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The annual consumption of petroleum products in India was about 221 million metric tons in 2015. Of this, 84% was imported. The Indian industrial sector accounts for about 16%-20% of the total fuel consumption for thermal energy for different heating applications in the temperature range of 50°C--250 °C. Solar collectors can meet these temperature requirements and offer the possibility to mitigate the consumption of oil. This study highlights the fact that conversion efficiency from solar energy is much higher for process heating than for electricity generation and that process heating applications constitute a significant share of industrial energy consumption. In this paper, a methodology has been developed to estimate the potential for integration of solar collectors for process heating. The methodology employs process operating temperatures to select the type of solar collectors. The size of the solar field is estimated taking into account the thermal heat loads, working fluid and temperatures of these processes, the efficiency of the chosen solar collectors, location-based solar irradiance and capacity utilization of the solar collectors. The proposed methodology has been validated with a software tool called System Advisor Model (SAM). The techno-economic analysis will indicate the viability of solar systems for integration in industries. Therefore, the consociated parameters on economic (capital cost, fuel oil savings, monetary benefits), financial (Payback periods, Rates of Returns) and environmental (Carbon savings) are estimated. Further, the methodology has been applied to select Indian industries to verify its potential quantitatively. The industries selected include Textile, Pulp & Paper, Dairy, Leather and Automobile. Process-wise energy demands are considered while estimating the potential as the fuel requirement offset by solar energy in terms of absolute fuel oil savings, monetary benefits and carbon savings. The other economic and financial parameters mentioned above were estimated to verify the capability and present the market position of solar systems. Further, sensitivity analyses have been performed with respect to solar energy penetration and fuel oil prices to address the viability of integration of solar energy for process heating. [ABSTRACT FROM AUTHOR]

Research on energy-saving retrofits of the existing industrial systems can effectively improve the systems' energy-saving level and increase company revenue. The energy-saving bottleneck diagnosis for systems is the foundation of the energy-saving retrofit design. The diagnosis also aims to yield a more targeted energy-saving retrofit, thus ensuring the energy-saving effect and investment income of the transformation project. Therefore, this paper proposes a new method to diagnose the energy-saving bottleneck of the existing industrial systems. First, the energy-saving bottleneck diagnosis is decomposed into two parts: the diagnosis of energy-saving bottleneck units and the diagnosis of energy-saving bottleneck factors. Then, the energy density decomposition method is improved and a multi-mode energy efficiency density decomposition method is proposed. Next, an energy-saving bottleneck diagnosis method for industrial systems based on multi-mode energy efficiency density decomposition and an orthogonal test method is proposed. The proposed method can analyze the energy-saving potential of existing systems, accurately locate energy-saving bottlenecks, and avoid the dependence on a large amount of expert experience or complete production data in the existing methods. Finally, the proposed method is applied to an actual circulating cooling water system and the system energy-saving bottleneck diagnosis is realized, thus verifying the practicability of the method. • Energy-saving bottlenecks in industrial systems are analyzed and decomposed. • A method for energy-saving bottleneck diagnosis from two directions is proposed. • An improved energy efficiency density decomposition method is proposed. • The diagnosis of energy-saving bottlenecks in industrial systems is achieved. • The verification is performed for an industrial circulating cooling water system. [ABSTRACT FROM AUTHOR]

As China gradually completes the process of industrialization, its industrial energy consumption growth is now slowing and even decreasing. Meanwhile, household energy consumption in the residential sector has seen steady growth. This paper aims to explore the mechanisms of factors affecting urban household energy-saving behavior including the habitual energy-saving behaviors and purchasing energy-saving behaviors. A structural equation model is built to analyze the influencing routes and effects of individual objective and subjective characteristic factors, external influencing factors, and energy-saving intentions on shaping energy-saving behaviors. The empirical results drawing on the survey data collected in Shandong province show that external influencing factors that have two kinds of mediating effects through energy-saving intentions and individual subjective characteristic factors are the most crucial factors to energy-saving behaviors. Values included in individual subjective factors and quality of energy-saving products included in external influencing factors have greatest effects on energy-saving behaviors. [ABSTRACT FROM AUTHOR]

The energy consumption of China’s six most energy-intensive sub-industries is about half of the total national energy consumption, and accounts for more than 70% of industrial energy consumption in recent years. These six industries are capital and energy intensive and have a great impact on the energy consumption of China, so they are directly related to the achievement of the energy conservation goal in the 13th Five Year Plan. This paper investigates the influential factors of energy consumption in the industries by employing the cointegration method, and estimates the possible energy conservation potential considering energy rebound effect. The results show that GDP and the scale of industries are the deterministic factors increasing energy consumption, while R&D intensity decreases it. Energy price has little impact on energy consumption. The average energy rebound effect is calculated using the latent variable approach and the result is 90.75%. Considering energy rebound effect, the energy conservation potential of China’s energy intensive industries is 14.18–26.54 million tons of standard coal equivalent in 2020 and 44.64–80.72 million tons of standard coal equivalent in 2030. [ABSTRACT FROM AUTHOR]

Promoting energy efficiency technologies (EETs) in heavy industrial sector is a crucial approach for energy conservation worldwide. Due to the existence of various barriers, the diffusion of EETs is often slow and is largely influenced by policy incentives. Insufficient consideration of the heterogeneity of EETs makes the one-size-fits-all policy design scheme ineffective and inefficient in practice. Therefore, this paper analyzes the design of differentiated technology policies to accelerate the promotion of EETs. The analysis is based on technology classification results from a bottom-up technology evaluation system. Technical attributes were qualitatively analyzed and the 130 total technologies were divided into three segments: 76 main production-process technologies (PP), 39 process-integrated resource and energy recycling technologies (RER) and 15 pollution control technologies (PC). Then the 115 PP and RER technologies were quantitatively analyzed by calculating benefit-cost ratio, investment payback time and technical penetration. The evaluation results proved that EETs had marked differences in economic efficiency and technical maturity, with dynamic investment payback time ranging from 0.3 to 11 years and penetrations ranging from 1% to 80%. Graphing investment payback time on a vertical axis and technical penetration on a horizontal axis, the 115 technologies were classified into four quadrants. Features and policy-support demands of those three types of technologies in the four quadrants were discussed and corresponding technology policies were proposed. The thorough technical investigations in this study also provided a complete technological database for policy-making, which was freely offered on the website of China's Ministry of Industry and Information Technology. [ABSTRACT FROM AUTHOR]

The industrial sector in China is energy-intensive and accounts for more than 60% of the nation's total energy consumption (demand). Narrating the story behind the growth of China's industrial energy consumption could help us understand the past and prepare for the future. This paper aims to investigate the factors affecting China's industrial energy consumption in the 21st century by using an extended production-theoretical decomposition approach (PDA) with considering the technological gap and scale of the economy effects. The new proposed decomposition framework includes four new factors, namely, the energy technological gap, the output technological gap, energy scale efficiency, and output scale efficiency. The results show that in the 21st century, the energy consumption of China's industry increased by more than one billion tons of standard coal. The expansion of the industrial economy is a dominant driver of China's industrial energy consumption, while potential energy intensity, energy technology, and output technology are the three largest energy-saving factors. In addition to the conventional factors, the newly proposed factors also have important effects on China's industrial energy consumption. Specifically, output scale efficiency is an energy-saving factor, while the energy technological gap, output technological gap, and energy scale efficiency are drivers of energy consumption. This suggests that China's industry is at the stage of returns to scale that is beneficial to output performance but harmful to energy performance. Meanwhile, the widening of the industrial technological gaps has negative impacts on China's industrial energy conservation. The proposed decomposition approach can provide information that cannot be obtained from traditional approaches and it can also be applied to many other cases for investigating feasible paths of energy-saving and emissions reduction. • A newly extended decomposition approach was proposed in this study. • The approach can quantify the effects of technological gap and scale economy. • Drivers of China's industrial energy consumption were investigated as a case. • The newly provided factors do have impacts on China's industrial consumptions. • It can provide information that cannot be obtained from traditional approaches. [ABSTRACT FROM AUTHOR]