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A Novel Framework for Synthesizing Power Profiles to Optimize Renewable Distributed Generation Allocation in Radial Distribution Networks
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Keywords
Renewable distributed generation
radial distribution network
power profile synthesis
stochastic optimization
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Abstract
The integration of renewable distributed generation (RDG) in radial distribution networks is challenged by uncertainties in renewable energy output, load variability, and network constraints. This paper proposes a novel framework for synthesizing representative power profiles to optimize RDG allocation, enhancing network efficiency and reliability. The framework incorporates probabilistic and stochastic modeling techniques to capture the variability of renewable resources and load dynamics (Zakaria, 2020; Ahmed, 2020). A multi-objective optimization approach is employed to minimize energy losses, voltage deviations, and system operation costs while maintaining network stability. Case studies demonstrate that the proposed framework provides superior allocation strategies compared to conventional methods, highlighting the critical role of accurate power profile generation in RDG integration. The study further identifies potential limitations and practical implications for large-scale deployment of renewable sources in radial distribution networks.
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