Optimization scheduling of a wind–photovoltaic–gas–electric vehicles Community-Integrated Energy System considering uncertainty and carbon emissions reduction

Coupling renewable energy power generation, electric vehicles, combined cooling heating and power system, and energy storage system is a new way for Community-Integrated Energy Systems (CIES) to shift to a low-carbon, highly efficient, environmentally friendly society, which is the key task in coordinating flexible demand response with multiple uncertainties in renewable energy. To this end, an integrated demand response program is used to explore the potential interaction ability of electricity–gas–heat–cool–Electric Vehicles flexible loads in a scheduling model based on chance-constrained programming, based on which an integrated demand respond-enabled CIES with uncertain renewable generation was built, meanwhile, a ladder-type carbon trading mechanism was designed, and then the original model was transformed into a solvable mixed-integer linear programming model using Sequence Operation Theory and linearization methods. Furthermore, the objective function was constructed by using the deviation preference optimization strategy, daily comprehensive cost and daily carbon emissions were introduced to reflect the decision-makers’ different optimization preferences by using weight coefficients as double optimization objectives. Finally, the simulation shows that CIES operation can effectively balance economy and reliability by setting an appropriate confidence level for the spinning reserve constraint, meanwhile, the comparative result shows that EV charging in the CIES has a very significant environmental benefit in carbon dioxide emissions reduction, while the number of EVs exceeds 500, EV charging in the CIES starts to show a better economic benefit.