Operation cost minimization of droop-controlled DC microgrids based on real-time pricing and optimal power flow

In this paper, an optimal power flow problem is formulated in order to minimize the total operation cost by considering real-time pricing in DC microgrids. Each generation resource in the system, including the utility grid, is modeled in terms of operation cost, which combines the cost-efficiency of the system with the demand response requirements of the utility. By considering the primary (local) control of the grid-forming converters of a microgrid, optimal parameters can be directly applied to the control of this level, thus achieving higher control accuracy and faster response. The optimization problem is solved in a heuristic way by using genetic algorithms. In order to test the proposed algorithm, a six-bus droop-controlled DC microgrid is used as a case-study. The obtained simulation results show that under variable renewable generation, load, and electricity prices, the proposed method can successfully dispatch the resources in the microgrid with lower total operation costs.