Open AccessOptimal design of hybrid DG systems for microgrid reliability enhancement
Author(s) -
Yahaya Abass Afolabi,
AlMuhaini Mohammad,
Heydt Gerald Thomas
Publication year - 2020
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.2019.0277
Subject(s) - microgrid , reliability engineering , particle swarm optimization , sizing , renewable energy , reliability (semiconductor) , pareto principle , computer science , photovoltaic system , distributed generation , wind power , component (thermodynamics) , monte carlo method , mathematical optimization , electric power system , hybrid system , engineering , power (physics) , algorithm , electrical engineering , mathematics , physics , quantum mechanics , art , statistics , machine learning , visual arts , thermodynamics
While the concept of microgrids and renewable energy systems is not entirely new, these integrated technologies have become a special topic of interest for researchers, utility providers and governments. Many challenges must be overcome to achieve better integration of renewable sources into the energy framework. This study presents some viable possibilities for the utilisation of a hybridised microgrid system. The hybridisation is achieved by an efficient design approach for the enhancement of both load and system reliability indices through the intelligent placement and sizing of hybrid distributed generation (DG) systems. Real‐time models of solar photovoltaics, wind turbines, batteries and thermal DGs are presented and implemented. Also, network component failures are stochastically modelled via Monte Carlo simulations, and a general tie‐set algorithm using an adapted breadth‐first search is proposed. Moreover, mixed‐integer multi‐objective particle swarm optimisation is employed, giving a four‐dimensional Pareto solution that is attained by optimising four reliability‐related objectives, namely system average interruption frequency index, System Average Interruption Duration Index (SAIDI), Energy Not Supplied (ENS) and total cost.