ECONOMIC ESTIMATION OF RESERVE REQUIREMENTS OF WIND FARMS WITH USING NEURAL NETWORKS TO PREDICT WIND SPEED

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KHOSRAVI SAM; EMARATI MOHAMMAD REZA; FADAEI NEJAD ROOH ALAH; KEI NIA FARSHID

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Journal: JOURNAL OF ENERGY MANAGEMENT Year:2017 | Volume:7 | Issue:1 Page(s): 2-13

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Title

ECONOMIC ESTIMATION OF RESERVE REQUIREMENTS OF WIND FARMS WITH USING NEURAL NETWORKS TO PREDICT WIND SPEED

Author(s)

KHOSRAVI SAM | EMARATI MOHAMMAD REZA | FADAEI NEJAD ROOH ALAH | KEI NIA FARSHID | Issue Writer Certificate

Keywords

WIND SPEEDS PREDICTIONSQ1

RESERVEQ1

UNCERTAINTY OF WIND ENERGYQ1

WIND FARMQ2

COST OF PROVISION OF RESERVESQ1

Abstract

Nowadays, increasing the renewable energy applications in power system, especially wind power, has caused higher imbalance probability between generation and demand. Therefore, an accurate estimateion of WIND FARM RESERVE requirements and the RESERVE cost reduction in power systems with high wind power penetration is very important. In this paper, the RESERVE requirements of a WIND FARM is estimated by using a probabilistic approach. RESERVE requirements of WIND FARM are divided into two categories provided by fast-responsive and slow-responsive resources. Indeed the purpose of this division is decreasing the cost of RESERVE provision by reducing the use of fast-responsive resources that is more expensive in comparison with slow-responsive resources. Wind speed prediction has been done by the ANN (Artificial Neural Network) and ARIMA (Autoregressive Integrated Moving Average), with using real measured data on a WIND FARM in the state of Pennsylvania. In this study, the RESERVE requirements of WIND FARMs and the cost of provision of RESERVE requirements will be reduced by using artificial neural networks that is a method based on artificial intelligence and is more accurate than statistical and traditional method ARIMA.

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APA: Copy

KHOSRAVI, SAM, EMARATI, MOHAMMAD REZA, FADAEI NEJAD, ROOH ALAH, & KEI NIA, FARSHID. (2017). ECONOMIC ESTIMATION OF RESERVE REQUIREMENTS OF WIND FARMS WITH USING NEURAL NETWORKS TO PREDICT WIND SPEED. JOURNAL OF ENERGY MANAGEMENT, 7(1 ), 2-13. SID. https://sid.ir/paper/223815/en

Vancouver: Copy

KHOSRAVI SAM, EMARATI MOHAMMAD REZA, FADAEI NEJAD ROOH ALAH, KEI NIA FARSHID. ECONOMIC ESTIMATION OF RESERVE REQUIREMENTS OF WIND FARMS WITH USING NEURAL NETWORKS TO PREDICT WIND SPEED. JOURNAL OF ENERGY MANAGEMENT[Internet]. 2017;7(1 ):2-13. Available from: https://sid.ir/paper/223815/en

IEEE: Copy

SAM KHOSRAVI, MOHAMMAD REZA EMARATI, ROOH ALAH FADAEI NEJAD, and FARSHID KEI NIA, “ECONOMIC ESTIMATION OF RESERVE REQUIREMENTS OF WIND FARMS WITH USING NEURAL NETWORKS TO PREDICT WIND SPEED,” JOURNAL OF ENERGY MANAGEMENT, vol. 7, no. 1 , pp. 2–13, 2017, [Online]. Available: https://sid.ir/paper/223815/en

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