1. Optimal scheduling of integrated energy system for low carbon considering combined weights
- Author
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Jishuai Yu, Haixin Wang, Junyou Yang, Yunlu Li, Xiran Zhou, and Yiming Ma
- Subjects
Mathematical optimization ,Computer science ,business.industry ,Energy balance ,Particle swarm optimization ,chemistry.chemical_element ,Integrated energy systems ,Function (mathematics) ,Electric vehicle ,Renewable energy ,Power (physics) ,TK1-9971 ,Reduction (complexity) ,General Energy ,chemistry ,Renewable energy accommodation ,Electricity ,Electrical engineering. Electronics. Nuclear engineering ,business ,Carbon ,Combined weights method - Abstract
To handle the multiple-objective problem including carbon emission reduction and economic operation of integrated energy system (IES), this paper proposes an optimal scheduling model for IES considering combined weights for low-carbon and economic operation. In the dispatch model of IES, we mainly use the combined cold heat and power (CCHP) to optimize the energy distribution, and use the charge and discharge power of electric vehicles (EVs) to enhance the regulation capability of CCHP. Furthermore, aiming at the lowest carbon dioxide emission and economic cost, and the highest renewable energy accommodation, a multi-objective function considering combined weights is proposed, which combines subjective weights with objective weights. The balance constraints of electricity, heat and cold for the IES are established. Finally, the particle swarm optimization algorithm is used to optimize the multi-objective model based on the energy balance and unit constraints of IES. The proposed method is verified by the case studies. The results show that the proposed model can improve the accommodation of renewable energy and reduce carbon dioxide emissions.
- Published
- 2022