A Fuzzy Logic Approach to Evaluate Transformer Fleet Risk From Geomagnetic Storms

2016 ◽  
Author(s):  
Sujit Purushothaman
Keyword(s):  
Fuzzy Logic ◽  
Geomagnetic Storm ◽  
Geomagnetic Storms ◽  
Geomagnetic Latitude ◽  
Geomagnetic Disturbance ◽  
Specific Factor ◽  
Storm Event ◽  
Geoelectric Field ◽  
Fuzzy Logic Approach ◽  
Specific Factors

This paper presents a simple approach to evaluate risk to transformer units from geomagnetic storms. A simple fuzzy logic based approach was used to develop the model which is capable of categorizing transformers in a fleet into three risk categories, i.e., high, medium and low. This model may be used as a first screening step to evaluate a fleet of transformers without conducting time consuming simulations and studies. Critical factors that affect geomagnetically induced current (GIC) flow are used as input parameters to the model. These factors include location-specific, equipment-specific and geomagnetic storm event-specific factors. Location-specific factors include geomagnetic latitude of the location, earth conductivity structure at location and distance of location from coast. Equipment-specific factors include transformer rating and age. The storm event-specific factor of geoelectric field strength was used which is an indication of the return period of the geomagnetic disturbance event. The paper describes the implementation of this model to evaluate fleet risk for a 1 in 100 year event and the Carrington event (largest recorded geomagnetic storm in history). The fuzzy logic membership functions for the inputs are described in detail and the performance of the fuzzy logic model is evaluated.

The geoelectric structure of the Romanian underground and its contribution to the geoelectric hazard during the solar cycle 23

2020 ◽  
Author(s):  
Venera Dobrica ◽  
Dumitru Stanica ◽  
Crisan Demetrescu ◽  
Cristiana Stefan
Keyword(s):  
Solar Cycle ◽  
Geomagnetic Storms ◽  
Geomagnetic Disturbance ◽  
Geoelectric Field ◽  
Geomagnetically Induced Currents ◽  
Geomagnetic Variations ◽  
European Continent ◽  
Field Recordings ◽  
Weather Events ◽  
Solar Cycle 23

<p>A recent model of the Romanian lithosphere electric properties, based on magnetotelluric transects carried out in the past 50 years across main tectonic units, is used to assess the geoelectric hazard represented by geomagnetically induced currents (GICs) for certain space weather events. Based on the geomagnetic field recordings and on information regarding the underground electric conductivity, the surface geoelectric field associated to geomagnetic variations during several large geomagnetic storms of the solar cycle 23 (1986-1996) is determined using the plane wave approximation for the depth propagation of the geomagnetic disturbance. A comparison to the territory of the European continent is done as well.   </p>

scholarly journals A Qualitative Study of the Ionospheric Weak Response to Super Geomagnetic Storms

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 635
Author(s):  
Haimeng Li ◽  
Zhou Chen ◽  
Lianqi Xie ◽  
Fan Li
Keyword(s):  
Geomagnetic Storm ◽  
Geomagnetic Storms ◽  
Processing Method ◽  
Statistical Characteristics ◽  
High Solar Activity ◽  
Storm Event ◽  
Time Interval ◽  
Weak Response ◽  
Ionospheric Response ◽  
Middle Latitudes

The ionospheric response to a geomagnetic storm is a geophysical process. Although strong geomagnetic storms input more energy into the Earth’s upper atmosphere, the ionospheric response often does not reflect the same level of variation as the geomagnetic storm, and the response may be weak during a very strong storm. However, the estimated ionospheric response to geomagnetic activity also varies with extraction method. Here, two different methods—the spectral whitening method (SWM) and the monthly median method (MMM)—are used to verify whether the apparent weak ionospheric response is an artifact of the processing method. The weak ionospheric response is found with both methods, which suggests it is a real ionospheric phenomenon. The statistical characteristics of the regional and global ionospheric weak response to a super geomagnetic storm (SGS) and to an SGS with a preceding storm event (SGS-PRE) are investigated and compared. The results show that the regional ionospheric weak response to an SGS is more prevalent at middle latitudes than those at low and high latitudes. The global ionospheric weak response occurs more frequently under high solar activity and has a strong correlation with SGS-PRE, which suggests that the effect of a storm on the ionosphere can be influenced by its preconditioning, especially when there is an earlier storm and the time interval between the two storms is short. In fact, an ionospheric long-lasting disturbance may be an important reason for the ionospheric weak response caused by the SGS-PRE.

scholarly journals ANALISIS RESPON MEDAN GEOMAGNET ANTARA STASIUN DI EKUATOR MAGNET DAN STASIUN BIAK SAAT BADAI GEOMAGNET PADA MERIDIAN MAGNET 210⁰ MM

2016 ◽  
Vol 13 (2) ◽  
pp. 63
Author(s):  
Anwar Santoso
Keyword(s):  
Response Time ◽  
Geomagnetic Storm ◽  
Geomagnetic Field ◽  
Field Data ◽  
Geomagnetic Storms ◽  
Geomagnetic Disturbance ◽  
Magnetic Equator ◽  
High Latitudes ◽  
Geomagnetic Equator ◽  
Occurrence Probability

Geomagnetic storm is a geomagnetic disturbance that occurs globally. Until now believed that the greatest impact of geomagnetic storms occurred in the high latitudes and decreases with decreasing latitude to the equator. However, based on the data component of the geomagnetic field H obtained CPMN other phenomena, that is H minimum of Onagawa station (31,15o LU; 212,63o BT magnetic coordinates) is smaller than the H minimum at Biak station (9,73o latitude; 207,39o BT magnetic coordinates) during geomagnetic storms on July 15, 2000. This reality is different from what was believed to be on top. To ensure this, then done the analysis of the geomagnetic field H component response based on the latitude using the geomagnetic field data from Biak station and stations around 210o MM for the whole event a strong geomagnetic storms (Dst <-100 nT) during 1995-2001. Results of the analysis showed that the response time of geomagnetic field geomagnetic storm in Biak is greater than at the magnetic equator (YAP) with an difference average of H is 59,27 nT. EEJ and CEJ pattern in the EEJ region (10o S to 10o N magnetic coordinate) shown could effected to the response of geomagnetic geomagnetic. The most important to note that if the geomagnetic response in Indonesia higher than in the geomagnetic equator (YAP) then the occurrence probability of GIC in Indonesia is higher.  AbstrakBadai geomagnet merupakan gangguan geomagnet yang terjadi secara global. Sampai saat ini dipercaya bahwa dampak terbesar badai geomagnet terjadi di lintang tinggi dan semakin menurun dengan menurunnya lintang sampai di ekuator. Namun, berdasarkan olah data komponen H medan geomagnet dari CPMN diperoleh fenomena lain yaitu H minimum dari stasiun Onagawa (31,15⁰ LU; 212,63⁰ BT koordinat magnet) lebih kecil dari H minimum Balai Penjejakan dan Kendali Wahana Antariksa (BPKWA) Biak (9,73⁰ LS; 207,39⁰ BT koordinat magnet) saat badai geomagnet 15 Juli 2000. Kenyataan ini berbeda dari apa yang telah dipercayai di atas. Untuk memastikan hal ini maka dilakukan analisis respon komponen H medan geomagnet berdasarkan lintang menggunakan data komponen H medan geomagnet dari BPKWA Biak dan stasiun di sekitar 210⁰ MM untuk seluruh kejadian badai geomagnet kuat (Dst < -100 nT) selama 1995-2001. Hasil analisis diperoleh bahwa respon medan geomagnet saat badai geomagnet di Biak lebih besar dari pada di ekuator magnet (YAP) dengan rata-rata selisih ∆H-nya 59,27 nT. EEJ dan CEJ di daerah EEJ (10⁰ LU sampai 10⁰ LS magnet) terbukti mempengaruhi respon geomagnet. Hal terpenting yang perlu diperhatikan dari hasil ini adalah bahwa jika respon geomagnet di Indonesia lebih tinggi dibandingkan di daerah ekuator geomagnet (YAP) maka potensi kemunculan GIC juga lebih besar terjadi di Indonesia. 

Computing the Probability of Target Detection in Dyanmic Visual Scenes Containing Clutter Using Fuzzy Logic Approach

1998 ◽  
Author(s):  
Thomas Meitzler ◽  
Regina Kistner ◽  
Bill Pibil ◽  
Euijung Sohn ◽  
Darryl Bryk ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Target Detection ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Visual Scenes

Fuzzy logic approach for knowledge modeling in an Ontology: A review

2020 ◽  
Author(s):  
Abdoul Azize Kindo ◽  
Guidedi Kaladzavi ◽  
Sadouanouan Malo ◽  
Gaoussou Camara ◽  
Theodore Marie Yves Tapsoba ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Knowledge Modeling ◽  
Fuzzy Logic Approach ◽  
Logic Approach
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