Nested evolutionary algorithms for joint structure design and operation of micro-grids under variable electricity prices scenarios

This paper proposes to tackle the structure design and operation of a Micro-Grid in a jointly way, by means of a novel nested Evolutionary Algorithms (EAs) approach. Specifically, in an scenario of variable electricity prices in an hourly basis, we apply different EAs, nested, to obtain optimal values for the sizing of generators and Energy Storage System (ESS), also to obtain the optimal values for each access tariff periods (structure part of the MG), and ESS scheduling (operational part of the MG). The proposed nested EAs starts from an initial solution for the ESS scheduling given by a deterministic approach (DA algorithm), from which an initial structure part is obtained by means of a first evolution. This part is set, and a different EA is then applied to obtain an improved ESS scheduling, which will be set to apply a different EA for the structure part. This scheme is applied in a sequential fashion for a number of evolutions. We will show that the proposed evolution scheme is able to obtain excellent results in terms of MG design, better than those by a single EA with the same number of function evaluations.