The traditional power system optimization model usually use the inherent technical output of the thermal power unitas the output constraint of the unit

in actual operation

the unit’sdis patching output range is also affected by the net load and theunit’s output during the previous period

there is a large optimization space for output constraints. In order to effectively reduce the feasible range of unit output variables

a net load incremental indexis proposed

and the index and the output state of the unit in the previous period are used to determine the dispatch able space of eachunit. With the scope of schedulable space as a constraint

an improved dispatching model for improved power systems is established. A hybrid particle swarm optimization algorithm combining standard particle swarm optimization and simulated annealing algorithm is used. The example results show that the hybrid particles warm optimization algorithm can effectively improve the shortcomings of the standard particle swarm optimization algorithm to fall into the local optimum

and improve the accuracy of the model solution. In addition

compared with the traditional optimization scheduling model

the improved optimization scheduling model of power system that introduces schedulable space constraints

while ensuring the accuracy of the solution

the calculation amount is greatly reduced

and it is not easy to fall into a local optimum. the improved ideas and methods can also be applied to the optimization scheduling model of other energy systems.