Multi-energy collaborative optimization of park integrated energy system considering carbon emission and demand response

• Published in: Energy reports 2023-12, Vol.9, p.3683-3694
• Main Authors: Guo, Weishang, Wang, Qiang, Liu, Haiying, Desire, Wade Atchike
• Format: Article
• Language: English
• Subjects: Collaborative optimization; Demand response; Ladder carbon trading; Multi-objective; Park integrated energy system
• ISSN: 2352-4847; 2352-4847
• DOI: 10.1016/j.egyr.2023.02.051

Park integrated energy system (PIES) has become a key link of efficient energy conservation and carbon emission reduction. This paper proposes a multi-energy collaborative optimization method of PIES considering carbon emission and demand response (DR). Firstly, the typical structure of the electricity-thermal-gas cogeneration PIES including combined heat and power (CHP), heat pump (HP) and energy storage (ES) is built. Secondly, a ladder carbon trading model for PIES considering carbon quota and actual carbon emission is established. On this basis, a multi-objective collaborative optimization model considering the operation cost, energy utilization efficiency and consumption rate of renewable energy is established, and the multi-objective problem is solved by a multi-objective particle swarm optimization algorithm (MOPSO). Then, taking a typical PIES as an example, the operation conditions of the system before and after DR are analyzed, and the results show that the established model can realize the economic and low-carbon operation and improve renewable energy consumption rate. The numerical results show that when participating in DR, the operation cost of PIES is reduced by 10.18% and the carbon emission is reduced by 3.41%. Finally, the impact of carbon trading price on the operation cost, energy utilization efficiency and consumption rate of renewable energy is analyzed.