Intelligent Multi-Agent Based Multilayered Control System for Opportunistic Load Scheduling in Smart Buildings

• Published in: IEEE access Vol. 7; pp. 23990 - 24006
• Main Authors: Rasheed, Muhammad Babar, Javaid, Nadeem, Arshad Malik, Muhammad Sheraz, Asif, Muhammad, Hanif, Muhammad Kashif, Chaudary, Muhammad Hasanain
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Control systems; demand response; demand side management; Dynamic loads; Dynamic scheduling; Electric power systems; Electrical loads; Electricity consumption; Energy consumption; Load; Load management; multi-agent systems; Multiagent systems; Multilayers; optimal stopping rule; Optimization; Peak load; Power system dynamics; real time pricing; Real-time systems; Scheduling; Smart buildings; Time of use electricity pricing; user comfort; Volatility
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2019.2900049

Today's power systems are subject to the high penetration of dynamic load. Volatility and intermittency of the dynamic load demand need to be compensated through optimization and scheduling without compromising user comfort. This paper proposes a multi-agent-based multi-layered hierarchical control system for residential load management under real-time pricing environment. The major objectives are to reduce peak load demand, electricity cost, and user discomfort. In doing so, different types of agents, i.e., price agent <inline-formula> <tex-math notation="LaTeX">p_{a} </tex-math></inline-formula>, sensor agent <inline-formula> <tex-math notation="LaTeX">s_{a} </tex-math></inline-formula>, decision agent <inline-formula> <tex-math notation="LaTeX">d_{a} </tex-math></inline-formula>, load agent <inline-formula> <tex-math notation="LaTeX">l_{a} </tex-math></inline-formula>, and action agent <inline-formula> <tex-math notation="LaTeX">a_{a} </tex-math></inline-formula>, are developed to control residential loads, such as normal load ( nl ) and heavy load ( hl ). To handle price uncertainty, dynamically, optimal stopping rule (OSR) theory has been used. Two variants of OSR are proposed: 1) priority inversion logic-based OSR to subsidize the responsive consumers and 2) maximum energy consumption limit <inline-formula> <tex-math notation="LaTeX">Q </tex-math></inline-formula>-based OSR-Q to maximize the profit of energy retailers. Finally, the proposed mechanism is validated on a set of loads to show the applicability and proficiency under a dynamic environment.