An economic dispatch problem for power system with wind power is discussed.Using discrete scenario to describe uncertain wind powers,a threshold is given to identify bad scenario set.The bad-scenario-set robust econom...An economic dispatch problem for power system with wind power is discussed.Using discrete scenario to describe uncertain wind powers,a threshold is given to identify bad scenario set.The bad-scenario-set robust economic dispatch model is established to minimize the total penalties on bad scenarios.A specialized hybrid particle swarm optimization(PSO)algorithm is developed through hybridizing simulated annealing(SA)operators.The SA operators are performed according to a scenario-oriented adaptive search rule in a neighborhood which is constructed based on the unit commitment constraints.Finally,an experiment is conducted.The computational results show that the developed algorithm outperforms the existing algorithms.展开更多
This paper proposes a decentralized robust two-stage dispatch framework for multi-area integrated electric-gas systems (M-IEGSs), with the consideration of Weymouth and linepack equations of tie-pipelines. The overall...This paper proposes a decentralized robust two-stage dispatch framework for multi-area integrated electric-gas systems (M-IEGSs), with the consideration of Weymouth and linepack equations of tie-pipelines. The overall methodology includes the equivalent conversion for the robust two-stage program and the decentralized optimization for the equivalent form. To obtain a tractable and equivalent counterpart for the robust two-stage program, a quadruple-loop procedure based on the column-and-constraint generation (C&CG) and the penalty convex-concave procedure (P-CCP) algorithms is derived, resulting in a series of mixed integer second-order cone programs (MISOCPs). Then, an improved I-ADMM is proposed to realize the decentralized optimization for MISOCPs. Moreover, three acceleration methods are devised to reduce the computation burden. Simulation results validate the effectiveness of the proposed methodology and corresponding acceleration measures.展开更多
为充分利用源荷双侧资源实现低碳调度目标,文中提出一种基于信息间隙决策理论(Information Gap Decision Theory,IGDT)的含碳捕集发电厂和热负荷集群电热联合系统优化调度方法。在源侧建立具有储液式碳捕集装置的热电联产电厂模型,分析...为充分利用源荷双侧资源实现低碳调度目标,文中提出一种基于信息间隙决策理论(Information Gap Decision Theory,IGDT)的含碳捕集发电厂和热负荷集群电热联合系统优化调度方法。在源侧建立具有储液式碳捕集装置的热电联产电厂模型,分析其净出力特性。在负荷侧提出考虑用户舒适度的住宅热负荷聚合模型。通过不确定集对风电预测误差的不确定性进行建模,提出一种基于风险规避型IGDT的电热联合系统优化调度模型,可同时满足系统鲁棒性和经济性要求。结果表明,所提模型可有效提高风电消纳水平,提升系统运行的经济性。展开更多
基金supported by the National Natural Science Foundation of China(62173219,62073210).
文摘An economic dispatch problem for power system with wind power is discussed.Using discrete scenario to describe uncertain wind powers,a threshold is given to identify bad scenario set.The bad-scenario-set robust economic dispatch model is established to minimize the total penalties on bad scenarios.A specialized hybrid particle swarm optimization(PSO)algorithm is developed through hybridizing simulated annealing(SA)operators.The SA operators are performed according to a scenario-oriented adaptive search rule in a neighborhood which is constructed based on the unit commitment constraints.Finally,an experiment is conducted.The computational results show that the developed algorithm outperforms the existing algorithms.
文摘This paper proposes a decentralized robust two-stage dispatch framework for multi-area integrated electric-gas systems (M-IEGSs), with the consideration of Weymouth and linepack equations of tie-pipelines. The overall methodology includes the equivalent conversion for the robust two-stage program and the decentralized optimization for the equivalent form. To obtain a tractable and equivalent counterpart for the robust two-stage program, a quadruple-loop procedure based on the column-and-constraint generation (C&CG) and the penalty convex-concave procedure (P-CCP) algorithms is derived, resulting in a series of mixed integer second-order cone programs (MISOCPs). Then, an improved I-ADMM is proposed to realize the decentralized optimization for MISOCPs. Moreover, three acceleration methods are devised to reduce the computation burden. Simulation results validate the effectiveness of the proposed methodology and corresponding acceleration measures.
文摘为充分利用源荷双侧资源实现低碳调度目标,文中提出一种基于信息间隙决策理论(Information Gap Decision Theory,IGDT)的含碳捕集发电厂和热负荷集群电热联合系统优化调度方法。在源侧建立具有储液式碳捕集装置的热电联产电厂模型,分析其净出力特性。在负荷侧提出考虑用户舒适度的住宅热负荷聚合模型。通过不确定集对风电预测误差的不确定性进行建模,提出一种基于风险规避型IGDT的电热联合系统优化调度模型,可同时满足系统鲁棒性和经济性要求。结果表明,所提模型可有效提高风电消纳水平,提升系统运行的经济性。
