Local Energy Marketplace Agents-based Analysis

Abstract

Establishment of distributed energy generation through the home and commercial PV applications contributed to the emergence of the energy prosumer role, eliminating the distinction between energy producers and consumers. Blockchain technology provides a different and secure energy-trading solution by automating direct energy transactions within a distributed database architecture. It leverages cryptographic hashing and consensus-based verification. This study aims to implement a versatile Agent-Based Modeling (ABM) simulation framework for electricity exchange to assess the capability of Blockchain technology in household power usage prediction (see Fig. 1). A robust multi-agent structure was created and simulated for Transactive Energy (TE) Distributed Energy Resources (DER) within the ECCH microgrid, using Blockchain technology. The study found that Blockchain-based Local Energy Markets (LEMs) rely on precise short-term forecasts of individual households' energy production and consumption, which are often overlooked. The study initially assessed the accuracy of energy forecasting techniques for specific households to test this assumption. The second step analyzed prediction errors under three different supply scenarios in the market. The results showed low forecasting errors in an LSTM model, which was then integrated into a LEM built on a Blockchain. The research highlights the importance of accurate time series estimation of smart meter data1.