This paper presents three different methods to optimize a day-ahead self-scheduling for an isolated DC microgrid operation. Based on forecast data, a multi-objective cost function is formulated aiming to minimize the total energy cost by reducing the micro-turbine fuel consumption, avoiding photovoltaic power limitation and load shedding, while respecting the storage parameters and microgrid operation constraints. The problem is solved with two different optimization algorithms and one rule-based algorithm. The comparison is made on the total energy cost and computational cost for each proposed approach. The results prove that the mixed integer linear programing optimization permits to obtain the lower total energy cost with a reasonable computational cost.

Abstract:The microgrid system is an answer to the necessity of increasing renewable energy penetration and also works as a bridge for the future smart grid. Considering the microgrid system applied to commercial building equipped with photovoltaic sources, the usage of a DC microgrid architecture can improve the efficiency of the system, while ensuring robustness and reducing the overall energy cost. Given the power grid stress and the intermittency of the DC microgrid power production, backup power provision and load shedding operations may occur to stabilize the DC bus voltage. Based on the knapsack problem formulation, this paper presents a realistic optimization approach to shedding a building's appliances, considering the priority of each appliance, and also considering a minimum amount of load that must be attended. The problem is solved by mixed integer linear programming and the CPLEX solver. The proposed architecture ensures critical load supply and voltage stabilization through the real-time operation of the operational algorithm allowing the load shedding optimization approach to be applied without compromising the robustness of the system. The results obtained by simulation prove that the DC microgrid is able to supply the building power network by applying the load shedding optimization program to overcome, mainly, the renewable energy intermittency.

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