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This manuscript explores the selection of appropriate mixed strategies (MSs) in a Mixed Strategist Dynamics (MSD) application for load management of Plug-in Electric Vehicle (PEV) fleets. This selection is based on the convenience of PEV owners, aiming to choose those MSs that privilege early high (or fast) charging rates when it is possible. The previously published MSD and Maximum Entropy principle (MSD-MEP) approach is revised and illustrated with several examples, specially in the context of selection of MSs. This revision allows a wider understanding of the method, and aims to inspire new contributions on domains where distributed optimization methods are pertinent. Results obtained without any management structure are compared to those obtained with the MSD-MEP approach under different scenarios, where full sets of MSs and reduced sets of convenient MSs are applied. The performance of the method, using conveniently reduced sets of MSs, is tested with real historical active power measurements, provided by the SOREA utility grid company in the region of Savoie, France.

On the most convenient mixed strategies in a mixed strategist dynamics approach for load management of electric vehicle fleets