Temperature control load frequency response control method based on user satisfaction and reinforcement learning

• Main Authors: XU DIAN, WANG WENNA, CAI DEFU, LIU HAIGUANG, YANG XUAN, ZHOU YUE, SUN GUANQUN, LEE DAE-HO, CHEN RUSI, ZHOU KUNPENG, WANG ERXI
• Format: Patent
• Language: Chinese; English
• Published: 14.07.2023
• Subjects: CALCULATING; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; ELECTRICITY; GENERATION; PHYSICS; SYSTEMS FOR STORING ELECTRIC ENERGY; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention relates to a temperature control load frequency response control method based on user satisfaction and reinforcement learning. The method comprises a temperature control load user satisfaction quantification method and deep reinforcement learning agent model construction. Two control modes of direct switch control and temperature setting control of a temperature control load are considered, an energy storage index and an uncomfortable degree index are respectively defined as load adjusting indexes, and a fuzzy comprehensive evaluation method is adopted to evaluate user satisfaction; a multi-agent model of a temperature control load is established based on a flexible action device-discriminator algorithm, user satisfaction and a frequency adjustment error are weighted to establish a comprehensive evaluation index, the comprehensive evaluation index is used as an objective function of agent optimization, and an agent updates parameters according to local temperature control load information and fr