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 (CCHP) 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 (TS) 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 CCHP
system, but could easily extend to other energy system easily.
Optimal Hybrid Energy Storage System planning of Community Multi-Energy System Based on Two-Stage Stochastic Programming
