Resilient power grid for smart city

Modern power grid has a fundamental role in the operation of smart cities. However, high impact low probability extreme events bring severe challenges to the security of urban power grid. With an increasing focus on these threats, the resilience of urban power grid has become a prior topic for a modern smart city. A resilient power grid can resist, adapt to, and timely recover from disruptions. It has four characteristics, namely anticipation, absorption, adaptation, and recovery. This paper aims to systematically investigate the development of resilient power grid for smart city. Firstly, this paper makes a review on the high impact low probability extreme events categories that influence power grid, which can be divided into extreme weather and natural disaster, human-made malicious attacks, and social crisis. Then, resilience evaluation frameworks and quantification metrics are discussed. In addition, various existing resilience enhancement strategies, which are based on microgrids, active distribution networks, integrated and multi energy systems, distributed energy resources and flexible resources, cyber-physical systems, and some resilience enhancement methods, including probabilistic forecasting and analysis, artificial intelligence driven methods, and other cutting-edge technologies are summarized. Finally, this paper presents some further possible directions and developments for urban power grid resilience research, which focus on power-electronized urban distribution network, flexible distributed resource aggregation, cyber-physical-social systems, multi-energy systems, intelligent electrical transportation and artificial intelligence and Big Data technology

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

Big Data Analytics for QoS Prediction Through Probabilistic Model Checking

As competitiveness increases, being able to guaranting QoS of delivered services is key for business success. It is thus of paramount importance the ability to continuously monitor the workflow providing a service and to timely recognize breaches in the agreed QoS level. The ideal condition would be the possibility to anticipate, thus predict, a breach and operate to avoid it, or at least to mitigate its effects. In this paper we propose a model checking based approach to predict QoS of a formally described process. The continous model checking is enabled by the usage of a parametrized model of the monitored system, where the actual value of parameters is continuously evaluated and updated by means of big data tools. The paper also describes a prototype implementation of the approach and shows its usage in a case study.Comment: EDCC-2014, BIG4CIP-2014, Big Data Analytics, QoS Prediction, Model Checking, SLA compliance monitorin

Middleware architectures for the smart grid: A survey on the state-of-the-art, taxonomy and main open issues

The integration of small-scale renewable energy sources in the smart grid depends on several challenges that must be overcome. One of them is the presence of devices with very different characteristics present in the grid or how they can interact among them in terms of interoperability and data sharing. While this issue is usually solved by implementing a middleware layer among the available pieces of equipment in order to hide any hardware heterogeneity and offer the application layer a collection of homogenous resources to access lower levels, the variety and differences among them make the definition of what is needed in each particular case challenging. This paper offers a description of the most prominent middleware architectures for the smart grid and assesses the functionalities they have, considering the performance and features expected from them in the context of this application domain