Pregled bibliografske jedinice broj: 1074387
Smart Grid Monitoring by Wireless Sensors Using Binary Logistic Regression
Smart Grid Monitoring by Wireless Sensors Using Binary Logistic Regression // Energies, 13 (2020), 15; 1-12 doi:10.3390/en13153974 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1074387 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Smart Grid Monitoring by Wireless Sensors Using Binary
Logistic Regression
Autori
Hariprasath, Manoharan ; Yuvaraja, Teekaraman ; Irina Kirpichnikova ; Ramya, Kuppusamy ; Nikolovski, Srete ; Hamid, Reza, Baghaee ;
Izvornik
Energies (1996-1073) 13
(2020), 15;
1-12
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
smart grids (intelligent networks) ; phasor machine learning ; binary logistic regression ; wireless network ; Sensors
Sažetak
This article focuses on addressing the data aggregation faults caused by the Phasor Measuring Unit (PMU) by installing Wireless Sensor Networks (WSN) in the grid. All data that is monitored by PMU should be sent to the base station for further action. But the data that is sent from PMU does not reach the main server properly in many situations. To avoid this situation, a sensor-based technology has been introduced in the proposed method for sensing the values that are monitored by PMU. Also, the basic parameters that are necessary for determining optimal solutions like energy consumption, distance and cost have been calculated for wireless sensors, whereas, for PMU optimal placements with cost analysis have been restrained. For analyzing and improving the accuracy of the proposed method, an effective Binary Logistic Regression (BLR) algorithm has been integrated with an objective function. The sensor will report all measured PMU values to an Online Monitoring System (OMS). To examine the effectiveness of the proposed method, the examined values are visualized in MATLAB and results prove that the proposed method using BLR is more effective than existing methods in terms of all parametric values and the much improved results have been obtained at a rate of 81.2%
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek
Profili:
Srete Nikolovski
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus