Combined heat and power dispatch(CHPD)opens a new window for increasing operational flexibility and reducing wind power curtailment.Electric power and district heating systems are independently controlled by different...Combined heat and power dispatch(CHPD)opens a new window for increasing operational flexibility and reducing wind power curtailment.Electric power and district heating systems are independently controlled by different system operators;therefore,a decentralized solution paradigm is necessary for CHPD,in which only minor boundary information is required to be exchanged via a communication network.However,a nonideal communication environment with noise could lead to divergence or incorrect solutions of decentralized algorithms.To bridge this gap,this paper proposes a stochastic accelerated alternating direction method of multipliers(SA-ADMM)for hedging communication noise in CHPD.This algorithm provides a general framework to address more types of constraint sets and separable objective functions than the existing stochastic ADMM.Different from the single noise sources considered in the existing stochastic approximation methods,communication noise from multiple sources is addressed in both the local calculation and the variable update stages.Case studies of two test systems validate the effectiveness and robustness of the proposed SAADMM.展开更多
This paper proposes a decentralized demand management approach to reduce the energy bill of industrial park and improve its economic gains.A demand management model for industrial park considering the integrated deman...This paper proposes a decentralized demand management approach to reduce the energy bill of industrial park and improve its economic gains.A demand management model for industrial park considering the integrated demand response of combined heat and power(CHP)units and thermal storage is firstly proposed.Specifically,by increasing the electricity outputs of CHP units during peak-load periods,not only the peak demand charge but also the energy charge can be reduced.The thermal storage can efficiently utilize the waste heat provided by CHP units and further increase the flexibility of CHP units.The heat dissipation of thermal storage,thermal delay effect,and heat losses of heat pipelines are considered for ensuring reliable solutions to the industrial park.The proposed model is formulated as a multi-period alternating current(AC)optimal power flow problem via the second-order conic programming formulation.The alternating direction method of multipliers(ADMM)algorithm is used to compute the proposed demand management model in a distributed manner,which can protect private data of all participants while achieving solutions with high quality.Numerical case studies validate the effectiveness of the proposed demand management approach in reducing peak demand charge,and the performance of the ADMM-based decentralized computation algorithm in deriving the same optimal results of demand management as the centralized approach is also validated.展开更多
近年来,多用户多输入多输出(Multiple-User Multiple-Input Multiple-Output,MU-MIMO)下行链路的预编码算法设计吸引了越来越多研究者的兴趣。然而目前并没有对基站端已知信道误差概率分布且约束条件为单天线功率约束(Per-Antenna Power...近年来,多用户多输入多输出(Multiple-User Multiple-Input Multiple-Output,MU-MIMO)下行链路的预编码算法设计吸引了越来越多研究者的兴趣。然而目前并没有对基站端已知信道误差概率分布且约束条件为单天线功率约束(Per-Antenna Power Constraints,PAPCS)的情况下的线性预编码算法的研究。针对上述情况,以遍历和速率(Expected Sum Rate)最大化为优化准则,主要基于约束随机逐次凸近似(Constrained Stochastic Successive Convex Approximation,CSSCA)、二阶对偶法、交替方向乘子法(Alternating Direction Method of Multipliers,ADMM)及高斯随机化(Gaussian Randomization)设计了线性预编码算法。所提算法的适用场景更符合实际情况,而且实验仿真结果证明,算法的性能较好。展开更多
基金supported by the Key-Area Research and Development Program of Guangdong Province under Grant 2020B010166004the National Natural Science Foundation of China under Grant 52177086+2 种基金the Guangdong Basic and Applied Basic Research Foundation under Grant 2019A1515011408the Science and Technology Program of Guangzhou under Grant 201904010215the Talent Recruitment Project of Guangdong under Grant 2017GC010467.
文摘Combined heat and power dispatch(CHPD)opens a new window for increasing operational flexibility and reducing wind power curtailment.Electric power and district heating systems are independently controlled by different system operators;therefore,a decentralized solution paradigm is necessary for CHPD,in which only minor boundary information is required to be exchanged via a communication network.However,a nonideal communication environment with noise could lead to divergence or incorrect solutions of decentralized algorithms.To bridge this gap,this paper proposes a stochastic accelerated alternating direction method of multipliers(SA-ADMM)for hedging communication noise in CHPD.This algorithm provides a general framework to address more types of constraint sets and separable objective functions than the existing stochastic ADMM.Different from the single noise sources considered in the existing stochastic approximation methods,communication noise from multiple sources is addressed in both the local calculation and the variable update stages.Case studies of two test systems validate the effectiveness and robustness of the proposed SAADMM.
基金This work was supported by the National Key R&D Program of China(No.2018YFB0905000)the Science and Technology Project of State Grid Corporation of China(No.SGTJDK00DWJS1800232).
文摘This paper proposes a decentralized demand management approach to reduce the energy bill of industrial park and improve its economic gains.A demand management model for industrial park considering the integrated demand response of combined heat and power(CHP)units and thermal storage is firstly proposed.Specifically,by increasing the electricity outputs of CHP units during peak-load periods,not only the peak demand charge but also the energy charge can be reduced.The thermal storage can efficiently utilize the waste heat provided by CHP units and further increase the flexibility of CHP units.The heat dissipation of thermal storage,thermal delay effect,and heat losses of heat pipelines are considered for ensuring reliable solutions to the industrial park.The proposed model is formulated as a multi-period alternating current(AC)optimal power flow problem via the second-order conic programming formulation.The alternating direction method of multipliers(ADMM)algorithm is used to compute the proposed demand management model in a distributed manner,which can protect private data of all participants while achieving solutions with high quality.Numerical case studies validate the effectiveness of the proposed demand management approach in reducing peak demand charge,and the performance of the ADMM-based decentralized computation algorithm in deriving the same optimal results of demand management as the centralized approach is also validated.
文摘近年来,多用户多输入多输出(Multiple-User Multiple-Input Multiple-Output,MU-MIMO)下行链路的预编码算法设计吸引了越来越多研究者的兴趣。然而目前并没有对基站端已知信道误差概率分布且约束条件为单天线功率约束(Per-Antenna Power Constraints,PAPCS)的情况下的线性预编码算法的研究。针对上述情况,以遍历和速率(Expected Sum Rate)最大化为优化准则,主要基于约束随机逐次凸近似(Constrained Stochastic Successive Convex Approximation,CSSCA)、二阶对偶法、交替方向乘子法(Alternating Direction Method of Multipliers,ADMM)及高斯随机化(Gaussian Randomization)设计了线性预编码算法。所提算法的适用场景更符合实际情况,而且实验仿真结果证明,算法的性能较好。
