Heating

ventilating and air condition（HVAC）energy consumption on load side accounts for a large proportion of total energy consumption of the building. Adopting appropriate control scheme can effectively reduce energy consumption of energy consumption system. At present

the methods of energy saving regulation and control of HVAC on load side mostly focus on load forecasting control

which requires the combination of multiple model prediction results and high accuracy requirements. However

association rule analysis method can directly learn the law of historical operation data

and can more easily obtain more energy-saving regulation strategies. Energy consumption system of a shopping mall in Wuhan is taken as the research object

and operating data of the system load side in June are collected for research. After the data is cleaned and discretized

Apriori algorithm is used to calculate the association rules between power and device start-stop and frequency

and the energy-saving control scheme is presented based on this. Research results show that Apriori algorithm can learn the law of historical operation data of energy consumption system well. By analyzing the relationship between system power and adjustable parameters such as frequency

start and stop

the energy-saving control strategy can be obtained more quickly

conveniently and directly in actual use.