Constrained tâtonnement for fast and incentive compatible distributed demand management in smart grids

Shweta Jain, Narayanaswamy Balakrishnan, Yadati Narahari, Saiful A. Hussain, Nyuk Yoong Voo
2013 Proceedings of the the fourth international conference on Future energy systems - e-Energy '13  
Growing fuel costs, environmental awareness, government directives, an aggressive push to deploy Electric Vehicles (EVs) (a single EV consumes the equivalent of 3 to 10 homes) have led to a severe strain on a grid already on the brink. Maintaining the stability of the grid requires automatic agent based control of these loads and rapid coordination between them. In the literature, a number of iterative pricing, signaling and tâtonnement (or bargaining) approaches have been proposed to allow
more » ... t homes, storage devices and the autonomous agents that control them to be responsive to the state of the grid in a distributed manner. These existing approaches are not scalable due to slow convergence and moreover the approaches are not incentive compatible. In this paper, we present a tâtonnement framework for resource allocation among intelligent agents in the smart grid, that non-trivially generalizes past work in this area. Our approach based on the work in server load balancing involves communicating carefully chosen, centrally verifiable constraints on the set of actions available to agents and cost functions, leading to distributed, incentive compatible protocols that converge in a constant number of iterations, independent of the number of users. These protocols can work on the top of prior approaches and result in a substantial speed-up, while ensuring that it is in the best interests of the agents to be truthful. We demonstrate this theoretically and through extensive simulations for three important scenarios that have been discussed in the literature. We extend the techniques to account for capacity limits in each time slot, the EV charging problem and the distributed storage
doi:10.1145/2487166.2487180 dblp:conf/eenergy/JainBNHV13 fatcat:edkf2dtlo5cibgzqrzsv6t5rem