Optimization in computerized energy modelling for Tanzania

Luhanga, Matthew L.; Mwandosya, M. J.; Luteganya, P.R.

doi:10.1016/0360-5442(93)90089-v

Cited by 16 publications

(10 citation statements)

References 1 publication

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“…Focus of these studies were on management of electricity demand load, minimization of power outages, efficient use of scarce electricity production, minimizing the impacts of power production on the environment, finding optimal production timing to minimize cost of production, and optimal sale price of electricity to consumers. Few papers had also focused on building models for long-term developments and projections of future requirements of the energy (Suganthi and Jagadeesan, 1992;Luhanga et al, 1993;Jebaraja and Iniyanb, 2006;Zhang et al, 2012;Kishore and Singal, 2014;Mondal et al, 2014). Focus of few studies were also on minimization of investment cost of new projects and optimizing the projects portfolio with new projects underway (Sterna, 1977;Kuru, 1988;Omu et al, 2013).…”

Section: Power Supply Chain Of Pakistanmentioning

confidence: 98%

A short-run solution to the power crisis of Pakistan

Imran¹,

Amir

2015

Energy Policy

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Section: Power Supply Chain Of Pakistanmentioning

confidence: 98%

A short-run solution to the power crisis of Pakistan

Imran¹,

Amir

2015

Energy Policy

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“…The maximization of the marginal cost based on environmental constraints was the objective of the model. An overview of energy planning research was presented on the implementation of the long-range energy alternatives planning model (LEAP) model for Tanzania through the use of optimization models in combination with a forecasting model [5]. An overview of energy planning research was presented on the implementation of the long-range energy alternatives planning model (LEAP) model for Tanzania through the use of optimization models in combination with a forecasting model [5].…”

Section: Linear Programming Modelsmentioning

confidence: 99%

“…A few energy optimization models are also reviewed and presented. model for Tanzania through the use of optimization models in combination with a forecasting model [5]. A linear optimization model and a multiattribute value model were introduced [6] to estimate the long-term energy, economy and environment interactions for Turkey.…”

Section: Introductionmentioning

confidence: 99%

An optimal electricity allocation model for sustainable resource use in India

Jebaraj¹,

Iniyan

Goić

2012

Int. J. Energy Res.

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SUMMARY Energy demand is increasing rapidly because of developments in the agricultural, industrial, commercial and transportation sectors. Improved lifestyle and population rise are other reasons for the increase in energy demand. The development of an electricity allocation model will help in the proper allocation of the energy sources to meet the future electricity demand in India. In this paper, an attempt has been made to develop a fuzzy‐based linear programming, optimal electricity allocation model (OEAM) that minimizes the cost and determines the optimum allocation of different energy sources to the centralized and decentralized power generation in India. The potential of energy sources, energy demand, efficiency of the energy systems, emission released by the energy systems and carbon tax for the emissions released by each system are the main factors that influence the pattern of electricity distribution and are used as constraints in the model. Executing this model results in an optimal electricity distribution pattern. The results indicate that the commercial energy sources such as coal, nuclear and hydro would meet nearly 68% of total electricity demand and that the remaining 32% of the electricity demand will be met by the renewable energy sources, namely, wind, biomass, biogas, solid waste, cogeneration and mini hydel for the year 2020. Various scenarios are also developed by varying the demand, potential, emission and carbon tax. This study will help in the formation of strategies for effective utilization of energy sources in India. Copyright © 2012 John Wiley & Sons, Ltd.

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“…For a long time, many studies have been published on energy consumption models that use regression, time-series, linear programming techniques, and the quantitative method, etc. (Assimakopoulos, 1992;Tamimi and Kodah, 1992;Rijal et al, 1990;Zhen, 1993;Hirst et al, 1977;Luhanga et al, 1993;Reddy and Claridge, 1994;Li et al, 2009;Al-Garni et al, 1994;Sun, 1998;Tso and Yau, 2003;Chen et al, 2008), but few articles covered the energy consumption prediction, especially for developing countries (Gonzales Chavez et al, 1999;Saab et al, 2001). Therefore, objectively and correctly forecasting the energy consumption volume definitely has important theoretical and practical significance for China to properly lay out the energy consumption structure, coordinate the relationship between energy consumption and economic development, and establish pertinent countermeasures to fight against energy-related pollution.…”

Section: Introductionmentioning

confidence: 96%

Forecasting the Energy Consumption of China by the Grey Prediction Model

Feng

Song

et al. 2012

Energy Sources, Part B: Economics, Planning, and Policy

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Energy consumption has important significance for every country in the world. To successfully predict the future energy consumption by a mathematical method is very important for relevant scientific study. In this article, China, the rising power of the world and one of the biggest energy consumption countries, is significantly taken as the research target for grey theory prediction. According to the actual energy consumption statistics of China from 1998 to 2006, this article established the grey model GM(1,1) for the total energy, coal energy and clean energy consumption of China, respectively, with a corresponding precision check-up thereafter. The results show the three prediction models are all in the first precision level, which is suitable for simulating and forecasting the original data sequences of the energy consumption characterized by grey type. By comparing the results of the three models, all three energy consumption types are in the trending upward, but clean energy consumption is especially getting the upper hand.

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Optimization in computerized energy modelling for Tanzania

Cited by 16 publications

References 1 publication

A short-run solution to the power crisis of Pakistan

A short-run solution to the power crisis of Pakistan

An optimal electricity allocation model for sustainable resource use in India

Forecasting the Energy Consumption of China by the Grey Prediction Model

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