The application of seasonal latent variable in forecasting electricity demand as an alternative method

In this study, we used ARIMA, seasonal ARIMA (SARIMA) and alternatively the regression model with seasonal latent variable in forecasting electricity demand by using data that belongs to “Kayseri and Vicinity Electricity Joint-Stock Company” over the 1997:1–2005:12 periods. This study tries to examine the advantages of forecasting with ARIMA, SARIMA methods and with the model has seasonal latent variable to each other. The results support that ARIMA and SARIMA models are unsuccessful in forecasting electricity demand. The regression model with seasonal latent variable used in this study gives more successful results than ARIMA and SARIMA models because also this model can consider seasonal fluctuations and structural breaks.     

北京市能源消费与生产的灰色关联分析及能源需求预测

北京市作为我国第2大能源消费城市,对其能源消费现状和未来需求趋势进行分析是十分必要的。以2004—2010年的数据作为样本,利用灰色综合关联度对北京市近几年的能源消费和生产的关联性进行了分析,运用DGM（1,1）模型对北京市未来5年的能源消费趋势进行了预测。结果表明：北京市近几年能源消费和生产的灰色综合关联度为0.571 525,其能源消费对外地供给的依赖程度在增大,未来能源需求量将进一步增大。最后,对北京市能源发展规划提出了一些思考及建议。     

灰参数Verhulst模型在电力期货价格预测中的应用

针对GM(1，1)模型对于期货电价按照“S”形曲线增长或增长处于饱和阶段时预测误差较大的局限性，建立了预测电力期货的灰色Verhulst模型，并对参数α的变化规律进行了Verhulst模型预测。将改进的灰参数Verhulst模型运用于电力期货价格预测实例中，取得了较好的结果。     

Natural gas demand in Turkey

On average, energy demand of Turkey is mounting by 8% annually, one of the highest rates in the world. Among primary energy sources, natural gas is the fastest growing one in Turkey. Gas consumption started at 0.5 bcm (billion cubic meters) in 1987 and reached approximately 35 bcm in 2007. Turkish natural gas usage is projected to further increase remarkably in coming years. The present paper focuses the characteristics of this demand and estimates short and long-run price and income elasticities of sectoral natural gas demand in Turkey. The future growth in this demand is also forecasted using an ARIMA modelling and the results are compared with official projections. The paper reveals that natural gas demand elasticities are quite low, meaning that consumers do not respond possible abusive price increases by decreasing their demand or substituting natural gas with other energy sources. Since consumers are prone to monopoly abuse by incumbent, there is a need for market regulation in Turkish natural gas market. Based on forecasts obtained, it is clear that the current official projections do not over/under-estimate natural gas demand although past official projections highly overestimated it.     

改进灰色模型在电力负荷预测中的应用

灰色GM（1,1）模型是一种较有效的负荷预测模型,然而由于电力负荷具有多样性,导致对某些变化规律的负荷预测误差较大,精度不能满足要求,在实际应用中具有一定的局限陛。对灰色GM（1,1）模型进行必要的改进,利用等维新信息递推模型进行负荷预测,通过实例分析表明,可提高预测的精度。     

Modelling future private car energy demand in Ireland

Targeted measures influencing vehicle technology are increasingly a tool of energy policy makers within the EU as a means of meeting energy efficiency, renewable energy, climate change and energy security goals. This paper develops the modelling capacity for analysing and evaluating such legislation, with a focus on private car energy demand. We populate a baseline car stock and car activity model for Ireland to 2025 using historical car stock data. The model takes account of the lifetime survival profile of different car types, the trends in vehicle activity over the fleet and the fuel price and income elasticities of new car sales and total fleet activity. The impacts of many policy alternatives may only be simulated by such a bottom-up approach, which can aid policy development and evaluation. The level of detail achieved provides specific insights into the technological drivers of energy consumption, thus aiding planning for meeting climate targets. This paper focuses on the methodology and baseline scenario. Baseline results for Ireland forecast a decline in private car energy demand growth (0.2%, compared with 4% in the period 2000–2008), caused by the relative growth in fleet efficiency compared with activity.     

Improvement of energy demand forecasts using swarm intelligence: The case of Turkey with projections to 2025

The energy supply and demand should be closely monitored and revised the forecasts to take account of the progress of liberalization, energy efficiency improvements, structural changes in industry and other major factors. Medium and long-term forecasting of energy demand, which is based on realistic indicators, is a prerequisite to become an industrialized country and to have high living standards. Energy planning is not possible without a reasonable knowledge of past and present energy consumption and likely future demands. Energy demand management activities should bring the demand and supply closer to a perceived optimum. Turkey's energy demand has grown rapidly almost every year and is expected to continue growing. However, the energy demand forecasts prepared by the Turkey Ministry of Energy and Natural Resources overestimate the demand. Recently many studies are performed by researchers to forecast the energy demand of Turkey. Particle swarm optimization (PSO) technique has never been used for such a study. In this study a model is proposed, using PSO-based energy demand forecasting (PSOEDF), to forecast the energy demand of Turkey more efficiently. Although there are other indicators as well, gross domestic product (GDP), population, import and export are used as basic energy indicators of energy demand. In order to show the accuracy of the algorithm, a comparison is made with the ant colony optimization (ACO) energy demand estimation model which is developed for the same problem.     

Turkey’s short-term gross annual electricity demand forecast by fuzzy logic approach

This paper aims to forecast Turkey's short-term gross annual electricity demand by applying fuzzy logic methodology while general information on economical, political and electricity market conditions of the country is also given. Unlike most of the other forecast models about Turkey's electricity demand, which usually uses more than one parameter, gross domestic product (GDP) based on purchasing power parity was the only parameter used in the model. Proposed model made good predictions and captured the system dynamic behavior covering the years of 1970–2014. The model yielded average absolute relative errors of 3.9%. Furthermore, the model estimates a 4.5% decrease in electricity demand of Turkey in 2009 and the electricity demand growth rates are projected to be about 4% between 2010 and 2014. It is concluded that forecasting the Turkey's short-term gross electricity demand with the country's economic performance will provide more reliable projections. Forecasting the annual electricity consumption of a country could be made by any designer with the help of the fuzzy logic procedure described in this paper. The advantage of this model lies on the ability to mimic the human thinking and reasoning.     

城镇居民生活用电需求预测模型

随着我国经济的发展和经济结构的调整,居民用电占全社会用电量的比重逐渐增大并有继续增加的趋势。为了定量分析我国城镇居民生活用电的未来发展,从统计数据出发,选择城镇居民人均收入、城镇民用电价、前一年的城镇居民人均生活用电量作为解释变量,建立了城镇居民生活用电需求预测计量方程,确定了用电量和影响用电量的因素之间的理论和数量关系,同时为了提高模型的预测精度,揭示短期波动,建立了关于城镇居民生活用电的误差修正模型。并以此预测了2004年和2005年的用电量。结果表明,未来几年内,我国城镇居民人均生活用电量将以5.0%左右的年增长率变化。     

Evaluation of Natural Gas Supply Security in Turkey with Future Projection

Natural gas is one of the key energy resources for Turkey due to fact that 32% of annual primary energy supply and 45% of annual electricity production is obtained from natural gas with also common usage of residential and industrial zones. In this study, the supply security of natural gas was taken into consideration with strategic criteria of energy policy with the SWOT （strengths, weaknesses, opportunities and threats） analysis and the future projection for Turkey. It has been concluded on geopolitics criteria, domestic production and research for resources must be stimulated as high as possible and participation to abroad resources must be implemented.     

天然气发动机电控系统的市场研究

阐述伍德沃德天然气发动机电控系统所处的行业发展状况,分析天然气及柴油价格走势与天然气电控系统销售量间的相关关系,综合利用趋势预测法和线性回归预测法,得到行业成长率的预测,为企业的各项战略决策提供了重要依据。     

The prospects for liquefied natural gas development in the US

The objective of our paper is to analyze the prospects for LNG development in the US. In particular, we discuss LNG investment projects with respect to natural gas supply and demand, existing transmission infrastructure, and competing pipeline projects. At the same time potential competition between natural gas and coal in power generation is taken into account. We conclude that in the mid-term, LNG will assume an essential role in meeting US demand because of stagnating and declining domestic production in North America accompanied by an expected increase in demand for natural gas. Additional net imports will be required in the western US (mainly southern California), the Southeast, and in the Northeast—three areas of the nation that lack adequate supply. When accounting for the current status of existing natural gas infrastructure and forthcoming investments, we conclude that there should be little concern about sufficient investment incentives and supply security in the US competitive natural gas market.     

Turkey's natural gas policy

This article deals with natural gas policy of Turkey. Natural gas became important in the 1980s. In recent years, natural gas consumption has become the fastest growing primary energy source in Turkey. Natural gas becomes an increasingly central component of energy consumption in Turkey. Current gas production in Turkey meets 3% of the domestic consumption requirements. Natural gas consumption levels in Turkey have witnessed a dramatic increase, from 4.25 Bcm (billion cubic meters) in 1991 to 21.19 Bcm in 2003. Turkish natural gas is projected to increase dramatically in coming years, with the prime consumers expected to be industry and power plants. Turkey has chosen natural gas as the preferred fuel for the massive amount of new power plant capacity to be added in coming years. Turkey has supplied main natural gas need from Russian Federation; however, Turkmen and Iranian gas represent economically sound alternatives. Turkey is in a strategically advantageous position in terms of its natural gas market. It can import gas from a number of countries and diversify its sources. Turkey's motivation for restructuring its natural gas ownership and markets stems from its desire to fulfill EU accession prerequisites in the energy sector.     

基于灰色组合模型的浙江省需水量预测

针对传统需水量预测模型存在的不足,将GM(1,1)模型和灰色Verhulst模型相结合,构建了灰色组合模型,并对模型采用残差和权重分配相结合的二次修正方式进行修正,在分析浙江省1998~2012年用水现状的基础上,利用二次修正后的灰色组合模型预测了2013~2020年浙江省的用水情况。结果表明,在未来的一段时间内,浙江省的需水量增长会逐步加快,尤其体现在居民生活用水和工业用水上。因此,做好工业生产节水工作,加快产业结构调整是今后工作的重点。     

Ant colony optimization approach to estimate energy demand of Turkey

This paper attempts to shed light on the determinants of energy demand in Turkey. Energy demand model is first proposed using the ant colony optimization (ACO) approach. It is multi-agent systems in which the behavior of each ant is inspired by the foraging behavior of real ants to solve optimization problem. ACO energy demand estimation (ACOEDE) model is developed using population, gross domestic product (GDP), import and export. All equations proposed here are linear and quadratic. Quadratic_ACOEDE provided better-fit solution due to fluctuations of the economic indicators. The ACOEDE model plans the energy demand of Turkey until 2025 according to three scenarios. The relative estimation errors of the ACOEDE model are the lowest when they are compared with the Ministry of Energy and Natural Resources (MENR) projection.     

ARIMA forecasting of primary energy demand by fuel in Turkey

Forecasting of energy demand in emerging markets is one of the most important policy tools used by the decision makers all over the world. In Turkey, most of the early studies used include various forms of econometric modeling. However, since the estimated economic and demographic parameters usually deviate from the realizations, time-series forecasting appears to give better results. In this study, we used the Autoregressive Integrated Moving Average (ARIMA) and seasonal ARIMA (SARIMA) methods to estimate the future primary energy demand of Turkey from 2005 to 2020. The ARIMA forecasting of the total primary energy demand appears to be more reliable than the summation of the individual forecasts. The results have shown that the average annual growth rates of individual energy sources and total primary energy will decrease in all cases except wood and animal–plant remains which will have negative growth rates. The decrease in the rate of energy demand may be interpreted that the energy intensity peak will be achieved in the coming decades. Another interpretation is that any decrease in energy demand will slow down the economic growth during the forecasted period. Rates of changes and reserves in the fossil fuels indicate that inter-fuel substitution should be made leading to a best mix of the country's energy system. Based on our findings we proposed some policy recommendations.     

An adaptive network-based fuzzy inference system for short-term natural gas demand estimation: Uncertain and complex environments

Accurate short-term natural gas (NG) demand estimation and forecasting is vital for policy and decision-making process in energy sector. Moreover, conventional methods may not provide accurate results. This paper presents an adaptive network-based fuzzy inference system (ANFIS) for estimation of NG demand. Standard input variables are used which are day of the week, demand of the same day in previous year, demand of a day before and demand of 2 days before. The proposed ANFIS approach is equipped with pre-processing and post-processing concepts. Moreover, input data are pre-processed (scaled) and finally output data are post-processed (returned to its original scale). The superiority and applicability of the ANFIS approach is shown for Iranian NG consumption from 22/12/2007 to 30/6/2008. Results show that ANFIS provides more accurate results than artificial neural network (ANN) and conventional time series approach. The results of this study provide policy makers with an appropriate tool to make more accurate predictions on future short-term NG demand. This is because the proposed approach is capable of handling non-linearity, complexity as well as uncertainty that may exist in actual data sets due to erratic responses and measurement errors.     

Short-run and long-run elasticities of import demand for crude oil in Turkey

The aim of this study is to attempt to estimate the short-run and the long-run elasticities of demand for crude oil in Turkey by the recent autoregressive distributed lag (ARDL) bounds testing approach to cointegration. As a developing country, Turkey meets its growing demand for oil principally by foreign suppliers. Thus, the study focuses on modelling the demand for imported crude oil using annual data covering the period 1980–2005. The bounds test results reveal that a long-run cointegration relationship exists between the crude oil import and the explanatory variables: nominal price and income, but not in the model that includes real price in domestic currency. The long-run parameters are estimated through a long-run static solution of the estimated ARDL model, and then the short-run dynamics are estimated by the error correction model. The estimated models pass the diagnostic tests successfully. The findings reveal that the income and price elasticities of import demand for crude oil are inelastic both in the short run and in the long run.     

Demand for natural gas in Kuwait: An empirical analysis using two econometric models

This paper estimates the demand for natural gas in Kuwait for the period 1975–93 using two models. A partial flow-adjustment model and a co-integration and error correction model. It is found that natural gas demand is inelastic with respect to price and income in the short and long run. Furthermore, natural gas consumption adjusts towards its long-run level with about 61% of the adjustment occurring in the first year.