Distributed Thermal Storage Using Multi-Agent Systems

Thermal storage is an essential concept within many energy systems. Such storage is generally used in order to smooth out the time lag between the acquisition and the use of energy, for example by using heat water tanks within heating systems. In this work we use a multi-agent system in order to maintain and operate distributed thermal storage among a large group of buildings in a district heating system. There are several financial and environmental benefits of using such a system, such as avoiding peak load production, optimizing combined heat and power strategies and achieving general energy efficiency within the network. Normally a district heating system is purely demand driven, resulting in poor operational characteristics on a system wide scale. However, by using the thermal inertia of buildings it is possible to manage and coordinate the heat load among a large group of buildings in order to implement supply driven operational strategies. This results in increased possibilities to optimize the production mix from financial and environmental aspects. We present a multi-agent system that combines the thermal storage capacities of buildings with production optimization strategies. The system consist of producer agents responsible for valuing the heat load management, consumer agents managing the quality of service in individual buildings while consenting to participate in heat load management, and a market agent acting as a mediating layer between the producer and consumer agents. The market agent uses an auction-like process in order to coordinate the heat load management among the consumer agents, while the producer agents use load forecasting in order to evaluate the need for heat load management at any given point in time. A consumer agent uses continues feedback regarding indoor climate in order to uphold quality of service while participating in heat load management. Real-time data from a district heating system in Sweden is used in order to evaluate the agent system in relation to operational peak load management. The results show clear financial and environmental gains for the producer as well as participating consumers.