Multi-Objective Optimization of Steam Power System Under Demand Uncertainty

There are many uncertain factors, which are critical for the efficient operation of steam power systems (SPSs). Due to the modelling inaccuracy and the changing environment, it is challenging to directly formulate the model for SPS operation. In this paper, a method is proposed to alleviate the influence of small-scale fluctuation by discretizing the uncertainty working condition on the SPS. Moreover, the exergy analysis method is proposed to evaluate the quality of different energy and develop a mixed-integer nonlinear model of SPS considering the economic and exergy objectives. Finally, the
$\varepsilon $
-constraint method is used to obtain the Pareto front of the multi-objective optimization problem, and the fuzzy decision is used to determine the optimal strategy of the system. By introducing the multi-objective optimization of the SPS model with demand side uncertainty, a flexible scheduling scheme with good economic and exergy objectives is obtained. Comparing with the optimal scheduling without the demand-side uncertainty, numerical results indicate the feasibility and effectiveness of the model.