Voltage Profile Estimation And Reactive Power Control Of Distribution Feeders

Abstract

Distribution systems are important transportation links for the delivery of electric power. Understanding the system conditions of distribution feeders is vital for controlling power systems and maintaining electricity flow on power grids. With better knowledge of the system conditions on distribution feeders, a deliberate and systematic approach can be taken to achieve more efficient and reliable power delivery. Furthermore, better understanding of system conditions can be useful in reducing operation and maintenance costs in various power system applications such as voltage control and capacitor bank switching. This dissertation presents a novel method for estimating the voltage profile of a radial distribution feeder using forecasted load demands and a three-phase power flow program. Additionally, using the forecasted system load and voltage estimations, an efficient proactive capacitor bank switching algorithm has been developed to control the capacitor banks on distribution feeders. The results of a comprehensive study of the effects of the short-term load forecasting software, the voltage profile estimation algorithm, and the capacitor switching algorithm are displayed in this dissertation. The topics presented in this dissertation include artificial neural networks for short-term feeder load forecasting, voltage profile estimation using three-phase power flows, capacitor bank switching for voltage improvement, and capacitor bank switching for switching reduction. A software package based on the dissertation's research has been developed for electric delivery companies as a planning and operating tool for use in a distribution management system. The software package offers the electric delivery company the ability to estimate system load and voltage conditions on distribution feeders as well as control the feeder's capacitor banks in a more intelligent and coordinated manner. Future integration will allow the software to function as an autonomous component in the distribution management system.