There are different models which are used in analyzing ENERGY DEMAND. Some of them are designed only' FOR analyzing ENERGY DEMAND, while some others are not designed specifically FOR this purpose, but are used in the analyses. Structural and non-structural econometric models and end use models are the main models FOR analyzing ENERGY DEMAND. Model FOR ENERGY DEMAND Evaluation (MEDEE) is one of the famous end use models which are used only FOR analyzing ENERGY DEMAND. Stun linear expenditure system, trans log DEMAND system, the constant elasticity DEMAND system, Rotterdam DEMAND system, almost ideal DEMAND system, autoregressive process, moving average process, autoregressive moving average process, autoregressive integrated moving average process, vector autoregressive model and vector error correction models; are some of the famous structural and non-structural econometric models which are used in analyzing ENERGY DEMAND.In this paper, among the above models, vector error correction model (VECM) because of its unique characteristics has been used FOR dynamic analysis of ENERGY DEMAND in Iran. In this regard three separate models FOR studying DEMAND FOR oil products, electricity and natural gas have been FORmulated. Using Eviews and Microfit software and time series of RGDP, real price of ENERGY carriers and physical value of DEMAND FOR ENERGY carriers in 1959-2004, the FORmulated vector error correction model has been estimated. The Johansen method shows that there is one co integration vector between the variables entered in the models of DEMAND FOR oil - products and electricity; but there is no dynamic long - run equilibrium relationship in the VECM of natural gas. In the VECM of oil products, all estimated coefficients are statistically significant, and the error correction term has the correct sign. In this model, the adjustment speed of deviation from the equilibrium relationship is slow. According to coefficients in the VECM of electricity, the long run price and income elasticity of DEMAND FOR electricity are - 0.86 and 1.84, respectively. It is worth mentioning that in this research by short run we mean periods less than one year, and long run refers to periods more than one year until there will be no structural change in relations among variables.

The paper presents an analysis of both ENERGY intensity and ENERGY DEMAND FOR the Italian industrial sector. The aim of the paper is twofold: making a decomposition of ENERGY intensity at the aggregate level and modeling ENERGY DEMAND at the firm level. The decomposition of ENERGY intensity shows different patterns FOR the different sub-sectors in the period of interest. In the micro approach, panel data are used to investigate whether firms’ ENERGY DEMAND varies according to their dimension, to production factors’ price dynamic and to the sub-sector ENERGY intensity. This kind of application at firm level represents a novelty in the empirical literature on ENERGY in Italy.

It is FOR a long time that ENERGY security is the major concern FOR industrialized ENERGY consumers. The idea of the security of ENERGY supply coincided with the FORmation of the IEA and setting up of the response mechanism FOR oil emergency. Since oil and gas account FOR the biggest share of ENERGY basket, ENERGY security mainly alludes to oil and gas. However the concept of ENERGY security has evolved ever since. It incorporates security of supply security of DEMAND equally. Political and social stability of oil producers and the regional stability and economic development is very meaningful to the security of ENERGY supply. Without socio-economical stability of oil producers, a missing point in the eyes of major industrial powers, a robust ENERGY security will be far from materialization. This paper shows that a multi-dimensionally defined ENERGY security where producers, consumers and the investors share their views, interests, risks and opportunity costs is able to contribute to the emergence of a more secure ENERGY market.

The advent of 3D printers has been embraced globally within few years of its emergence. The surge in the acceptability of rapid manufacturing RM strategy can be attributed to the depletion and cost of natural resources, waste reduction and sustainability criterion of manufactured parts. This rapidly evolving 3D printing technologies is predicted to grow exponentially especially FOR the manufacture of customized and geometrically complex products. ThereFORe, it is appropriate to consider and optimize the resource efficiency of 3D printing technologies at this early stage of this technology development. In this work, the direct electrical ENERGY DEMAND of 3D printing (i. e. fused deposition modeling) was studied and a generic model proposed. The developed model was further validated with the Stratasys Dimension SST FDM in order to evaluate and ascertain the generic application of the model. This work is a further contribution to the existing foundation FOR electrical ENERGY DEMAND modeling and optimization FOR the rapidly expanding 3D printing processes.

To become a mass-market product, compressed natural gas (CNG) vehicles need to enjoy an extensive network of filling stations. At the moment, CNG is mainly carried via pipeline. However, an alternative way is carrying CNG modules by trailers that are considered one of the easiest ways to supply temporary DEMAND, especially in the rural areas. FOR this reason, the CNG modules filled in the main stations (mother stations) are transported to substations (daughter stations) by trucks and trailers. To this end, the first step is to determine the number of trailers and trucks used to supply the DEMAND points. The capacity of daughter stations and the distance between mother stations and daughter stations are two important factors affecting the economics of the system. FOR the purpose of this study, a mathematical model of transporting CNG modules was presented and the mobile CNG transport system was analyzed. The cost of the mother stations and daughter stations was also determined using the CNG Station Cost Model (CNG-SCM). The ultimate goal was to gain an insight into the total cost of mobile CNG transport networks considering different capacities and the distance between mother stations and daughter stations.

ENERGY DEMAND modeling, from estimation and methodology points of view, is one of the main challenging issues among ENERGY experts. This study attempts to identify the gaps and differences in ENERGY DEMAND modeling literature. More specifically the study concentrates on the properties of two approaches: "single equation" and "DEMAND system" that commonly used in this area. Our review indicates that the single-equation approach, despite its simplicity in estimating parameters, suffers from severe problems, such as endogeneity and instability in parameters. However, the serious problem with this approach is that its specification has not been supported by rigorous microeconomic theory. On the other hand, the ENERGY DEMAND system model is explicitly derived from the microeconomic theory that makes it possible to derive own-and cross-price elasticities of ENERGY fuels and to consider interfuel substitution. However, the severe problem of this approach is that the DEMAND elasticity estimates are more sensitive to selecting functional specifications. We investigate and compare the properties of the two common functional FORms in ENERGY DEMAND system namely, translog and linear logit model. Our review indicate that the linear logit model, under theoretical regularity conditions, can provide more convenient estimates of DEMAND elasticities compared to translog functional FORm.

Identification of reliable and stable markets is one of the most important requirements FOR oil and natural gas exports. The importance of this issue can be answered from standpoint of ENERGY security DEMANDs. China, India and the European Union are Iran's potential strategic ENERGY markets, regardless of sanctions. In October 2014 The European Council agreed on a new 2030 Framework FOR climate and ENERGY, including EU-wide targets and policy objectives FOR the period between 2020 and 2030. In this study, we seek to investigate the effects of this policy on the security of Iran's ENERGY DEMAND. To this end, we examine the effects of this policy on the ENERGY DEMAND of one of the EU countries, namely Greece, which was also a customer of Iranian oil. Despite the fact that the EU ENERGY Strategy 2030 reduces the security of Iran's ENERGY DEMAND, it is necessary to examine the possible scenarios of this strategy and assess the Iran's situation in each of these scenarios. During the next ten years Greece ENERGY policies will have to be harmonized with the European Union Directives, focusing on the reduction of the greenhouse gas (GHG) emissions, penetration of renew able ENERGY sources (RES) and ENERGY saving. In this study, Goalprogramming method is used to model the macro-ENERGY policies of Greece up to the 2030 EU ENERGY Strategy. After creating the mathematical model of goal programming, environment scenario and Renewable efficiency and Influence scenario have developed. The Shannon-Wiener index and the share of oil and natural gas in primary ENERGY in Renewable efficiency and Influence are higher than in environment scenario. ThereFORe, Renewable efficiency and Influence scenario in EU countries is favorable FOR Iran in terms of increasing security of ENERGY DEMAND in 2030.