Economic Operation of a Microgrid Considering Uncertainties

This research presents economic operation of distributed energy resources in an islanded microgrid considering uncertainties associated with forecasting error of load, wind, and solar series. The forecasting is performed using artificial neural networks (ANN). A distribution of the forecasting errors was fitted. A discrete set of probabilities was used to create a set of possible scenarios representing possible deviations from the forecasted outputs of load, wind, and solar. The problem of economical operation of the electric grid was formulated as a stochastic optimization model to minimize expected total cost (ETC). The ETC expression consists of (a) expected operating cost of the generators, which includes linearized fuel cost and startup costs (b) expected operating costs of energy storage system and (c) expected interruption cost. Load demand data from New England area was tested to study the efficacy of this approach. A test system consisting of 10 conventional generators, 100 wind turbines at a maximum of 0.14 MW each, totaling 14 MW and 100 solar panels at a maximum of 0.36 MW each, totaling 36 MW was considered. Simulations were carried out in MATLAB and the results show that coordinating all energy resources (1) significantly enhances the power management capability of the grid (2) reduces the ETC in addition to (3) maintaining grid balance under high penetration of renewable energy sources.