Three-stage optimization method for distributed energy system design under uncertainty

Abstract

Reasonable capacity configurations of distributed energy system are issues which need to be discussed. Determinate design without considering variations in energy load and energy prices can result in non-achievement of project targets during its service life. Therefore, a design method that takes into account uncertain factors takes precedence over other methods. In this paper, a three-stage optimization method is proposed to provide theoretical guidance on the optimization of combined cooling, heating, and power system configurations. The first two stages link the optimization of the operation strategy and equipment capacities simultaneously under current load and energy prices. The Monte-Carlo simulation is applied in the third stage to fully consider the effects of various possible scenarios, and the Tabu search algorithm was introduced for system optimization. The comprehensive benefits include energy consumption, economy, and emission level. These were taken into consideration in the objective function. Moreover, a detailed design process was presented to illustrate the application of the proposed method. In conclusion, the proposed method is not only suitable for the design of combined cooling, heating, and power system, but could easily extend to other energy system easily.