Blockchain-based prosumer incentivization for peak mitigation through temporal aggregation and contextual clustering

Peak mitigation is of interest to power companies as peak periods may require the operator to over provision supply in order to meet the peak demand. Flattening the usage curve can result in cost savings, both for the power companies and the end users. Integration of renewable energy into the energy infrastructure presents an op-portunity to use excess renewable generation to supplement supply and alleviate peaks. In addition, demand side management can shift the usage from peak to off-peak times and reduce the magnitude of peaks. In this work, wepresent a data driven approach for incentive-based peak mitigation. Understanding user energy profiles is anessential step in this process. We begin by analysing a popular energy research dataset published by the Ausgrid corporation. Extracting aggregated user energy behavior in temporal contexts and semantic linking and contex-tual clustering give us insight into consumption and rooftop solar generation patterns. We implement, and per-formance test a blockchain-based prosumer incentivization system. The smart contract logic is based on ouranalysis of the Ausgrid dataset. Our implementation is capable of supporting 792,540 customers with a reasonablylow infrastructure footprint.