An integrated decision support method for strategic planning and tactical management of regional biomass power plants under uncertainties. (15th February 2023)

• Record Type: Journal Article
• Authors: Ji, Ling; Zheng, Zixuan; Huang, Yunuo; Xie, Yulei; Sun, Lijian; Huang, Guohe
• Is Part Of: Journal of cleaner production. Volume 388(2023)
• Publication Date: 2023-02-15
• Subjects: GIS -- Multi-criteria decision making -- Type-2 fuzzy -- Uncertainties -- Biomass power generation; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2023.135968
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: In the context of global climate change and energy security pressures, biomass power generation has been regarded as an effective way to supplement the energy supply, reduce fossil fuel consumption, and alleviate environmental pollutants. This paper presents an integrated modeling framework to address the regional biomass power generation planning to facilitate biomass utilization in developing countries. By combining the geographic information system, multi-criteria decision-making approach, as well as the type-2 fuzzy inexact programming method, the proposed integrated framework could assist the optimal decision-making for the specific site and size selection of biomass power plants in the whole region as well as the optimal operation strategies under deep uncertainties. The proposed modeling framework is applied to the particular context of Henan, an agricultural province in China with great biomass potential. The results suggested that biomass power plants with a total capacity of 2.4 GW could be established, which could satisfy 6% of local electricity consumption and avoid 18.51 Mt of carbon emissions. The sensitivity analysis of the main economic parameters indicated that lower investment and operation costs were essential to stimulate the utilization of local biomass energy. A higher feed-in tariff is not encouraged due to the limited incentive effect but is a heavy burden for the government. Furthermore, the optimal strategies for biomass power generation planning under uncertainties could be suggested for different decision makers with various risk preferences to achieve a tradeoff between system cost and risk.