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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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TL;DR: In this paper, a review of the different computer tools that can be used to analyse the integration of renewable energy is presented, and the results in this paper provide the information necessary to identify a suitable energy tool for analysing the integration into various energy-systems under different objectives.
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Optimization methods applied to renewable and sustainable energy: A review

TL;DR: A review of the current state of the art in computational optimization methods applied to renewable and sustainable energy can be found in this article, which offers a clear vision of the latest research advances in this field.
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A survey of data envelopment analysis in energy and environmental studies

TL;DR: A literature survey on the application of data envelopment analysis (DEA) to E&E studies is presented and an introduction to the most widely used DEA techniques is introduced.
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Energy systems modeling for twenty-first century energy challenges

TL;DR: In this article, the authors look at models relevant to national and international energy policy, grouping them into four categories: energy systems optimization models, energy systems simulation models, power systems and electricity market models, and qualitative and mixed-methods scenarios.
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Artificial intelligence techniques for photovoltaic applications: A review

TL;DR: The paper outlines an understanding of how AI systems operate by way of presenting a number of problems in photovoltaic systems application, mainly because of their symbolic reasoning, flexibility and explanation capabilities.
References
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Journal ArticleDOI

1.4. Credibility of models

TL;DR: This paper presented a study on model credibility and found that the model with the smallest prediction error was a very simple model: a linear extrapolation of the trend in the previous year, in other words the hypothesis that the GNP growth rate during a year is the same as the rate during the previous one proved to be an accurate forecast.
Journal ArticleDOI

Energy planning in urban historical centres A methodological approach with a case-study

TL;DR: In this paper, the authors present a methodology for energy planning in urban historical centres, using the historical centre of Coimbra, an old Portuguese city, for illustrating purposes, and present the formulation of the mid-term energy plan for the historical center of Coimra.
Journal ArticleDOI

5.1. Pay-off matrix technique

TL;DR: An approach to the solution of decision problems that is based on the computation and analysis of the pay-off matrix is presented and special Wald, Laplace etc. criteria, as well as subjective probability estimations are applied.
Journal ArticleDOI

2.6. Demand forecasting methodologies: An overview for electric utilities

TL;DR: The current trend in utility forecasting is toward strategic forecasting models as discussed by the authors, which combine elements of the econometric approach with the technology detail found in the end-use/process models.
Journal ArticleDOI

2.3 The hybrid approach to demand modeling

TL;DR: In this article, an approach combining the economic theory of production with engineering process data is presented for developing energy demand models. But it is not shown how to use the Logit function to specify a fuel share model and how the CES function can be used to specify an energy conservation model.
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