A Virtual Power Plant Optimization Scheduling Model Considering Multiple Types of Loads

With the rapid construction of new power systems, the proportion of renewable energy continues to increase, posing huge challenges to the safety and stability of traditional power systems. It is difficult to cope solely with the regulation capabilities of traditional power plants, and it is necessary to tap into the regulation potential of flexible resources on the user side to ensure the low-carbon economic operation of virtual power plants. Therefore, this article analyzes the market operation mode and carbon trading mechanism of virtual power plants. Based on the elasticity coefficient and active acceptance degree of multiple types of loads on the user side, a virtual power plant day ahead optimization scheduling model is established in the time-of-use pricing environment, and three strategies are designed for example analysis. The results indicate that Strategy 3, taking into account the demand response capabilities of different types of loads, adopts time-of-use pricing for all users, which can reduce the costs of virtual power plant electricity and carbon markets, increase the profits of virtual power plant operators and users, and significantly improve the internal load rate and user acceptance of virtual power plants while ensuring that the electricity costs of users remain unchanged.