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Abstract Addressing environmental concerns alongside economic development and energy transitions is a challenge for all countries and effective policy making requires approaches that can balance all these concerns. In this paper, combining a range of modeling methodologies is proposed as a way of addressing these questions in an integrated manner. The choice of models to be used would depend on the specific characteristics of the system and region being studied. One possible combination of models is discusses in this paper for the specific case of India. The Integrated Modeling Framework (IMF) proposed combines three modeling approaches – i) index decomposition to estimate impacts of structural changes in the economy, ii) constrained optimization to estimate least cost fuel options for the power sector, iii) input-output analysis to estimate economic impacts. The model results indicate that the mode of investment for climate change mitigation is a significant determinant of the impact on economic growth, incomes, and income distribution in India. In some scenarios, higher investments in green energy negatively affects low income households significantly more as compared to other households. The paper also demonstrates how the IMF can be used to determine the reasons for and therefore alleviate the negative impacts. Highlights • An Integrated Modeling Framework (IMF) combining three modeling methods is presented. • IMF built for India, but applicable for other developing countries also. • IMF useful to study balance between energy, environment, economy, and equity. • Negative trade-off between equity and renewable energy transition in some scenarios. • IMF useful for identifying ways to alleviate the negative trade-off. [ABSTRACT FROM AUTHOR]

By 2020 Europe has to increase its energy efficiency and share of renewables in 20%. However, even accomplishing these challenging objectives Europe will be effectively wasting energy as we demonstrate in this paper. In our way towards a fully renewable scenario, we need at least to stop wasting energy in order to guarantee the energy supply needed for growth and comfort. We waste energy when we employ more primary energy than the final energy we ultimately use and this excess cannot be reutilized. In this paper we propose the WE (wasted energy) as a novel metric to measure the performance of energy systems and set up appropriate targets. The WE incorporates information about energy efficiency and renewable sources. Unlike European legislation, the WE considers them in an integrated way. This approach will help Member States to exploit their intrinsic capabilities and design their optimum strategy to reach their objectives. Using the information in Eurostat, we calculate the WE of Member States in EU-28 and their evolution. We also analyze illustrative examples to highlight strategies to reduce the WE, study the connection between economic development and WE, and provide a tool to diagnose the potential of improvement of an energy system. [ABSTRACT FROM AUTHOR]

Recently a great number of empirical research studies have been conducted on the relationship between certain indicators of environmental degradation and income. The EKC (Environmental Kuznets Curve) hypothesis has been tested for various types of environmental degradation. The EKC hypothesis states that the relationship between environmental degradation and income per capita takes the form of an inverted U shape. In this paper the EKC hypothesis was investigated with regards to the relationship between carbon emissions, income and energy consumption in 16 EU (European Union) countries. We conducted panel data analysis for the period of 1990–2008 by fixing the multicollinearity problem between the explanatory variables using their centered values. The main contribution of this paper is that the EKC hypothesis has been investigated by separating final energy consumption into renewable and fossil fuel energy consumption. Unfortunately, the inverted U-shape relationship (EKC) does not hold for carbon emissions in the 16 EU countries. The other important finding is that renewable energy consumption contributes around 1/2 less per unit of energy consumed than fossil energy consumption in terms of GHG (greenhouse gas) emissions in EU countries. This implies that a shift in energy consumption mix towards alternative renewable energy technologies might decrease the GHG emissions. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents Concrete Institutional Economics as an economic paradigm to understand how the wish for sustainable energy in times of economic crisis can be used to generate jobs as well as economic growth. In most countries, including European countries, the USA and China, the implementation of sustainable energy solutions involves the replacement of imported fossil fuels by substantial investments in energy conservation and renewable energy (RE). In such situation, it becomes increasingly essential to develop economic thinking and economic models that can analyse the concrete institutions in which the market is embedded. This paper presents such tools and methodologies and applies them to the case of the Danish heating sector. The case shows how investments in decreasing fossil fuels and CO2 emissions can be made in a way in which they have a positive influence on job creation and economic development as well as public expenditures. [Copyright &y& Elsevier]

Abstract: This paper is concerned with modeling possible future paths for Lebanon’s electricity future and evaluating them. The baseline scenario (BS) reflects the business-as-usual state of affairs and thus describes the most likely evolution of the power sector in the absence of any climate change-related or other policies. Two alternative scenarios are examined in contrast to the BS; the renewable energy scenario (RES) and the natural gas scenario (NGS). Using the Long range Energy Alternatives Planning System (LEAP) software we conduct a full-fledged scenario analysis and examine the technical, economic, and environmental implications of all scenarios. From an economic standpoint as well as from an environmental perspective both alternative scenarios are superior to the baseline. Hence, the results of the simulation show that the alternative scenarios are more environmentally and economically attractive than the BS. They would help Lebanon meet its social, environmental, and economic development goals, while at the same time providing other unquantifiable benefits that are discussed further in the paper. Anticipated barriers to the shift in energy mix from conventional sources to renewable energy sources are also presented and discussed [Copyright &y& Elsevier]

Abstract: India’s aspiration for economic growth has consequences for energy growth and CO2 emissions. This paper examines India’s need for energy with 20 year perspectives. From an earlier paper by K. Parikh et al. (2009), demand scenario are examined from the supply perspectives ranging from coal, hydrocarbon, nuclear, hydrogen, hydro and other renewable etc. None of these are substantial and India will have to rely on imports. The need for energy has to be reduced by a drive for energy efficiency and renewable energy. Government programmes for the above are also commented upon. Though India’s CO2 emissions are unlikely to grow very much due to energy scarcity and energy mix the article examines the potential to reduce CO2 emissions and the associated costs involved in various options. It finds that 30% reduction in CO2 emissions by 2030 is feasible but would involve additional costs. The most promising option is to reduce energy demand by various measures to increase energy use efficiency in production and consumption. [Copyright &y& Elsevier]

Rapid economic growth in China has lead to an increasing energy demand in the country. In combination with China's emission control and clean air initiatives, it has resulted in large-scale expansion of the leading renewable energy technologies, wind and solar power. Their intermittent nature and uneven geographic distribution, however, raises the question of how to best exploit them in a future sustainable electricity system, where their combined production may very well exceed that of all other technologies. It is well known that interconnecting distant regions provides more favorable production patterns from wind and solar. On the other hand, long-distance connections challenge traditional local energy autonomy. In this paper, the advantage of interconnecting the contiguous provinces of China is quantified. To this end, two different methodologies are introduced. The first aims at gradually increasing heterogeneity, that is non-local wind and solar power production, to minimize production costs without regard to the match between production and demand. The second method optimizes the trade-off between low cost production and high utility value of the energy. In both cases, the study of a 100% renewable Chinese electricity network is based on 8 years of high-resolution hourly time series of wind and solar power generation and electricity demand for each of the provinces. From the study we conclude that compared to a baseline design of homogeneously distributed renewable capacities, a heterogeneous network not only lowers capital investments but also reduces backup dispatches from thermal units. Installing more capacity in provinces like Inner Mongolia, Jiangsu, Hainan and north-western regions, heterogeneous layouts may lower the levelized cost of electricity (LCOE) by up to 27%, and reduce backup needs by up to 64%. [ABSTRACT FROM AUTHOR]

Wind power is a type of clean and renewable energy, and reasonable utilization of wind power is beneficial to environmental protection and economic development. Therefore, a short-term hydro-thermal-wind economic emission dispatching (SHTW-EED) problem is presented in this paper. The proposed problem aims to distribute the load among hydro, thermal and wind power units to simultaneously minimize economic cost and pollutant emission. To solve the SHTW-EED problem with complex constraints, a modified gravitational search algorithm based on the non-dominated sorting genetic algorithm-III (MGSA-NSGA-III) is proposed. In the proposed MGSA-NSGA-III, a non-dominated sorting approach, reference-point based selection mechanism and chaotic mutation strategy are applied to improve the evolutionary process of the original gravitational search algorithm (GSA) and maintain the distribution diversity of Pareto optimal solutions. Moreover, a parallel computing strategy is introduced to improve the computational efficiency. Finally, the proposed MGSA-NSGA-III is applied to a typical hydro-thermal-wind system to verify its feasibility and effectiveness. The simulation results indicate that the proposed algorithm can obtain low economic cost and small pollutant emission when dealing with the SHTW-EED problem. [ABSTRACT FROM AUTHOR]

This study explores the economic growth – energy consumption nexus for two samples of MENA Net Oil Exporting Countries (NOECs) during the period 1980–2012. Using panel cointegration approach, we found strong evidence for the existence of a long-run relationship between real GDP, renewable and non-renewable energy consumption, real gross fixed capital formation, and the labor force. Moreover, empirical results from the estimation of the panel error correction model indicate evidence of a unidirectional causality running from economic growth to renewable energy consumption in the short-run. In the long-run, the results show evidence of a bidirectional causality for the entire group of MENA NOECs. For the 5 selected MENA NOECs sample, we found strong evidence for bidirectional causality between renewable energy and economic growth. Additionally, our results confirm bidirectional causality between renewable and non-renewable energy consumption with negative and significant coefficient in the short-run indicating substitutability between these two types of energy. Finally, the paper discusses the economic implications of the results and proposes certain policies recommendations. [ABSTRACT FROM AUTHOR]

Annual power load forecasting is essential for the planning, operation and maintenance of electric power system, which can also mirror the economic development of a country or region to some extent. Accurate annual power load forecasting can provide valuable reference for electric power system operators and economic managers. With the development of smart grid and renewable energy power, power load forecasting has become a more difficult and challenging task. In this paper, a hybrid optimized grey model (namely Grey Modelling (1, 1) optimized by Ant Lion Optimizer with Rolling mechanism, abbreviated as Rolling-ALO-GM (1, 1)) was proposed. The parameters of Grey Modelling (1, 1) were optimally determined by employing Ant Lion Optimizer, which is a new nature-inspired metaheuristic algorithm. Meanwhile, the rolling mechanism was incorporated to improve the forecasting accuracy. Two cases of annual electricity consumption in China and Shanghai city were selected to verify the effectiveness and feasibility of the proposed Rolling-ALO-GM (1, 1) for annual power load forecasting. The empirical results indicate the proposed Rolling-ALO-GM (1, 1) model shows much better forecasting performance than Grey Modelling (1, 1), Grey Modelling (1, 1) optimized by Particle Swarm Optimization, Grey Modelling (1, 1) optimized by Ant Lion Optimizer, Generalized Regression Neural Network, Grey Modelling (1, 1) with Rolling mechanism, and Grey Modelling (1, 1) optimized by Particle Swarm Optimization with Rolling mechanism. Ant Lion Optimizer, as a new intelligence optimization algorithm, is attractive and promising. The Grey Modelling (1, 1) optimized by Ant Lion Optimizer with Rolling mechanism can significantly improve annual power load forecasting accuracy. [ABSTRACT FROM AUTHOR]

In the United States, the industrial sector is the driving engine of economic development, and energy consumption in this sector may be considered as the fuel for this engine. In order to keep this sector sustainable (diverse and productive over the time), energy planning should be carried out comprehensively and precisely. This paper describes the development of two types of numerical energy models which are able to predict the United States' future industrial energy-demand. One model uses an ANN (artificial neural network) technique, and the other model uses a MLR (multiple linear regression) technique. Various independent variables (GDP, price of energy carriers) are tested. The future industrial energy demand can then be forecasted based on a defined scenario. The ANN model anticipates a 16% increase in energy demand from 2012 by 2030. In this forecast, the model assumes that the effective independent parameters remain constant during this period and only GDP grows with a second-order polynomial trend. The forecast result, which shows consistency with published predictions, may be considered as an indication of the need for development of new and low-cost energy sources. This study suggests that the ANN technique is a reliable and powerful technique which can effectively perform input/output mapping. In order to validate the performance of the models, the results of the ANN model is compared to the projections from the Energy Information Administration of the U.S. Department of Energy. [ABSTRACT FROM AUTHOR]

Abstract: Energy consumption and efficiency are important in regional low-carbon economic development and environmental protection. This paper provides a system dynamics and fuzzy multi-objective programming integrated approach for the prediction of energy consumption and CO2 emissions at a regional level. First, a general system dynamics model is constructed to analyze an economy-energy system. To deal with the uncertainties and optimize the parameters in the system, a fuzzy multiple objective programming model is used. This decision support model is then applied to predict the energy consumption of a world heritage area in China during 2010–2020. The results reveal that the energy consumption and CO2 emissions increase dramatically with rapid economic growth. In the scenario herein considered, which is based on the proposed optimization model, a 19.32% reduction was found in the energy intensity decreases from 0.88 tce/104 RMB to 0.71 tce/104 RMB, and a 23.26% reduction in the CO2 emission intensity, from 2.15 t/104 RMB to 1.65 t/104 RMB. Policy suggestions such as adjusting the industrial structure, enhancing local hydro-power and renewable energy and increasing investment in energy technology and efficiency are indicated for the promotion of a low-carbon oriented economy in world heritage areas. [Copyright &y& Elsevier]

Abstract: Many islands face problems in regard to sustainable development, both environmentally and economically. Due to geographical isolation energy is often imported from the mainland. Focusing on local energy use may help islands to identify sustainable strategies and solutions. Islands in transition towards using more renewable energy sources are part of the project “Cradle to Cradle Islands”, funded by the EU Interreg IVb North Sea Region Programme. Energy systems on islands are diverse and linked to each specific location. Opportunities for the development of sustainable energy solutions are often inhibited by institutional, organisational or habitual problems. It is therefore essential to examine islands individually in their context; both in regard to energy use and available resources. This can be used to assess possible energy savings and unused renewable energy sources, and visualise their interaction, the consequences for the environment, as well as the effect on insular economy. Even though islands face different problems, they may inspire each other. In this paper a straightforward tool for examining insular energy systems is presented. The tool has been applied to five different islands in the North Sea Region. The application of the model has facilitated the identification of possibilities for each island to improve the regional development in these areas. Furthermore, a learning process can be identified, which helps to develop renewable energy systems on these islands, while addressing insular development. [Copyright &y& Elsevier]

Abstract: Because of the needs of sustainable development of the mankind society and natural environment building a renewable energy system is one of the most critical issues that today''s society must address. In the new energy system there is a requirement for a renewable fuel to replace current energy carrier. Hydrogen is an ideal secondary energy. Using solar energy to produce hydrogen in large scale can solve the problems of sustainability, environmental emissions, and energy security and become the focus of the international society in the area of energy science and technology. It has also been set as an important research direction by many international hydrogen programs. The Ministry of Science and Technology of China supported and launched a project of National Basic Research Program of China (973 Program) – the Basic Research of Mass Hydrogen Production using Solar Energy in 2003 for R&D in the areas of solar hydrogen production. The current status of solar hydrogen production research is reviewed and some significant results achieved in the project are reported in this paper. The trends of development and the future research directions in the field of solar hydrogen production in China are also briefly discussed. [Copyright &y& Elsevier]

Abstract: The development of a combined cooling, heating, and power (CCHP) system in China is presented in this paper. The key scientific problems of a distributed energy system and the integration principles of a CCHP system are also pointed out. Moreover, two corresponding CCHP systems: one with the complementarities of fossil fuels energy and renewable energy, and the other integrated with desalination technology, are investigated. With special attention to thermal energy utilization, the integrating characteristics of these systems are likewise revealed, and the important role that the principle of cascade utilization of physical energy plays in system integration is identified. We have found that the energy-saving ratio of the integrated CCHP systems can be as high as 30%, and as such, the innovative CCHP systems suitable for China''s sustainable development are also recommended. [Copyright &y& Elsevier]

This study explored the relationship between renewable energy consumption and economic growth from new risk-based perspectives, including political risks, financial risks, economic risks and composite risks. The study uses a panel threshold model to empirically analyze panel data for the Organization for Economic Cooperation and Development (OECD) countries from 1997 to 2015. The results show when composite risks and political risks are used as threshold variables, there is a single threshold between renewable energy consumption and economic growth. When that threshold is exceeded, the positive effect of renewable energy on economic development increases. When economic risks and financial risks are used as threshold variables, there is a double threshold between renewable energy consumption and economic growth. When the first threshold value is exceeded, but not the second, renewable energy positively impacts economic development. However, when economic risk and financial risk do not lie between the two threshold values, there is an insignificant negative correlation between renewable energy consumption and economic growth. [Display omitted] • This paper explores the impact of country risks on renewable energy consumption and economic growth. • At different risk levels, the impact of renewable energy consumption on economic development is different. • When the composite risk and political risk crosses the threshold, the positive effect is significantly enhanced. • Effect is positive only if economic risks and financial risks crosses the first threshold but not crosses the second. [ABSTRACT FROM AUTHOR]