Secure Communication Architecture for Dynamic Energy Management in Smart Grid

open access articleSmart grid takes advantage of communication technologies for efficient energy management and utilization. It entails sacrifice from consumers in terms of reducing load during peak hours by using a dynamic energy pricing model. To enable an active participation of consumers in load management, the concept of home energy gateway (HEG) has recently been proposed in the literature. However, the HEG concept is rather new, and the literature still lacks to address challenges related to data representation, seamless discovery, interoperability, security, and privacy. This paper presents the design of a communication framework that effectively copes with the interoperability and integration challenges between devices from different manufacturers. The proposed communication framework offers seamless auto-discovery and zero- con figuration-based networking between heterogeneous devices at consumer sites. It uses elliptic-curve-based security mechanism for protecting consumers' privacy and providing the best possible shield against different types of cyberattacks. Experiments in real networking environment validated that the proposed communication framework is lightweight, secure, portable with low-bandwidth requirement, and flexible to be adopted for dynamic energy management in smart grid

Optimal provision of distributed reserves under dynamic energy service preferences

We propose and solve a stochastic dynamic programming (DP) problem addressing the optimal provision of regulation service reserves (RSR) by controlling dynamic demand preferences in smart buildings. A major contribution over past dynamic pricing work is that we pioneer the relaxation of static, uniformly distributed utility of demand. In this paper we model explicitly the dynamics of energy service preferences leading to a non-uniform and time varying probability distribution of demand utility. More explicitly, we model active and idle duty cycle appliances in a smart building as a closed queuing system with price-controlled arrival rates into the active appliance queue. Focusing on cooling appliances, we model the utility associated with the transition from idle to active as a non-uniform time varying function. We (i) derive an analytic characterization of the optimal policy and the differential cost function, and (ii) prove optimal policy monotonicity and value function convexity. These properties enable us to propose and implement a smart assisted value iteration (AVI) algorithm and an approximate DP (ADP) that exploits related functional approximations. Numerical results demonstrate the validity of the solution techniques and the computational advantage of the proposed ADP on realistic, large-state-space problems

A two level feedback system design to provide regulation reserve

Demand side management has gained increasing importance as the penetration of renewable energy grows. Based on a Markov jump process modelling of a group of thermostatic loads, this paper proposes a two level feedback system design be- tween the independent system operator (ISO) and the regulation service provider such that two objectives are achieved: (1) the ISO can optimally dispatch regulation signals to multiple providers in real time in order to reduce the requirement for expensive spinning reserves, and (2) each regulation provider can control its thermostatic loads to respond the ISO signal. It is also shown that the amount of regulation service that can be provided is implicitly restricted by a few fundamental parameters of the provider itself, such as the allowable set point choice and its thermal constant. An interesting finding is that the regulation provider’s ability to provide a large amount of long term accumulated regulation and short term signal tracking restrict each other. Simulation results are presented to verify and illustrate the performance of the proposed framework