Optimal optimisation‐based microgrid scheduling considering impacts of unexpected forecast errors due to the uncertainty of renewable generation and loads fluctuation
| Autor: | Maickel Tuegeh, Chun-Yao Lee |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Mathematical optimization
Power station Renewable Energy Sustainability and the Environment Total cost business.industry Computer science 020209 energy 020208 electrical & electronic engineering Photovoltaic system Scheduling (production processes) Particle swarm optimization 02 engineering and technology Power (physics) Renewable energy Computer Science::Systems and Control 0202 electrical engineering electronic engineering information engineering Microgrid business |
| Zdroj: | IET Renewable Power Generation. 14:321-331 |
| ISSN: | 1752-1424 1752-1416 |
| Popis: | Unlike conventional power plants, wind farm and solar photovoltaic (PV) module operations involved uncontrollable factors such as wind and solar irradiation, making the dispatch problem more complex. This study proposes optimal scheduling using a modification inertia weight of the particle swarm optimisation (PSO) algorithm and take into account unexpected forecast errors due to uncertainty in renewable distributed generators and loads in the day-ahead market in a microgrid. Modified inertia weight makes the PSO algorithm have a strong global searching ability to solve the scheduling. Meanwhile, the microgrid coordinates the realistic production of its power plant to get the optimal total cost. The uncertainty of renewable distributed generators is modelled based on forecast data. The Simulation result shows the advantages of the proposed method. |
| Databáze: | OpenAIRE |
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