This paper presents a comprehensive framework for optimizing medium voltage distribution networks, addressing the challenges of energy loss reduction, voltage stability, and operational cost minimization. The study combines methodologies from two complementary approaches: one focusing on the optimal reconfiguration of radial distribution networks using Mixed-Integer Nonlinear Programming (MINLP) models implemented in the General Algebraic Modeling System (GAMS), and the other highlighting advanced strategies for distributed generation (DG) integration and reactive power compensation. The proposed MINLP formulation employs branch-to-node incidence, enabling accurate representation of active and reactive power flows as functions of real and imaginary voltage and current components. By merging these approaches, the unified framework not only minimizes total power losses but also enhances voltage profiles and supports sustainable network operations. Case studies on IEEE-standard networks validate the effectiveness of the methodology, demonstrating its potential to address the complex challenges of modern power distribution systems
Primary Language | English |
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Subjects | Power Plants |
Journal Section | Articles |
Authors | |
Early Pub Date | December 28, 2024 |
Publication Date | December 31, 2024 |
Submission Date | December 12, 2024 |
Acceptance Date | December 26, 2024 |
Published in Issue | Year 2024 Volume: 5 Issue: 2 |