Modeling and Control of Intermediate Point Temperature of A 1000-WM Ultra Supercritical Thermal Power Plant

This paper proposes an improved fuzzy particle swarm optimization algorithm (FPSO) to model intermediate point temperature. In FPSO, the plant-wide operation region with high nonlinearity is divided into several local regions by clustering algorithm. Following an improved particle swarm optimization algorithm is used to obtain local linear models. Then, fuzzy strategy is introduced to fuse the local models to get the model of the whole system. Besides, an improved generalized predictive control (GPC) is introduced to improve the control performance based on the identified modes. Finally, the simulation results show that the proposed modeling and control method can achieve accurate model identification and effective control of the intermediate point temperature.