An economic study of control strategies for microgrids

A centralized model predictive control algorithm (MPCA) and an optimal centralized control algorithm (OCCA) are applied on main grid connected with a group of interconnected microgrids (MGs). Maximizing the profit for all of the units constituting the MGs is the primary objective in both algorithms,...

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Published in2018 4th International Conference on Renewable Energies for Developing Countries (REDEC) pp. 1 - 8
Main Authors Hajar, Khaled, Hably, Ahmad, Bacha, Seddik, Elrafhi, Ahmad
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2018
Subjects
Energy management
Energy storage
Load modeling
Microgrids
Optimization
Prediction algorithms
Production
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Summary:A centralized model predictive control algorithm (MPCA) and an optimal centralized control algorithm (OCCA) are applied on main grid connected with a group of interconnected microgrids (MGs). Maximizing the profit for all of the units constituting the MGs is the primary objective in both algorithms, further the advantages of the principle grid. A forcasting information about production power, energy price and loads is needed for the application of MPCA in our study. five interconnected MGs related to the principle grid are tested in this paper using the algorithm implemented in MATLAB. The performance of the proposed algorithms has been shown especially for the benefits of MG owners at the same time as respecting the constraints associated to every considered one of them. Then the results of OCCA and MPCA are compared technically and economically for each MG.
DOI:10.1109/REDEC.2018.8598121