为减少温室气体的排放,以风电为代表的清洁能源大规模接入电网。如何消纳高占比、波动剧烈的风电,成为现代电力系统所面临的重要问题。在此背景下,将多端柔性直流输电系统(VSC based multi-terminal HVDC,VSCMTDC)对功率的灵活调节能力...为减少温室气体的排放,以风电为代表的清洁能源大规模接入电网。如何消纳高占比、波动剧烈的风电,成为现代电力系统所面临的重要问题。在此背景下,将多端柔性直流输电系统(VSC based multi-terminal HVDC,VSCMTDC)对功率的灵活调节能力纳入安全约束机组组合(security-constrained unit commitment,SCUC)问题中进行调控。设计日前机组组合、短期实时调节和滚动重调节三段式配合的调度框架,并基于列与约束生成算法(column-andconstraint generation,C&CG)设计三层迭代求解方法。通过该方法解决了传统二阶段鲁棒性机组组合偏于保守的弊端,有效提高了风电消纳。为了充分利用VSC换流站能独立调节有功、无功的优势,在SCUC结果的基础上进行无功电压优化,并基于Benders分解算法进行求解,有效降低了系统网损。最后,将所提模型应用于改进IEEE 30节点系统算例,验证模型的有效性和可行性。展开更多
Task scheduling for electro-magnetic detection satellite is a typical combinatorial optimization problem. The count of constraints that need to be taken into account is of large scale. An algorithm combined integer pr...Task scheduling for electro-magnetic detection satellite is a typical combinatorial optimization problem. The count of constraints that need to be taken into account is of large scale. An algorithm combined integer programming with constraint programming is presented. This algorithm is deployed in this problem through two steps. The first step is to decompose the original problem into master and sub-problem using the logic-based Benders decomposition; then a circus combines master and sub-problem solving process together, and the connection between them is general Benders cut. This hybrid algorithm is tested by a set of derived experiments. The result is compared with corresponding outcomes generated by the strength Pareto evolutionary algorithm and the pure constraint programming solver GECODE, which is an open source software. These tests and comparisons yield promising effect.展开更多
区域能源中心(districtenergycentre,DEC)是多能流耦合的枢纽,主要实现多能流在区域级的优化传输和分配。随着能源市场管制的放松,以能源价格为调节手段引导需求侧进行互动响应有利于提升DEC的优化潜力。该文首先基于能量枢纽模型,建立...区域能源中心(districtenergycentre,DEC)是多能流耦合的枢纽,主要实现多能流在区域级的优化传输和分配。随着能源市场管制的放松,以能源价格为调节手段引导需求侧进行互动响应有利于提升DEC的优化潜力。该文首先基于能量枢纽模型,建立DEC的稳态能量流方程,探究功率平衡视角下的需求响应机理。考虑到价格调控下能源需求在时间上和类型上可相互转移,引入广义价格型需求侧响应(price based generalized demand response,P-GDR)的概念。同时,基于价格弹性及离散选择模型对P-GDR下能源需求的时空转移特性进行建模。并在此基础上建立DEC日前最优经济调度的混合整数非线性规划模型,通过广义Benders理论对其进行解耦求解。算例结果表明,考虑P-GDR有利于减少能源负荷峰谷差,并提高新能源消纳能力。此外,P-GDR下考虑能源负荷的可替代性更加符合用户行为实际,降低用户的能源购置成本。展开更多
文摘为减少温室气体的排放,以风电为代表的清洁能源大规模接入电网。如何消纳高占比、波动剧烈的风电,成为现代电力系统所面临的重要问题。在此背景下,将多端柔性直流输电系统(VSC based multi-terminal HVDC,VSCMTDC)对功率的灵活调节能力纳入安全约束机组组合(security-constrained unit commitment,SCUC)问题中进行调控。设计日前机组组合、短期实时调节和滚动重调节三段式配合的调度框架,并基于列与约束生成算法(column-andconstraint generation,C&CG)设计三层迭代求解方法。通过该方法解决了传统二阶段鲁棒性机组组合偏于保守的弊端,有效提高了风电消纳。为了充分利用VSC换流站能独立调节有功、无功的优势,在SCUC结果的基础上进行无功电压优化,并基于Benders分解算法进行求解,有效降低了系统网损。最后,将所提模型应用于改进IEEE 30节点系统算例,验证模型的有效性和可行性。
基金supported by the National Security Fundamental Research Foundation of China (61361)the National Natural Science Foundation of China (61104180)
文摘Task scheduling for electro-magnetic detection satellite is a typical combinatorial optimization problem. The count of constraints that need to be taken into account is of large scale. An algorithm combined integer programming with constraint programming is presented. This algorithm is deployed in this problem through two steps. The first step is to decompose the original problem into master and sub-problem using the logic-based Benders decomposition; then a circus combines master and sub-problem solving process together, and the connection between them is general Benders cut. This hybrid algorithm is tested by a set of derived experiments. The result is compared with corresponding outcomes generated by the strength Pareto evolutionary algorithm and the pure constraint programming solver GECODE, which is an open source software. These tests and comparisons yield promising effect.
文摘区域能源中心(districtenergycentre,DEC)是多能流耦合的枢纽,主要实现多能流在区域级的优化传输和分配。随着能源市场管制的放松,以能源价格为调节手段引导需求侧进行互动响应有利于提升DEC的优化潜力。该文首先基于能量枢纽模型,建立DEC的稳态能量流方程,探究功率平衡视角下的需求响应机理。考虑到价格调控下能源需求在时间上和类型上可相互转移,引入广义价格型需求侧响应(price based generalized demand response,P-GDR)的概念。同时,基于价格弹性及离散选择模型对P-GDR下能源需求的时空转移特性进行建模。并在此基础上建立DEC日前最优经济调度的混合整数非线性规划模型,通过广义Benders理论对其进行解耦求解。算例结果表明,考虑P-GDR有利于减少能源负荷峰谷差,并提高新能源消纳能力。此外,P-GDR下考虑能源负荷的可替代性更加符合用户行为实际,降低用户的能源购置成本。
