Optimal investment decision of agrivoltaic coupling energy storage project based on distributed linguistic trust and hybrid evaluation method

• Published in: Applied energy Vol. 353; p. 122139
• Main Authors: Ji, Zhengsen, Li, Wanying, Niu, Dongxiao
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-01-2024
• Subjects: Agrivoltaic coupling energy storage; Distributed linguistic trust; Hybrid evaluation method; Multi-criteria decision making; Hybrid evaluation method; Multi-criteria decision making; Agrivoltaic coupling energy storage; Distributed linguistic trust
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2023.122139

Photovoltaic (PV) power generation is becoming a good solution to meet energy demand. However, centralized PV production sites may pose a threat to industrial land or agricultural land. To solve the energy-environment-land conflict, agrivoltaic coupling energy storage (AVCES) projects become a feasible new land use model. The investment decision of AVCES project is a multi-criteria decision problem (MCDM). Therefore, this paper firstly constructs an evaluation index system containing four criteria: resources, economy, social, environment and ecology. Secondly, the subjective weights of each indicator are determined based on the distributed linguistic trust model and the cloud model, and the objective weights are determined based on the cloud model and the integrated determination of objective criteria weights (IDOCRIW) model. Subjective and objective weights are combined based on game theory. Finally, the TODIM model is used to get the optimal choice among multiple schemes. After the case study, the applicability and stability of the proposed framework are validated, and the research results will provide good reference values for the investment decision of AVCES projects.
•Propose an investment framework of agrivoltaic coupling energy storage projects.•An evaluation index system of AVCES projects is constructed.•Combine distributed linguistic trust and cloud model for subjective weights.•IDOCRIW and cloud model are combined to determine objective weights.