Comparative study of optimization method and optimal operation strategy for multi-scenario integrated energy system. (15th February 2021)

• Record Type: Journal Article
• Authors: Wu, Di; Han, Zhonghe; Liu, Zhijian; Li, Peng; Ma, Fanfan; Zhang, Han; Yin, Yunxing; Yang, Xinyan
• Is Part Of: Energy. Volume 217(2021)
• Publication Date: 2021-02-15
• Subjects: Integrated energy system -- Isolated and connected scenarios -- Optimization scheme -- Minimal annualized cost -- Collaborative optimization method; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.119311
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Integrated energy system as a welcome multiple-energy system has significant contribution to alleviate the worldwide energy shortage problem. In this paper, the theoretical model of integrated energy system was initially built. Also, a new self-adaption strategy relying on exhaustive search method is proposed for minimal hourly-operation-cost. On the basis, an optimization scheme oriented by minimal annualized system cost is presented for integrated energy system. Based on a case study, the optimal nominal capacity of devices and operation parameters are determined by the optimization scheme, respectively for isolated and connected scenarios with different operation strategies. In isolated scenario, the annualized system cost with self-adaption strategy is the lowest, around $23.60/m 2 for commercial building and around $19.39/m 2 for office building. In connected scenario, the minimal annualized system cost is $693.3 k (about $19.26/m 2 ). Moreover, the applicability of building-scale and district-scale integrated energy systems in economy is compared. Finally, a collaborative optimization method that combines genetic algorithm and orthogonal experimental design is introduced to determine multiple decision variables for district-scale integrated energy system. The results show that the district-scale integrated energy system determined by collaborative optimization reduces the annualized cost by 0.67% (about $78.8 k), compared by non-collaborative optimization. These findings could provide the reference about integrated energy system optimization and further explore the development potential of multiple-energy system. Graphical abstract: Image 1 Highlights: A new self-adaption strategy is proposed for minimal hourly-operation-cost. An optimization scheme oriented by minimal annualized system cost is presented. Optimal configuration and operation parameters are determined for isolated and connected scenarios. A collaborative optimization method is introduced to optimize district-scale integrated energy system.