As the major load of residential electricity system

air conditioning has been of great significance for the energy management of household microgrid because of its thermal storage ability. With air conditioning load as the focal point and an eye to other controllable loads and energy storage system

an energy management strategy considering the adaptive adjustment model of air conditioning is proposed. In view of the difficulty in obtaining coefficients of performance of air conditioning and the parameters of the building

it is proposed to use the historical data on air conditioning operation in current scenario to obtain more accurate fitting method using the genetic algorithm to get more accurate parameters. Besides

the human activity and the effect of other loads may lead to the indoor temperature deviate from the reference temperature. Thus a Q-learning algorithm is proposed to adjust the set temperature of air conditioning online to improve the accuracy of energy management. Finally

the cases in point verify the correctness and effectiveness of the proposed household energy management strategy.