Optimal Load Distribution In Plant-level Based On Equipment Status

With the development of new energy sources such as wind power and photoelectricity,the competitive pressure of thermal power plants is increasing.Unit load optimal distribution is an important part of power plant in optimization of operation,and it is also a typical optimization problem in power system.The traditional load optimal distribution thinks that the thermal power unit is fully adjustable,but in the actual power generation process,there are many uncontrollable factors in the thermal power unit,it is not fully adjustable,it is necessary to consider the operation state of the thermal power unit equipment into the load optimal distribution model.In this paper,based on the in-depth analysis of the domestic and foreign methods of unit load optimal distribution,a particle swarm optimization method based on the equipment state is proposed.The multi-element state estimation method(MSET)is used to evaluate the equipment state.The orthogonal local preserving projection(OLPP)algorithm is introduced to reduce the dimension of the parameters in the model,and the OLPP-MSET state evaluation model is established.Taking the induced draft fan as an example,the validity of OLPP-MSET model is verified.The OLPP-MSET state evaluation model is applied to evaluate the equipment state of thermal power unit.According to the evaluation results of equipment state,the maximum possible output of the unit under different operation boundaries is analyzed,and the operation state of the equipment is considered in the optimal load distribution.The optimization model of load distribution considers the economy and environmental protection of load distribution.The improved multi-objective particle swarm optimization(MOPSO)algorithm is applied to optimize the load distribution.The optimization ability of the improved MOPSO algorithm is stronger than that of MOPSO.The results show that the optimal load distribution considering the equipment status of the thermal power unit can reflect the actual situation of the unit,and can better ensure the rationality of the optimal load distribution of the thermal power unit under different operating conditions.It provides the basis for further research on improving the operation optimization of thermal power units.