Advancing Electrification Planning Through Automated Network Design and Optimization
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| Publicado en: | ProQuest Dissertations and Theses (2025) |
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| Acceso en línea: | Citation/Abstract Full Text - PDF |
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| Resumen: | Electrical engineering design automation and optimization will help accelerate solutions to energy access challenges in sub-Saharan Africa. Conventional approaches rely on manual drafting and incomplete datasets that constrain scalability and hinder consistency in network performance across diverse geographies. This dissertation addresses that challenge by developing an integrated framework that automates distribution network design and extends the analytical capability to regions where empirical data are limited or unavailable. The framework combines geospatial modeling, data fusion techniques, and optimization to generate physically and electrically valid network layouts from minimal spatial and demand information. Using a mixed-integer linear programming (MILP) formulation, the framework converts geospatial configurations into standards-compliant networks that satisfy voltage, ampacity, and loss constraints while minimizing cost requirements for infrastructure. This approach transforms network design from a heuristic, case-by-case process into a reproducible, performance-driven optimization suitable for portfolio-scale planning with speed, transparency, and technical precision. For scenarios with sparse distribution data, a synthetic feeder generation algorithm is introduced for constructing realistic distribution networks from open geospatial information. The algorithm traces viable network paths, enforces geometric and electrical constraints, and generates geographically realistic and electrically feasible network models that replicate the structure and performance of real systems. By integrating geospatial analysis, optimization, open data, and electrical standards, the dissertation presents a unified methodology for automated distribution network planning for design of new builds or retrofit of existing builds. The proposed framework strengthens the analytical foundations of electrification modeling and enables faster, lower-cost, and technically consistent projects that can be implemented to advance equitable energy access at scale. |
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| ISBN: | 9798265458551 |
| Fuente: | ProQuest Dissertations & Theses Global |