Optimal generation scheduling of small diesel generators in a microgrid

To optimize generation scheduling of four diesel generators in a planned microgrid, we applied General Algebraic Modeling System (GAMS) and Genetic Algorithm (GA). The aim is to minimize power generation costs which depend on high and volatile diesel prices, and consequently to reduce emissions. A mixed-integer quadratic constrained model for the optimal scheduling was formulated and solved by CPLEX solver in GAMS. Results were confirmed by reformulating the model using penalty functions and solving it by the GA. A saving of 37.7% on weekly operation cost was realised by using GAMS. In some instances, the GA converged to the same results as those of GAMS while in others it converged to a suboptimal cost with a an error of 1.02%. These results quantify economic gain obtained by optimizing operation of a group of small diesel generators in a microgrid even without including renewable energy sources.