Abstract:

This paper proposes an adjustable resource aggregation method and a coordinated scheduling strategy in distribution transformer station area based on time-of-use price and charge-discharge strategy for distributed energy storage considering the user's electricity cost and energy comfort. The proposed methods can realize the coordinated scheduling of adjustable resources and the coordinated optimization of different types of energy units in the distribution transformer station areas. First, the framework of the platform energy use management and control system is constructed, following the architecture of the distribution Internet of Things and based on the "cloud-edge" collaborative technology. Then, the platform loads are classified according to the response uncertainty, and the Monte Carlo algorithm is used to aggregate the power of typical adjustable resources. The effectiveness of the aggregation model is then analyzed. Finally, the load aggregator is introduced to interact with the station area. The linear weighting method is used to calculate the electricity cost and energy consumption comfort level of users, and the charge-discharge strategy of distributed energy storage is combined to model the adjustable resource scheduling model of the distribution transformer station area. The differential evolution algorithm is then used to solve the model. The example analysis shows that the adjustable resource aggregation model and the coordinated scheduling strategy proposed in this paper can effectively reduce the energy consumption cost of users, improve the energy consumption comfort level, promote the enthusiasm of users to participate in grid response and improve the station area's ability to control the adjustable resources.

Key words: distribution internet of things, power consumption control in distribution transformer station area, adjustable resources aggregation, load aggregators, coordinated scheduling