Solar PV Energy Trading Market Blockchain-based: Agent-Models Community

PV applications in residential and commercial properties obliterate the traditional divide between producers and consumers. By automating direct energy transactions through cryptographic hashing and consensus-based verification, blockchain provides consumers, prosumers and utilities with a novel, secure and cost-effective energy-trading solution. A simulation environment based on Agent-Based Modeling (ABM) was developed and implemented for blockchain-based energy trading in Qatar's Education City Community Housing (ECCH), incorporating a Geographic Information System (GIS). In order to recreate the spatiotemporal characteristics of trading in a small market, we would need to gather and analyze a great deal of data about day-to-day energy activities. This sort of simulations can aid stakeholders in understanding the dynamics of a real trading market to make better decisions towards the development of a decentralized energy market. The results show that the GIS information combined with an agent-based design can be easily customized to examine the characteristics of transactions performed in a local community housing market by simply readjusting parameters.