Optimal dispatch of combined heat and power units based on particle swarm optimization with genetic algorithm

The main purpose of this paper is to optimize the consumption of renewable energy and minimize the total cost of system operation, and a combined heat and power unit is added to the wind, water, and water combined dispatching model to solve typical daily dispatch problems in different seasons. Initially, a combined wind–solar–water-fired optimal scheduling model containing cogeneration units and renewable energy preferential consumption is constructed, and the model is solved using particle swarm optimization with the genetic algorithm. The simulation analysis of typical electrical load and heat load during summer and winter in a certain area is implemented as an example to verify the feasibility of the model and algorithm. Compared with the traditional vertical integrated electric-heated coordinated dispatch, the proposed method reflects the willingness of the combined heat and power to actively participate in the paid peak regulation of the power grid under economic incentives.