Research On The Control Strategy Of The Home Energy Management System Based On The LDWPSO

With the development of smart grid in China, the requirement of reliability and energy efficiency of power grid is becoming higher. As the electrical energy use will inevitably become the development trend of the intelligent use of electricity is an important part of smart grid, the core characteristics is grid and flexible user interaction, demand response, as one of the ways to achieve the twoway interaction is one of the most important and demand response is refers to the terminal user directly according to the market information, such as price signals or operator incentive mechanism using active users change daily habits in order to achieve saving energy and reducing consumption. The mainly by price or incentives to guide the user change electricity load to participate in peak load regulation of power grid and users actively participate in optimization of power consumption in order to increase the demand side in electricity market role. So for ordinary home users, in response to the needs of the implementation of the project should be how to better family load is controlled according to the price signals, manage a household energy, thus reduces the energy consumption and electricity cost based on more further implementation of peak shaving and valley filling, the effect of energy saving and emission reduction. This is one of the key issues for the success of the future electricity market.In this dissertation, the development of intelligent electricity technology as the background, through to the residents of electricity conduct research and analysis, formulate the corresponding demand response strategy. The research of the smart grid, intelligent electricity concepts and the home energy management system technology needs, and intelligence at home and abroad in recent years the electricity project are analyzed.Access to a large number of documents on the definition of demand response, the implementation of the required technology and the introduction of relevant national policies and the implementation of the domestic andinternational demand for response to research and analysis.The existing technical conditions and demand response project implementation, in view of our country residents household appliances load habits, put forward the corresponding requirements of the project price points.The family load involved in the project analysis, design of control strategy and objective function. According to the set of target functions using the linearly decreasing weight of the particle group(linear decreasing weight particle swarm optimization, referred to as(LDWPSO) algorithm for optimization, and analyze the feasibility of the control strategy.This dissertation program and simulate home energy control optimization algorithm in MATLAB platform. Including single-user, multi-user, constraints of optimization algorithm and the price level of demand response programs et al,various factors that affect the simulation results of home energy control the will be analyzed. The experimental results show that the control strategy and optimization of the algorithm proposed in this paper can achieve the family to save electricity, peak effect.