OPERATION OPTIMIZATION OF SECONDARY WATER SUPPLY SYSTEM BASED ON DQN
Secondary water supply system(SWSS)is the key process for water supply to reach the users'tap water.Aimed at the problem that water age in SWSS affects water quality,the optimized operation model based on deep Q-learning network(DQN)is proposed.The optimization objectives of water pressure,water age and energy consumption were calculated to the corresponding rewards.In the model,the inputs were the hydraulic state of SWSS,and the outputs were the operation instructions of the pool inlet and the pumps.Taking a SWSS in the residential community as an example,the hydraulic model was established by using the software EPANET.Based on DQN,the operation instructions of the pool and the pumps were optimized.The results show that on the premise of ensuring water pressure,the water age is reduced.
Secondary water supply systemDeep Q-learning networkOperation optimizationWater age
万方数据
维普
