Data Prediction for a Blockchain-based Energy Market

A new role known as an energy prosumer is created when distributed energy generation is established through home and commercial PV applications. This eliminates the conventional distinction between energy producers and consumers. Blockchain technology automates direct energy transactions within a distributed database architecture based on cryptographic hashing and consensus-based verification, consumers, prosumers, offering energy, and utilities with a unique, affordable, and safe energy-trading solution. The goal of this study is to deploy a general ABM simulation framework for electricity exchange and illustrate the predicted households' power profiles as well as the functionality of any blockchain process (see Figure. 1). For a Transactive Energy (TE) type Distributed Energy Resources (DER) within the ECCH microgrid that is dependent on blockchain engineering, an original version of a robust multi-agent structure was built and simulated. Recent blockchain-based LEM proposals use auction systems to balance supply and demand in the future. As a result, these blockchain-based LEMs depend on precise short-term projections of the energy output and consumption of specific households. Such precise estimates are frequently just taken for granted. This assumption was put to the test in the current study by first assessing the forecast accuracy that can be achieved for specific households using cutting-edge energy forecasting techniques, and then by analysing the impact of prediction errors on market outcomes in three different supply scenarios. Although an LSTM model can produce reasonably low forecasting errors, the evaluation revealed. The prediction procedure will be adjusted to the configuration of an LEM built on a blockchain. Therefore, the current research stands out significantly from earlier experiments that make a complete attempt to estimate the time sequence of smart meters in general.