Optimizing thermal–electric load distribution of large-scale combined heat and power plants based on characteristic day

Abstract

Optimizing thermal–electric load distribution toward combined heat and power (CHP) units can improve the efficiency of thermal power plants. Here, a thermal–electric load distribution method is proposed based on the energy consumption characteristics of CHP plants. The influence of operation modes on the energy consumption characteristics has been considered. Based on the energy consumption characteristics, the influence of load distribution on the heat rate is expounded considering two units operating in parallel. Firstly, a 600 MW unit model is developed using the EBSILON software, and the associated energy consumption model is established by passing the simulation results to a MATLAB routine. Then, three distribution methods are used to study the influence of the thermal–electric load distribution on the heat rate. Finally, the energy consumption model is embedded into a momentum particle swarm optimization (MPSO) algorithm, and the thermal–electric load distribution is optimized using the load data from a characteristic day with the operation feasible region taken as the boundary. The results show that the thermal load plays a major role in the energy efficiency of the unit, and the electric load determines the exergy efficiency distribution. The operation mode of the unit has little influence on the energy utilization rate, but has a significant influence on the exergy efficiency. When two CHP units are running in parallel, their heat rate can be reduced by optimizing the thermal–electric load distribution. A more uneven distribution of thermal–electric load between units results in a lower heat rate. The optimized heat rate given by the MPSO algorithm for a characteristic day is 6887.93 kJ·kWh−1, which is 304.44 kJ·kWh−1 less than under the average thermal–electric load distribution. These findings may be helpful to get insight into the energy consumption characteristics of CHP plants and guide for its economic operation.