4.6 Article

Multi-timescale coordinated schedule of interdependent electricity-natural gas systems considering electricity grid steady-state and gas network dynamics

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.ijepes.2019.105763

关键词

Coordinated scheduling; Gas dynamics; Integrated electricity-natural gas system; Uncertainty; Wind power

资金

  1. National Natural Science Foundation of China [51777182]
  2. U.S. National Science Foundation [CMMI-1906780]

向作者/读者索取更多资源

The tight interdependency between electricity and natural gas systems brings new operation challenges to coordinate the two systems for achieving optimized multi-energy supply. The coordinated short-term schedule and real-time dispatch of an integrated electricity-natural gas system (IEGS) with energy coupling components (i.e., P2G (power to gas) assets and gas-fired generators) are proposed. Specifically, in the short-term schedule, electricity generators and gas sources are optimized in a unified model to achieve the minimal operation cost, where prevailing operation constraints related to hourly-scale steady-state power flow and minute-scale gas transmission dynamics are satisfied and extreme wind power scenarios are also considered. In the real-time dispatch, P2G assets and gas-fired generators are optimized to smooth the wind power forecast errors, aiming at mitigating impacts of wind power uncertainties on gas pressures variations. Through real-time dispatch, extreme wind power scenarios which cause violations of gas pressures will be identified and fed back to the short-term schedule problem, seeking for new operation strategies that would mitigate potential gas pressure violations induced by wind power uncertainties in real time. An IEGS, consisting of a 15-node and 14-pipeline natural gas network and a 24-bus and 35-branch power network, is established to validate the proposed approach. Simulation results demonstrate that linepack, P2G, and gas-fired generators can be utilized to effectively enhance operational economics and robustness of LEGS against uncertainties.

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