机译:基于拉格朗日乘数最优选择方法的分布式实时需求响应
Tsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China;
Tsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China;
Tsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China;
Tsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China;
Tsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China;
Tsinghua Univ, Dept Elect Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China;
Demand response (DR); Distributed algorithm; Lagrangian multiplier optimal selection (LMOS); Lagrangian relaxation (LR); Sensitivity analysis;
机译:基于神经网络的Lagrange乘法器选择,用于智能网格中的分布式需求响应
机译:考虑容量曲线和基于实时价格的需求响应的分布式发电的两级鲁棒优化分配模型
机译:考虑容量曲线和基于实时价格的需求响应的分布式发电的两级鲁棒优化分配模型
机译:智能电网中需求响应的分布式,实时,非参数方法
机译:具有分布式动态需求的混合能量存储系统最佳管理的弹性和实时控制
机译:基于种群的选择策略改善基因组选择的响应:最佳种群值选择
机译:基于乘法器交替方向方法的智能电网需求响应实时定价