Abstract
The management optimization of energy systems composed by different generators is nowadays a very important topic to increase the efficiency of power generation and reach the goals of polluting emissions control. When considering complex energy systems composed by different technologies, like small power grids, the management strategy is a key aspect that is related with both economic and energy demands. To this purpose, optimization methods and algorithms have to be developed to define the unit commitment of generators and avoid economic and energy losses. In this paper, a novel Mixed Integer Linear Programming (MILP) optimization algorithm has been developed to compute the optimal management of an energy system composed by four Internal Combustion Generators (ICGs). The algorithm optimizes a multi objective function that takes in consideration the total cost and the NOx emissions of the system, while considering some technological constraints, like start-ups and transients that are typically neglected. The model proved to be very flexible and to be a proper basis to be adopted in more complex systems embedding energy storage devices and renewable energy systems.