AAAI Publications, Twenty-Seventh AAAI Conference on Artificial Intelligence

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Multiagent Coordination for Energy Consumption Scheduling in Consumer Cooperatives
Andreas Veit, Ying Xu, Ronghuo Zheng, Nilanjan Chakraborty, Katia Sycara

Last modified: 2013-06-29


A key challenge to create a sustainable and energy-efficient society is in making consumer demand adaptive to energy supply, especially renewable supply. In this paper, we propose a partially-centralized organization of consumers, namely, a consumer cooperative for purchasing electricity from the market. We propose a novel multiagent coordination algorithm to shape the energy consumption of the cooperative. In the cooperative, a central coordinator buys the electricity for the whole group and consumers make their own consumption decisions based on their private consumption constraints and preferences. To coordinate individual consumers under incomplete information, we propose an iterative algorithm in which a virtual price signal is sent by the coordinator to induce consumers to shift demand. We prove that our algorithm converges to the central optimal solution. Additionally we analyze the convergence rate of the algorithm via simulations on randomly generated instances. The results indicate scalability with respect to the number of agents and consumption slots.


Demand-Side Energy Management, Multi-Agent Systems, Consumer Cooperative

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