Grid Optimal Integration of Electric Vehicles: Examples with Matlab Implementation by Andrés Ovalle Ahmad Hably & Seddik Bacha

Author:Andrés Ovalle, Ahmad Hably & Seddik Bacha
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

4.3 The MSD Approach for PEV Load Management

Taking into account the MSD description and following some analogies, a multi-population model is proposed for the PEV load scheduling problem. In this multi-population model, energetic quantities must be allocated to time slots according to a certain benefit. First, the total load of a transformer in a distribution system is considered as the total population. The forecast load of the transformer is represented as a sedentary population that does not follow any dynamics. On the other hand, the numerous controllable PEV loads are represented by nomad populations choosing among mixed strategies (defined by PEV owners as it will be observed). Each time slot considered in the forecast horizon is represented as an environment or pure strategy. Each nomad population can be distributed in several time slots or environments. The distribution of single populations will evolve following the MSD according to the payoff obtained from their mixed strategies. As it is defined before, MSs are convex combinations of pure strategies. In this case a mixed strategy can be seen as one of multiple options for fully charging the PEV. Conversely, MSs are ways of distributing the individual population among environments (among time slots).

Fig. 4.6 a Example of a distribution of a single population (PEV load) in three environments (pure strategies, or time slots). b Example of a multi-population model, with populations willing to migrate (PEV load) through available environments, and sedentary populations (Base load forecast). c Example of distribution of a single population (PEV load) among three predefined MSs, and the resulting distribution among pure strategies.

[2017] IEEE. Reprinted, with permission, from [Ova+16b]

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