article · Engineering Technology & Applied Science Research
Autonomous power networks relying solely on diesel generators often run inefficiently because fluctuating demand forces generators to operate at partial load, increasing specific fuel use. An optimisation framework has been created to calculate the optimal size for battery energy storage integrated into these isolated systems. By factoring in non-linear fuel consumption, variable daily demand profiles, and dynamic battery behaviour, the method minimises overall system costs, including capital investment, fuel, and operational expenses. Tested through a simulation case study of an isolated power system, the sizing method allows the battery to smooth load fluctuations and keep the generator operating in higher efficiency bands. The resulting configuration reduces fuel consumption by roughly 25 percent and raises average generator efficiency from approximately 65 percent to 80 percent, offering a practical design method for standalone diesel systems.
Many remote communities and isolated facilities rely entirely on diesel generators, which burn expensive fuel inefficiently when electrical demand changes throughout the day. By determining the exact battery capacity needed to support these generators, operators can dramatically cut fuel use, lower running costs, and reduce greenhouse gas emissions without needing to rebuild their systems around renewable energy sources immediately.
The framework provides an engineering design tool for operators of remote microgrids, off-grid industrial sites, and isolated utilities seeking to retrofit existing diesel installations with energy storage. Because the methodology is validated through simulated case studies rather than physical field deployment, it currently sits at an applied research stage. Further testing in operational microgrids would be required before embedding it into commercial power-system planning software.
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This paper proposes an optimization-based approach for the optimal sizing of battery energy storage in autonomous diesel-based power systems operating under variable load conditions. In such systems, diesel generators frequently operate at partial load, resulting in increased specific fuel consumption and reduced overall efficiency. To address this limitation, a unified mathematical framework is developed that integrates nonlinear fuel consumption characteristics of the diesel generator, time-varying load profiles, and dynamic battery charge–discharge behavior. The optimization problem is formulated to minimize the total system cost, including fuel consumption, operational expenses, and battery investment, subject to power balance and operational constraints. A simulation-based iterative optimization procedure is employed to determine the optimal battery capacity that ensures efficient system operation. The proposed approach is validated through a case study of a representative isolated power system with realistic daily load variations. The results demonstrate that the optimal integration of battery energy storage significantly smooths the load profile and shifts generator operation toward higher efficiency regions. Compared to the baseline system without storage, the optimized configuration achieves a reduction in fuel consumption of approximately 25% and improves the average operating efficiency of the diesel generator from approximately 65% to 80%. Unlike conventional approaches that primarily focus on hybrid renewable systems, the proposed method specifically addresses diesel-only autonomous systems and provides a practical and computationally efficient tool for techno-economic system design. The developed framework can be applied to a wide range of isolated power supply systems to enhance operational efficiency and reduce environmental impact.
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DOI: 10.48084/etasr.19724
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