Optimization of Urban Multi-energy Flow Systems Considering Seasonal Peak Shaving of Natural Gas

In order to alleviate the shortage of natural gas supply in winter, relevant policies have been issued to promote the construction of gas peak-shaving and storage facilities. Large-scale gas storage can transfer the supply-demand relationship of natural gas in time sequence, which has great potential in improving the economy and reliability of urban multi-energy flow systems. Addressing this issue, this paper proposes amid-and long-term energy optimization method for urban multi-energy flow system that considers seasonal peak shaving of natural gas. First, the energy supply and demand features of different energy subsystems are analyzed. Then, a network model of the electricity-gas-heat multi-energy flow system is established. Considering the time-of-use electricity price mechanism and the seasonal fluctuations of the natural gas price, a mid- and long-term energy optimization model maximizing the annual economic revenue is established. The alternative direction mul-tiplier method with Gaussian back substitution (ADMM-GBS) algorithm is used to solve the optimal dispatch model. Finally, the proposed method is verified by employing the actual data of the demonstration zone in Yangzhong City, China. The simulation results show that the proposed method is effective.