An intelligent methodology to improve distribution system operational parameters utilising smart inverter functionalities of PV sources

Abstract

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.

Keywords

• genetic algorithms
• invertors
• distributed power generation
• distribution networks
• photovoltaic power systems
• power distribution control
• smart inverters parameters
• distribution management system
• distribution feeder
• intelligent methodology
• distribution system operational parameters
• pv source
• distributed pv sources
• low voltage distribution networks instigate issues
• modern smart inverters
• controllable settings
• power injection these issues
• intelligent method utilising smart inverter functionalities
• distribution network
• power import
• network losses
• voltage violation
• optimal settings
• load
• generation variables
• scenario-based method