Open AccessAn intelligent methodology to improve distribution system operational parameters utilising smart inverter functionalities of PV sources
Author(s) -
Verma Aprajay,
Verma Pranjal Pragya,
Eluvathiangal Anoop V,
Swarup K. Shanti
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.9241
Subject(s) - smart grid , computer science , inverter , voltage , photovoltaic system , genetic algorithm , power (physics) , distributed generation , low voltage , reliability engineering , grid , renewable energy , engineering , electrical engineering , mathematics , physics , geometry , quantum mechanics , machine learning
The addition of distributed PV sources to low voltage distribution networks instigate issues to various operational parameters of the network. With modern smart inverters having controllable settings for voltage and power injection these issues can be alleviated. An Intelligent method utilising smart inverter functionalities of a PV source in a distribution network is proposed in present work to minimise, the power import from the grid, reduce network losses and minimise the magnitude of voltage violation. The optimal settings depend on load and generation variables. In order to reduce computational complexity, a scenario‐based method is used to handle these stochastic components in the system. A Non‐Sorted Genetic Algorithm (NSGA) is used for optimising the smart inverters parameters. The proposed scheme is envisaged to be realised by a Distribution Management System (DMS) which measures and coordinates all the smart inverters within the distribution feeder.