Smart grid

About: Smart grid is a research topic. Over the lifetime, 37536 publications have been published within this topic receiving 627844 citations. The topic is also known as: intelligent grid.

Fog Computing architecture to enable consumer centric Internet of Things services

Abstract: Fog Computing is a recent computing paradigm that is extending cloud computing towards the edge of network. Due to its proximity to end-users, dense geographical distribution, open platform and support for high mobility, Fog Computing platforms can provide services with reduced latency and improved QoS. Thus it is becoming an important enabler for consumer centric Internet of Things based applications and services that require real time operations e.g. connected vehicles, smart road intersection management and smart grid. The paper discusses one such architecture for connected vehicles with Road Side Units (RSUs) and M2M gateways including the Fog Computing Platform. M2M data processing with semantics, discovery and management of connected vehicles are briefly discussed as consumer centric IoT services enabled by the distinct characteristics of Fog Computing.

Distribution System State Estimation Based on Nonsynchronized Smart Meters

Abstract: Distribution systems are undergoing many enhancements and developments to enable the future smart grid, and distribution system state estimation (DSSE) provides the control centers with the information necessary for several of its applications and operational functions. However, the quality of DSSE typically suffers from a lack of adequate/accurate measurements. Recently, many electric utilities have started to install fairly accurate smart meters throughout their distribution networks, which create an opportunity to achieve higher quality DSSE. However, the signals provided by smart meters are generally not synchronized and the difference between the measurement times of smart meters can be significant. Therefore, a complete snapshot of the entire distribution system may not be available. This paper proposes a method to deal with the issue of nonsynchronized measurements coming from smart meters based on the credibility of each available measurement and appropriately adjusting the variance of the measurement devices. To illustrate the effectiveness of the proposed method, two IEEE benchmark systems are used. The results show that the proposed method is robust and improves the accuracy of DSSE compared with the traditional DSSE approach.

Blockchain in Smart Grids: A Review on Different Use Cases

Abstract: With the integration of Wireless Sensor Networks and the Internet of Things, the smart grid is being projected as a solution for the challenges regarding electricity supply in the future. However, security and privacy issues in the consumption and trading of electricity data pose serious challenges in the adoption of the smart grid. To address these challenges, blockchain technology is being researched for applicability in the smart grid. In this paper, important application areas of blockchain in the smart grid are discussed. One use case of each area is discussed in detail, suggesting a suitable blockchain architecture, a sample block structure and the potential blockchain technicalities employed in it. The blockchain can be used for peer-to-peer energy trading, where a credit-based payment scheme can enhance the energy trading process. Efficient data aggregation schemes based on the blockchain technology can be used to overcome the challenges related to privacy and security in the grid. Energy distribution systems can also use blockchain to remotely control energy flow to a particular area by monitoring the usage statistics of that area. Further, blockchain-based frameworks can also help in the diagnosis and maintenance of smart grid equipment. We also discuss several commercial implementations of blockchain in the smart grid. Finally, various challenges to be addressed for integrating these two technologies are discussed.

Sparse Attack Construction and State Estimation in the Smart Grid: Centralized and Distributed Models

Abstract: New methods that exploit sparse structures arising in smart grid networks are proposed for the state estimation problem when data injection attacks are present. First, construction strategies for unobservable sparse data injection attacks on power grids are proposed for an attacker with access to all network information and nodes. Specifically, novel formulations for the optimization problem that provide a flexible design of the trade-off between performance and false alarm are proposed. In addition, the centralized case is extended to a distributed framework for both the estimation and attack problems. Different distributed scenarios are proposed depending on assumptions that lead to the spreading of the resources, network nodes and players. Consequently, for each of the presented frameworks a corresponding optimization problem is introduced jointly with an algorithm to solve it. The validity of the presented procedures in real settings is studied through extensive simulations in the IEEE test systems.