Development and Analysis of a Blockchain-Based Energy Trading Marketplace Forecasts

The rise of distributed energy generation through solar panels in homes and businesses sparks the creation of fresh energy markets. This shift removes the old boundaries between energy suppliers and users, leading to the emergence of energy 'prosumers.' Blockchain technology enhances safe and affordable direct energy swaps within a decentralized setup, employing encryption and consensus checks. The research utilized a unique approach called 'Agent-Based Modeling (ABM) along with Geographic Information System (GIS)' to assess energy trading within the real estate sector. This process encompassed gathering and analyzing data about daily energy consumption to grasp market dynamics and construct a decentralized energy trading approach. The initial simulation involved five key stages: collecting, processing, predicting, analyzing, confirming, and evaluating performance. The primary actors in this model were individuals, consumers, energy providers, and producers. The outcomes from the experiments indicated that one could assess the distinct households' features by incorporating GIS data and an agent-centric model. Harnessing high-performance computing makes it possible to manage large-scale simulations involving multiple participants. Generally, this approach is anticipated to enhance the model's efficiency and offer a flexible environment for scrutinizing how energy blockchain impacts finance, technology, and society.