Design of a hybrid wind power storage and generation system for a remote community

Devgan, S S; Walker, Jr, D R

Title: Design of a hybrid wind power storage and generation system for a remote community

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Abstract

There are thousands of small communities in various parts of the world, even in developed countries, that are too far away to be economically connected to an electric supply system. Clean water is essential for health and well being and electric energy is essential for economic development of the community. This paper describes the design of a {open_quotes}hybrid{close_quotes} Wind/Diesel power generation and storage system. and the electric power distribution system for a small rural community of 50 persons and live stock. The most cost effective and reliable system designed to satisfy reasonable growth over the next twenty-five years consists of three 10 kW wind turbines, a 30 kWh storage battery and a 17.5 kW backup diesel generator. This paper also describe efforts to train a neural network to predict wind power over the next time interval and few more time intervals. This is very essential for significant penetration of wind power systems.

Authors:

Devgan, S S; Walker, Jr, D R ^[1]

Tennessee State Univ., Nashville, TN (United States)

Publication Date:: Sun Dec 31 00:00:00 EST 1995

Research Org.:: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

OSTI Identifier:: 377059

Report Number(s):: PNL-SA-26375; CONF-9503142-
ON: DE96009360; CNN: Subcontract XAH-3-13203-01; TRN: 96:003982-0016

Resource Type:: Conference

Resource Relation:: Conference: Workshop on environmental and energy applications of neural networks conference, Richland, WA (United States), 30-31 Mar 1995; Other Information: PBD: [1995]; Related Information: Is Part Of Applications of neural networks in environmental and energy sciences and engineering. Proceedings of the 1995 workshop on environmental and energy applications of neural networks; Hashem, S.; Keller, P.E.; Kouzes, R.T.; Kangas, L.J.; PB: 193 p.

Country of Publication:: United States

Language:: English

Subject:: 17 WIND ENERGY; 99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; FORECASTING; NEURAL NETWORKS; WIND POWER PLANTS; DESIGN; WIND POWER; DIESEL ENGINES; HYBRID SYSTEMS

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                    Devgan, S S, and Walker, Jr, D R. Design of a hybrid wind power storage and generation system for a remote community.  United States: N. p., 1995. 
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                    Devgan, S S, & Walker, Jr, D R. Design of a hybrid wind power storage and generation system for a remote community.  United States.

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                    Devgan, S S, and Walker, Jr, D R. 1995.  
        "Design of a hybrid wind power storage and generation system for a remote community".  United States.  https://www.osti.gov/servlets/purl/377059.

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@article{osti_377059,

  title        = {Design of a hybrid wind power storage and generation system for a remote community},

  author       = {Devgan, S S and Walker, Jr, D R},

  abstractNote = {There are thousands of small communities in various parts of the world, even in developed countries, that are too far away to be economically connected to an electric supply system. Clean water is essential for health and well being and electric energy is essential for economic development of the community. This paper describes the design of a {open_quotes}hybrid{close_quotes} Wind/Diesel power generation and storage system. and the electric power distribution system for a small rural community of 50 persons and live stock. The most cost effective and reliable system designed to satisfy reasonable growth over the next twenty-five years consists of three 10 kW wind turbines, a 30 kWh storage battery and a 17.5 kW backup diesel generator. This paper also describe efforts to train a neural network to predict wind power over the next time interval and few more time intervals. This is very essential for significant penetration of wind power systems.},

  doi          = {},

  url          = {https://www.osti.gov/biblio/377059},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {Sun Dec 31 00:00:00 EST 1995},

  month        = {Sun Dec 31 00:00:00 EST 1995}

}

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