An IGDT-based robust optimization model for optimal operational planning of cooperative microgrid clusters: A normal boundary intersection multi-objective approach

Economical and reliable energy management of isolated networked microgrids (NMGs) is a vital task on operators to optimally preserve system sustainability and security under severe uncertainties. To that end, in this paper, multi-objective risk-averse (RA) and opportunity-seeker (OS) information gap decision theory (IGDT) approaches are proposed to optimize the operational planning of isolated NMGs and assign robustness and opportuneness functions. Three optimization cases are defined as (I) only RES output power, (II) only load consumption, and (III) simultaneous RES and load uncertainties. Furthermore, an effective pricing model based on the microgrid marginal pricing is proposed for the proper management of power exchanges. A normal boundary intersection strategy is applied to generate distributed Pareto Frontier of the optimization model in Case III. The proposed approach is implemented on a test system with five NMGs in a 24-hour scheduling time horizon in which operating constraints are appropriately considered. Evaluating the IGDT-based numerical results verifies the effective performance of the proposed framework in the NMGs compared to the stochastic and Monte Carlo simulation methodologies. According to the results in Cases I and II, by increasing the total operating cost (TOC) up to 23% and 16%, it takes a perfect RA strategy. Also, opportunistic decision makings can be concluded with a 5% decrease in TOC. For Case III, the results with TOCs equal to 19769.19$ in RA strategy and 17612.55$ in OS strategy, are fully conservative and economic, respectively.