A decision-making and planning optimization framework for multi-regional rural hybrid renewable energy system. (1st December 2022)

• Record Type: Journal Article
• Authors: Li, Songrui; Zhang, Lihui; Wang, Xijiao; Zhu, Chunxu
• Is Part Of: Energy conversion and management. Volume 273(2022)
• Publication Date: 2022-12-01
• Subjects: Rural energy -- Hybrid renewable energy system -- Decision-making -- Planning optimization -- Operation schedule; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2022.116402
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: The characteristics of a hybrid renewable energy system are analysed. The MCDM system for multi-regional rural renewable energy is established. A two-stage decision-making and planning optimization model is constructed. Abstract: Rural Hybrid Renewable Energy Systems (RHRESs) coupled with rooftop photovoltaics, wind power, small hydropower and biogas digesters effectively drive the rural energy transition. Rural areas have different resource endowments and development levels, yet there is a lack of RHRES planning theory that considers regional differentiation. The study develops a two-stage framework for multi-regional RHRES decision-making and planning optimization with four counties in China as the case study. First, a multi-criteria decision evaluation is established for multi-regional rural renewable energy planning. Secondly, the physical model of RHRES is constructed for different regions, and the planning optimization model is established with the minimum cost and maximum exergy efficiency. The decision results show that resource conditions are the main factor limiting rural renewable energy development. Then, four scenarios are set up. The "Wind Power + Solar power + Biomass power" scenario has the lowest cost at 50.71 million yuan. The exergy efficiency of the "Wind Power + Solar Power + Hydropower" scenario is the highest, at 79.32 %. Secondly, the cost and exergy efficiency varies in different planning goals. For the scenario "Wind Power + Solar power + Biomass power + Hydropower", the cost of the min cost goal is 5.40 % and 3.34 % lower than the maximum exergy efficiency goal and the bi-objective, respectively. However, the exergy efficiency of the min cost goal is the lowest. Therefore, the bi-objective optimization scheme can balance economy and exergy efficiency. The proposed energy planning framework fully uses rural renewable energy sources, improves energy use efficiency, and informs RHRES investments.