Agent-based simulation of home energy management system in residential demand response

This paper presents an agent-base model to evaluate the home energy management system in residential demand response implementation. Residential demand response aims to change people´s electricity consumption patterns to reduce the peak demand and therefore improve energy efficiency and power system stability. The home energy management system intelligently controls household loads with association of smart meters. It plays key roles in a success demand response implementation. In the proposed agent-based model, the main stakeholders are modelled by the software agents including Conventional Home Agents, Smart Home Agents, a Utility Agent, a Primary Plant Agent and Secondary Plant Agents. A mechanism of dynamic pricing is applied to both the Conventional Home Agent System (Scenario #1) and the Smart Home Agent System (Scenario #2). Comparing to the Scenario #1, the peak demand, average householder´s bills and generation cost in the Scenario #2 is decreased by 24.6%, 7.4% and 14.7% respectively. This demonstrates the effectiveness of the home energy management system in the residential demand response implementation. The proposed model can be a test-bed to evaluate various demand response strategies and technologies.