Abstract
In view of the increasing proportion of renewable energy access in the distribution network, traditional distribution network planning methods have been unable to meet the needs of grid development. This paper proposes a data-driven distribution network energy-saving plan based on cluster division with high-penetration renewable energy access. This method firstly optimizes the capacity and layout of high-proportion renewable energy to realize the initial site selection and fixed capacity of renewable energy; secondly, it divides the distribution network based on data-driven clusters to realize the zoning planning of the distribution network, and finally, through a two-level iterative programming model is constructed to realize an optimized decision-making model with cost and energy-saving benefits as the goal. The calculation example uses real power grid data to analyze, and the simulation results show the effectiveness and feasibility of the model and method proposed in this paper.
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Hua, K., Wang, Z., Wu, B., Fu, M. (2022). Data-Driven Distribution Network Energy-Saving Planning Based on Cluster Division and High-Penetration Renewable Energy Access. In: Tian, Y., Ma, T., Khan, M.K., Sheng, V.S., Pan, Z. (eds) Big Data and Security. ICBDS 2021. Communications in Computer and Information Science, vol 1563. Springer, Singapore. https://doi.org/10.1007/978-981-19-0852-1_49
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DOI: https://doi.org/10.1007/978-981-19-0852-1_49
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