Blockchain-based Local Energy Marketplace Agent-Based Modeling and Simulation

Recently, there has been an increase in policymakers' focus on residential demand response (RDR) programs due to the critical peak load generated by residential consumers. However, residential customers tend to react rather than proactively engage with price or incentive-based signals, leading to a lag in RDR actions. This paper comprehensively utilizes social and agent-based modeling (ABM) simulations to evaluate demand response profiles. The study considers the roles of generation companies, residential customers, retailers, and distributed system operators (DSO), who regulate the market for maximum social welfare. Real data from 628 residential households in Qatar was used to verify the proposed methods and model. The study findings indicate that a distributed energy exchange based on Blockchain among the agents offers significant benefits to both the demand and supply sides. The proposed methods and models can be valuable tools for Qatar's market operators, policymakers, retailers, and utility companies to evaluate proactive RDR results in an interactive multi-entity market.