Open AccessA mathematical model‐based approach for DC multi‐microgrid performance evaluations considering intermittent distributed energy resources, energy storage, multiple load classes, and system components variations
Author(s) -
Anees Hafiz Muhammad,
Kazmi Syed Ali Abbas,
Naqvi Muhammad,
Naqvi Salman Raza,
Dastgeer Faizan,
Gelani Hassan Erteza
Publication year - 2021
Publication title -
energy science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.638
H-Index - 29
ISSN - 2050-0505
DOI - 10.1002/ese3.901
Subject(s) - microgrid , computer science , energy storage , distributed generation , dependency (uml) , efficient energy use , smart grid , intermittency , reliability engineering , distributed computing , engineering , renewable energy , power (physics) , turbulence , physics , control (management) , software engineering , quantum mechanics , artificial intelligence , electrical engineering , thermodynamics
The efficiency of DC microgrid needs investigation from a smart grid perspective, since their spread has expected to prevail in comparison with AC counterparts. Furthermore, there is a need to address the limitations (majorly to cater the intermittency of distributed energy resources (DERs) as well as the time dependency of systematic parameters etc.) in previous model and propose a new mathematical model to evaluate system efficiency for given parameters and scenarios. The core focus of current study aims at formulation of an improved (composite) mathematical model, that is capable of bridging issues and serve as a tool to address requirements of future DC systems including microgrids (MGs) and multi‐microgrids (MMGs). This research work offers such a mathematical model that consists of 3D matrices based on newly derived set of discrete time dependent equations, which evaluates the system efficiency of residential DC‐MMGs. Each DC‐MG is embedded with intermittent DERs, storage, components (with efficiency variations), and multi‐class load (with discrete time dependency), for evaluation across worst, normal, and best scenarios. A comprehensive sensitivity analysis across various cases and respective scenarios are also presented to evaluate overall system performance. Also, the impacts of system parameters on various system variables, states, and overall system efficiency have presented in this paper.