Research On Automatic Demand Response System For Intelligent Building

In smart grid, demand response is the latest development of demand side management in the electricity market. It is defined as an action of electricity consumers that in order to decrease the load of power grid, consumers changed the temporary electricity habits under the command of electricity price or compensation from the power grid when the reliability of power system is in danger or the price of the electricity market is increasing. During the implement of electricity demand response, the demand of electricity consumers is also a kind of manageable recourses. The consumption could be adjusted based on the balance of their electricity demand and the ability of power system to satisfy the demands. Therefore, auto-demand response and the real-time bidirectional communication are the foundation to realize the interaction. In this way, consumers could make the electricity plans and choose the auto-response. Since buildings contributed to the 40 percent of global power consumption, a growing number of intelligent buildings have been built to meet the increased energy requirements in an efficient way. Furthermore, as the major load of all energy consumption devices, air conditioning not only relates to the improvement of energy efficiency but also makes a great difference in consumers’satisfaction. As a result, an auto-demand response system considering the demand of interaction in smart grid is designed. Then, the multi-objective optimization strategies for air-conditioning load considering both the consumers’comfort and electricity expense are formulated, which is of great significance to the application of demand response.In this paper, firstly, related local and foreign researches are introduced; the situation of demand response is concluded; the development trend of intelligent buildings’auto-demand response is analyzed. Secondly, the basic theory and main technologies of demand response and intelligent building are discussed respectively. Then the specific requirements to design the auto-demand response system of the intelligent building are proposed. Thirdly, the framework, specific function and interaction mode of the system are designed for the major loads of intelligent building, including air-conditioning systems, lights and plugs. Last but not least, an efficient optimal control method of air conditioning load, which allows the decision-making of electricity consumers, is put forward, and a multi-objective optimization strategy based on the improved immune clonal selection algorithm, which optimizes comfort and electricity expense of air conditioning users, is established. Results of simulation and tests indicate that multi-objective optimization could effectively balance the users’demand for economy and comfort and both effectiveness and advantage of the improved algorithm are verified.