The connection of large-capacity loads at nodes in a radial distribution network can readily lead to severe voltage sag phenomena, thereby significantly deteriorating power supply quality. To ensure the safe operation of both voltage-sensitive equipment and the power grid, the deployment of Dynamic Voltage Restorers (DVR) and Static Var Compensators (SVC) is recognized as one of the most effective countermeasures for addressing voltage sag issues. Considering the inherent topological characteristics of the radial distribution network, a dimensional collaborative governance strategy is proposed, which takes longitudinal dimension collaborative governance as the primary approach and horizontal dimension collaborative governance as a supplementary measure. Based on sensitivity analysis, the concepts of horizontal sensitivity and longitudinal sensitivity are defined. Furthermore, considering the response time of governance equipment, the voltage sag governance process is divided into two distinct stages: in the first stage, governance is primarily reliant on DVR, and a longitudinal dimension collaborative optimization algorithm is proposed to solve the corresponding optimization model; in the second stage, governance mainly utilizes SVC, where a standard particle swarm optimization (PSO) algorithm is employed to solve its optimization model. A case study conducted on a 42-node radial distribution network validates that the proposed approach effectively governances the voltage sag problem in the distribution network. Through analysis, the number of nodes experiencing voltage sag was reduced from 29 to 0 in both the first and second governance stages. In the first stage, the total compensation voltage of the DVR is 0.581 p.u. With the coordinated participation of SVC in the second stage, the total DVR compensation voltage decreases to 0.100 p.u., corresponding to a significant reduction of 82.79%. Given the higher capital cost of DVR relative to SVC, this substantial decrease in required DVR capacity effectively lowers the overall governance cost.
Liu et al. (Wed,) studied this question.