Exposure of Population and Energy-Related Base Facilities to Shaking Intensity Predicted for Nankai Megathrust Earthquakes

2017 ◽  
Vol 12 (1) ◽  
pp. 106-117
Author(s):  
Nobuoto Nojima ◽  
◽  
Hiroki Kato
Keyword(s):  
Power Generation ◽  
Subduction Zones ◽  
Nankai Trough ◽  
Strong Motion ◽  
Oil Refining ◽  
Population Exposure ◽  
Oil Refineries ◽  
Megathrust Earthquakes ◽  
Fundamental Information ◽  
And Storage

The exposure of the area and population as well as energy-related base facilities to the shaking intensity predicted for the anticipated megathrust earthquakes along the Nankai Trough subduction zones is evaluated. First, area and population exposure is evaluated considering six cases of shaking intensity distribution calculated using strong motion prediction methods and an attenuation formula. Next, the exposure of energy-related base facilities is evaluated for power generation plants, oil refineries, and LNG terminals in terms of their capacities for power generation, oil refining, and storage, respectively. Exposed capacities can be evaluated approximately for arbitrary levels of shaking intensity, providing fundamental information on the potential reduction of energy supply capabilities in an earthquake disaster.

scholarly journals Open-source multi-year power generation, consumption, and storage data in a microgrid

2021 ◽  
Vol 13 (2) ◽  
pp. 025301
Author(s):  
Sushil Silwal ◽  
Colton Mullican ◽  
Yi-An Chen ◽  
Avik Ghosh ◽  
John Dilliott ◽  
...  
Keyword(s):  
Power Generation ◽  
Open Source ◽  
And Storage

Proposed methodology for estimating the magnitude at which subduction megathrust ground motions and source dimensions exhibit a break in magnitude scaling: Example for 79 global subduction zones

2020 ◽  
Vol 36 (3) ◽  
pp. 1271-1297
Author(s):  
Kenneth W. Campbell
Keyword(s):  
Ground Motion ◽  
Subduction Zones ◽  
Ground Motions ◽  
Seismic Source ◽  
Scaling Relations ◽  
Megathrust Earthquakes ◽  
Source Dimensions ◽  
Magnitude Scaling ◽  
Aspect Ratios ◽  
Source Scaling

In this article, I propose a method for estimating the magnitude [Formula: see text] at which subduction megathrust earthquakes are expected to exhibit a break in magnitude scaling of both seismic source dimensions and earthquake ground motions. The methodology is demonstrated by applying it to 79 global subduction zones defined in the literature, including Cascadia. Breakpoint magnitude is estimated from seismogenic interface widths, empirical source scaling relations, and aspect ratios of physically unbounded earthquake ruptures and their uncertainties. The concept stems from the well-established observation that source-dimension and ground motion scaling decreases for shallow continental (primarily strike-slip) earthquakes when rupture exceeds the seismogenic width of the fault. Although a scaling break for megathrust earthquakes is difficult to observe empirically, all of the instrumentally recorded historical [Formula: see text] mega-earthquakes have occurred on subduction zones with [Formula: see text] (8.1–8.9), consistent with an observed break in source scaling relations derived from these same events. The breakpoint magnitudes derived in this study can be used to constrain the magnitude at which the scaling of ground motion is expected to decrease in subduction ground motion prediction equations.

ENERGY EFFICIENCY EVALUATION FOR A “GREEN” POWER GENERATION PROCESS WITH MINIMUM EFFORT ON CARBON DIOXIDE CAPTURE AND STORAGE

2012 ◽  
Vol 199 (12) ◽  
pp. 1642-1651 ◽  
Author(s):  
Suttichai Assabumrungrat ◽  
Janewit Phromprasit ◽  
Siriporn Boonkrue ◽  
Worapon Kiatkittipong ◽  
Wisitsree Wiyaratn ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Power Generation ◽  
Energy Efficiency ◽  
Carbon Dioxide Capture ◽  
Efficiency Evaluation ◽  
Generation Process ◽  
Green Power ◽  
Energy Efficiency Evaluation ◽  
And Storage

scholarly journals Solar Tower Power Plants of Molten Salt External Receivers in Algeria: Analysis of Direct Normal Irradiation on Performance

2018 ◽  
Vol 8 (8) ◽  
pp. 1221 ◽  
Author(s):  
Abdelkader Rouibah ◽  
Djamel Benazzouz ◽  
Rahmani Kouider ◽  
Awf Al-Kassir ◽  
Justo García-Sanz-Calcedo ◽  
...  
Keyword(s):  
Power Generation ◽  
Energy Storage ◽  
Thermal Energy ◽  
Greenhouse Effect ◽  
Energy Production ◽  
Power Plants ◽  
Storage Capacity ◽  
Real Data ◽  
Multiple Power ◽  
And Storage

The increase of solar energy production has become a solution to meet the demand of electricity and reduce the greenhouse effect worldwide. This paper aims to determine the performance and viability of direct normal irradiation of three solar tower power plants in Algeria, to be installed in the highlands and the Sahara (Béchar, El Oued, and Djelfa regions). The performance of the plants was obtained through a system advisor model simulator. It used real data gathered from appropriate meteorological files. A relationship between the solar multiple (SM), power generation, and thermal energy storage (TES) hours was observed. The results showed that the optimal heliostat field corresponds to 1.8 SM and 2 TES hours in Béchar, 1.2 SM and 2 TES hours for El Oued, and 1.5 SM and 4 TES hours for Djelfa. This study shows that there is an interesting relationship between the solar multiple, power generation, and storage capacity.

scholarly journals Prediction of Wave Power Generation Using a Convolutional Neural Network with Multiple Inputs

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2097 ◽  
Author(s):  
Chenhua Ni ◽  
Xiandong Ma
Keyword(s):  
Neural Network ◽  
Power Generation ◽  
Convolutional Neural Network ◽  
Wave Height ◽  
Regression Models ◽  
Cost Effective ◽  
Wave Power ◽  
Marine Energy ◽  
Artificial Network ◽  
And Storage

Successful development of a marine wave energy converter (WEC) relies strongly on the development of the power generation device, which needs to be efficient and cost-effective. An innovative multi-input approach based on the Convolutional Neural Network (CNN) is investigated to predict the power generation of a WEC system using a double-buoy oscillating body device (OBD). The results from the experimental data show that the proposed multi-input CNN performs much better at predicting results compared with the conventional artificial network and regression models. Through the power generation analysis of this double-buoy OBD, it shows that the power output has a positive correlation with the wave height when it is higher than 0.2 m, which becomes even stronger if the wave height is higher than 0.6 m. Furthermore, the proposed approach associated with the CNN algorithm in this study can potentially detect the changes that could be due to presence of anomalies and therefore be used for condition monitoring and fault diagnosis of marine energy converters. The results are also able to facilitate controlling of the electricity balance among energy conversion, wave power produced and storage.

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