A multi-objective and robust optimization approach for sizing and placement of PV and batteries in off-grid systems fully operated by diesel generators: An Indonesian case study. (1st October 2018)

• Record Type: Journal Article
• Authors: Rodríguez-Gallegos, Carlos D.; Yang, Dazhi; Gandhi, Oktoviano; Bieri, Monika; Reindl, Thomas; Panda, S.K.
• Is Part Of: Energy. Volume 160(2018)
• Page Start: 410
• Page End: 429
• Publication Date: 2018-10-01
• Subjects: Multi-objective optimization -- PV hybrid systems -- Robust optimization -- Sizing and placement optimization; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2018.06.185
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This paper proposes an approach to optimize sizing and placement of photovoltaic solar panels (PV) and batteries in systems which employ diesel generators (DGs) as their only source of electrical energy, forming a PV hybrid system. Three objectives have been defined: reduction of the levelized cost of electricity (economic objective); levelized CO2 equivalent life cycle emissions (environmental objective); and accumulated grid voltage deviation (grid quality objective). As this is a multi-objective optimization problem, the current state-of-the-art meta-heuristic algorithm is applied, namely non-dominated sorting genetic algorithm III. Furthermore, a robust design has been developed by considering the worst case scenarios regarding weather conditions. Subsequently, its outcome is compared with non-robust designs. Optimal pareto fronts composed of many combinations are generated with a lot of freedom to choose for a desired design. The results show the advantages of PV hybrid system in remote locations ranging from being cost effective, reducing the accumulated emissions and even to improving the grid quality. Highlights: A novel sizing and siting optimization method for PV + battery + diesel hybrid systems. Employment of multiobjective and robust optimization approaches. Lower life cycle cost, CO2e emissions and grid voltage deviations are achieved. Generation of initial investments up to 16% of the life cycle cost.