Probabilistic Optimal Bi-level Scheduling of a Multi-Microgrid System with Electric Vehicles
| Autor: | Mohammad Mirzaei, Keyvan Golalipour, Reza Keypour, Mehdi Savaghebi |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Demand response
Mathematical optimization Bi-level stochastic programming Computer science Plug-in electric vehicles 020209 energy 020208 electrical & electronic engineering Multi-microgrid system Probabilistic logic Adaptive particle swarm optimization Particle swarm optimization 02 engineering and technology Optimal scheduling Load profile Scheduling (computing) Cost reduction 0202 electrical engineering electronic engineering information engineering Microgrid Electrical and Electronic Engineering Efficient energy use |
| Zdroj: | Mirzaei, M, Keypour, R, Savaghebi, M & Golalipour, K 2020, ' Probabilistic Optimal Bi-level Scheduling of a Multi-Microgrid System with Electric Vehicles ', Journal of Electrical Engineering & Technology, vol. 15, no. 6, pp. 2421-2436 . https://doi.org/10.1007/s42835-020-00504-8 |
| ISSN: | 2093-7423 1975-0102 |
| Popis: | In this paper, an efficient energy management system (EMS) is proposed for optimal operation of multiple electrically coupled microgrids (MGs). A new bi-level EMS is employed as an enhanced technique to coordinate vehicle-to-grid (V2G) operation of electric vehicles (EVs) with a stochastic framework in a multi-microgrid system. Hierarchical EMS helps the system to preserve the privacy of each MG. The EV scheduling and demand response programs have been integrated simultaneously in the optimization strategy to reduce the load demand of the peak hours and reshape the load profile. Uncertainties related to the system load demand, renewable generations, EV fleet behavior and energy price are considered. The proposed stochastic system is solved by adaptive particle swarm optimization algorithm. Numerical studies on a two electrically coupled industrial and residential MGs test system verify the efficiency of proposed EMS for cost reduction of the system and optimal operation of V2G. |
| Databáze: | OpenAIRE |
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