针对能源电力系统的优化管理与控制问题,提出了一种信息物理融合的智慧能源系统(Intelligent energy systems,IES)多级对等协同优化方法.在信息物理融合能源系统(Cyber-physical energy systems, CPES)的基础上,构建了智慧能源系统的局...针对能源电力系统的优化管理与控制问题,提出了一种信息物理融合的智慧能源系统(Intelligent energy systems,IES)多级对等协同优化方法.在信息物理融合能源系统(Cyber-physical energy systems, CPES)的基础上,构建了智慧能源系统的局域和广域两级协同优化架构.综合考虑产消者能源实体对等交互过程中的社会福利、供求平衡和需求意愿等因素,基于Stone-Geary函数和双向拍卖机制构建了智慧能源系统能量优化模型,给出了通过收敛判定域引导的全局随机寻优与区域定向寻优策略,有效地提高了算法的局部搜索能力.此外,通过双向拍卖机制的理性定价以及智能合约的辅助服务,有效地实现了用户友好的对等交易模式.仿真实例表明,在社会福利最大化的前提下可获得产消者电力资源最优分配结果,进一步验证了本文方法的有效性和可行性.展开更多
This paper is a research on the characteristics of power big data. According to the characteristics of ＂large volume＂, ＂species diversity＂, ＂sparse value density＂, ＂fast speed＂ of the power big data, a predict...This paper is a research on the characteristics of power big data. According to the characteristics of ＂large volume＂, ＂species diversity＂, ＂sparse value density＂, ＂fast speed＂ of the power big data, a prediction model of multi-source information fusion for large data is established, the fusion prediction of various parameters of the same object is realized. A combined algorithm of Map Reduce and neural network is used in this paper. Using clustering and nonlinear mapping ability of neural network, it can effectively solve the problem of nonlinear objective function approximation, and neural network is applied to the prediction of fusion. In this paper, neural network model using multi layer feed forward network--BP neural network. Simultaneously, to achieve large-scale data sets in parallel computing, the parallelism and real-time property of the algorithm should be considered, further combined with Reduce Map model, to realize the parallel processing of the algorithm, making it more suitable for the study of the fusion of large data. And finally, through simulation, it verifies the feasibility of the proposed model and algorithm.展开更多
文摘针对能源电力系统的优化管理与控制问题,提出了一种信息物理融合的智慧能源系统(Intelligent energy systems,IES)多级对等协同优化方法.在信息物理融合能源系统(Cyber-physical energy systems, CPES)的基础上,构建了智慧能源系统的局域和广域两级协同优化架构.综合考虑产消者能源实体对等交互过程中的社会福利、供求平衡和需求意愿等因素,基于Stone-Geary函数和双向拍卖机制构建了智慧能源系统能量优化模型,给出了通过收敛判定域引导的全局随机寻优与区域定向寻优策略,有效地提高了算法的局部搜索能力.此外,通过双向拍卖机制的理性定价以及智能合约的辅助服务,有效地实现了用户友好的对等交易模式.仿真实例表明,在社会福利最大化的前提下可获得产消者电力资源最优分配结果,进一步验证了本文方法的有效性和可行性.
文摘This paper is a research on the characteristics of power big data. According to the characteristics of ＂large volume＂, ＂species diversity＂, ＂sparse value density＂, ＂fast speed＂ of the power big data, a prediction model of multi-source information fusion for large data is established, the fusion prediction of various parameters of the same object is realized. A combined algorithm of Map Reduce and neural network is used in this paper. Using clustering and nonlinear mapping ability of neural network, it can effectively solve the problem of nonlinear objective function approximation, and neural network is applied to the prediction of fusion. In this paper, neural network model using multi layer feed forward network--BP neural network. Simultaneously, to achieve large-scale data sets in parallel computing, the parallelism and real-time property of the algorithm should be considered, further combined with Reduce Map model, to realize the parallel processing of the algorithm, making it more suitable for the study of the fusion of large data. And finally, through simulation, it verifies the feasibility of the proposed model and algorithm.
