| Popis: |
Flexibility from stationary batteries and electric vehicles allow home energy management systems to optimally consume local photovoltaic generation. The aggregated flexibility potential of a set of energy management systems can further contribute to a common objective, e.g., peak shaving at the transformer station. This paper formalizes the (non-convex) goals of involved stakeholders when disaggregating a flexibility request to a pool of energy management systems as multi-objective problem. The proposed genetic algorithm optimizes for the resource aggregator ( minimizing cost and maximizing delivery probability ), the grid operator ( minimizing grid losses ), the resource provider ( maximizing autarky and self-consumption ), and a fairness provider ( maximizing fairness among participants ). A disaggregation schedule that satisfies the objectives of all stakeholders can be chosen a posteriori from the Pareto-optimal solution set, which is demonstrated with a case study on the IEEE 906 low voltage test feeder. |
