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Abstract: This paper will summarise the European Strategy for Energy and Climate Change. In current international negotiations Europe has proposed a 20% reduction in GHG (greenhouse gases) in the developed countries by 2020 or 30% should there be an international agreement in the domain. However it is important to define measures to achieve the targets. One of the principal tools is to improve energy efficiency under the energy efficiency action plan, which will help to achieve a 20% energy saving by 2020. On the other hand, the amount of energy from renewable sources consumed in Europe will have to rise from its current level of 8.5%–20% by 2020. These are ambitious but achievable targets. Nonetheless, these can only be achieved through strong investment in areas of the knowledge triangle which strengthens research and innovation in the energy sector in Europe. The paper covers European Energy and Climate Change Policy, the European Strategic Energy Technology plan, the consequences of the Lisbon Treaty, European and national Road maps to a low carbon economy, the Energy Efficiency Plan for 2011 and finishes with a brief consideration of the EU’s energy infrastructure priorities. [Copyright &y& Elsevier]

Abstract The current study discusses the linear and non-linear relationship between trade, and non-renewable and renewable energy consumption using data of 72 countries extending from 1990 to 2012. Our empirical models integrate some additional variables which affect the above-mentioned relationship such as GDP, CO 2 emissions, domestic resources abundance, and some interaction terms. The innovation of the paper is not only to compare between developed and developing countries but also between industrialized countries and non-industrialized ones by integrating some dummy variables into the models. The empirical results demonstrate that trade and energy consumption (renewable or non-renewable) have a mutually reinforcing linear relationship. Moreover, the validity of non-linear relationships is accepted only in the case of the impact of non-renewable on trade. This latter follows an inverted U-shape form in the case of developed and industrialized countries while a U-Shape one in the case of developing and non-industrialized countries. In addition, the findings indicate a positive contribution of GDP, capital, and labor on trade and energy consumption. However, CO 2 emissions and natural resource have positive impacts on trade and non-renewable energy while negative effect on renewable energy. It implies that policy makers should develop appropriate policies to profit from trade and energy consumption. Highlights • We investigate the linear and non-linear relationship between energy consumption (renewable or non-renewable), and trade. • We focus in developed versus developing countries and industrialized versus non-industrialized ones from 1990 to 2012. • We use GMM dynamic panel data models. • We state bidirectional linear links between trade and renewable energy consumption. • We obtain a non-linear impact of trade on non-renewable energy consumption against a linear effect in the opposite sense. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we use time-varying copula and VAR-DAG models to investigate oil-stock contagion and its propagation among seven countries with different levels of economic development. Our results present evidence of positive lower tail dependence between oil and stock markets of the seven countries, which is indicative of contagion in the sense of Okimoto [ 1 ]. Evolution patterns of contagion are similar in the developed countries but different in the developing ones. Moreover, contagion is significantly affected by the 2008 financial crisis, and the contagious magnitude in China and India is considerably smaller than in the other five countries. The empirical evidence also suggests that oil-stock contagion is propagated from developed countries to developing ones, and Brazil is the most affected by the developed countries' contagion. Highlights • Time-varying copula and VAR-DAG models are developed and estimated. • There exists a contagion between oil and seven stock markets. • The oil-stock contagion is significantly affected by the 2008 financial crisis. • The oil-stock contagion is propagated from developed countries to developing ones. • The contagious magnitude in China and India is smaller than in the other five countries. [ABSTRACT FROM AUTHOR]

This paper defines the diverging interests of multiple actors in typically achieving and advancing energy efficiency. Gaps in the literature include the short elaboration of energy efficiency factors and conditions and the lack of information about developed and developing countries and thorough consideration of their specific features, impeding the development and implementation of detailed energy efficiency management strategies. It is against this backdrop that this paper seeks to identify the essence of energy efficiency and developing specific recommendations for achieving the most beneficial effect and well-balanced energy efficiency on the global scale, within the achievements of international goals in sustainable development. The paper exposes the critical factors of energy efficiency, accurately models the best energy efficiency characteristics, and settles the best energy consumption structure. The methodological purpose is to find different energy efficiency scenarios and disentangle fundamental differences in energy efficiency in developed and developing countries. The paper indicates that the reasonable likelihood of noteworthy achievement results in energy efficiency with insignificant mid-term changes. We give recommendations about well-balanced energy efficiency on the global scale and global progress in sustainable development. • This paper disentangles key differences in energy efficiency in developed and developing countries. • We identify the essence of energy efficiency and develop recommendations for achieving balanced energy efficiency globally. • The paper models the best energy efficiency characteristics and settles the best energy consumption structure. • We give recommendations about well-balanced energy efficiency in sustainable development. • The study shows energy consumption optimization in terms of GDP structure, energy consumption, and sustainability. [ABSTRACT FROM AUTHOR]

In the rapid process of globalization, merchandise trade has increased year by year, and the circulation and consumption of the energy embodied in the merchandise trade have increased. To study the relevant nature of the global embodied energy trade network (GEETN) from an overall perspective and the control and dependence relationships between various countries and regions from a partial perspective, this paper establishes a GEETN model, through an ecological network analysis (ENA) method and the motif of complex networks for research. From an overall perspective, a GEETN is a system that achieves stability quickly. Some developed countries, such as the United States and the European Union, and some emerging economies, such as China and Russia, play important roles in GEETN. From a partial perspective, in the GEETN model, US is mainly controlled by Asian countries and CA (Canada), EU is mainly controlled by other European countries, both due to their industrial layout in some extent. The scientific value of this article not only includes the improvement of model, but also provides a new perspective and a reference for the formulation of energy and climate change policies. [Display omitted] • We integrated ecological network analysis (ENA) with motif. • We analyzed the nature of global embodied energy trade network (GEETN). • The key countries and regions within the GEETN are detected. • The key control and dependence relationships within the GEETN are detected. • The results support policies of energy consumption and climate change. [ABSTRACT FROM AUTHOR]

Abstract: This paper measures environmental productivity in 70 countries over the period 1981–2007. Differences in green (environmental) productivity growth across countries under distinct country specific production frontier are measured using directional distance function model, which incorporates desirable output (GDP) and undesirable output (CO2 emissions). The metafrontier which envelops the two country groups, developed countries and developing countries, are estimated using balanced panel data for the sample countries over the study period. A parametric method is used to compute technical efficiency change, technical change, and scale efficiency change, which aggregate to the generalized metafrontier Malmquist productivity index. The overall results indicated the two country groups operated under distinct stochastic production frontiers and therefore used different production technologies. It is found that developing countries achieved higher growth in their average environmental productivity relative to the metafrontier. Thus the results coincide with the convergence growth theory. [Copyright &y& Elsevier]

Abstract: Throughout the last years the use of on-site renewable energy sources (RES) in residential houses has continuously increased in many industrial countries and it is expected that many of the supply systems will be based solely on renewable sources in the medium term future. However, the explicitly higher installation costs compared to conventional systems and the variability of the energy sources require an optimized design of the overall system. To achieve this, a new approach is needed which accounts for the interdependencies between the different supply technologies as well as consumption profiles of residents and on-site energy resource availability. This paper aims at developing a model based on linear programming for the optimal sizing of 100% renewable supply systems in terms of the overall system costs. It has been successfully applied in a case study for a so called Net Zero Energy Building in Denmark with three technology options. It is shown that under the chosen conditions the optimal configuration is given by a PV model combined with a heat pump for heat supply. The model allows for a fast evaluation of different supply options and is intended to be extended in future to all kind of residential RES technologies. [Copyright &y& Elsevier]

The main aim of the present paper is to explore how the interactions between crude oil (CO) price changes and stock returns of five developed countries namely U.S.A, Canada, Germany, Japan and U.K., evolve simultaneously over time and frequency, in light of the conflicting evidence provided by much of recent studies on the sign and the direction of this relationship. To this end, we apply a more efficient wavelet tool, namely Haar à trous wavelet transform that helps circumvent the problems of the standard regression techniques and proves its effectiveness in encircling the real data features. In order to provide more credible conclusions, the wavelet variance, correlation and cross-correlation are implemented. In general, we extend the existing empirical works by providing more generalized and convincing results inherent to the stock-oil markets interactions which are usually reputed to be complicated. First, we find evidence that the wavelet variances of all the variables decrease with increasing scales. Second, from the analysis of the wavelet correlation, changes in CO and almost all the stock prices do not move together up to the intermediate scale, but since they abruptly shift their direction in unison. Third, results for the wavelet CCF at scales 2, 3 and/or 4 generally illustrate no transmission mechanism between CO and the stock market returns although we provide support for massive CO variations at these scales. In contrast, the CO-equity market relationships at higher scales become interconnected in a negative unidirectional pattern running from CO to stock market returns for only two oil importing countries but also Canada. For oil exporting countries, we have seen that while highly transient (scale 1) positive/negative causalities flowing from TSX stock market to CO changes are detected, highly persistent (scale 6) positive causality running from FTSE to the CO changes are rather found. Finally, the implications of the study's results vary depending on the oil – stock market linkages' sensitivity to the degree of improvement in energy efficiency of a given country, the degree of oil shock persistence, and to whether a country is oil importer or exporter (among other suggested factors). [Copyright &y& Elsevier]

The efficient and sustainable operation of building energy systems is playing an increasingly important role in most industrialized countries. At the same time, building energy systems are becoming increasingly complex; fault-free and optimal operation, under dynamic boundary conditions, is becoming more and more challenging. There are many approaches in research to address the optimal control problem of building energy systems, such as Rule-based Control, Model Predictive Control, or Adaptive Control. However, most methods rely on models of the system dynamics with high prediction accuracies. This is especially the case in Model Predictive Control, where the model is part of a continuously executed optimization problem; but models are also required when it comes to the optimal design of Rule-based Controllers, the safe pre-training of Adaptive Controllers, or model-based fault detection. A limiting factor for the manual development of physical models, for building energy systems, are the low monetary incentives for engineering services, due to the low energy prices in most countries. In addition, the creation of such models is time-consuming and error-prone, even for domain experts. Another weakness is that changes in the system dynamics are not automatically adapted within the models. These challenges are contrasted by an increasing availability of monitoring-data and computational power in recent years; with machine-learning algorithms, these resources are used in numerous application areas to achieve very promising results. Machine-learning methods can help to obtain data-driven, self-calibrating models, which can be learned from monitoring-data. In this paper, we apply methods for automated data-driven model generation. We demonstrate how machine-learning algorithms together with structured hyper-parameter tuning can be used to model individual subsystems as well as a complete energy supply system. To represent the dynamics of the supply system, it is first decomposed into simple functional relationships, which are aggregated into the overall system after training of the comparatively simple subsystem models. We evaluate the accuracy of the data-driven subsystem models using established metrics for the evaluation of regression models, namely the R2-score and the RMSE. The considered system is integrated into a district cooling network and consists of two compression chillers and an ice storage unit. Our investigations show that the dynamics of the subsystems can be learned with high accuracies, depending on the operation mode and the selected features. The prediction of the power demand of the compression chillers is learned with R2-scores between 0.94 and 0.99 and RMSE values between 2.02 kW and 3.51 kW. Also, the prediction of the percentage of ice formation within the ice storage is learned accurately with a R2-score of 1 and RMSE values between 0.08 % and 0.72 %. The dynamics of the aggregated system also show plausible behavior and can thus be used in future work. This work is part of an ongoing research project with the aim to optimize the operation of the entire campus cooling energy supply system. Our results show that, if detailed monitoring-data are available, data-driven modelling represents a viable alternative to the labor-intensive physical modelling approach. Furthermore, we emphasize the importance of structured hyper-parameter tuning, discuss the specifics of different machine-learning algorithms, and elaborate on possible future developments in this research area. • Modelling of energy systems is labor-intensive and uneconomical in many cases. • Data-driven modelling represents a promising alternative. • Different dynamics of a cooling supply system are modelled via machine-learning. • We demonstrate the process and show promising results but also discuss limitations. • Investigating the intersection of data infrastructures and automated modelling. [ABSTRACT FROM AUTHOR]

Different from the expectations of energy development in other industrialized countries, China is pursuing an orderly-synergistic energy transition. The necessity and effect of orderliness-synergy in the sustainable development of China's power generation industry during the transition period is focused in this paper. The orderly-synergistic development process can be regarded as the game of interest balance for both the clean energy power generation enterprises and the thermal power generation ones. Hence evolutionary game method with six Assumptions, basic model and normative analysis is adopted. And then to explain the process more scientifically, the numerical simulation with scenario analysis is used to study two types of power generation enterprises. Three important conclusions are drawn: (1) when two types of power generation enterprises make the "same direction" decision at the same time, the population stability can be formed within the industry; (2) the revenues of both clean power generation enterprises and thermal power generation enterprises have shown a positive correlation with adopting active strategies; (3) when the power generation industry tends to the policy orientation, the orderly-synergistic benefits will be smaller, however, when the power generation industry tends to the market orientation, the orderly-synergistic benefits will be greater. And then some recommendations are put forward. • The evolutionary game method is used for the orderly-synergistic development of power generation industry. • This method is proposed for the necessity and effect of orderliness-synergy in terms of China's power generation industry. • Two types of power generation enterprises are analyzed by the numerical simulation with scenario analysis. • Conclusion section considers the policy orientation problem and market orientation problem. [ABSTRACT FROM AUTHOR]