A novel optimization model based on game tree for multi-energy conversion systems. (1st May 2018)

• Record Type: Journal Article
• Authors: Huang, Zishuo; Yu, Hang; Chu, Xiangyang; Peng, Zhenwei
• Is Part Of: Energy. Volume 150(2018)
• Page Start: 109
• Page End: 121
• Publication Date: 2018-05-01
• Subjects: Multi-energy conversion systems -- Multi-stakeholders -- Game tree -- CCHP-HP optimization; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2018.02.091
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Well-designed multi-energy conversion systems have the potential to reduce energy consumption and carbon emissions. Based on the literature review and the typical energy flow network of multi-energy conversion systems, the necessity of stakeholders' taking part in multi-energy projects have been emphasized. Considering of different stakeholders have different interest demand and theirs' decision-making behaviors interact with each other, both the final results and decision process are important for stakeholders in multi-energy system planning. Game analysis, which is an analysis method for the conveying scheme evolution in different situations, was proposed to descript the complex relationship between stakeholders' profits and technical schemes. A hierarchical game playing scheme and a simplified multi-energy system optimization method were put forward to assist stakeholders to participate in techno-economic analysis process. Annual equivalent full capacity operation time and hourly earnings of each energy conversion technology are used to calculate returns on investment. The total revenues and every stakeholders' economic returns in different situations (energy price) and technical proposals can be acquired and compared. The proposed method is also illustrated and verified along with a case study. Results indicated that all parties can make contingent decisions under multi-partner negotiation with the assist of game analysis method. Highlights: Proposed typical energy flow networks of multi-energy system. Hierarchical game playing scheme descript stakeholders' participation. Load frequency statistic instead of hourly calculation. Game analysis method clarify the decision process.