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Simulation of Blockchain based Power Trading with Solar Power Prediction in Prosumer Consortium Model

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Document pages: 10 pages

Abstract: Prosumer consortium in a local group can be one of the solutions for energycosts, increasing performance and supplying university with improvedelectrification with distributed power generations. This research studydemonstrates the simulation of blockchain based power trading with thesupplement of solar power prediction with MLFF neural network training in twoprosumer nodes. It can be the forefront to implement a market model withdistributed generations based decentralized blockchain system in a universitygrid system which can balance the electricity demand and supply within theinstitute market, secure and rapid transaction, moreover, the local marketsystem can be reinforced by forecasting solar generation. The performance ofthe MLFF training to predict the Because of it, prosumer bodies can do decisionmaking before trading as for their benefit.

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