Research on Virtual Energy Storage Scheduling Strategy for Air Conditioning Based on Adaptive Thermal Comfort Model

Abstract

With the rapid development of a social economy, the yearly increase in air conditioning load in the winter and summer seasons may bring serious challenges to the safe and economic operation of the power grid during the peak period of electricity consumption. So, how we reasonably adjust the set temperature of air conditioning so as to cut down the load during peak periods is very important. In this paper, considering the thermal inertia of air-conditioned buildings and the adaptability of human thermal comfort to temperature changes, the air conditioning load is regarded as virtual energy storage, the air conditioning temperature adjustment range for different users is determined based on the adaptive thermal comfort model of different geographic locations and climatic conditions, and a compensation mechanism is set up based on air conditioning users’ level of participation. Then, an optimal scheduling strategy for a microgrid was constructed with the objectives of user satisfaction, carbon emissions, and microgrid operation benefits, as well as regulating the users’ electricity consumption behavior, and the strategy was solved by using a multi-objective JAYA algorithm. Finally, winter and summer are used as case studies to analyze the results, which demonstrate that regulating the virtual energy storage of air conditioning can effectively improve the economy and environmental friendliness of a microgrid operation and reduce the cost of electricity consumption for the users, taking into account the comfort of the users.

Keywords

• virtual energy storage
• multi-objective optimization
• air conditioning load
• optimal dispatch