Robust Energy Scheduling for Smart Buildings Considering Uncertainty in PV Generation
The fast growth of renewable energy sources in the residential building led to a complex problem related to the energy management system: the uncertainty associated with the forecast of photovoltaic power generation. To solve this challenge, this paper proposes a robust optimization model to obtain...
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| Outros Autores: | , , , |
| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2022
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/10400.22/20666 |
| País: | Portugal |
| Oai: | oai:recipp.ipp.pt:10400.22/20666 |
| Resumo: | The fast growth of renewable energy sources in the residential building led to a complex problem related to the energy management system: the uncertainty associated with the forecast of photovoltaic power generation. To solve this challenge, this paper proposes a robust optimization model to obtain the optimal solution for the worst-case scenario of photovoltaic generation. A Mixed Binary Linear Programming problem is transformed into a trackable robust counterpart to provide immunity against the worst-case realization. Through the budget of uncertainty, the risk of the solution can be adjusted. The results demonstrate that the influence of Battery Energy Storage System and Electric Vehicles against uncertainties leads to higher economic gains up to 6% reduction. |
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