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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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Citations
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DissertationDOI

Decarbonising the English residential sector: modelling policies, technologies and behaviour within a heterogeneous building stock

Scott Kelly
TL;DR: In this article, it is argued that the lack of progress stems from a poor understanding of the highly complex socioeconomic, socio-dynamic and technical physical systems that underpin energy use in dwellings.
Book ChapterDOI

Formulating National Action Plans for Energy Business Environment: An Intelligent Information System

TL;DR: The European Council of 8 / 9 March 2007 adopted an Action Plan for energy market 2007-2009 and committed the EU to achieving at least a 20% reduction in greenhouse gas emissions by 2020 compared to 1990 as discussed by the authors.
Journal ArticleDOI

Quantitative Analysis of Clean Transition Strategy of Traditional Coal-dominated GenCos

TL;DR: Wang et al. as discussed by the authors developed a computer simulation tool for the study of medium and long-term transition of GenCo to simulate the dynamic process of its clean transition, and quantitatively analyzed the dynamic performance such as business structure, profit, and carbon emission of a traditional GenCo according to its 2020 and 2030 clean development strategic targets.

Spatial modelling of renewable energy integrating remote sensing data

Shifeng Wang
TL;DR: ......................................................................................................................
Proceedings ArticleDOI

Neural Network Power Controller for P E M Fuel Cells Systems

TL;DR: This paper considers that any system of production is subjected permanently to load steps change variations, and considers a static production system including a PEMFC is subjected to variations of active and reactive power.
References
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Journal ArticleDOI

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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Journal ArticleDOI

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Journal ArticleDOI

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).
Journal ArticleDOI

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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