Development of optimization algorithms for the Leaf Community microgrid
| Autor: | Sotiris Papantoniou, Gino Romiti, Elena Provata, Maila Pietrini, Dionysia Kolokotsa, Antonio Giovannelli |
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| Rok vydání: | 2015 |
| Předmět: |
Optimization
Engineering Mathematical optimization Microgrid Artificial neural network Renewable Energy Sustainability and the Environment business.industry Time horizon Energy storage Genetic algorithm Production (economics) business MATLAB computer Neural networks Energy (signal processing) computer.programming_language |
| Zdroj: | Renewable Energy. 74:782-795 |
| ISSN: | 0960-1481 |
| DOI: | 10.1016/j.renene.2014.08.080 |
| Popis: | Δημοσίευση σε επιστημονικό περιοδικό Summarization: The aim of this work is the development of an optimization model in order to minimize the cost of Leaf Community microgrid. This cost is a sum of energy cost and the maintenance cost of the energy storage system (ESS). The developed objective function is constrained and the problem here is solved by using the method of genetic algorithms at Matlab. The genetic algorithm decides about the transportation of the energy from or to the ESS and it calculates an optimum cost. The optimization time horizon is 24 h ahead, thus the prediction of energy production and consumption was necessary. This was achieved by using neural networks. In order to verify the performance of the developed model, some scenarios were tested. This study concludes that a management of a microgrid can achieve energy and money savings. Παρουσιάστηκε στο: Renewable Energy |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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