Open AccessEffect of load models on scheduling of VVC devices in a distribution network
Author(s) -
Satsangi Saran,
Kumbhar Ganesh Balu
Publication year - 2018
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.5262
Subject(s) - scheduling (production processes) , load profile , computer science , reliability engineering , energy consumption , electrical impedance , automotive engineering , power (physics) , schedule , constant current , control theory (sociology) , simulation , voltage , electrical engineering , engineering , mathematical optimization , electricity , mathematics , control (management) , physics , quantum mechanics , artificial intelligence , operating system
Volt/VAr optimisation (VVO) is one of the important techniques used for reduction of energy consumption, energy losses, and peak demand. The proper load modelling is necessary in order to accurately schedule the volt/VAr control (VVC) devices. In the past, most of the studies have evaluated energy losses of the network by considering constant power type of loads. Some studies also have considered different types of loads such as constant power ( PQ ), constant current ( I ), and constant impedance ( Z ). However, there is no literature on the effect of load models on the scheduling of VVC devices. The purpose of this study is to show the impact of load models on various operating parameters in VVC. In this study, the impact of different load models on the scheduling of VVC devices is analysed. Time‐series simulations are carried on the modified IEEE‐123 node unbalanced radial distribution network, where industrial, commercial, and residential loads are connected at various locations. A comparative study is performed under VVO framework to analyse energy consumption, losses, and peak power demand. The important objective of this study is to find the best settings of VVC devices with various load models while minimising apparent energy losses of the network.