A novel multi-objective method with online Pareto pruning for multi-year optimization of rural microgrids. (1st October 2021)

• Record Type: Journal Article
• Authors: Petrelli, Marina; Fioriti, Davide; Berizzi, Alberto; Bovo, Cristian; Poli, Davide
• Is Part Of: Applied energy. Volume 299(2021)
• Publication Date: 2021-10-01
• Subjects: Hybrid minigrid sizing -- Mixed-Integer Linear Programming (MILP) -- eps-constraint method -- Online pareto filter -- Holistic design -- Off-grid PV-wind-battery-diesel system; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2021.117283
• Languages: English
• ISSNs: 0306-2619

Abstract

Abstract: Decentralized hybrid energy systems are promising long-lasting solutions to support socio-economic development in compliance with environmental concerns. Traditionally, microgrid planning has mainly focused on economics only, sometimes with reliability or environmental considerations, and the project costs have been estimated by approximating the multi-year operation of the system with a single-year approach, thus neglecting long-term phenomena. We propose a multi-objective multi-year method to plan microgrids in the Global South, accounting for socio-economic (Net Present Cost, job creation), security (public lighting coverage) and environmental impacts (carbon emissions, land use); the entire multi-year lifespan of the project is considered, including demand growth and assets degradation. The advanced version of the augmented ε -constraint algorithm, denoted as A-AUGMECON2, is here proposed to efficiently solve the multi-objective model, by using a novel pruning algorithm that avoids solving redundant optimizations. The method is applied to an isolated community in Uganda. The approach successfully quantifies the trade-off between local long-term impacts, supporting policy makers and local developers in designing effective policies and actions. In particular, our results suggest that the environmental targets can be aligned with the project economics, and that the financial impact of public lighting is limited, which encourages its implementation in electrification projects. Conversely, optimal land use and job creation lead to high economic and environmental costs, highlighting the need for a trade-off for policy and business decision makers. Moreover, the novel A-AUGMECON2 algorithm enables reducing by 48% the computational requirements of the standard AUGMECON2, extending the application of multi-objective methodologies to more complex problems. Highlights: Multi-objective multi-year planning of a rural hybrid power system. Evaluation of costs, emissions, land use, job creation and public lighting coverage. Development of Advanced-AUGMECON2 (A-AUGMECON2) for skipping redundant iterations. The computational burden for identifying the Pareto frontier is reduced by 48%. Environmental targets show alignment with cost minimization objectives.