Hierarchical Optimization of DGs, BESSs, and D-STATCOMs for Reducing Energy Losses and CO2 Emissions in Unbalanced Off-Grid Networks
In developing countries, Non-Interconnected Zones often depend on costly, environmentally unsustainable, diesel-based power systems. These systems typically experience unbalanced load conditions, limited voltage regulation, and difficulty accommodating renewable energy sources. In this context, Dist...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universidad de Jaén |
| Repositorio: | RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén |
| OAI Identifier: | oai:ruja.ujaen.es:10953/6593 |
| Acceso en línea: | https://www.sciencedirect.com/science/article/pii/S2590123025031536?via%3Dihub https://doi.org/10.1016/j.rineng.2025.107098 https://hdl.handle.net/10953/6593 |
| Access Level: | acceso abierto |
| Palabra clave: | Distributed energy resources CO2 emission reduction Battery energy storage systems Distributed generation Distribution static compensators 621.35 |
| Sumario: | In developing countries, Non-Interconnected Zones often depend on costly, environmentally unsustainable, diesel-based power systems. These systems typically experience unbalanced load conditions, limited voltage regulation, and difficulty accommodating renewable energy sources. In this context, Distributed Energy Resources—including Distributed Generation (DG), Battery Energy Storage Systems (BESS), and Distribution Static Synchronous Compensators (D-STATCOMs)—represent a viable alternative, provided they are integrated and operated optimally under realistic technical and environmental constraints. This paper presents a methodology for the optimal integration and coordinated operation of DG, BESS, and D-STATCOMs in unbalanced three-phase distribution systems within NIZs. The approach is formulated as a bi-objective mixed-integer nonlinear programming problem to minimize annual energy losses and CO2 emissions. To validate the proposed methodology, two benchmark distribution systems—one with 25 nodes and one with 37 nodes—were adapted to represent the operating conditions of Leticia and San Andrés Island (both in Colombia), using actual demand and solar irradiance data. Five metaheuristic algorithms—Whale Optimization Algorithm (WOA), Vortex Search Algorithm (VSA), Chu & Beasley Genetic Algorithm (CBGA), Multi-Verse Optimizer (MVO), and Black Widow Optimization Algorithm (BWOA)—were implemented and compared after 100 independent runs per case study. BWOA demonstrated the best performance in both scenarios: in Leticia, it reduced energy losses by 77.0164% and CO2 emissions by 61.1426%; in San Andrés, it reduced energy losses by 65.4489% and emissions by 59.9654%. All solutions met voltage and thermal constraints, confirming the technical feasibility and environmental benefits of the proposed strategy for DER integration in isolated and constrained distribution networks. |
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