Mid-term operational planning of pre-installed voltage regulators in distribution networks. (December 2021)

• Record Type: Journal Article
• Authors: Attar, Mehdi; Repo, Sami; Homaee, Omid; Siano, Pierluigi
• Is Part Of: International journal of electrical power & energy systems. Volume 133(2021)
• Publication Date: 2021-12
• Subjects: Genetic algorithm -- Mid-term operational planning -- Power loss reduction -- Settings optimization -- Tap operation -- Voltage regulator -- ZIP Load model; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2021.107276
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Offline setting optimization of pre-installed voltage regulators. ZIP load model consideration in setting optimization of voltage regulators. Impact of load model negligence or inaccuracy on setting optimization of voltage regulators. New and practical method of voltage control based on offline settings optimization. Abstract: In this paper, a methodology is presented to maximize the effectiveness of pre-installed Voltage Regulators (VRs) in medium voltage distribution networks. While considering the daily tap operation limitation of VRs, this method contains mid-term operational planning of VRs' settings which is carried out to satisfy voltage constraints in distribution networks and reduce power losses throughout the network. The proposed approach optimizes the settings periodically, leading to Distribution System Operators (DSOs) ' financial benefit because energy losses are reduced by applying the proposed method. Using different combinations of ZIP load model coefficients in the optimization process, the importance and impacts of the load model in the optimization of VRs' settings are also investigated because the operation of a VR directly influences the consumption of voltage-dependent loads (depending on their type of voltage dependency). Due to the discrete nature of the problem, the Genetic Algorithm (GA) has been employed as a tool to attain the previously mentioned goals by optimizing the settings of VRs for forthcoming months. Numerical studies carried out for a 70-bus distribution network show that a reduction of energy loss is achieved by applying the article's proposed method.