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A Model of Electro-thermal Hybrid energy Storage System for Autonomous Control Capability Enhancement of multi-energy microgrid

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CSEE Journal of Power and energy Systems 2019年第4期5卷 489-497页

作者： Yun Teng Peng Sun Qian Hui Yan Li Zhe Chen Shenyang University of Technology Shenyang 110870China Department of energy Technology Aalborg UniversityAalborg 9220Denmark State Grid East Inner Mongolia Electric Power Company Huhhot 010020China

In view of the problem of low self-service capability of the microgrid due to the high operating cost and low capacity of the traditional battery energy storage *** this paper,an electrothermal hybrid energy storage model based on electricity,hydrogen and thermal energy conversion and storage is introduced,and a microgrid autonomous operational strategy is ***,the addition of the power to hydrogen transfer equipment in the traditional combined heat and power(TCHP)system without battery energy storage is studied,and a micro gas turbine,electric to hydrogen transfer equipment and electric boiler based electrothermal energy storage system(ETSS)model is *** at the lowest comprehen-sive operating cost of multiple energy sources in a microgrid and maximizing the consumption of curtailed wind,the multi-objective scheduling model of an electrothermal hybrid energy storage system is established,then the multi-energy autonomous operational strategy of a microgrid is ***,the simulation of a multi-energy microgrid in Northeast China is taken as an *** results of the simulation showed that compared with a combined heat and power microgrid system considering conventiona battery energy storage,a multi-energy microgrid system using electrothermal hybrid energy storage has better flexibility and economy,and can improve wind power accommodation.

关键词： Autonomous operation energy storage multi-objective optimization multi-energy microgrid wind power

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Federated double DQN based multi-energy microgrid energy management strategy considering carbon emissions

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Global energy Interconnection 2023年第6期6卷 689-699页

作者： Yanhong Yang Tengfei Ma Haitao Li Yiran Liu Chenghong Tang Wei Pei Institute of Electrical Engineering Chinese Academy of SciencesBeijing 100190P.R.China Faculty of Information Technology Beijing University of TechnologyBeijing 100124P.R.China State Grid Electric Power Research Institute Nanjing211100P.R.China

multi-energy microgrids(MEMG)play an important role in promoting carbon neutrality and achieving sustainable *** study investigates an effective energy management strategy(EMS)for ***,an energy management system model that allows for intra-microgrid energy conversion is developed,and the corresponding Markov decision process(MDP)problem is ***,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 ***,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 *** simulation results validate the superior performance of the proposed energy management strategy in minimizing the economic costs of the MEMG while reducing CO_2 emissions and protecting data privacy.

关键词： multi-energy microgrid Federated learning Improved double DQN energy conversion

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Joint energy Trading and Scheduling for multi-energy microgrids with Storage

Joint Energy Trading and Scheduling for Multi-Energy microgr...

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第三十九届中国控制会议

作者： Dafeng Zhu Bo Yang Qi Liu Kai Ma Shanying Zhu Xinping Guan Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Electrical Engineering Yanshan University

Considering that energy trading might not completely absorb excess renewable energy, we propose a multi-energy management framework including fuel cell vehicles, energy storage, combined heat and power system, and renewable energy to further realize the local absorption of renewable energy and enhance the economic benefits of microgrids. In order to reduce the influence of multi-energy coupling, stochastic renewable energy generation and energy demand, this paper designs a joint energy scheduling and trading algorithm based on Lyapunov optimization and a double-auction mechanism to optimize the long-term energy cost of each microgrid. Coupling with the auction mechanism is a dynamic, efficient energy trading and scheduling algorithm, which carefully decides the valuations of energy in the auction, optimally schedules energy, and judiciously purchases and sells energy on the current electricity prices. Simulations based on real data show that each individual microgrid, by carrying out the proposed algorithm, can achieve a time-averaged profit arbitrarily close to an optimum value while not compromising its own comfort.

关键词： multi-energy microgrid energy storage energy trading Lyapunov optimization double-auction

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