Decarbonization Scheduling Strategy Optimization for Electricity-Gas System Considering Electric Vehicles and Refined Operation Model of Power-to-Gas

Abstract

As the global warming crisis becomes increasingly serious, decarbonized integrated electricity-gas system (IEGS) which can reduce CO2 emissions are gradually developed. However, with high proportion of renewable energy access, the inherent randomness and volatility bring great difficulties to energy scheduling optimization of decarbonized IEGS. In this article, for reducing CO2 emissions, meanwhile improving the utilization efficiency of wind power, a novel IEGS architecture with collaborative operation of power-to-gas (P2G), carbon capture system (CCS) and electric vehicles (EVs) is constructed. P2G is operated in a refined model combined with H2 storage and captured CO2 by CCS can be further consumed in reaction of P2G. Besides, EVs are innovatively adopted in IEGS as flexible energy resource to reduce the impact of wind power fluctuations. Additionally, a multi-step day ahead-intraday collaborative optimization framework is proposed to handle with the uncertainty of wind power, more accurate predicted wind power can be adopted under this framework. The objective function of constructed IEGS is minimize the total operating costs, which takes the CO2 processing costs and penalty costs of wind power deviations into consideration. Numerical studies are conducted with different cases, with the constructed structure and proposed multi-step optimization framework, the emissions of CO2 can be efficiently reduced and wind power utilization can be significantly improved, the total operating costs of IEGS can be reduced more than 20% compared with other cases, which demonstrates that the research of this article has better economic benefits and environmental friendliness.

Keywords

• CO₂ emissions reduction
• carbon capture system
• decarbonized integrated electricity-gas system
• power-to-gas
• uncertainty of wind power