Demand Response Under Real-Time Pricing For Domestic Energy System With DG And Storage

With the distributed generation (DG), e.g. small scaled wind turbines and photovoltaic panels, installed at the domestic scope, and the advances of domestic hybrid power supply system technology, as well as flexible loads’ increasing proportion in household electric appliances, how to fully use self-produced DG resources to obtain the optimal match between the demand and generation arises to people’s attention. However, due to the impact of environment factors, e.g. wind speed and light intensity, the power outputs of renewable DG are often fluctuant, stochastic and intermittent, and their power supplies are often limited during different time periods throughout a day. Such intermittent nature of DG make them barely can meet the demand of all domestic equipment at any time, and hence appropriately schedule flexible loads’working periods, allocate battery’s charging/discharging behaviors, so as to promote the overall efficiency of resource utilization have an important theoretical significance and market value.In this paper, the Advanced Metering Infrastructure (AMI) has been deployed in the domestic side, to provide bidirectional communication between real-time pricing (RTP) and load demand. Through establishing liner inequality operational constraints as flexible loads’working models, and setting demand response program in AMI, the energy compution cotroller can fastly calculate appliances’best-fit working periods, thus automatically arrange the corresponding devices’start up and off conditions, and present battery’s charging/discharging behaviors to the appropriate time-slots as well. The energy scheduling approach proposed in the paper includes three aspects:(1) Establishing multi-objective integer programming problem to lessen the purchase cost and seek the balance between power supply and demand. It can be implemented through adopting genetic algorithm (GA) to fulfill the domestic load scheduling functionality to achieve the best-fit supply-demand matching performance.(2) Using the real-time pricing (RTP) mechanism as a leveraging tool to automatically search for the situation where the total purchase cost is lessen through appropriately shifting the operational working periods of appliances to another allowable time slots, in accordance to the DG outputs and RTP information.(3) The storage based scheduling is further incorporated into the energy management to optimize the global utilization efficiency of DG and promote the generation-demand match from both space and temporal aspects, as well as minimize the electricity purchase cost, and it can be realized through searching the optimal DG-storage-load energy optimization model which is piecewisely-defined. In the process, RTP is assisted in making decisions about buying electricity from the utility to the battery or the loads, in order to reduce the purchase cost to the greatest extent.The domestic hybrid power supply system is built in the MATLAB simulation platform, to assess its cost minimization and utility maximization performance by carrying out a set of simulation experiments for a range of system scenarios. The numerical results demonstrate that the domestic energy can be well managed to meet the demand requirement with significantly improved resource utilization efficiency and reduced purchase cost, and the robustness of the solution is also evaluated in presence of prediction errors.