@Article{ee.2025.060658,
AUTHOR = {Ganesh Wakte, Mukesh Kumar, Mohammad Aljaidi, Ramesh Kumar, Manish Kumar Singla},
TITLE = {Advanced Nodal Pricing Strategies for Modern Power Distribution Networks: Enhancing Market Efficiency and System Reliability},
JOURNAL = {Energy Engineering},
VOLUME = {122},
YEAR = {2025},
NUMBER = {6},
PAGES = {2519--2537},
URL = {http://www.techscience.com/energy/v122n6/61351},
ISSN = {1546-0118},
ABSTRACT = {Nodal pricing is a critical mechanism in electricity markets, utilized to determine the cost of power transmission to various nodes within a distribution network. As power systems evolve to incorporate higher levels of renewable energy and face increasing demand fluctuations, traditional nodal pricing models often fall short to meet these new challenges. This research introduces a novel enhanced nodal pricing mechanism for distribution networks, integrating advanced optimization techniques and hybrid models to overcome these limitations. The primary objective is to develop a model that not only improves pricing accuracy but also enhances operational efficiency and system reliability. This study leverages cutting-edge hybrid algorithms, combining elements of machine learning with conventional optimization methods, to achieve superior performance. Key findings demonstrate that the proposed hybrid nodal pricing model significantly reduces pricing errors and operational costs compared to conventional methods. Through extensive simulations and comparative analysis, the model exhibits enhanced performance under varying load conditions and increased levels of renewable energy integration. The results indicate a substantial improvement in pricing precision and network stability. This study contributes to the ongoing discourse on optimizing electricity market mechanisms and provides actionable insights for policymakers and utility operators. By addressing the complexities of modern power distribution systems, our research offers a robust solution that enhances the efficiency and reliability of power distribution networks, marking a significant advancement in the field.},
DOI = {10.32604/ee.2025.060658}
}