Next Generation Real-Time Smart Meters for ICT Based Assessment of Grid Data Inconsistencies

Abstract

Abstract:The latest technological developments are challenging for finding new solutions to mitigate the massive integration of renewable-based electricity generation in the electrical networks and to support new and dynamic energy and ancillary services markets. Smart meters have become ubiquitous equipment in the low voltage grid, enabled by the decision made in many countries to support massive deployments. The smart meter is the only equipment mandatory to be mounted when supplying a grid connected user, as it primarily has the function to measure delivered and/or produced energy on its common coupling point with the network, as technical and legal support for billing. Active distribution networks need new functionalities, to cope with the bidirectional energy flow behaviour of the grid, and many smart grid requirements need to be implemented in the near future. However there is no real coupling between smart metering systems and smart grids, as there is not yet a synergy using the opportunity of the high deployment level in smart metering. The paper presents a new approach for managing the smart metering and smart grid orchestration by presenting a new general design based on an unbundled smart meter (USM) concept, labelled as next generation open real-time smart meters (NORM), for integrating the smart meter, phasor measurement unit (PMU) and cyber-security through an enhanced smart metering gateway (SMG). NORM is intended to be deployed everywhere at the prosumer's interface to the grid, as it is usually now done with the standard meter. Furthermore, rich data acquired from NORM is used to demonstrate the potential of assessing grid data inconsistencies at a higher level, as function to be deployed in distribution security monitoring centers, to address the higher level cyber-security threats, such as false data injections and to allow secure grid operations and complex market activities at the same time. The measures are considering only non-sensitive data from a privacy perspective, and is therefore able to be applied everywhere in the grid, down to the end-customer level, where a citizen's personal data protection is an important aspect.

Smart Sensors for Smart Grid Reliability

“…In both cases, the DG penetration level is 50%. Figure 9 illustrates, for the main feeder fault scenarios (A, C, D and E), the optimal settings of • the red dots indicate the tripping times of ER1 and ER2 when the classical tripping function is considered according to IEC standard 60255-151 [23,24]; • the green dots indicate the tripping times for IED1 and IED2 when the linear programming technique is implemented [40]; and • the blue dots indicate the optimal tripping time established by the smart-sensor optimal APS coordination (S_1 and S_2).…”

“…However, their application to short-line distribution networks is still very limited. There is a study [40] that proposes the integration of PMUs with smart meters in distribution networks to improve the metering infrastructure.…”

Incremental Heuristic Approach for Meter Placement in Radial Distribution Systems

“…To collect the field measurement data, communication must be ensured between the DSO control center and the measurement points. In literature, different solutions are suggested to support smart grid applications, such as wireless, power line communications (PLC) or hybrid solutions, which can be also combined in an Internet of Things (IoT) platform [26][27][28][29][30][31][32][33]. On the other hand, currently, in MV networks DSOs deploy communication infrastructures only for automatic meter reading (AMR) and MV grid protection and supply restoration.…”

Collaborative Optimal Pricing and Day-Ahead and Intra-Day Integrative Dispatch of the Active Distribution Network with Multi-Type Active Loads

“…However, with the development of smart grids, especially smart measurement technologies, small users, such as residential users, have taken a lot of development to participate in demand-side bidding after packaging [37]. As for the diversity of cluster users, they are often in different states when dispatch instructions are issued, making it difficult to cut off all the load agreed at the designated moment.…”