Geographic information-driven two-stage optimization model for location decision of solar power plant: A case study of an Algerian municipality

Settou, Belkhir; Settou, Noureddine; Gahrar, Youcef; Negrou, Belkhir; Bouferrouk, Abdessalem; Gouareh, Abderrahmane; Mokhtara, Charafeddine

Abstract

This paper presents an interdisciplinary framework for optimal mapping and integration of solar photovoltaic based DG systems. In a two-stage process, the proposed framework combines both spatial and technical-economic analysis, and uses efficient optimization techniques to make decisions. First, a GIS and a MCDM are used to identify the sites with the highest potential for hosting PV power plants. Second, the Backward-Forward Sweep (BFS) load flow algorithm is used to investigate nominated sites, taking into account three indices, namely, active power losses, VSI, and voltage profile improvement. In addition, a techno-economic feasibility assessment is performed based on the characteristics of a real distribution grid in N'goussa region, Algeria. The results show that 78% of the studied area is suitable for installing PV farms. The optimal zone represents only 1.52% of the obtained suitable area. In addition, two zones are eliminated from 7 suitable zones, as they are too far from the existing grid busbars. Based on the BFS method, and considering VSI and voltage profile, the busbar 104 is the optimal point for the connected PV-farm. Furthermore, the techno-economic assessment for the investigated system indicates that the LCOE is decreased by 0.4 $/kWh for each penetration-rate.

• Journal Article Type: Article
• Acceptance Date: Nov 20, 2021
• Online Publication Date: Nov 23, 2021
• Publication Date: 2022-02
• Deposit Date: Nov 24, 2021
• Publicly Available Date: Nov 24, 2022
• Journal: Sustainable Cities and Society
• Print ISSN: 2210-6707
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 77
• Article Number: 103567
• DOI: https://doi.org/10.1016/j.scs.2021.103567
• Keywords: Transportation; Renewable Energy, Sustainability and the Environment; Civil and Structural Engineering; Geography, Planning and Development
• Public URL: https://uwe-repository.worktribe.com/output/8174365