A survey and comparison of leading-edge uncertainty handling methods for power grid modernization

Rahim, Sahar; Siano, Pierluigi

doi:10.1016/j.eswa.2022.117590

Cited by 12 publications

(4 citation statements)

References 161 publications

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“…Overall, the levels of Pb and As in Galician cattle do not pose a threat to animal health. However, in some areas of Galicia, up to 20% of the cattle had toxic levels of Cd in their kidney ( Table 3 ) ( 235 , 237 ).…”

Section: Geographical Distribution Of Metal Toxicity In Cattlementioning

confidence: 99%

“…Several preclinical and clinical research has examined the effects of heavy metal supplementation as chelating agents to facilitate pollutants elimination or as synthetic antioxidants to mitigate the oxidative stress caused by environmental pollutants to avoid or lessen toxicity ( 237 , 296 ). These therapies and approaches themselves are believed to have a variety of safety and effectiveness issues.…”

Section: Prevention and Control Of Bioaccumulation Of Toxic Metalsmentioning

confidence: 99%

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A review of important heavy metals toxicity with special emphasis on nephrotoxicity and its management in cattle

Tahir

Alkheraije

2023

Front. Vet. Sci.

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Toxicity with heavy metals has proven to be a significant hazard with several health problems linked to it. Heavy metals bioaccumulate in living organisms, pollute the food chain, and possibly threaten the health of animals. Many industries, fertilizers, traffic, automobile, paint, groundwater, and animal feed are sources of contamination of heavy metals. Few metals, such as aluminum (Al), may be eliminated by the elimination processes, but other metals like lead (Pb), arsenic (As), and cadmium (Ca) accumulate in the body and food chain, leading to chronic toxicity in animals. Even if these metals have no biological purpose, their toxic effects are still present in some form that is damaging to the animal body and its appropriate functioning. Cadmium (Cd) and Pb have negative impacts on a number of physiological and biochemical processes when exposed to sub-lethal doses. The nephrotoxic effects of Pb, As, and Cd are well known, and high amounts of naturally occurring environmental metals as well as occupational populations with high exposures have an adverse relationship between kidney damage and toxic metal exposure. Metal toxicity is determined by the absorbed dosage, the route of exposure, and the duration of exposure, whether acute or chronic. This can lead to numerous disorders and can also result in excessive damage due to oxidative stress generated by free radical production. Heavy metals concentration can be decreased through various procedures including bioremediation, pyrolysis, phytoremediation, rhizofiltration, biochar, and thermal process. This review discusses few heavy metals, their toxicity mechanisms, and their health impacts on cattle with special emphasis on the kidneys.

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Section: Geographical Distribution Of Metal Toxicity In Cattlementioning

confidence: 99%

Section: Prevention and Control Of Bioaccumulation Of Toxic Metalsmentioning

confidence: 99%

A review of important heavy metals toxicity with special emphasis on nephrotoxicity and its management in cattle

Tahir

Alkheraije

2023

Front. Vet. Sci.

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“…The intricacy of an interconnected power network has forced most power systems to be operating close to their stability breakpoint [1]. This is because power systems with much uncertainty are vulnerable to voltage instability, especially when faced with contingency.…”

Section: Introductionmentioning

confidence: 99%

Neural Network Based Approach for Steady-State Stability Assessment of Power Systems

2023

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The quest for an intelligence compliance system to solve power stability problems in real-time with high predictive accuracy, and efficiency has led to the discovery of deep learning (DL) techniques. This paper investigates the potency of several artificial neural network (ANN) techniques in assessing the steady-state stability of a power system. The new voltage stability pointer (NVSP) was employed to parameterize and reduce the input data to the neural network algorithms to predict the proximity of power systems to voltage instability. In this study, we consider five neural network algorithms viz. feedforward neural network (FFNN), cascade-forward neural network (CFNN), layer recurrent neural network (LRNN), linear layer neural network (LLNN), and Elman neural network (ENN). The evaluation is based on the predictability and accuracy of these techniques for dynamic stability in power systems. The neural network algorithms were trained to mimic the NVSP dataset using a Levenberg-Marquardt (LM) model. Similarly, the performance analyses of the neural network techniques were deduced from the regression learner algorithm (RLA) using a root-mean-squared error (rmse) and response plot graph. The effectiveness of these NN algorithms was demonstrated on the IEEE 30-bus system and the Nigerian power system. The simulation results show that the FFNN and the CFNN possess a relatively better performance in terms of accuracy and efficiency for the considered power networks.

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“…However, to effectively integrate these sources, the modernization of existing power grids is required. The Smart Grid (SG) is a modernization of the existing conventional power grid [2]. Moreover, traditional power grids cannot incorporate new technologies and integrate renewable energy sources from individual households [3].…”

Section: Introductionmentioning

confidence: 99%

A Graph-Theoretic Approach for Modelling and Resiliency Analysis of Synchrophasor Communication Networks

Jha

Appasani

Bizon

et al. 2023

ASI

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In recent years, the Smart Grid (SG) has been conceptualized as a burgeoning technology for improvising power systems. The core of the communication infrastructure in SGs is the Synchrophasor Communication Network (SCN). Using the SCN, synchrophasor data communication is facilitated between the Phasor Measurement Unit (PMU) and Phasor Data Concentrator (PDC). However, the SCN is subjected to many challenges. As a result, the components, such as the links, PMUs, PDCs, nodes, etc., of the SCN are subjected to failure. Such failure affects the operation of the SCN and results in the performance degradation of the SG. The performance degradation of the smart grid is observed either temporarily or permanently due to packet loss. To avoid dire consequences, such as a power blackout, the SCN must be resilient to such failures. This paper presents a novel analytical method for the resiliency analysis of SCNs. A graph-theoretic approach was used to model SCN from the resiliency analysis perspective. Furthermore, we proposed a simulation framework for validating the analytical method using the Network Simulator-3 (ns-3) software. The proposed non-intrusive simulation framework can also be extended to design and analyse the resiliency of generic communication networks.

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A survey and comparison of leading-edge uncertainty handling methods for power grid modernization

Cited by 12 publications

References 161 publications

A review of important heavy metals toxicity with special emphasis on nephrotoxicity and its management in cattle

A review of important heavy metals toxicity with special emphasis on nephrotoxicity and its management in cattle

Neural Network Based Approach for Steady-State Stability Assessment of Power Systems

A Graph-Theoretic Approach for Modelling and Resiliency Analysis of Synchrophasor Communication Networks

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