Energy management strategy based on short-term resource scheduling of a renewable energy-based microgrid in the presence of electric vehicles using θ-modified krill herd algorithm
| Autor: | Mohsen Latifi, Ziad M. Ali, Abdallah Aldosary, Muhyaddin Rawa, Armin Razmjoo, Alireza Rezvani |
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| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization Wind power business.industry Computer science Energy management Photovoltaic system Fossil fuel 02 engineering and technology Electrical grid Stochastic programming Renewable energy 020901 industrial engineering & automation Artificial Intelligence Distributed generation 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Microgrid business Software |
| Zdroj: | Neural Computing and Applications. 33:10005-10020 |
| ISSN: | 1433-3058 0941-0643 |
| DOI: | 10.1007/s00521-021-05768-3 |
| Popis: | Providing of energy is one of the most important issues for each country. Also, environmental issues due to fossil fuel depletion are other serious concern of them. In this regard, moving toward energy sustainability is a constructive solution for each country. This paper studies the short-term planning of generating units in renewable energy-based distribution networks equipped with plug-in electric vehicles (PEVs). PEVs can cause problems for distributed energy sources in the electrical grid, as well as power units inside the grid. So, to overcome this problem, an efficient stochastic programming technique is designed to allow the control entity to control the charging behavior of PEVs for managing power units. In this paper, to obtain the least total cost, a new method is suggested to decrease the reliability expenses. In other words, the vehicle-2-grid (V2G) is applied to decrease the operating. On the other hand, a novel stochastic flow using the unscented transform is suggested to improve the model of the severe uncertainty due to the wind power, photovoltaic (PV) and charging/discharging power of PEVs. In this research work, a novel and efficient optimization algorithm called ‘θ-modified krill herd (θ-MKH)” is used as an applicable technique to optimize the microgrid (MG) operation. This algorithm is useful and has many advantages like the runaway from the local optima with fast converging in comparison with other methods. Also, the satisfactory efficiency of the suggested randomized manner is validated on an MG connected to the main grid. |
| Databáze: | OpenAIRE |
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