Modelling and Energy Management of an Off-Grid Distributed Energy System: A Typical Community Scenario in South Africa

Adewale Zakariyahu Obaro (), Josiah Lange Munda and Adedayo Adedamola Yusuff
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Adewale Zakariyahu Obaro: Department of Electrical Engineering, Tshwane University of Technology, Staatsartillerie Rd, Pretoria West, Pretoria 0183, South Africa
Josiah Lange Munda: Department of Electrical Engineering, Tshwane University of Technology, Staatsartillerie Rd, Pretoria West, Pretoria 0183, South Africa
Adedayo Adedamola Yusuff: Department of Electrical Engineering, University of South Africa, Florida Campus, Johannesburg 1709, South Africa

Energies, 2023, vol. 16, issue 2, 1-30

Abstract: Conventional power systems have been heavily dependent on fossil fuel to meet the increasing energy demand due to exponential population growth and diverse technological advancements. This paper presents an optimal energy model and power management of an off-grid distributed energy system (DES) capable of providing sustainable and economic power supply to electrical loads. The paper models and co-optimizes multi-energy generations as a central objective for reliable and economic power supply to electrical loads while simultaneously satisfying a set of system and operational parameters. In addition, mixed integer nonlinear programing (MINLP) optimization technique is exploited to maximize power system generation between interconnected energy sources and dynamic electrical load with highest reliability and minimum operational and emission costs. Due to frequent battery cycling operation in the DES, rainflow algorithm is applied to the optimization result to estimate the depth of discharge (DOD) and subsequently count the number of cycles. The validity and performance of the power management strategy is evaluated with an aggregate load demand scenario of sixty households as a benchmark in a MATLAB program. The simulation results indicate the capability and effectiveness of optimal DES model through an enhanced MINLP optimization program in terms of significant operational costs and emission reduction of the diesel generator (DG). Specifically, the deployment of DES minimizes the daily operational cost by 71.53%. The results further indicate a drastic reduction in CO 2 emissions, with 22.76% reduction for the residential community load scenario in contrast to the exclusive DG system. This study provides a framework on the economic feasibility and effective planning of green energy systems (GESs) with efficient optimization techniques with capability for further development.

Keywords: distributed energy system; photovoltaic system; energy storage system; wind turbine; greenhouse gas emission; mixed integer nonlinear programing (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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