Abstract
To improve the reliability and reduce power loss of distribution network, the dynamic reconfiguration is widely used. It is employed to find an optimal topology for each time interval while satisfying all the physical constraints. Dynamic reconfiguration is a non-deterministic polynomial problem, which is difficult to find the optimal control strategy in a short time. The conventional methods solved complex model of dynamic reconfiguration in different ways, but only local optimal solutions can be found. In this paper, a data-driven optimization control for dynamic reconfiguration of distribution network is proposed. Through two stages that include rough matching and fine matching, the historical cases which are similar to current case are chosen as candidate cases. The optimal control strategy suitable for the current case is selected according to dynamic time warping (DTW) distances which evaluate the similarity between the candidate cases and the current case. The advantage of the proposed approach is that it does not need to solve complex model of dynamic reconfiguration, and only uses historical data to obtain the optimal control strategy for the current case. The cases study shows that the optimization results and the computation time of the proposed approach are superior to conventional methods.
Highlights
The reconfiguration of distribution network is an important mean to improve the reliability and economy of the distribution network by opening the normally closed sectionalizing switches and subsequently closing the normally open switches
Taking 1 h as the step size, 48 numeric features of each load series are extracted by piecewise aggregate approximation
To screen several candidate cases for the first time, and adjust the threshold by dichotomy until 50 the optimal control strategy for static reconfiguration is obtained by the enumeration method
Summary
The reconfiguration of distribution network is an important mean to improve the reliability and economy of the distribution network by opening the normally closed sectionalizing switches and subsequently closing the normally open switches. The reconfiguration of distribution network can be divided into static reconfiguration and dynamic reconfiguration according to the different optimization time scales. The static reconfiguration of distribution network is a multi-objective nonlinear hybrid optimization problem that focuses on one determined time point. The optimization process requires a lot of computing time because of its nonlinear characteristics. The static reconfiguration neglects the conditions such as load changes and switch operation constraints, which are difficult to apply directly in practical projects. Many scholars have proposed various algorithms to solve static reconfiguration. The traditional methods mainly include newton method, quadratic programming, artificial neural network, interior point method, heuristic algorithm and so on.
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