Jian Dong, Haixin Wang, Junyou Yang*, Liu Gao, Kang Wang, Xiran Zhou
CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 319-340, 2022, DOI:10.32604/cmes.2022.020394
- 02 June 2022
Abstract Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy. This
paper studies an electric-gas-heat integrated energy system, including the carbon capture system, energy coupling
equipment, and renewable energy. An energy scheduling strategy based on deep reinforcement learning is proposed
to minimize operation cost, carbon emission and enhance the power supply reliability. Firstly, the low-carbon
mathematical model of combined thermal and power unit, carbon capture system and power to gas unit (CCP)
is established. Subsequently, we establish a low carbon multi-objective optimization model considering system
operation cost, carbon emissions cost, integrated demand More >
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