An energy management strategy for a wind power plant based on energy storage and wind power prediction

B. Yaǧcitekin; Ö Güler; Ü Çali

doi:10.1080/15567249.2011.601702

An energy management strategy for a wind power plant based on energy storage and wind power prediction

B. Yaǧcitekin^*, Ö Güler, Ü Çali

^*Corresponding author for this work

Energy Institute

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

Wind energy is the most common and fastest-growing application of renewable energy in power systems. Wind power generation is an intermittent and unpredictable energy, therefore power system operators have to face some difficulties such as stability, reliability, power quality, etc. Wind forecast and energy storage techniques are used for system reliability, stability, and increasing the penetration level of wind energy. The aim of this study to find a new usable solution to reduce the energy balance funding and increase the system reliability. According to the results of the proposed system, system reliability has obtained 83% and the wind penetration level has increased by 9%. Additionally, balance cost is reduced for the mentioned system.

Original language	English
Pages (from-to)	152-161
Number of pages	10
Journal	Energy Sources, Part B: Economics, Planning and Policy
Volume	7
Issue number	2
DOIs	https://doi.org/10.1080/15567249.2011.601702
Publication status	Published - 1 Jan 2012

Keywords

energy management
energy storage
reliability
wind power
wind power prediction

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1080/15567249.2011.601702

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abstract = "Wind energy is the most common and fastest-growing application of renewable energy in power systems. Wind power generation is an intermittent and unpredictable energy, therefore power system operators have to face some difficulties such as stability, reliability, power quality, etc. Wind forecast and energy storage techniques are used for system reliability, stability, and increasing the penetration level of wind energy. The aim of this study to find a new usable solution to reduce the energy balance funding and increase the system reliability. According to the results of the proposed system, system reliability has obtained 83% and the wind penetration level has increased by 9%. Additionally, balance cost is reduced for the mentioned system.",

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AU - Güler, Ö

AU - Çali, Ü

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N2 - Wind energy is the most common and fastest-growing application of renewable energy in power systems. Wind power generation is an intermittent and unpredictable energy, therefore power system operators have to face some difficulties such as stability, reliability, power quality, etc. Wind forecast and energy storage techniques are used for system reliability, stability, and increasing the penetration level of wind energy. The aim of this study to find a new usable solution to reduce the energy balance funding and increase the system reliability. According to the results of the proposed system, system reliability has obtained 83% and the wind penetration level has increased by 9%. Additionally, balance cost is reduced for the mentioned system.

AB - Wind energy is the most common and fastest-growing application of renewable energy in power systems. Wind power generation is an intermittent and unpredictable energy, therefore power system operators have to face some difficulties such as stability, reliability, power quality, etc. Wind forecast and energy storage techniques are used for system reliability, stability, and increasing the penetration level of wind energy. The aim of this study to find a new usable solution to reduce the energy balance funding and increase the system reliability. According to the results of the proposed system, system reliability has obtained 83% and the wind penetration level has increased by 9%. Additionally, balance cost is reduced for the mentioned system.

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KW - energy storage

KW - reliability

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KW - wind power prediction

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An energy management strategy for a wind power plant based on energy storage and wind power prediction

Abstract

Keywords

UN SDGs

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