Legacy and shockwaves: A spatial analysis of strengthening resilience of the power grid in Connecticut

Gallaher, Adam; Graziano, Marcello; Fiaschetti, Maurizio

doi:10.1016/j.enpol.2021.112582

Cited by 19 publications

(6 citation statements)

References 42 publications

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“…In [11], the interruptions' frequency, extent, and duration were considered. The analysis of tree pruning operations was evaluated based on a set of actual data, where two autoregressive models were introduced: the spatial autoregressive model and the spatial Durbin model.…”

Section: A Literature Reviewmentioning

confidence: 99%

“…Adopting preventive measures is crucial to mitigate the faults, inconveniences, and additional costs after they occur in PDS. To the best of the authors' knowledge, specialized literature studies aim to detect, classify, and locate faults after they occur -post-fault studies [11], [12]. On the other hand, estimating regions whose distribution feeders are vulnerable to faults can be a valuable input to power utilities to plan and execute preventive actions to minimize the occurrence of faults and all maintenance costs related to them.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of Vulnerable Areas to Faults Caused by Tree Vegetation in Power Distribution Systems

Santos,

Faria,

Boschi

et al. 2024

IEEE Access

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Faults in power distribution feeders cause damage to power utilities due to the deterioration of reliability and power quality indexes and the displacement of field maintenance teams to replace or repair power grid equipment. Additionally, consumer units have energy supply interruptions for an undetermined time. Studies in specialized literature usually detect, classify, and locate faults after they occur. In contrast, preventing faults by estimating areas vulnerable to them is crucial to mitigate all inconveniences and additional costs after they occur. Tree vegetation is an essential factor contributing to faults. In this sense, an enhanced method for tree vegetation mapping by areas is developed using multilayer perceptron neural networks trained on high-resolution images from Google Earth. A geographic space is incorporated to estimate the regions vulnerable to failures due to tree vegetation. Geographically weighted spatial analysis is applied from local variables aggregated by areas. Spatial data analysis is used to real faults and tree vegetation data from a medium-sized Brazilian city via QGIS and R programming environments. As a result, thematic maps are produced with the areas whose feeders are vulnerable to faults, where there is a moderate positive correlation by regions between the faults in distribution transformers and tree vegetation in the northeast and southwest areas of the city under study.

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Section: A Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimation of Vulnerable Areas to Faults Caused by Tree Vegetation in Power Distribution Systems

Santos,

Faria,

Boschi

et al. 2024

IEEE Access

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“…In Europe, the energy shortage caused by Covid 19 has recognized the importance of resilient grids. It has led European countries to plan policies to increase system flexibility and resilience during the epidemic [68] . In the face of the impending post-epidemic era, the US state of Connecticut has adopted Tree-trimming operations (TTOs) in space to enhance local grid resilience [69] .…”

Section: Other Social Crisismentioning

confidence: 99%

Resilient power grid for smart city

Song

Wan

et al. 2022

iEnergy

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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-physicalsocial systems, multi-energy systems, intelligent electrical transportation and artificial intelligence and Big Data technology.

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“…Furthermore, due to spillover effects of the technology-push policy and demand-pull policy on the neighbors, we explore how the spillover effects impact regional green innovation. Therefore, we refer to Gallaher et al (2021) [36], Huang et al (2021) [37], and Zhao et al (2020) [38] using the spatial Dubin model, with two types of policy variables and their spatial lag terms, to explore the impact of strategic interactions between local governments on innovation. The model is set in the following form:…”

Section: Model Settingmentioning

confidence: 99%

How Strategic Interaction of Innovation Policies between China’s Regional Governments Affects Wind Energy Innovation

Shi

Zeng

et al. 2022

Sustainability

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Prior research has shown the importance of innovation policies that promote innovation in renewable energy, such as wind power. We study the impact of the strategic interaction of innovation policies between regional governments in terms of wind energy innovation in China. Based on panel data from 2007 to 2018 on a provincial level in China, we construct an innovation strength index of each province in the wind power industry and investigate the inductive effect of the technology-push policy and the demand-pull policy, as well as their spatial spillover effect on wind energy innovation. The results show that the technology-push policy of local governments has an obvious inductive effect on wind energy innovation in the region, while also having a negative spillover effect through R&D factor competitions between regions with geography proximity or with proximity in the ranking of R&D funds input. In terms of the demand-pull policy, only changes at the national level can produce positive spillover effects by promoting expectations of market growth. Yet, competition between regions with proximity in the ranking of wind energy resource reserves produce negative spillover effects. The findings should have a far-reaching impact on the sustainable development of global wind power.

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Legacy and shockwaves: A spatial analysis of strengthening resilience of the power grid in Connecticut

Cited by 19 publications

References 42 publications

Estimation of Vulnerable Areas to Faults Caused by Tree Vegetation in Power Distribution Systems

Estimation of Vulnerable Areas to Faults Caused by Tree Vegetation in Power Distribution Systems

Resilient power grid for smart city

How Strategic Interaction of Innovation Policies between China’s Regional Governments Affects Wind Energy Innovation

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