October – Sensing and Monitoring

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Written by Mohamed A Ali, Ahmed A Mohamed, and Tanvir Rahman

The widespread adoption of distributed, intermittent, and bi-directional DERs at the grid’s edge poses a myriad of technical, operational, and regulatory challenges to all stakeholders. The key challenge is how to cost-effectively and quickly interconnect DERs to the distribution grid without negatively impacting grid resilience and reliability. Currently, the traditional worst-case scenario approach to interconnection, which is typically used by utilities, is both too slow and expensive for DER developers. In this approach, if one or more solar farms want to connect to the same area of the distribution grid, utility performs a detailed analysis to determine the worst-case scenario impact of these interconnection(s) on the grid for a very small number of hours in a year (1-4% of the time during the year) [1]. Fearing instability, utilities have typically capped the portion of residential solar systems they’ll allow to be interconnected to a neighborhood feeder line at 30% or even lower. 

Written by Sourabh Ghosh, Navneet Kumar Singh, Asheesh Kumar Singh, and Sri Niwas Singh

Globally, the carbon footprint from fossil fuel-based energy generation and industrial processes has crossed 36 Gigatons marking an annual increase of 6% in 2021. This has encouraged governments and enterprises to increase investments in Renewable Energy Sources (RESs) which have risen to $2.4 trillion with an annual increase of 8% in 2022 [1]. Distributed on-site energy generation-based microgrids at multiple sites may be integrated using a central control system to form a Virtual Power Plant (VPP) offering efficient monitoring, forecast, and decision-making capabilities. Digital Twin (DT) of EESs uses real-time data streams from physical assets and high-fidelity models to cater to predictive maintenance, real-time remote monitoring, and decision-making. In 2021, the DT industry was valued at $6.5 billion and is estimated to reach $125.7 billion by 2030, growing at a compound annual growth rate of 39.48%. The application of DT technology in EESs is significantly underdeveloped which encourages both researchers and entrepreneurs. In this light, this article aims to provide a concise but wide view of the concepts, applications, enabling technologies, challenges, and future scope in the domain of digitization of EESs.

Written by Mayank Panwar1, Rob Hovsapian1, Manish Mohanpurkar1, and Clay Koplin2
1National Renewable Energy Laboratory, Boulder, CO, USA
2Cordova Electric Cooperative, Cordova, AK, USA

This article presents the digital twin development of an actual microgrid in Cordova, Alaska, in a real-time simulation environment using multi-resolution data from SCADA at one second resolution, distribution phasor measurement units (PMUs), and smart meter (approx. 2000 meters). The work is performed under the DOE Grid Modernization project titled Resilient Alaskan Distribution system Improvements using Automation, Network analysis, Control, and Energy storage (RADIANCE) for field validation of resilience enhancement technologies. The development process and setup are described, and some relevant use-cases for field validation are discussed.

Written by Marta Vanin and Dirk Van Hertem

Digital models of distribution networks are essential for most smart grid applications like system monitoring, congestion forecasts, and hosting capacity calculations, to name a few. However, in real life, these models notoriously present errors or missing information. This has a detrimental impact on both operations and simulation results, which might become unreliable or suboptimal. This article discusses the use of state estimation and residual analysis (in particular) to identify such errors and validate their correction process.

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IEEE Smart Grid Bulletin Compendium

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