Day-ahead joint scheduling of multiple park-level integrated energy systems considering coupling uncertainty of electricity-carbon-gas prices

Abstract

In the context of carbon neutrality and energy shortage crisis, integrated energy systems achieve low carbon emissions through efficient conversion of various energy sources. However, most scheduling models of integrated energy systems merely regard the electricity, carbon, and natural gas prices as subject to deterministic distributions or simple constants, while their uncertainties are ignored which leads to less practical scheduling plans. In addition, most processing methods of uncertainty take no account of the correlations between uncertainties can result in less accurate evaluations of energy prices. Therefore, a day-ahead joint scheduling model considering coupling uncertainty of electricity, carbon, and gas prices with minimizing total operating costs of multiple park-level integrated energy systems as the objective is proposed to address the above issues. First, the correlation modeling of electricity and gas prices is conducted based on Copula theory, and an initial scenarios generation method of electricity-gas prices is then proposed; next, a typical scenarios construction method of electricity-carbon-gas prices’ coupling uncertainty based on multivariate quadratic polynomial regression-Copula is proposed; after that, the day-ahead joint scheduling model of multiple electricity-gas-thermal park-level integrated energy systems is established considering the typical scenarios of electricity-carbon-gas prices’ coupling uncertainty. Finally, the case studies on 3 energy systems verify the effectiveness of the proposed model. Results demonstrate accurate electricity-carbon-gas prices in typical scenarios with high correlations between uncertainties, and significant reductions in gas consumption and carbon emission by about 29.25% and 24.27% respectively.