China;Electric Power Research Institute of China Southern Power Grid Company Limited,Guangzhou 510663,China)

机构地区：[1]广西电力系统最优化与节能技术重点实验室(广西大学),南宁市530004 [2]广西大学电气工程学院,南宁市530004 [3]南方电网科学研究院有限责任公司,广州市510663

出　　处：《电力建设》2024年第12期39-53,共15页Electric Power Construction

基　　金：广西自然科学基金项目(2021GXNSFAA220042)。

摘　　要：光热(concentrated solar power,CSP)电站是一种清洁、灵活的新型可再生能源设备,在综合能源系统(integrated energy system,IES)中引入CSP电站为推动能源向低碳转型提供了有效方式。然而,可再生能源的不确定性以及经济与环境的矛盾,给系统的经济、低碳、灵活和稳定运行带来了挑战。为此,提出一种计及多能灵活性的多目标分布鲁棒优化(distributionally robust optimization,DRO)调度策略。首先,针对可再生能源的不确定性,采用拉丁超立方抽样法结合Kantorovich场景削减法生成风电、光伏和CSP电站收集热功率的离散典型场景。其次,分别从能源供给、需求和转换环节对系统中灵活性资源进行量化,建立多能灵活性供需平衡约束。然后,以经济性和碳排放最优作为目标函数,建立基于多离散场景的两阶段多目标DRO模型,并采用列与约束生成算法进行迭代求解。针对多目标优化问题,通过ε-约束法求解得到帕累托前沿,并根据客观赋权法(criteria importance though intercrieria correlation,CRITIC)与优劣解距离法(technique for order preference by similarity to ideal solution,TOPSIS)(CRITICTOPSIS)综合决策出最终运行方案。仿真结果表明,所提模型有效提升了IES运行的灵活性裕度,达到了经济与环境的合理权衡。Concentrated solar power(CSP)plant is a new type of clean,flexible renewable energy equipment;integrating CSP plants into integrated energy systems(IES)drives the energy transition to low-carbon energy.However,the uncertainty of renewable energy sources and the tension between the economy and the environment pose challenges to the economic,low-carbon,flexible,and stable operation of the system.A multi-objective distributionally robust optimal(DRO)scheduling strategy considering multi-energy flexibility is proposed to this end.First,discrete typical scenarios of wind,photovoltaic,and CSP plants collecting thermal power are generated using the Latin hypercubic sampling method combined with the Kantorovich scenario reduction method for the uncertainty of renewable energy sources.Second,the flexibility resources in the system are quantified in terms of energy supply,demand,and conversion,and the multi-energy flexibility supply-demand balance constraints are established.Subsequently,a two-stage multi-objective DRO model based on multiple discrete scenarios is developed with economy and carbon emission optimization as the objective function and solved iteratively using the column-and-constraint generation algorithm.The multi-objective optimization problem is solved using the-constraint method to obtain the Pareto surface,and the final operating scheme is synthesized and determined according to the CRITIC-TOPSIS method.Finally,the simulation results show that the proposed model improves the flexibility margin of IES operation and achieves a reasonable trade-off between the economy and th environment.

关 键 词：光热电站 综合能源系统 灵活性 多目标分布鲁棒优化 优化调度 

分 类 号：TM73[电气工程—电力系统及自动化]