Integrating Multi-Agent and Quantum-Inspired Evolution for Supply and Demand Matching in the Future Power Energy Networks

Rashad Badawy, Axel Heßler, Benjamin Hirsch, and Sahin Albayrak

Keywords

Artificial intelligence applications in energy and power, Supply and demand matching, Multi-agent systems, Quantum-inspired evolution

Abstract

There is a great effort directed toward realizing the power network of the future. It is envisioned that the future power network will depend on a large number of renewable energy resources connected directly to the low and medium voltage power network(s). Demand Side Management (DSM) is clearly to be an important element to meet this goal. Demand side management is concerned with actions that reshape the energy consumption pattern for the end-users during peak energy consumption times. To control and coordinate the operation of the network with these new characteristics efficiently and with a certain degree of reliability, intelligent coordination approaches are required. Agent-based systems are proposed and implemented to control and coordinate the operation of different entities within the future power network. By using agent technology, we can satisfy the local constraints of different entities while simultaneously satisfying global goals by using approaches for coordinating and adapting the agents’ actions (resources production or consumption). Thus, we introduce a multi-agent coordination approach for supply and demand matching in the energy power networks. In this paper, we focus on an approach that depends on integrating a quantum-inspired evolution algorithm and multiagent system, which in turn controls the power consumption for matching supply and demand. In order to evaluate the performance of the proposed algorithm, we simulate it using the JIAC-V multi-agent platform.

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