Online Load Scheduling Under Price and Demand Uncertainty in Smart Grid

With the availability of communication technologies within the smart grid infrastructure, demand response has emerged as a viable mechanism of influencing user behavior. Varying prices in real-time motivates the users to modify their energy consumption schedule and obtain fiscal benefits by running non-critical loads at off-peak hours. This paper considers the design of domestic load scheduler under real-time pricing and demand uncertainty. We propose an online load scheduler that maximizes the users' average welfare while satisfying their fluctuating daily demands. In contrast to existing schedulers that rely on price- and load-prediction techniques, the proposed algorithm handles price and demand uncertainties through the use of stochastic dual descent. Detailed simulations demonstrate the efficacy of the proposed algorithm.