Robust optimization of distributed generation investment in buildings

This paper presents a robust optimization method to determine the optimum capacity of distributed generation technologies for buildings in the face of uncertain energy demand. The model presents capacity requirements of energy system that is almost optimal for different realizations of the uncertain demand. By adjusting the penalty and degree of solution robustness parameters, the trade-off between optimality and feasibility is analyzed. The optimization is carried out on three related criteria, economical, primary energy saving, and environmental performance as a multi-objective optimization.The optimum capacity of distributed generation technologies has a great effect on the performance indicators of the building. In order to show this effect, the proposed method is applied to a hospital in Iran as a case study. It is assumed that the Combined Heat and Power (CHP) unit has both absorption and electric chiller for cooling loads, and a supplementary boiler for heating loads. In addition to them, thermal storages and renewable technologies are an option. The results show that by taking into account more solution and model robustness, the capacities of CHP and absorption chiller are increasing until they reach to their respective capacities in the solution of high scenario, while the capacities of others are decreasing. Furthermore, recommended values for the penalty and degree of solution robustness parameters are presented.

► We modeled optimizing the capacity of DG technologies for buildings.
► A multi-objective optimization is carried out.
► A robust optimization method is presented.
► The optimum capacities of CHP and absorption chiller increase in comparison to SP solution.
► The capacities of the electric chiller and boiler decrease in comparison to SP solution.