Training Neural Networks for Loss Allocation in Power System
收藏Mendeley Data2024-03-27 更新2024-06-27 收录
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https://ieee-dataport.org/documents/training-neural-networks-loss-allocation-power-system
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Power transmission system losses can typically represent from five to tenpercent of the total generation, a quantity worth millions ofdollars per year.The purpose of loss allocation in the context of pooldispatch is to assign to each individual generation and load theresponsibility of paying for part of the system transmissionlosses.Since the system losses arenon-separable, non-linear functions of the real powergeneration and loads, the allocation of transmission loss is achallenging and contentious issue in a fully deregulatedsystem. Loss allocation is a procedure for subdividing thesystem transmission losses into fractions, the cost of whichthen becomes the responsibilities of individual users of thepower system (Gencos, Discos, and Marketers). Loss allocationdoes not affect generation level or power flows; however, itmodifies the distribution of revenues and payments at thenetwork buses among suppliers and consumers.This dataset presents the data used in the paper titled "ANN Based Z-Bus Loss Allocation for PoolDispatch in Deregulated Power System" and also the data for the practical IEEE 30 bus system.Dataset 1 (fivebus.csv)FIve bus test system used in the paperDataset 2 (book30.csv)IEEE 30 bus system
创建时间：
2023-06-28
