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.
| Original language | English |
|---|---|
| Pages (from-to) | 410-429 |
| Number of pages | 20 |
| Journal | Energy |
| Volume | 160 |
| DOIs | |
| State | Published - 1 Oct 2018 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Multi-objective optimization
- PV hybrid systems
- Robust optimization
- Sizing and placement optimization
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