PV-Battery-Diesel microgrid layout design based on stochastic optimization
| Autor: | Georg Frey, Felix Felgner, Mohammed Hijjo |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Power management
Mathematical optimization Engineering Optimization problem business.industry Energy management 020209 energy 02 engineering and technology Load profile Genetic algorithm 0202 electrical engineering electronic engineering information engineering Stochastic optimization Microgrid business Metaheuristic |
| Zdroj: | 2017 6th International Conference on Clean Electrical Power (ICCEP). |
| DOI: | 10.1109/iccep.2017.8004787 |
| Popis: | This work presents a layout design method for a grid-connected PV-Battery-Diesel microgrid considering the effect of the applied power management strategy among the system's components. The proposed microgrid is dedicated to those areas in the world which suffer from prolonged grid outages and depend mainly on diesel generators to cover the periods of power deficit. Conventionally, such hybrid microgrids are designed assuming two prime impractical hypotheses: namely, a full utilization of the generated power from renewable resources, and no losses due to power conversion among DC/AC buses; both hypotheses lead to specifically optimistic and encouraging results from an economic point of view. In addition, many approaches do not include the energy management scheme during optimization. By contrast, the layout herein is optimized taking into account a developed rule-based energy management (EM) scheme and realistic power conversion efficiencies, which together play the key role in determining the realistic percentage of utilized renewable energy. The optimization algorithm employs a Genetic Algorithm (GA), which is one of the metaheuristic stochastic optimization techniques that can provide a solution to an optimization problem with less computational effort than iterative ones. The simulations are carried out using a typical load profile of a hospital in Gaza Strip over a one-year period. |
| Databáze: | OpenAIRE |
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