Capacity planning and optimization of business park-level integrated energy system based on investment constraints. (15th December 2019)

• Record Type: Journal Article
• Authors: Wang, Yongli; Li, Ruiwen; Dong, Huanran; Ma, Yuze; Yang, Jiale; Zhang, Fuwei; Zhu, Jinrong; Li, Shuqing
• Is Part Of: Energy. Volume 189(2019)
• Publication Date: 2019-12-15
• Subjects: Investment constraint -- Integrated energy system -- Capacity planning and optimization -- Bi-level optimization -- Multiple target; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2019.116345
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Through the coordination and complementarity of multiple energy sources, the optimal capacity planning of integrated energy system under limited financial constraints can promote the local absorption of renewable energy, realize the optimal utilization of resources and improve the utilization rate of comprehensive energy. Aiming at the integrated energy system formed by multi-energy coupling, this paper adopts three investment restraint schemes, simulates the economic operation of the system based on typical daily load characteristic curves in different seasons, and establishes an optimal capacity allocation model of the integrated energy system taking into account the investment cost restraint and minimizing the total annual cost and carbon dioxide emissions. Strength Pareto Evolutionary Algorithm 2 (SPEA2) and Technology for Order Preference by Similarity to an Ideal Solution (TOPSIS) are used to optimize the solution. Finally, a park in Beijing is taken as an example to verify the model optimization results and the actual results. The deviation of the target results is less than 5%. This study realizes the scientific capacity allocation of integrated energy system, and provides theoretical basis and technical support for the planning and design of integrated energy system. Highlights: Capacity planning optimization under different equipment investment constraints. Bi-level model framework for universal capacity planning optimization. The model of multi-objective capacity planning considering economic-environmental cost. Three schemes are simulated and compared, and sensitivity analysis is carried out.