Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Node selection”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

IM3 Projected U.S. Western Interconnection Grid Stress Dataset

This dataset provides projected grid stress and reliability results (including all model inputs and outputs from GO WEST and TEP) for Integrated Multisector, Multiscale Modeling (IM3) Phase 2 simulations across eight different scenarios for the U.S. Western Interconnection through 2055. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States from a set of Thermodynamic Global Warming (TGW) simulations. These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 GO WEST is an open-source power grid modeling framework for the U.S. Western Interconnection, which allows users to tailor the model depending on their research study and science questions. It covers 28 balancing authorities (BAs) and 12 states in U.S. Western Interconnection. GO WEST allows users to select different number of nodes and come up with a simplified network by utilizing 10,000 nodal topology of the U.S. Western Interconnection (ACTIVSg10k). Users can select different number of nodes, mathematical formulations (linear programming vs. mixed-integer linear programming), transmission line limit scaling factors, and hurdle rate scaling factors. GO WEST offers a unit commitment and economic dispatch (UC/ED) module to simulate grid operations on an hourly scale. In this sense, users can calibrate and validate their model versions by comparing model outputs to historical datasets. TEP is an open-source transmission capacity expansion model, built on the GO WEST framework. It utilizes linear programming to optimize transmission capacity addition investment on existing lines within the GO WEST framework. The TEP model only increases the thermal capacity of existing transmission lines and does not add new lines to the system, which leaves the topology preserved. In order to use TEP model, users need to create scenarios with the GO WEST framework. Please refer to README file for a detailed description of the dataset including individual files and references.

Capacity Expansion Model↗

SU-F-P-40: Analysis of Pelvic Lymph Node Margin Using Prostate Fiducial Markers, for SBRT Treatments

Purpose: The use of fiducials markers in prostate treatment allows a precise localization of this volume. Typical prostate SBRT margins with fiducials markers are 5mm in all directions, except toward the rectum, where 3mm is used. For some patients nearby pelvic lymph nodes with 5mm margin need to be irradiate assuming that its localization is linked to the prostate fiducial markers instead of bony anatomy. The purpose of this work was to analyze the geometric impact of locate the lymph node regions through the patient positioning by prostate fiducial markers. Methods: 10 patients with prostate SBRT with lymph nodes irradiation were selected. Each patient had 5 implanted titanium fiducial markers. A Novalis TX (BrainLAB-Varian) with ExacTrac and aSi1000 portal image was used. Treatment plan uses 11 beams with a dose prescription (D95%) of 40Gy to the prostate and 25Gy to the lymph node in 5 fractions. Daily positioning was carried out by ExacTrac system based on the implanted fiducials as the reference treatment position; further position verification was performed using the ExacTrac and two portal images (gantry angle 0 and 90) based on bony structures. Comparison between reference position with bony based ExacTrac and portal image localization, was done for each treatment fraction Results: A total of 50 positioning analysis were done. The average discrepancy between reference treatment position and ExacTrac based on bony anatomy (pubic area) was 4.2mm [0.3; 11.2]. The discrepancy was <5mm in 61% of the cases and <9mm in 92%. Using portal images the average discrepancy was 3.7mm [0.0; 11.1]. The discrepancy was <5mm in 69% of the cases and <9mm in 96%. Conclusion: Localizing lymph node by prostate fiducial markers may produce large discrepancy as large as 11mm compared to bony based localization. Dosimetric impact of this discrepancy should be studied.

60 APPLIED LIFE SCIENCES↗

Electrochemically-assisted removal of cadmium ions by redox active Cu-based metal-organic framework

An electrochemically-assisted wastewater treatment using Faradaic materials offers a promising technique for the selective removal of hazardous substances. Here, we demonstrate the reversible capture and release of cadmium ions in aqueous solutions, using a redox-active metal-organic framework (MOF) electrode. As-synthesized copper-based MOF (Cu-MOF-74; copper 2,5-dihydroxyterephthalate) is a highly attractive candidate for Faradaic electrosorption due to its large surface area, water stability, and redox-active metal nodes. Our work demonstrates the reversible capture and release of Cd 2+ ions assisted by the electrochemical redox reaction of Cu 2+ /Cu + within the MOF structure. Combined material characterization and electrosorption tests were carried out to determine the operational conditions for maximizing adsorption capacity, energy efficiency, and material stability, thus leading to excellent electrosorption (>100 mg g -1 ) and regeneration efficiency (>90%). This study demonstrates the feasibility of leveraging MOFs containing redox-active metal nodes for the selective separation of toxic cations, and paves the way for promising future applications of these 3-D porous structures for wastewater treatment and environmental remediation.

42 ENGINEERING↗

IM3 GO WEST Parameter Search Dataset

GO WEST is an open-source power grid modeling framework for U.S. Western Interconnection, which allows users to tailor the model depending on their research study and science questions. It is developed to address weather and water dynamics, and associated vulnerabilities in this bulk power system. It covers 28 balancing authorities (BA) and 12 states in U.S. Western Interconnection. GO WEST allows users to select different number of nodes and come up with a simplified network by utilizing 10,000 nodal topology of U.S. Western Interconnection created by Texas A&M University. Users can try and select different number of nodes, mathematical formulations (linear programming vs. mixed-integer linear programming), transmission line limit scaling factors, and hurdle rate scaling factors. GO WEST offers a unit commitment and economic dispatch (UC/ED) module to simulate grid operations on an hourly scale. In this sense, users can calibrate and validate their model versions by comparing model outputs to historical datasets. Therefore, GO WEST can help researchers to strike a balance between model fidelity (i.e. accuracy) and computational complexity (i.e. runtime). This dataset includes model inputs and outputs from 600 model versions for each 2019, 2020, and 2021. The folder naming convention is as follows: Exp{Number of Nodes}_{Mathematical Formulation}_{Transmission Line Limit Scaling Factor in MW}_{Hurdle Rate Scaling Factor in %}_{Year}. Linear programming is designated with "simple" label whereas mixed-integer linear programming is designated with "coal" label. For example, "Exp100_simple_1000_50_2019" folder contains inputs and outputs from 2019 model version with 100 nodes, linear programming, +1000 MW transmission line limit scaling factor, and +50% hurdle rate scaling factor. GO WEST GitHub repository hosts all raw datasets, processing scripts, and model scripts. Please refer to the README file for a detailed description of the included files.

Economics↗

Cooperative Transmission Expansion Planning Experiment Data and Results

GO WEST is an open-source power grid modeling framework for U.S. Western Interconnection, which allows users to tailor the model depending on their research study and science questions. It covers 28 balancing authorities (BA) and 12 states in U.S. Western Interconnection. GO WEST allows users to select different number of nodes and come up with a simplified network by utilizing 10,000 nodal topology of U.S. Western Interconnection created by Texas A&M University. Users can try and select different number of nodes, mathematical formulations (linear programming vs. mixed-integer linear programming), transmission line limit scaling factors, and hurdle rate scaling factors. GO WEST offers a unit commitment and economic dispatch (UC/ED) module to simulate grid operations on an hourly scale. In this sense, users can calibrate and validate their model versions by comparing model outputs to historical datasets. TEP is an open-source transmission capacity expansion model, built on GO WEST framework. It utilizes linear programming to optimize transmission capacity addition investment on existing lines within GO WEST framework. In this sense, TEP model only increases the thermal capacity of existing transmission lines and does not add new lines to the system, which leaves the topology preserved. TEP minimizes the total cost of the system which comprises the operational cost of satisfying electricity demand (i.e., generation cost), cost of loss of load (i.e., unserved energy), cost of power flow, and cost of new transmission capacity additions (i.e., investment cost). In order to use TEP model, users need to create scenarios with GO WEST framework. In this analysis, outputs from several models are used to create future inputs to GO WEST and TEP models, including GCAM-USA, TELL, CERF and reV. This dataset includes experiment inputs and outputs from three different transmission expansion scenarios (cooperative, intermediate, and individual) for 2019 and 2059. For 2019, a base scenario to illustrate the default (i.e., historical) power grid operations is also included. This study utilizes rcp45hotter_ssp3 scenario from a previous version of GCAM-USA simulations. Sources of the shapefiles in supplementary data are HIFLD Open and U.S. Energy Atlas. Please see the README file for a detailed description of the main and supplementary data.

Capacity Expansion Model↗

SU-E-T-393: Evaluation of Large Field IMRT Versus RapidArc Planning for Carcinoma Cervix with Para-Aotic Node Irradiation

Purpose: The objective of this work is to evaluate and compare Large field IMRT and RapidArc planning for Carcinoma Cervix and Para-aotic node irradiation. Methods: In this study, ten patients of Cervix with para-aotic node have been selected with PTV length 35+2cm. All plans were generated in Eclipse TPS V10.0 with Dynamic IMRT and RapidArc technique using 6MV photon energy. In IMRT planning, 7 fields were chosen to get optimal plan and in RapidArc, double Full arc clockwise and counter clockwise were used for planning. All the plans were generated with single isocenter and calculated using AAA dose algorithm. For all the cases the prescribed dose to PTV was same and the plan acceptance criteria is; 95% of the PTV volume should receive 100% prescribed dose. The tolerance doses for the OAR’s is also taken in to account. The evaluation criteria used for analysis are; 1) Homogeneity Index, 2) Conformity Index, 3) Mean Dose to OAR’s, 4)Total monitor units delivered. Results: DVH analysis were performed for both IMRT and RapidArc planning. In both the plans, 95% of PTV volume receives prescribed dose and maximum dose are less than 107%. The conformity index are same in both the techniques. The mean Homogeneity index are 1.036 and 1.053 for IMRT and RapidArc plan. The mean (mean + SD) dose of bladder and rectum in IMRT is 44.2+1.55, 42.05+2.52 and RapidArc is 46.66+1.6, 44.2+2.75 respectively. There is no significant difference found in Right Femoral head, Left Femoral head and Kidney doses. It is found that total MU’s are more in IMRT compared with RapidArc planning. Conclusion: In the case of cervix with Para-arotic node single isocenter irradiation, IMRT planning in large-field is better compared to RapidArc planning in terms of Homogeneity Index and mean dose of Bladder and Rectum.

60 APPLIED LIFE SCIENCES↗

Enhancement of Distribution System State Estimation Using Pruned Physics-Aware Neural Networks

Realizing complete observability in the three-phase distribution system remains a challenge that hinders the implementation of classic state estimation algorithms. In this paper, a new method, called the pruned physics-aware neural network (P2N2), is developed to improve the voltage estimation accuracy in the distribution system. The method relies on the physical grid topology, which is used to design the connections between different hidden layers of a neural network model. To verify the proposed method, a numerical simulation based on one- year smart meter data of load consumptions for three-phase power flow is developed to generate the measurement and voltage state data. The IEEE 123-node system is selected as the test network to benchmark the proposed algorithm against the classic weighted least squares (WLS). Numerical results show that P2N2 outperforms WLS in terms of data redundancy and estimation accuracy.

distribution system state estimation↗

Latency and Bandwidth Microbenchmarks of US Department of Energy Systems in the June 2023 Top 500 List

As a rule, Top 500 class supercomputers are extensively benchmarked as part of their acceptance testing process. However, barring publicly posted LINPACK / HPCG results, most benchmark results are often inaccessible outside the hosting institution. Moreover, these higher level benchmarks do not provide easy answers to common questions such as “What is the realizable memory bandwidth?” or “What is the launch latency on the accelerator?” To partially address these issues, we executed selected single-node micro-benchmarks — focused on latencies and memory bandwidth — on every US Department of Energy system above rank 150 of the June 2023 Top 500 list, excepting NERSC’s Cori and ORNL’s Frontier TDS (now decommissioned or repurposed). We hope to provide an easy “first stop” reference for users of current Top 500 systems and inspire users and administrators of other Top 500 systems to similarly compile and make available benchmark results for their systems.

Siefert, Christopher M.↗

Constructing Regulatory Networks to Compare Axenic and Interspecies Microbial Gene Transcription

In this preliminary study, we constructed gene regulatory networks (GRNs) from transcriptional expression data of axenic and interspecies microbial cultures with the goal of predicting how cocultivation affected greenhouse gas respiration by these species. The specific strains of Methylotuvimicrobium alkaliphilum 20Z, a methylotroph, and Cyanobacterium stanieri HL-69, a phototroph, were chosen for their viability in industrial bioprocessing. We ranked directed interactions between gene pairs based on the ability of the input gene to predict the expression of a target gene relative to their transcriptomes. While we were able to identify topological differences between conditions, our initial findings require validation through experimental analysis and further modeling. We aimed to develop a systematic thresholding approach to optimize the accuracy of our networks. We filtered out trial networks separately from top gene interactions of the scored rankings. Parameters of unfiltered and filtered networks were used to test and develop thresholding approaches. Knee point detection of edge weight distributions was explored as an approach for separating significant interactions from insignificant interactions in unfiltered networks. While knee detection failed to produce analogous networks for broad cross-condition comparisons, the results informed us about the proportions of significant edges present in unfiltered networks. We also calculated the average mean degree for nodes in a selection of trial networks to find a thresholding value characteristic to all groups. While we did not reach a definitive conclusion, we gained insight into the coregulatory structures of our groups and made critical evaluations of systematic methods for filtering networks. We recommend an iterative process for the inference of GRNs, where the most significant results from preliminary explorations are used to improve the efficiency with which regulatory motifs are chosen for experimental characterization. Experimental results can then inform the framework of adjusted models to improve broad interpretations of GRNs.

59 BASIC BIOLOGICAL SCIENCES↗

Multi-Area Distribution System State Estimation Using Decentralized Physics-Aware Neural Networks

The development of active distribution grids requires more accurate and lower computational cost state estimation. In this paper, the authors investigate a decentralized learning-based distribution system state estimation (DSSE) approach for large distribution grids. The proposed approach decomposes the feeder-level DSSE into subarea-level estimation problems that can be solved independently. The proposed method is decentralized pruned physics-aware neural network (D-P2N2). The physical grid topology is used to parsimoniously design the connections between different hidden layers of the D-P2N2. Monte Carlo simulations based on one-year of load consumption data collected from smart meters for a three-phase distribution system power flow are developed to generate the measurement and voltage state data. The IEEE 123-node system is selected as the test network to benchmark the proposed algorithm against the classic weighted least squares and state-of-the-art learning-based DSSE approaches. Numerical results show that the D-P2N2 outperforms the state-of-the-art methods in terms of estimation accuracy and computational efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Enhancement of Distribution System State Estimation Using Pruned Physics-Aware Neural Networks: Preprint

Realizing complete observability in the three-phase distribution system remains a challenge that hinders the implementation of classical state estimation algorithms. In this paper, a new method so-called pruned physics-aware neural network (P2N2) is developed to improve the voltage estimation accuracy in the distribution system. The method relies on the physical grid topology, which is used to design the connections between different hidden layers of a neural network model. To verify the proposed method, a numerical simulation based on one-year smart meter data of load consumptions for threephase power flow is developed to generate the measurement and voltage state data. The IEEE 123 node system is selected as the test network to benchmark the proposed algorithm against the classical weighted least squares (WLS). Numerical results show that P2N2 outperforms WLS, in terms of data redundancy and estimation accuracy.

distribution systems state estimation↗

Design and fabrication of non silicon substrate based MEMS energy harvester for arbitrary surface applications

Internet of Things (IoT) uses MEMS sensor nodes and actuators to sense and control objects through Internet. IOT deploys millions of chemical battery driven sensors at different locations which are not reliable many times because of frequent requirement of charging & battery replacement in case of underground laying, placement at harsh environmental conditions, huge count and difference between demand (24 % per year) and availability (energy density growing rate 8% per year). Energy harvester fabricated on silicon wafers have been widely used in manufacturing MEMS structures. These devices require complex fabrication processes, costly chemicals & clean room. In addition to this silicon wafer based devices are not suitable for curved surfaces like pipes, human bodies, organisms, or other arbitrary surface like clothes, structure surfaces which does not have flat and smooth surface always. Therefore, devices based on rigid silicon wafers are not suitable for these applications. Flexible structures are the key solution for this problems. Energy transduction mechanism generates power from free surrounding vibrations or impact. Sensor nodes application has been purposefully selected due to discrete power requirement at low duty cycle. Such nodes require an average power budget in the range of about 0.1 microwatt to 1 mW over a period of 3-5 seconds. Energy harvester is the best alternate source in contrast with battery for sensor node application. Novel design of Energy Harvester based on cheapest flexible non silicon substrate i.e. cellulose acetate substrate have been modeled, simulated and analyzed on COMSOL multiphysics and fabricated using sol-gel spin coating setup. Single cantilever based harvester generates 60-75 mV peak electric potential at 22Hz frequency and approximately 22 µW power at 1K-Ohm load. Cantilever array can be employed for generating higher voltage by replicating this structure. This work covers design, optimization, fabrication of harvester and schottky diodes based voltage multiplier.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A new approach to the method of source-sink potentials for molecular conduction

We re-derive the tight-binding source-sink potential (SSP) equations for ballistic conduction through conjugated molecular structures in a form that avoids singularities. This enables derivation of new results for families of molecular devices in terms of eigenvectors and eigenvalues of the adjacency matrix of the molecular graph. In particular, we define the transmission of electrons through individual molecular orbitals (MO) and through MO shells. We make explicit the behaviour of the total current and individual MO and shell currents at molecular eigenvalues. A rich variety of behaviour is found. A SSP device has specific insulation or conduction at an eigenvalue of the molecular graph (a root of the characteristic polynomial) according to the multiplicities of that value in the spectra of four defined device polynomials. Conduction near eigenvalues is dominated by the transmission curves of nearby shells. A shell may be inert or active. An inert shell does not conduct at any energy, not even at its own eigenvalue. Conduction may occur at the eigenvalue of an inert shell, but is then carried entirely by other shells. If a shell is active, it carries all conduction at its own eigenvalue. For bipartite molecular graphs (alternant molecules), orbital conduction properties are governed by a pairing theorem. Inertness of shells for families such as chains and rings is predicted by selection rules based on node counting and degeneracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fixed-node diffusion Monte Carlo potential energy curve of the fluorine molecule F{sub 2} using selected configuration interaction trial wavefunctions

The potential energy curve of the F{sub 2} molecule is calculated with Fixed-Node Diffusion Monte Carlo (FN-DMC) using Configuration Interaction (CI)-type trial wavefunctions. To keep the number of determinants reasonable and thus make FN-DMC calculations feasible in practice, the CI expansion is restricted to those determinants that contribute the most to the total energy. The selection of the determinants is made using the CIPSI approach (Configuration Interaction using a Perturbative Selection made Iteratively). The trial wavefunction used in FN-DMC is directly issued from the deterministic CI program; no Jastrow factor is used and no preliminary multi-parameter stochastic optimization of the trial wavefunction is performed. The nodes of CIPSI wavefunctions are found to reduce significantly the fixed-node error and to be systematically improved upon increasing the number of selected determinants. To reduce the non-parallelism error of the potential energy curve, a scheme based on the use of a R-dependent number of determinants is introduced. Using Dunning’s cc-pVDZ basis set, the FN-DMC energy curve of F{sub 2} is found to be of a quality similar to that obtained with full configuration interaction/cc-pVQZ.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reducing I/O variability using dynamic I/O path characterization in petascale storage systems

In petascale systems with a million CPU cores, scalable and consistent I/O performance is becoming increasingly difficult to sustain mainly because of I/O variability. Furthermore, the I/O variability is caused by concurrently running processes/jobs competing for I/O or a RAID rebuild when a disk drive fails. We present a mechanism that stripes across a selected subset of I/O nodes with the lightest workload at runtime to achieve the highest I/O bandwidth available in the system. In this paper, we propose a probing mechanism to enable application-level dynamic file striping to mitigate I/O variability. We also implement the proposed mechanism in the high-level I/O library that enables memory-to-file data layout transformation and allows transparent file partitioning using subfiling. Subfiling is a technique that partitions data into a set of files of smaller size and manages file access to them, making data to be treated as a single, normal file to users. Here, we demonstrate that our bandwidth probing mechanism can successfully identify temporally slower I/O nodes without noticeable runtime overhead. Experimental results on NERSC’s systems also show that our approach isolates I/O variability effectively on shared systems and improves overall collective I/O performance with less variation.

97 MATHEMATICS AND COMPUTING↗

Streptococcus gallolyticus conspires myeloid cells to promote tumorigenesis of inflammatory bowel disease

Highlights: • Streptococcus gallolyticus shows a distinctive enrichment at colonic mucosa in colitis-associated carcinoma. • Introduction of Streptococcus gallolyticus could aggravate the development of colitis-associated carcinoma. • CD11b{sup +} myeloid cells recruitment are initialed by Streptococcus gallolyticus to promote colitis-associated carcinoma progress. Metagenomic analyses indicate that streptococcus gallolyticus is enriched at carcinoma in colitis associated colorectal cancer compared with sporadic colorectal cancer. But the particular mechanism of streptococcus gallolyticus in Inflammatory Bowel Disease malignant progression remains undefined yet. We aim to explore the biological carcinogenesis efficacy of streptococcus gallolyticus and its potential mechanism in azoxymethane and dextran sodium sulphate-induced colitis associated colorectal cancer in mice. Oral pretreatment of streptococcus gallolyticus was adopted to evaluate its detrimental effect. The colorectums of experimental C57BL/6 mice were collected and examined for the degree of tumorigenesis. Comparative 16S rRNA sequencing was carried out to observe streptococcus gallolyticus alterations in abundance. We found that streptococcus gallolyticus are enriched in colonic carcinoma compared to adenoma and healthy mice. Pretreatment of Streptococcus gallolyticus aggravated tumor formation, with more colonic obstruction, larger number and diameter of tumor node. Furthermore, Streptococcus gallolyticus selectively recruits tumor-infiltrating myeloid cells but not mast cells, including marrow-derived suppressor cells, tumor-associated macrophages and dendritic cells, which can inhibit competence of T cells. Moreover, several myeloid-cell-derived proinflammatory cytokines (IL-6, IL-1β, IL-8, CCL2, COX-2, TNF-α) were increased with the formation of carcinoma in IBD. Collectively, these data suggest that, through recruitment of tumor-infiltrating immune cells, Streptococcus gallolyticus generate an immune suppressive microenvironment that is conducive for neoplasia progression of Inflammatory Bowel Disease.

60 APPLIED LIFE SCIENCES↗

Impact of electric vehicles on the IEEE 34 node distribution infrastructure

With the growing penetration of the electric vehicles to our daily life owing to their economic and environmental benefits, there will be both opportunities and challenges to the utilities when adopting plug-in electric vehicles (PEV) to the distribution network. In this study, a thorough analysis based on real-world project is conducted to evaluate the impacts of electric vehicles infrastructure on the grid relating to system load flow, load factor, and voltage stability. IEEE 34 node test feeder was selected and tested along with different case scenarios utilizing the electrical distribution design (EDD) software to find out the potential impacts to the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

WISP: Watching grid Infrastructure Stealthily through Proxies (Final Technical Report)

The complex interdependencies of cyber systems (sensors and communications), physical grids and associated electricity market operations make protecting electric power grids a significant challenge. The energy sector is constantly under new, targeted, advanced and dangerous cyber-attacks that have the potential to result in the loss of human life. These threats are further exacerbated by our need to modernize the grid. One focus of cyber security research in smart grids is the securing of the SCADA system through advanced intrusion detection systems (IDS) and bad data detection algorithms in state estimation. These methods either require full knowledge of the system topology and parameters or fail to understand the physical behaviors under attack. WISP (Watching grid Infrastructure Stealthily through Proxies) is designed to provide additional protection to the power grid using only publicly available data. In particular, WISP exploits the spatio-temporal nature of the real time locational marginal prices (LMPs), in conjunction with other information such as bids, weather, outages and load data to analyze anomalous power pricing behaviors and then correlate those observations to localize regions of interest and identify potential cyber events. WISP is non-intrusive as the tool is deployed as a service in the Cloud or on premise and provides reliable information to system operators for enhanced situational awareness, without impeding energy delivery functions. The WISP technology comprises three modules: the data-driven anomaly detection core, the vulnerability and risk analysis and the root cause analysis. The data-driven anomaly detection core performs the tasks of feature selection, anomaly detection and attack region localization. The vulnerability and risk analysis module provides system level information of the vulnerable variables and times, assisting the operators in selecting monitoring and protection nodes. The root cause analysis module takes the detection results and identifies potential operational conditions that contribute to the detected anomalies. In Phase I, we have demonstrated the feasibility and effectiveness of WISP. We developed a realistic electricity market simulator capable of generating normal and attack market data under various operational conditions. We developed a series of cyber-attack detection and analysis algorithms and evaluated them under multiple data sources. Finally, we integrated all modules into an end-to-end software, providing functions for data management, data analytics and visualization. Specifically, we have achieved: (i) real-time data acceptance from external utility interfaces with >99% acceptance rate; (ii) high performance anomaly detection algorithms with >98% detection accuracy and <0.1% false alarm rate; and (iii) ultra-low computing delay <50 milliseconds. Additionally, our team developed algorithms to identify the vulnerable variables in electricity market operations and root cause analysis functions to identify major contributors to the price spikes. These ancillary modules are necessary when deploying WISP in real world industry environment. In Phase II, we have demonstrated the effectiveness of WISP software on realistic largescale power systems. We performed red team testing for the Phase I WISP software and identified software vulnerabilities and implemented corresponding mitigation solutions. We adapted the electricity market simulator for the Texas synthetic 2000-bus system and generated datasets for the false data injection attacks. We created database and visualization interfaces for the Texas system and the ISO New England system. We performed software optimization in terms of operation efficiency, computing speed and detection accuracy. Finally, we tested the software on the Texas system and the ISO New England system and evaluated the detection performance. Overall, we achieved above 89% detection rate, below 3% false alarm rate and below 37 seconds of end-to-end detection delay.

24 POWER TRANSMISSION AND DISTRIBUTION↗