全球能源互联网（英文）2023，Vol.6Issue(6)：689-699,11.DOI:10.1016/j.gloei.2023.11.003
计及碳排放的联邦DDQN多能微网能量管理策略
Federated double DQN based multi-energy microgrid energy management strategy considering carbon emissions
摘要
Abstract
Multi-energy microgrids(MEMG)play an important role in promoting carbon neutrality and achieving sustainable development.This study investigates an effective energy management strategy(EMS)for MEMG.First,an energy management system model that allows for intra-microgrid energy conversion is developed,and the corresponding Markov decision process(MDP)problem is formulated.Subsequently,an improved double deep Q network(iDDQN)algorithm is proposed to enhance the exploration ability by modifying the calculation of the Q value,and a prioritized experience replay(PER)is introduced into the iDDQN to improve the training speed and effectiveness.Finally,taking advantage of the federated learning(FL)and iDDQN algorithms,a federated iDDQN is proposed to design an MEMG energy management strategy to enable each microgrid to share its experiences in the form of local neural network(NN)parameters with the federation layer,thus ensuring the privacy and security of data.The simulation results validate the superior performance of the proposed energy management strategy in minimizing the economic costs of the MEMG while reducing CO2 emissions and protecting data privacy.关键词
多能微电网/联邦学习/改进的DDQN/能量转换Key words
Multi-energy microgrid/Federated learning/Improved double DQN/Energy conversion引用本文复制引用
杨艳红,马腾飞,黎海涛,刘伊然,唐成虹,裴玮..计及碳排放的联邦DDQN多能微网能量管理策略[J].全球能源互联网（英文）,2023,6(6):689-699,11.基金项目
This work was supported by the Research and Development of Key Technologies of the Regional Energy Internet based on Multi-Energy Complementary and Collaborative Optimization(BE2020081). （BE2020081）
