Multi-Agent-Based Forecast Update Methods for Profit Enhancement of Intermittent Distributed Generators in a Smart Microgrid

Abstract

Uncertainty in generation from intermittent sources makes a strong case to have effective forecasting methods. However, errors in forecast lead to losses to the distributed generation (DG) owners. In this article, multi-agent-based forecast update methods are proposed which minimize the forecast errors. The effectiveness of the proposed methods in enhancing the profit of intermittent generators and microgrid operational cost is analyzed using a microgrid with two scenarios, namely simple ownership and multiple ownership. A modified IEEE 13 bus system is used as the case study system and the system simulation for the microgrid is performed on the OpenDSS platform and the proposed multi-agent system is developed using JAVA Agent DEvelopment (JADE) framework. From the simulation results, the proposed approaches are found effective in increasing profit margins for the investors or owners of the DGs.