Dynamic reactive power optimization of distribution network with distributed generation based on fuzzy time clustering

Abstract

In order to solve the coordinated optimization problem of distributed generation (DG), on-load tap changer (OLTC) and capacitor banks, a dynamic reactive power optimization (DRPO) method based on fuzzy time clustering is proposed. In the method, fuzzy time clustering algorithm is used to cluster the static optimal switching sequence of OLTC and capacitor banks. The time decoupling of control variables is realized and it meets the constraints of the maximum switching times. Next, the influencing factors of DG reactive power limit are analysed. Considering the control ability of OLTC, capacitor banks and DG in voltage and reactive power optimization, a coordinated optimization method is proposed. Since the adjustment of OLTC tap position directly affects the voltage and reactive power distribution of the whole line, the switching time and tap position of OLTC are determined based on the static optimization results of each time and fuzzy time clustering algorithm. Then, the switching time of capacitor banks is determined by fuzzy time clustering algorithm. At last, the switching capacity of capacitor banks and DG reactive power are jointly optimized to get the final control scheme. The proposed method demonstrated good performance in the modified IEEE33 node system and two actual power grid examples.

Traceless Kalman filter threshold estimation for distributed power loads

“…In reality, power load is not a fixed trend due to the influence of many factors such as economy, region, enterprise, power supply system, etc. [10][11]. It has an obvious stochastic and time-varying nature, so the reliability of the power load prediction results of the traditional model is difficult to ensure.…”