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Journal ArticleDOI

A review of energy models

S. Jebaraj, +1 more
- 01 Aug 2006 - 
- Vol. 10, Iss: 4, pp 281-311
TLDR
In this paper, a review paper on energy modeling will help the energy planners, researchers and policy makers widely, and an attempt has been made to understand and review the various emerging issues related to the energy modeling.
Abstract
Energy is a vital input for social and economic development of any nation. With increasing agricultural and industrial activities in the country, the demand for energy is also increasing. Formulation of an energy model will help in the proper allocation of widely available renewable energy sources such as solar, wind, bioenergy and small hydropower in meeting the future energy demand in India. During the last decade several new concepts of energy planning and management such as decentralized planning, energy conservation through improved technologies, waste recycling, integrated energy planning, introduction of renewable energy sources and energy forecasting have emerged. In this paper an attempt has been made to understand and review the various emerging issues related to the energy modeling. The different types of models such as energy planning models, energy supply–demand models, forecasting models, renewable energy models, emission reduction models, optimization models have been reviewed and presented. Also, models based on neural network and fuzzy theory have been reviewed and discussed. The review paper on energy modeling will help the energy planners, researchers and policy makers widely.

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References
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Applications of artificial neural-networks for energy systems

TL;DR: In this paper, the authors present various applications of neural networks in energy problems in a thematic rather than a chronological or any other way, including modeling and design of a solar steam generating plant, estimation of a parabolic-trough collector's intercept factor and local concentration ratio, and performance prediction of solar water-heating systems.
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Artificial neural networks for the prediction of the energy consumption of a passive solar building

TL;DR: In this paper, a multilayer recurrent architecture using the standard back-propagation learning algorithm has been applied to predict the energy consumption of a passive solar building for two seasons: winter and summer.
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Decision-making in energy planning. Application of the Electre method at regional level for the diffusion of renewable energy technology

TL;DR: The authors show an application of the multicriteria decision-making methodology used to assess an action plan for the diffusion of renewable energy technologies at regional scale, carried out for Sardinia.
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Solar radiation model

TL;DR: In this article, the authors used the Angstrom-Prescott equation to predict the average daily global radiation with hours of sunshine for Hong Kong (22.3°N latitude, 114. 3°E longitude).
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A comparison of various forecasting techniques applied to mean hourly wind speed time series

TL;DR: A comparison of various forecasting approaches, using time series analysis, on mean hourly wind speed data, including the traditional linear (ARMA) models and the commonly used feed forward and recurrent neural networks is presented.
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