Research On Demand Side Management In Smart Gird

Demand Side Management(DSM)is an essential part of the smart grid systems.With the development of smart grid,new characteristics have emerged in DSM.DSM in smart grid has advanced management and control techniques,advanced load monitoring and intelligent control technology.It provides the access to distributed energy generation and storage devices and supports real-time demand response.In other part,the impact of big data technologies to smart grid can not be ignored.These changes urge the appearance of novel and advanced technologies for DSM.In this thesis,energy management algorithms are studied in smart grid.Then,a big data analytics architecture for smart grid is proposed.Finally,an energy storage planning algorithm based on this architecture is designed.The main contributions of this thesis are listed as follows:(1)To solve the energy management issue among users in smart grid,an energy management algorithm based on game theory is proposed.The energy management is described where the scheduling of appliances,energy generation and energy storage are jointly considered.Since shifting appliances may lead to consumer-discomfort,we propose a cost function consisting of the billing,generation costs and discomfort costs to balance users' desire with the payment.Then,a game theoretical approach is used to obtain optimal scheduling among all users.Furthermore,a distributed algorithm is proposed to realize the proposed DSM scheme.Simulation results show that the proposed scheme can reduce the peak load and save costs,and it is helpful to both the whole grid and each user.(2)To solve the planning issue of energy storage devices in the big data environment of smart grid,a big data analytics architecture for smart grid is first proposed.Secondly,to enable the big data computing in smart grid,key technologies to enable the big-data-aware wireless communication for smart grid are investigated in a proposed next-generation communication architecture.Finally,considering the storage planning of distributed energy storage devices owning by users,a hybrid approach combining the generic algorithm(GA)with an energy management algorithm is proposed to obtain the optimal deployment of storage devices.Simulation results show that the algorithm can balance the initial installing cost and the cost saved from daily usage,making a good profit during the lifetime of storage devices.