Probabilistic optimal coordinated planning of molten carbonate fuel cell-CHP and renewable energy sources in microgrids considering hydrogen storage with point estimate method

The ever-growing augmentation of Renewable Energy Sources (RES) and Combined Heat and Power (CHP) units in microgrids (MG) exacerbates schedule management requirements in such systems. In this paper, a modified hybrid Bird Mating Optimization Differential Evolution (BMO-DE) algorithm is developed to address the mixed integer nonlinear programming problem of MG units' probabilistic optimal planning. The proposed MG structure is consisted of MCFC-CHP, Wind Turbines (WT) and Photovoltaics (PV). The presented stochastic model schedules MG units coordinately, while the strategy of MCFC-CHP hydrogen storage is taken into account. The proposed solution models the uncertain parameters of electricity price, wind speed and sun irradiation using the 2m + 1 Point Estimate Method (PEM). The modeling of uncertain parameters results in more accurate planning and operation of the entire system. The proposed solution is applied on a 33-bus distribution network. In this manner, the total power loss decreased to 358.5 kW and the total operation cost is 3.1349 x 10(4)$, which shows 18% decrease compared to MINLP method and 25% decrease compared to GA-PSCAD method of the total operation cost using the BMO-DE method. The results also justified the usage of CHPs while supplying thermal loads due to increased efficiency and profit.