Online updating of a Markovian solar forecast representation
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Sward, Jeffrey A. (ORCID:0000000217438944)↗
SEARCH · Engineering Papers
Results for “risk score”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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The Effects to Exposure of Simulated Spaceflight Radiation on Behavioral Health of Male and Female Mice
Exposure to space radiation is a principal consideration of spaceflight missions as risk is leveraged as time and dose—both expected to increase with future missions to the Moon, Mars, and beyond. Previous mission exposure levels, galactic cosmic radiation (GCR) and solar particle events (SPE), have been characterized as increased compared to those natural to Earth and are predicted to cause robust deficits at higher doses and longer durations. The cognitive health implications of this critical difference are understood as risks to mission and crew operations. We examined potential radiation-induced disruptions on brain health through resting-state in-cage behavior. 23–24-week-old male and female mice were exposed to 0 cGy (Sham), 5 cGy, 15 cGy, and 50 cGy via Five-Ion GCR Simulation (H, Si, He, O, Fe) at the NASA Space Radiation Lab in Brookhaven National Labs. Behavioral and cognitive performance were evaluated via frequency/duration of digging, rearing, and grooming within the 72-hour period immediately following irradiation. Additionally, during this time we evaluated nestlet building using a 5-stage Deacon score, rating shredding and shelter assembly of cotton material from untouched (1) to shredded and formed into a crater shape (5). We have observed differences in Deacon score only among the 15 cGy subset. Further comparative performance analysis will be completed evaluating the differences in irradiation effects between male and female mice. These experimental design aspects that allot for gender-inclusivity is supportive of the diversification of future space travel mission plans. Investigating gender differences is an element under our main objective of determining radiation dose-response curves. In brief, these studies identified a space-relevant radiation dose of 15 cGy that that can be utilized for future standardized ground studies on the nervous system.
spaceflight cognition impairment↗
Assessment of oil and gas fields in California as potential CO 2 storage sites
California's total annual greenhouse gas (GHG) emissions (425.3 MtCO 2 e) in 2018 were about 6.4% of the US total (6,677 MtCO 2 e) and around 1% of global emissions. About 39% of 2018 GHG emissions in California were from the industrial and electrical sectors. Many of these emissions were from large stationary point sources and were suitable for carbon capture retrofit with subsequent storage of the captured carbon dioxide (CO 2 ) in geological formations. Previous studies of California found suitable geology and CO 2 storage resource. This study refines and furthers prior work using a three-stage screening process of oil fields, gas fields, and underground natural gas storage (UGS) sites by combining criteria from previous studies while excluding sites that pose technical risk or are located in regions with surface restrictions including sensitive habitats and dense populations. In the first stage, 129 CO 2 storage sites in California were identified using qualification criteria based upon formation properties including geological conditions and pore pressure. The second stage identified sensitive sites by applying conservative screens including seismic activity, faulting, population density, restricted lands, and sensitive habitats. During the third stage, 61 CO 2 potential storage sites were identified by subtraction of stage 2 areas from stage 1. The potential storage volume in the third stage ranged from 1.0 to 2.0 GtCO 2 . Finally, we applied a scoring system with seven parameters to rank the 61 potential sites based on subsurface technical criteria. The scored sites are classified as high priority, medium priority, and sites for future study. Prospective CO 2 storage sites with high and moderate priority were selected and linked to CO 2 sources. There are 14 prospective sites (above 20 MtCO 2 storage resource per site) with a total storage resource of 1024 MtCO 2 distributed in Northern and Southern California. Of these sites, there are 9 potential CO 2 -EOR sites and 1 depleted oil field with a total estimated CO 2 storage volume of ~800 MtCO 2 in the Southern San Joaquin and Ventura Basin. These 10 prospective sites with a storage resource greater than 20 MtCO 2 could potentially deliver more than 20 years of storage with an average injection rate of 40 MtCO 2 /year. The remaining 4 highly prospective sites are in Northern California. Additionally, study results suggest that saline formations should be re-evaluated in concert with storage in oil, gas, and natural gas storage reservoirs.
58 GEOSCIENCES↗
New framework for benchmarking decadal predictions leveraging the PCMDI Metric Package with interactive visualization
Reliable climate predictions across multiple timescales are increasingly critical as climate-related risks continue to rise. With the growing number and diversity of climate prediction systems, systematic intercomparison has become essential. Here, we present a comprehensive evaluation framework based on the PCMDI Metric Package to assess the performance of multiple decadal climate prediction systems. Unlike uninitialized simulations, initialized predictions exhibit bias and predictive skill that evolve with forecast lead time. To address this, we introduce (1) model-by-lead-time portrait plots, which efficiently summarize metrics of global temperature, precipitation, and Arctic/Antarctic sea-ice extent, and (2) an HTML-based interactive visualization platform that provides detailed regional and seasonal diagnostics of model bias, skill scores, and ensemble spread for each model and lead time. Comparisons with uninitialized simulations further quantify the relative impacts of initialization and external forcing on prediction skill. The proposed framework provides a scalable and transparent approach for multi-model climate prediction assessments and can be readily extended to a wide range of operational and research forecasting systems.
54 ENVIRONMENTAL SCIENCES↗
Changes in Cognitive Performance and Behavior Induced by Space-like Environment
Exposure to space radiation is a principal consideration of spaceflight missions as risk is leveraged as time and dose—both expected to increase with future missions to the Moon, Mars, and beyond. Previous mission exposure levels, galactic cosmic radiation (GCR) and solar particle events (SPE), have been characterized as increased compared to those natural to Earth and are predicted to cause robust deficits at higher doses and longer durations. The cognitive health implications of this critical difference are understood as risks to mission and crew operations. We examined potential radiation-induced disruptions on brain health through resting-state in-cage behavior. 23–24-week-old male and female mice were exposed to 0 cGy (Sham), 5 cGy, 15 cGy, and 50 cGy via Five-Ion GCR Simulation (H, Si, He, O, Fe) at the NASA Space Radiation Lab in Brookhaven National Labs. Behavioral and cognitive performance were evaluated via frequency/duration of digging, rearing, and grooming within the 72-hour (acute) and 91-day (delayed) period following irradiation. Additionally, during this time we evaluated nestlet building using a 5-stage Deacon score, rating shredding and shelter assembly of cotton material from untouched (1) to shredded and formed into a crater shape (5). We have observed differences in behavior frequency and duration differences among the 15 cGy subset within the acute observation window. There were no significant differences in behavior frequencies nor duration during the delayed observation period. These experimental design aspects that allot for gender-inclusivity is supportive of the diversification of future space travel mission plans. Investigating gender differences is an element under our main objective of determining radiation dose-response curves. In brief, these studies identified a space-relevant radiation dose of 15 cGy that that can be utilized for future standardized ground studies on the nervous system.
O. Siu↗
Analyzing human errors in flight mission operations
A long-term program is in progress at JPL to reduce cost and risk of flight mission operations through a defect prevention/error management program. The main thrust of this program is to create an environment in which the performance of the total system, both the human operator and the computer system, is optimized. To this end, 1580 Incident Surprise Anomaly reports (ISA's) from 1977-1991 were analyzed from the Voyager and Magellan projects. A Pareto analysis revealed that 38 percent of the errors were classified as human errors. A preliminary cluster analysis based on the Magellan human errors (204 ISA's) is presented here. The resulting clusters described the underlying relationships among the ISA's. Initial models of human error in flight mission operations are presented. Next, the Voyager ISA's will be scored and included in the analysis. Eventually, these relationships will be used to derive a theoretically motivated and empirically validated model of human error in flight mission operations. Ultimately, this analysis will be used to make continuous process improvements continuous process improvements to end-user applications and training requirements. This Total Quality Management approach will enable the management and prevention of errors in the future.
Bruno, Kristin J.↗
Prognostic importance of the preoperative New‐Naples prognostic score for patients with gastric cancer
Abstract Background The wide applicability of the Naples prognostic score (NPS) is still worthy of further study in gastric cancer (GC). This study aimed to construct a New‐NPS based on the differences in immunity and nutrition in patients with upper and lower gastrointestinal tumors to help obtain an individualized prediction of prognosis. Methods This study retrospectively analyzed patients who underwent radical gastrectomy from April 2014 to September 2016. The cutoff values of the preoperative neutrophil‐to‐lymphocyte ratio (NLR), lymphocyte‐to‐monocyte ratio (LMR), serum albumin (Alb), and total cholesterol (TC) were calculated by ROC curve analysis. ROC and t‐ROC were used to evaluate the accuracy of the prognostic markers. The Kaplan–Meier method and log‐rank test were used to analyze the overall survival probability. Univariate and multivariate analyses based on Cox risk regression were used to show the independent predictors. The nomogram was made by R studio. The predictive accuracy of nomogram was assessed using a calibration plot, concordance index (C‐index), and decision curve. Results A total of 737 patients were included in training cohort, 411 patients were included in validation cohort. ROC showed that the New‐NPS was more suitable for predicting the prognosis of GC patients. NPS = 2 indicated a poor prognosis. Multivariate analysis showed that CEA ( P = 0.026), Borrmann type ( P = 0.001), pTNM ( P < 0.001), New‐NPS ( P < 0.001), and nerve infiltration ( P = 0.035) were independent risk factors for prognosis. Conclusion The New‐NPS based on the cutoff values of NLR, LMR, Alb, and TC is not only suitable for predicting prognosis but can also be combined with clinicopathological characteristics to construct a nomogram model for GC patients.
Wang, Hao↗
Cortical proteins may provide motor resilience in older adults
Motor resilience proteins may be a high value therapeutic target that offset the negative effects of pathologies on motor function. This study sought to identify cortical proteins associated with motor decline unexplained by brain pathologies that provide motor resilience. We studied 1226 older decedents with annual motor testing, postmortem brain pathologies and quantified 226 proteotypic peptides in prefrontal cortex. Twenty peptides remained associated with motor decline in models controlling for ten brain pathologies (FDR < 0.05). Higher levels of nine peptides and lower levels of eleven peptides were related to slower decline. A higher motor resilience protein score based on averaging the levels of all 20 peptides was related to slower motor decline, less severe parkinsonism and lower odds of mobility disability before death. Cortical proteins may provide motor resilience. Targeting these proteins in further drug discovery may yield novel interventions to maintain motor function in old age.
Buchman, Aron↗
Predictive Modeling for Differential Diagnosis and Mortality Risk Assessment
The prevalence of electronic health record (EHR) systems has brought prodigious biomedical informatics opportunity. Automated machine learning methods can effectively utilize such data and have become common tools for healthcare predictive modeling. Researches in medical informatics have explored the potential of deep learning and classical models in emergent care scenarios. In particular, predicting differential diagnoses for admissions have proven useful in decreasing unnecessary lab tests and improving inpatient triage decision-making. Moreover, identification of high-risk patients for in-hospital mortality is vitally important to maximize allocation of medical resources.The Medical Information Mart for Intensive Care (MIMIC-III) database, containing de-identified critical care inpatient was used in our study. This data set captures hospital patient laboratory measurements, pharmacologic prescriptions, diagnostic data and procedure event recordings. When considering adult patients and discounting admissions with ICU length of stay less than 24 hours, there were 37,787 unique admissions and 30,414 total patients. We examined the top 25 most prevalent ICD-9 group-level disease specificities in MIMIC-III using a multi-label classification model. In-hospital mortality was modeled as binary classification with 4,155 (13%) adult patients that expired, of which 3,138 (75.5%) were in the ICU setting. The metrics AUC, F1 score, sensitivity and specificity values calculated for each disease label measured prediction performance.The usage of ICD-9 group codes reduced feature dimension from 14,567 to 942 and greatly improved distribution of patient diagnostic categories. Disease temporal patterns were captured by considering the most frequently sampled 6 vital signs and 13 laboratory values. Missing data were imputed at each time-stamp. Time-series raw hourly average values were converted into 5 summary features (mean, standard deviation, number of observations, min & max values). Patient demographic variables such as age, gender, marital status and ethnicity were also factored into the modeling. Choi et al showed that contextual embedding of medical data, diagnostic and procedural codes alone can predict future diagnoses with sensitivity as high as 0.79. We utilized an embedding technique called word2vec which allowed sparse representations of medical history to be transformed into dense word vectors. The mappings captured contextual information by treating each admission as a sentence and learning the most likely neighboring words in a sliding window fashion. Binary and multi-label classification was achieved via collapse models, which do not consider temporal information, as well as recurrent neural networks with regularization, Softmax output layer activation together with categorical cross-entropy as the loss function.
US Army collaboration↗
Performance Risk Model (PRisM) Proof-of-Concept: An Operational Decision Support Tool to Predict Crew Performance in Space from Available Performance Tests
The Crew Health and Performance-Probabilistic Risk Assessment (CHP-PRA) team at NASA Glenn Research Center has developed a range of tools to evaluate astronaut health during spaceflight and to optimize the medical set required for missions. Among these, the Performance Risk Model (PRisM) represents a novel advancement, extending CHP-PRA’s focus beyond medical systems into the domain of human performance. Such tool could be pivotal in optimizing astronaut capabilities during space travel, thereby enhancing overall mission success. PRisM leverages data from well-established performance assessments conducted during previous crewed space missions and Earth analogs to strategically predict outcomes for planned tasks, even when direct performance testing has not been conducted for those specific tasks. To evaluate performance, PRisM references the various metrics outlined in NASA-STD-3001 and employs a methodology to integrate different performance scales. This framework analyzes the contribution of various human system task categories (HSTCs) to task execution and compares these contributions to the HSTCs’ involvement in other known tests. The model further employs a Monte Carlo simulation to sample performance scores from their distribution in operationally relevant tests such as those in Mulavara et al. (2018) and, by leveraging similarities in HSTC involvement, transfers this knowledge to actual mission tasks, such as those outlined in the "Human Exploration of Mars: Preliminary List of Crew Tasks”. The current PRisM proof-of-concept includes analyses of the impact of exercise and specific medications on astronauts’ performance, with provisions to incorporate additional countermeasures as data becomes available. Furthermore, the tool is customizable to include any system necessary to fully encompass the domain of human systems and can be adapted to evaluate performance for any spaceflight activities as requested by operational stakeholders. PRisM has the potential to assist the Human Research Program in exploring the capabilities trade space for optimized crew performance.
performance modeling↗
Joint Resource Modeling and Assessment for Hybrid Distributed Solar and Wind Systems
The inherent variability and uncertainty in distributed energy resources can presents myriad challenges to the planning and operations of power systems. These risks are poised to become larger as the penetration of renewable energy sources rises in the power generation mix. Hybrid solar-wind energy systems are able to mitigate some of these risks by their complementary resource availability. Surface solar and wind fields are coupled and correlated in both space and time. Appropriately estimating the hybrid solar wind energy system requires simulating the spatio-temporal structure of these fields that can be produced for each time horizon. We introduce a novel joint spatio-temporal stochastic differential equation (SPDE) approach that captures the spatio-temporal dynamics of solar and wind fields and their joint dependency over a domain for each time step. In the case study on Colorado, we consider nonstationary three-level hierarchical spatio temporal models for both hourly solar irradiance data and wind speed data in Colorado. Dependence between the solar irradiance data and wind speed data is captured by a shared spatio-temporal random effect. Our approach performs well in terms of the prediction score criterion.
joint modeling↗
Results of a 3-day Pilot Study to Validate Planetary Prebreathe Protocols Using a 56.5 kPa 34% O2, 66% N2 Saturation Cabin Atmosphere
INTRODUCTION: Apollo missions used 100% O2 cabin atmospheres which effectively eliminated the risk of decompression sickness (DCS) during extravehicular activities (EVAs, ‘spacewalks’); however, this atmosphere presented a flammability risk that is no longer acceptable to NASA. Denitrogenation prebreathe protocols used to mitigate DCS risk for Space Shuttle and International Space Station EVAs are validated for the microgravity environment, but the significantly increased risk of DCS during equivalent ambulatory surface EVAs make these protocols inapplicable to planetary/Lunar missions. An “exploration atmosphere” of 56.5 kPa (8.2 psia), 34% O2, 66% N2 has been recommended by NASA for future Moon and Mars missions as a compromise that balances subsequent pre-EVA prebreathe duration, hypoxia, and flammability risk, assuming a 29.6 kPa (4.3 psi) spacesuit. Prebreathe validation studies was initiated utilizing a three-story 6m diameter hypobaric chamber at NASA’s Johnson Space Center. Here, we report the results of a 3-day human-in-the-loop system checkout. METHODS: Six volunteers acclimated to the 56.6kPa/34% O2 66% N2 environment for 48hrs prior to conducting a 20-minute prebreathe and a 6-hour simulated EVA at 34kPa/85% O2 / 15% N2. The EVA simulation was designed to include tasks that are physically and ergonomically representative of future planetary EVAs. Decompression stress was evaluated by serial doppler and echocardiographs, as well as by clinical features of DCS signs/symptoms. RESULTS AND DISCUSSION: Preliminary data analysis noted venous gas emboli (VGE) in 3 of 6 subjects, with peak Grade II VGE by Doppler and peak E-B score of 5 by cardiac ultrasonography. No volunteers were diagnosed with DCS during this initial test. No acute hypoxic symptoms were noted. Musculoskeletal and gastrointestinal complaints were noted, likely associated with the exercise load and the food system. Validation of exploration prebreathe protocols has since been initiated with an 11-day saturation test using the same facility and protocol.
Alejandro Garbino↗
Late ophthalmological complications after total body irradiation in non-human primates
PURPOSE: To investigate the long-term effects of total body irradiation (TBI) on the incidence and time course of ocular complications. MATERIALS AND METHODS: Rhesus monkeys treated with TBI photon doses up to 8.5 Gy and proton doses up to 7.5 Gy were studied at intervals up to 25 years post-irradiation. They were compared with control groups with a similar age distribution. Cataract formation and ocular fundus lesions were scored according to a standardized protocol. Fluorescein angiography and histopathology was performed in selected animals. RESULTS: Cataract formation occurred after a latent period of 3-5 years. Significant cataract induction was observed for photon-doses of 8 and 8.5 Gy and beyond 20 years after proton irradiation. The severity of the lesions represents significant impairment of vision and would require cataract surgery if similar results occurred in human bone marrow transplant patients. Fluorescein angiography demonstrated a normal pattern of retinal vessels in 13 out of 14 animals (93%) from the irradiated group and in eight out of nine animals (89%) from the control group. No additional lesions apart from age-related degenerative changes could be demonstrated. Histological evaluation revealed no radiation-associated vasculopathy. CONCLUSIONS: Radiation alone for doses up to 8.5 Gy of photons does not carry a potential risk for fundus pathology, whereas clinically important cataract induction should be anticipated within 5 years after photon doses of 8.0 and 8.5 Gy and proton doses in excess of 2.5 Gy.
NASA Discipline Radiation Health↗
A Case Study in Assessing a Potential Severity Framework for Incidents from a Decadal Sample
In this study, the primary objective of this case study is to determine the applicability and feasibility of a framework that leverages occupational incident details to prospectively identify “potential Serious Injury or Fatality” (pSIF) cases. This study comprehensively reviewed a random sample of 1,081 injury and illness cases across 21 generalized incident types spanning over a decade at Lawrence Livermore National Laboratory (LLNL), a U.S. Department of Energy research and development facility with more than 9,000 employees. The review applied a general framework that classified each case on information suitability, potential severity, and future incident mitigation. The findings from the study indicate that 86.6% of the cases had sufficient information to make a high-confidence determination on potential severity, underscoring the feasibility of applying this general framework. Additionally, cases with a higher pSIF score had, on average, a higher level of institutional response. Implementing a simplified methodology for incident classification that emphasizes incidents that pose high potential severity, regardless of incident type, can help LLNL prioritize resources and tailor responses to such incidents using a graded approach. LLNL has recognized the value of this capability and is integrating the framework into their injury and illness process in the 2024 calendar year.
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
Neck Muscle Coactivation Response to Varied Levels of Mental Workload During Simulated Flight Tasks
Objective To evaluate neck muscle coactivation across different levels of mental workload during simulated flight tasks. Background Neck pain (NP) is highly prevalent among military aviators. Given the complex nature within the flight environment, mental workload may be a risk factor for NP. This may induce higher levels of neck muscle coactivity, which over time may accelerate fatigue, increase neck discomfort, and affect flight task performance. Method Three counterbalanced mental workload conditions represented by simulated flight tasks modulated by interstimulus frequency and complexity were investigated using the Modifiable Multitasking Environment (ModME). The primary measure was a neck coactivation index to describe the neuromuscular effort of the neck muscles as a system. Additional measures included perceived workload (NASA TLX), subjective discomfort, and task performance. Participants ( n = 60; 30M, 30F) performed three test conditions over 1 hr each while seated in a simulated seating environment. Results Neck coactivation indices (CoA) and subjective neck discomfort corresponded with increasing level of mental workload. Average CoAs for low, medium, and high workloads were: .0278(SD = .0232), .0286(SD = .0231), and .0295(SD = .0228), respectively. NASA TLX mental, temporal, effort, and overall scores also increased with the level of mental workload assigned. For ModME task performance, the overall performance score, monitoring accuracy, and resource management accuracy decreased while reaction times increased with the increasing level of mental workload. Communication accuracy was lowest with the low mental workload but had higher reaction times relative to increasing workload. Conclusion Mental workload affects neck muscle coactivation during combinations of simulated flight tasks within a simulated helicopter seating environment. Application The results of this study provide insights into the physical response to mental workload. With increasing multisensory modalities within the work environment, these insights may assist the consideration of physical effects from cognitive factors.
Behavioral Sciences↗
Non-subjective cataract analysis and its application in space radiation risk assessment
Experimental animal studies and human observations suggest that the question is not whether or not prolonged space missions will cause cataracts to appear prematurely in the astronauts, but when and to what degree. Historically the major impediment to radiation cataract follow-up has been the necessarily subjective nature of assessing the degree of lens transparency. This has spurred the development of instruments which produce video images amenable to digital analysis. One such system, the Zeiss Scheimpflug slit lamp measuring system (SLC), was incorporated into our ongoing studies of radiation cataractogenesis. It was found that the Zeiss SLC measuring system has high resolution and permits the acquisition of reproducible images of the anterior segment of the eye. Our results, based on about 650 images of the rats lens, and followed over a period of 91 weeks of radiation cataract development, showed that the Integrated Optical Density (IOD) of the lens correlated well with conventional assessment with the added advantages of objectivity, permanent and transportable records and linearity as cataracts become more severe. This continuous data acquisition, commencing with cataract onset, can proceed through more advanced stages. The SLC exhibits much greater sensitivity reflected in a continuously progressive severity despite the artifactual plateaus in staging which occur using conventional scoring methods. Systems such as the Zeiss SLC should be used to monitor astronauts frequent visits to low earth orbit to obtain a longitudinal data-base on the influence of this activity on the lens.
Wu, B.↗
Pre-Flight Training of Autonomic Responses for Mitigating the Effects of Spatial Disorientation During Spaceflight
The National Aeronautics and Space Administration (NASA) has identified a potential risk of spatial disorientation, motion sickness, and degraded performance to astronauts during re-entry and landing of the proposed Orion crew vehicle. The purpose of this study was to determine if a physiological training procedure, Autogenic-Feedback Training Exercise (AFTE), can mitigate these adverse effects. Fourteen men and six women were assigned to two groups (AFTE, no-treatment Control) matched for motion sickness susceptibility and gender. All subjects received a standard rotating chair test to determine motion sickness susceptibility; three training sessions on a manual performance task; and four exposures in the rotating chair (Orion tests) simulating angular accelerations of the crew vehicle during re-entry. AFTE subjects received 2 hours of training before Orion tests 2, 3, and 4. Motion sickness symptoms, task performance, and physiological measures were recorded on all subjects. Results showed that the AFTE group had significantly lower symptom scores when compared to Controls on test 2 (p=.05), test 3 (p=.03), and test 4 (p=.02). Although there were no significant group differences on task performance, trends showed that AFTE subjects were less impaired than Controls. Heart rate change scores (20 revolutions per minute minus baseline) of AFTE subjects indicated significantly less reactivity on Test 4 compared to Test 1 (10.09 versus 16.59, p=.02), while Controls did not change significantly across tests. Results of this study indicate that AFTE may be an effective countermeasure for mitigating spatial dis-orientation and motion sickness in astronauts.
Orion↗
Data-driven Cyberattack Detection for Photovoltaic (PV) Systems through Analyzing Micro-PMU Data
With increasing exposure to software-based sensing and control, Photovoltaic (PV) systems are facing higher risks of cyber attacks. Here, to ensure the system stability and minimize potential economic losses, it is imperative to monitor operating states and detect attacks at the early stage. To meet this demand, Micro-Phasor Measurement Units (μPMU) are increasingly popular in monitoring distribution networks. However, due to the relatively low sampling rate, μPMU has not yet been used to detect and classify cyber-attacks in power electronics enabled smart grid. To our knowledge, this is one of the first attempts to use μPMU to detect cyber attacks that degrade the performance of power electronics systems. We propose to apply data-driven methods on micro-PMU data to implement attack detection. We have evaluated data-driven methods, including decision tree (DT), K-nearest neighbor (KNN), support vector machine (SVM), artificial neural network (ANN), long short-term memory (LSTM) and convolutional neural network (CNN). The proposed CNN model achieves the required performances with the highest 99.23% accuracy and 0.9963 F 1 score.
14 SOLAR ENERGY↗