In this paper, we develop a comprehensive real-time interactive framework for the utility and customers in a smart grid while ensuring grid-stability and quality-of-service (QoS). First, we propose a hierarchical architecture for the utility-customer interaction consisting of sub-components of customer load prediction, renewable generation integration, power-load balancing and demand response (DR). Within this hierarchical architecture, we focus on the problem of real-time scheduling in an abstract grid model consisting of one controller and multiple customer units. A scalable solution to the real-time scheduling problem is proposed by combining solutions to two sub-problems: (1) centralized sequential decision making at the controller to maximize an accumulated reward for the whole micro-grid and (2) distributed auctioning among all customers based on the optimal load profile obtained by solving the first problem to coordinate their interactions. We formulate the centralized sequential decision making at the controller as a hidden mode Markov decision process (HM-MDP). Next, a Vikrey auctioning game is designed to coordinate the actions of the individual smart-homes to actually achieve the optimal solution derived by the controller under realistic gird interaction assumptions. We show that though truthful bidding is a weakly dominant strategy for all smart-homes in the auctioning game, collusive equilibria do exist and can jeopardize the effectiveness and efficiency of the trading opportunity allocation. Analysis on the structure of the Bayesian Nash equilibrium solution set shows that the Vickrey auctioning game can be made more robust against collusion by customers (anticipating distributed smart-homes) by introducing a positive reserve price. The corresponding auctioning game is then shown to converge to the unique incentive compatible truthful bidding Bayesian Nash equilibrium, without jeopardizing the auctioneer's (microgrid controller's) profit. The paper also explicitly discusses how this two-step solution approach can be scaled to be suitable for more complicated smart grid architectures beyond the assumed abstract model.

The goal of this paper is to serve as a reference for researchers in robotics and control that are interested in realistic modeling, theoretical analysis and simulation of wireless links. To realize the full potentials of networked robotic systems, an integration of communication issues with motion planning/control is necessary. While considerable progress has been made in the area of networked robotic systems, communication channels are typically considered ideal or ideal within a certain radius of the transmitter, both considerable oversimplifications of wireless channels. It is the goal of this paper to provide a comprehensive overview of the key characteristics of wireless channels, as relevant to networked robotic operations. In particular, we provide a probabilistic framework for characterization of the underlying multi-scale dynamics of a wireless link: small-scale fading, large-scale fading and path loss. We furthermore confirm these mathematical models with channel measurements made in our building. We also discuss channel characterization based on the knowledge available on the geometry and dielectric properties of the environment.