| Household distributed power generation can supply power for the terminal user directly with providing clean energy, but also it may cause power imbalances and power quality problems due to its two-way power flow and intermittent power supply. It is worthy of further study to effectively integrate the potential of user-side to respond to power grid, so as to improve its secure, stable and economic operation. The traditional demand response technology developed mainly around large electricity users, and did not realize its automation and intellectualization. In the support of the smart grid technologies, it is of great significance to research on the intelligent load control technology to effectively integrate the demand response potential of user-side, with the purpose of power peaking and promoting the consumption of the distributed power generation.In this thesis, focusing on residential customers’intelligent load and distributed power generation participating in demand response, with the capabilities of bi-direction interactive operation of smart grid, the concept of user-side energy management system is elaborated. The characteristics of the residential loads are studied emphatically, and the intelligent load control programs for the residential users to participate in power peaking and promoting the consumption of the distributed power generation are proposed. On these bases, the design of the dispatch system and its project implementation plan for the user-side intelligent demand response are depicted in detail.Firstly, the load characteristics of the residents to participate in power demand response are researched in-depth, including residential controllable load such as air conditioner, water heater, electric vehicle and photovoltaic power generation system. Their physical models are established according to their load characteristics, which lays the foundation for the future research of the management and control technology of intelligent load participating in DR for power peaking and promoting consumption of the distributed power generation.Secondly, based on the capabilities of bi-direction interactive operation of smart grid, a smart Home Appliances Management (HAM) system with its control scheme is introduced comprehensively. Models of different appliances are established and according to their operating characteristics, an evaluation index is proposed that can represent the comfort of different appliances. In meeting the requirements of power peaking and premise the users’comfort, dynamic priorities of different appliances are calculated online according to their real-time status, and load control decision is performed in order of the priority. Simulation results of the examples show that the proposed load control programs can benefit both the power companies and the users.Thirdly, demand response programs for the residential active load to promote the consumption of the distributed power generation are deeply studied. The demand response characteristics of the residential loads are analyzed. Load state probability matrix of the residents is proposed, and accordingly a probability model representing the users’electricity consumption is established. On this basis, dynamic demand response strategies are proposed with the objective of maximizing the local consumption of the distributed photovoltaic. Monte Carlo simulation is used to simulate of the behavior of users’ electricity consumption. Simulation results of a practical example show that reasonable demand response strategies can effectively promote the local consumption of the distributed generation, with bettering the load curves and benefiting the users significantly.Finally, based on the above theory, for the residential customers participating in demand response of the regional power grid, the design of the dispatch system and its implementation plan for the user-side intelligent demand response are elaborated in detail, including the functional design of the scheduling platform, system design and its hardware and software scheme, the implementation of home energy management system’s network, and the design of the user-side human-machine interface and so on, providing the theoretical and technical basis for the residential users realizing intelligent electricity consumption in the future. |
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