Load curve data cleansing and imputation via sparsity and low rank

The smart grid vision is to build an intelligent power network with an unprecedented level of situational awareness and controllability over its services and infrastructure. This paper advocates statistical inference methods to robustify power monitoring tasks against the outlier effects owing to faulty readings and malicious attacks, as well as against missing data due to privacy concerns and communication errors. In this context, a novel load cleansing and imputation scheme is developed leveraging the low intrinsic-dimensionality of spatiotemporal load profiles and the sparse nature of "bad data.'' A robust estimator based on principal components pursuit (PCP) is adopted, which effects a twofold sparsity-promoting regularization through an $\ell_1$-norm of the outliers, and the nuclear norm of the nominal load profiles. Upon recasting the non-separable nuclear norm into a form amenable to decentralized optimization, a distributed (D-) PCP algorithm is developed to carry out the imputation and cleansing tasks using networked devices comprising the so-termed advanced metering infrastructure. If D-PCP converges and a qualification inequality is satisfied, the novel distributed estimator provably attains the performance of its centralized PCP counterpart, which has access to all networkwide data. Computer simulations and tests with real load curve data corroborate the convergence and effectiveness of the novel D-PCP algorithm.Comment: 8 figures, submitted to IEEE Transactions on Smart Grid - Special issue on "Optimization methods and algorithms applied to smart grid

Efficient Cooperative Anycasting for AMI Mesh Networks

We have, in recent years, witnessed an increased interest towards enabling a Smart Grid which will be a corner stone to build sustainable energy efficient communities. An integral part of the future Smart Grid will be the communications infrastructure which will make real time control of the grid components possible. Automated Metering Infrastructure (AMI) is thought to be a key enabler for monitoring and controlling the customer loads. %RPL is a connectivity enabling mechanism for low power and lossy networks currently being standardized by the IETF ROLL working group. RPL is deemed to be a suitable candidate for AMI networks where the meters are connected to a concentrator over multi hop low power and lossy links. This paper proposes an efficient cooperative anycasting approach for wireless mesh networks with the aim of achieving reduced traffic and increased utilisation of the network resources. The proposed cooperative anycasting has been realised as an enhancement on top of the Routing Protocol for Low Power and Lossy Networks (RPL), a connectivity enabling mechanism in wireless AMI mesh networks. In this protocol, smart meter nodes utilise an anycasting approach to facilitate efficient transport of metering data to the concentrator node. Moreover, it takes advantage of a distributed approach ensuring scalability

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems