Determination of Estimation Accuracy of Voltage Profiles Required for Proper Voltage Control by On-Load Tap Changer in Distribution Systems

Author:

Akasaka Riku1,Hara Ryoichi1ORCID,Kita Hiroyuki1,Sugimura Shuhei2,Kurihara Toshiharu2

Affiliation:

1. Power and Energy Systems Laboratory, Faculty of Information Science and Technology, Hokkaido University, Sapporo 060-0808, Japan

2. Meidensha Corp., Tokyo 141-6029, Japan

Abstract

The introduction of a large number of photovoltaic systems to distribution systems has increased the complexity of the voltage profile. It is thus necessary to manage voltage at a higher system level. For this purpose, the voltage profile of the distribution system can be calculated using state estimation and the voltage can be controlled based on the estimated values. Many methods for estimating voltage profiles using state estimation have been developed. However, the estimation accuracy of voltage profiles required for proper voltage control has not been discussed. If the assumed required estimation accuracy is too high, then more meters than necessary will be installed, unnecessarily increasing costs. Conversely, if the assumed required estimation accuracy is too low, voltage control equipment will not operate properly, and voltage violations may occur. Thus, it is important to determine the required estimation accuracy of voltage profiles for proper voltage control. In this paper, the estimation error of the voltage profile is expressed using a probability density function, and the estimation accuracy of voltage profiles required for proper voltage control is examined. A numerical case study was performed on a distribution network model with 2160 consumers, and revealed the following. To prevent voltage violations, an estimation accuracy of voltage profile that is approximately 10 times lower than that of the estimation accuracy based on current measurement equipment data is sufficient. To minimize the number of tap operations, an estimation accuracy needs to be improved by 70% compared with the estimation accuracy based on current measurement equipment data.

Funder

JST

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Reference24 articles.

1. Hemetsberger, W., Schmela, M., and Cruz-Capellan, T. (2023). Global Market Outlook For Solar Power 2023–2027, SolarPower Europe.

2. Power system dynamic state estimation: Motivations, definitions, methodologies, and future work;Zhao;IEEE Trans. Power Syst.,2019

3. Observability analysis and bad data processing for state estimation with equality constraints;Wu;IEEE Trans. Power Syst.,1988

4. Koopman Kalman Particle Filter for Dynamic State Estimation of Distribution System;Wang;IEEE Access,2022

5. State Estimation in Power Distribution Systems Based on Ensemble Kalman Filtering;Carquex;IEEE Trans. Power Syst.,2018

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