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The paper is devoted to energy demand forecasting in Uzbekistan. Studies show that in spite of the abundant reserves of hydrocarbons, low energy efficiency can have an adverse impact on energy security in Uzbekistan in the future. Oil and gas are the main primary energy source and they ensure energy security of Uzbekistan. Energy demand forecasting is essential in order to develop an effective energy policy. Such forecast can be useful to plan oil and gas production volumes, to identify priorities for the industrial modernization and to create favorable conditions for sustainable economic development in the future. Author proposes model based on translog function for developing medium-and long-term development programs in energy sector and the modernization and technological re-equipment of industry.
2020
The article considers the possibility of using the least squares method (LSM) for long-term forecasting of the parameters of the regime of electric power systems. There is presented least squares method for predicting the parameters of the regime of electric power systems. It is shown that, based on the least-squares method, it is possible to obtain prognostic equations, as well as coefficients of approximating functions necessary for the formation of these equations. The results of the analysis of the comparison of linear, hyperbolic, logarithmic, exponential and quadratic functions on the use of LSMs to predict specific fuel consumption are presented. The criterion of the least squares method, which is according for using the statistical data of the control sample in the obtained prognostic functions, the standard deviations are found.
The main purpose of the present study is to provide a proper model for forecasting residential as well as commercial sectors in Iran that can be used as a tool of scenario analysis to predict the emerging energy demand in future. In this way, this paper proposes a systematically developed model based on a previously performed exogeneity investigation of various quantified variables. A certain model among a collection of 13824 models with different inputs is chosen as the most appropriate model. Structure of all competing models is established according to logical conjunctive and disjunctive relationships between variables. Different combinations of the exogenous variables generate these models. An automated fuzzy decision-making (FDM) process determines the winner model, which is a log-linear model, among the other remaining models. Furthermore, the energy demand of residential and commercial sector in Iran for the period of 2011 to 2020 is estimated.
Energies, 2016
Policymakers in developing and transitional economies require sound models to: (i) understand the drivers of rapidly growing energy consumption and (ii) produce forecasts of future energy demand. This paper attempts to model electricity demand in Azerbaijan and provide future forecast scenarios-as far as we are aware this is the first such attempt for Azerbaijan using a comprehensive modelling framework. Electricity consumption increased and decreased considerably in Azerbaijan from 1995 to 2013 (the period used for the empirical analysis)-it increased on average by about 4% per annum from 1995 to 2006 but decreased by about 4 1 2 % per annum from 2006 to 2010 and increased thereafter. It is therefore vital that Azerbaijani planners and policymakers understand what drives electricity demand and be able to forecast how it will grow in order to plan for future power production. However, modeling electricity demand for such a country has many challenges. Azerbaijan is rich in energy resources, consequently GDP is heavily influenced by oil prices; hence, real non-oil GDP is employed as the activity driver in this research (unlike almost all previous aggregate energy demand studies). Moreover, electricity prices are administered rather than market driven. Therefore, different cointegration and error correction techniques are employed to estimate a number of per capita electricity demand models for Azerbaijan, which are used to produce forecast scenarios for up to 2025. The resulting estimated models (in terms of coefficients, etc.) and forecasts of electricity demand for Azerbaijan in 2025 prove to be very similar; with the Business as Usual forecast ranging from about of 19 1 2 to 21 TWh.
Energy Efficiency, 2015
The main purpose of the present study is to develop a simple yet proper top-down model for forecasting the energy demand of the residential and commercial sectors in Iran. This model can be used as a tool of scenario analysis to predict the emerging energy demand in future. The proposed model would be systematically developed and selected based on various quantified exogenous variables. For this purpose, a certain model out of a collection of 41,472 parallel models with different inputs and dynamics is chosen as the most appropriate model. According to the logical conjunctive relationships between the variables, the structure of all competing models is established to log-linear. Different possible combinations of various measures for the exogenous variables generate parallel models. Then, an automated fuzzy decision-making (FDM) process determines the best model. Finally, defining several scenarios, the energy demand of the residential and commercial sectors in Iran for the period of 2013 to 2021 is forecasted. The results showed that despite of de-subsidization, which is included by a dummy variable, the energy demand will grow by an average rate of about 3 % annually.
Purpose -Iran as an energy-rich country faces many challenges in the optimal utilization of its vast resources. High rates of population and economic growth, a generous subsidies program, and poor resource management have contributed to rapidly growing energy consumption and high energy intensity over the past decades. The continuing trend of rising energy consumption will bring about new challenges as it will shrink oil export revenues, restraining economic activities. This calls for a study to explore alternative scenarios for the utilization of energy resources in Iran. The purpose of this paper is to model demand for energy in Iran and develop two business-as-usual and efficiency scenarios for the period 2005-2030. Design/methodology/approach -The authors use a techno-economic or end-use approach to model energy demand in Iran for different types of energy uses and energy carriers in all sectors of the economy and forecast it under two scenarios: business as usual (BAU) and efficiency. Findings -Iran has a huge potential for energy savings. Specifically, under the efficiency scenario, Iran will be able to reduce its energy consumption 40 percent by 2030.The energy intensity can also be reduced by about 60 percent to a level lower than the world average today. Originality/value -The paper presents a comprehensive study that models the Iranian energy demand in different sectors of the economy, using data at different aggregation levels and a techno-economic end-use approach to illuminate the future of energy demand under alternative scenarios.
Balance between electricity production and consumption plays an important role for future strategic plan of a region. From this point of view, the concerning region should be aware of and forecast future production-consumption cycle and balance them. In this research, Northern-Iraq situation is taken into consideration to elaborate electricity energy consumption and compare with the generation. Competitive models such as Winters Additive and Box-Jenkins are considered to choose best model for the elaboration.
Energy Policy, 2006
A comprehensive analysis of the possible future long-term development of Syrian energy and electricity demand covering the period 1999-2030 is presented. The analysis was conducted using the IAEA's model MAED, which relies upon the end-use approach. This model has been validated during the last two decades through the successful application in many developing countries, even those having partial market economy and energy subsidy.
2013
The aim of this paper is modeling and forecasting supply of new energies in Netherlands by time series approach. We have used the methodology of Box-Jenkins for modeling the series of new energies. The variable is Energy production (kt of oil equivalent) for Netherlands. The sample of data is during 1960-2010 period. Based on Schwarz criterion, ARMA(2,1) is the best model for forecasting the series of energy. We have forecasted the supply of new energies of Netherlands during 1960-2013.
2017
Today among the various energies conspicuous, electric power is a significant source of industrial energy that is important for industries, agriculture and household use. Therefore, this article aims to study the trend of probable power generation in Iran, its state of consumption following Iran’s vision plan in the year 2025. Although, there are some studies on Iran’s electricity demands; the researchers studied on the relation between electricity consumption and GDP in a bi-variable assumption. Thus, this study focused on a multi-variable model to predict efficiently the electricity need for Iran 2025. During the recent years following sanctions, development of electricity power industry in Iran has been faced to some problems. Therefore, if the capacity of power plants in Iran would not be increased, it is anticipated that the relative probable power outages control would be unavoidable in the country, especially during peak hours. Accordance with international agreements made be...
2016
According on indigenous and exogenous economic factors, estimation of natural gas demands in industry sector from 1986 to 2013 will be discussed respectively, and the consumption of it will be predicted. In this study, structural time series models have been applied due to the considering exogenous economic factors, implicit Underlying Energy Demand Trend (UETD) which mainly are unobservable. Estimation's results imply on stochastic trend and demonstrate that uneconomical unobservable factors have effective role on featuring natural gas demand in industry sector. Upward trend of UEDT indicate that industrial natural gas has been consumed in non-optimized way. In fact, the effects of unobservable factors on consumption of natural gas are positive. So, the resent result implicate that some unobservable factors like technology advancement, structural reforms, have failed in decreasing consumption of natural gas duo to not regarding some efficiency standards. The estimation's re...
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