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Nasiri, M.
- Robust Control of PMSG-based Wind Turbine under Grid Fault Conditions
Abstract Views :228 |
PDF Views:0
Authors
Affiliations
1 Department of Electrical Engineering, Amirkabir University of Technology, Tehran, 15875–4413, IR
1 Department of Electrical Engineering, Amirkabir University of Technology, Tehran, 15875–4413, IR
Source
Indian Journal of Science and Technology, Vol 8, No 13 (2015), Pagination:Abstract
This paper presents modeling of a direct-driven permanent magnet synchronous generator – based wind turbine and proposes a new controller for Back-To-Back (BTB) converters to enhance Low Voltage Ride Through (LVRT). The LVRT is implemented without any additional devices during grid fault conditions. In this structure, the Proportional-Integral (PI) controllers of Machine Side Converter (MSC) and Grid Side Converter (GSC) are replaced by Sliding Mode (SM) controllers. The MSC controls dc-link voltage and the GSC controls Maximum Power Point Tracking (MPPT) by regulating turbine-generator speed. This control strategy implements different grid code requirements such as Danish grid code. The proposed SM controller in comparison with the PI controller can eliminate dc-link voltage oscillations and reduce the converter voltage and current stresses. Simulation results verify the robustness and effectiveness of the proposed strategy. Hence, by using SM controller, there is no need for additional equipments to enhance LVRT in PMSG-based wind turbines and cost and complexity are significantly reduced.Keywords
DC-Link Voltage, Low Voltage Ride-Through (LVRT), PMSG, Sliding Mode Control, Wind EnergyFull Text
- Survey of the Euro Currency Fluctuation by Using Data Mining
Abstract Views :176 |
PDF Views:124
Authors
Affiliations
1 Department of Computer Engineering, Iran University of Science and Technology, Narmak, 16846-13114, Tehran, IR
1 Department of Computer Engineering, Iran University of Science and Technology, Narmak, 16846-13114, Tehran, IR
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 5, No 4 (2013), Pagination: 121-129Abstract
Data mining or Knowledge Discovery in Databases (KDD) is a new field in information technology that emerged because of progress in creation and maintenance of large databases by combining statistical and artificial intelligence methods with database management. Data mining is used to recognize hidden patterns and provide relevant information for decision making on complex problems where conventional methods are inecient or too slow. Data mining can be used as a powerful tool to predict future trends and behaviors, and this prediction allows making proactive, knowledge-driven decisions in businesses. Since the automated prospective analyses offered by data mining move beyond the analyses of past events provided by retrospective tools, it can answer the business questions which are traditionally time consuming to resolve. Based on this great advantage, it provides more interest for the government, industry and commerce. In this paper we have used this tool to investigate the Euro currency fluctuation. For this investigation, we have three different algorithms: K, IBK and MLP and we have extracted Euro currency volatility by using the same criteria for all used algorithms. The used dataset has 21,084 records and is collected from daily price fluctuations in the Euro currency in the period of10/2006 to 04/2010.Keywords
Euro Currency Fluctuation, Data Mining, Stock Market, Knowledge Discovery in Databases.Full Text