Energy Management of Multi-Area Islanded Hybrid Microgrids: A Stochastic Approach

This paper provides a stochastic framework for the energy management of multi-area hybrid microgrids to identify the optimal daily power dispatch in the islanded mode of operation. The primary goal of this framework is to minimize operational costs and power outages for customers by effectively mana...

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Vydáno v:IEEE access Ročník 11; s. 101409 - 101424
Hlavní autoři: Ibrahim, Mohamed M., Hasanien, Hany M., Farag, Hany E. Z., Omran, Walid A.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
AC-DC power converters
AC/DC power flow
Algorithms
Alternative energy sources
Computer simulation
Costs
Diesel generators
Distributed generation
Electric vehicle charging
Electric vehicles
Energy management
Energy resources
Energy storage
Heuristic methods
islanded hybrid microgrid
Load flow
Microgrids
Mixed integer
Monte Carlo simulation
Nonlinear programming
Operating costs
Optimization
Optimization techniques
Power dispatch
Reactive power
Reliability
Renewable energy sources
Renewable resources
Storage systems
Uncertainty
ISSN:2169-3536, 2169-3536
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Shrnutí:This paper provides a stochastic framework for the energy management of multi-area hybrid microgrids to identify the optimal daily power dispatch in the islanded mode of operation. The primary goal of this framework is to minimize operational costs and power outages for customers by effectively managing the power resources of the hybrid microgrid. These resources include renewable energy sources, battery energy storage systems, and electric vehicles. To obtain accurate results, the costs related to active and reactive powers of diesel generator units are considered in this study. In addition, the uncertainties in the, power generated from renewable energy sources, electric vehicles charging and microgrid demand are modeled using the Monte Carlo Simulation as a scenario generation technique. The number of generated scenarios is reduced using the Fast Forward Scenario reduction technique. The proposed problem is formulated as a constrained mixed-integer nonlinear programming optimization problem and is solved using the Transient Search Optimization algorithm. The obtained solution is compared against other meta-heuristic optimization techniques to ensure the reliability of the results. To investigate the effectiveness of the proposed framework, several case studies are simulated on an islanded hybrid microgrid. The simulation results show the improvement in the economic performance and the reliability of the hybrid MG. The results also indicate the impact of increasing penetration levels of renewable energy resources on the operation cost and power exchange between AC and DC areas.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2023.3313259