• Energy Research
• Closed Access close
• Embargo close
• 9. Industry and infrastructure close

Scientifically evaluating the level of low-carbon development in terms of theoretical and practical significance is extremely important to coal enterprise groups for implementing national energy-related systems. This assessment can assist in building institutional mechanisms that are conducive for the economic development of coal business cycle and energy conservation as well as promoting the healthy development of coal enterprises to realize coal scientific development and resource utilization. First, by adopting systematic analysis method, this study builds low-carbon development evaluation index system for coal enterprise groups. Second, to determine the weight serving as guideline and criteria of the index, analytic hierarchy process (AHP) is applied using integrated linear weighted sum method to evaluate the level of low-carbon development of coal enterprise groups. Evaluation is also performed by coal enterprise groups, and the process comprises field analysis and evaluation. Finally, industrial policies are proposed regarding the development of low-carbon coal conglomerate strategies and measures. This study aims mainly to guide the low-carbon development of coal enterprise groups, solve the problem of coal mining and the destruction of ecological environment, support the conservation of raw materials and various resources, and achieve the sustainable development of the coal industry.

Smart grids have attracted increasing interest in the field of industrial research. These systems allow electricity consumers to communicate with electrical systems using bidirectional communications. However, these bidirectional channels may introduce privacy threats to consumers. Considerable research has been conducted with the aim of resolving these threats. Unfortunately, a practical smart grid design with adequate efficiency and security functionalities has not yet been produced. In this paper, we propose lightweight privacy preserving metering protocols by designing a distributed authentication method to further increase the speed of the message authentication process. We confirmed the efficiency and security of our method by performing a detailed analysis.

A balance between industrial pollution and economic growth becomes a major policy issue to attain a sustainable society in the world. To discuss the problem from economics and business perspectives, this study proposes a new use of DEA (Data Envelopment Analysis) as a methodology for unified (operational and environmental) assessment. A unique feature of the proposed approach is that it separates outputs into desirable and undesirable categories. Such separation is important because energy industries usually produce both desirable and undesirable outputs. This study discusses how to unify the two types of outputs under natural and managerial disposability. The proposed DEA approach evaluates various organizations by the three efficiency measures such as OE (Operational Efficiency), UEN (Unified Efficiency under Natural disposability) and UENM (Unified Efficiency under Natural and Managerial disposability). An important feature of UENM is that it separates inputs into two categories and unifies them under the two disposability concepts in addition to the proposed output separation and unification. This study incorporates an amount of capital assets for technology innovation, as one of the two input group, into the measurement of UENM. Then, it compares UENM with the other two efficiency measures. This study is the first research effort in which DEA has an analytical capability to quantify the importance of investment on capital assets for technology innovation. To confirm the practicality of the proposed approach, this study applies the three efficiency measures to a data set regarding manufacturing and non-manufacturing industries of 47 prefectures in Japan. This study empirically confirms the validity of Porter hypothesis in Japanese manufacturing industries, so implying that environmental regulation has been effective for betterment on the performance of Japanese manufacturing industries. Another important finding is that the emission of greenhouse gases is a main source of unified inefficiency in the two groups of industries. Therefore, Japanese industries, examined in this study, need to make their efforts to reduce the greenhouse gas emissions and air pollution substances by investing in capital assets for technology innovation.

Abstract This study sheds new light on the variability of wind power across the Australian NEM (National Electricity Market) and in doing so gives an insight on the potential network configuration for a high RE (Renewable Electricity) future. We present idealised cost-minimised simulations for the NEM utilising onshore wind, large-scale solar, pumped hydro and OCGT (open cycle gas turbines) technologies. A model using gridded meteorological data from the regional ACCESS-R (Australian Community Climate and Earth-System Simulator) simulates wind and solar technology output along with generation from OCGT to meet demand in the NEM for the period 2010–2011. A cost for connecting each location to the nearest major load centre is introduced and a base scenario created from an initial connection cost of $1 M/km. A sensitivity study reveals that a cost of $8 M/km results in the contraction of all renewable resources to four major wind installations. Compared to the base scenario the four major wind locations share much of the variability in renewable energy output, demonstrating that the NEM region has four distinct wind regimes. Separated by 1,400 km these four wind installations provide an optimisation-based decorrelation length for the NEM. This information is particularly useful for long-term planners of large-scale energy infrastructure.

Sustainable development emergent subfields have been rapidly evolving, and their popularity increased in recent years. Sustainable development is a broad concept having numerous sub-concepts including, but not limited to, circular economy, sustainability, renewable energy, green supply chain, reverse logistics, and waste management. This polymorphism makes decision-making in this field to be an abstruse task. In this perplexing circumstance, the presence of VUCA conditions makes decision-making even more challenging. By taking advantage of artificial intelligence tools and approaches, this paper aims to study with a concentration on sustainable development-related decision-making under VUCA phenomena elements using bibliometric and network analyses which can propose numerous novel insights into the most recent research trends in this area by analyzing the most influential and cited research articles, keywords, author collaboration network, institutions, and countries that finally provides results not previously fully comprehended or assessed by other studies on this topic. In this study, an extensive systematic literature review and bibliometric analysis are conducted using 534 research articles out of more than 3600. From the content analysis part, four clusters have been found. The decision parameters, presumptions, and research goal(s) for each model are pointed out too. The findings contribute to both conceptual and practical managerial aspects and provide a powerful roadmap for future research directions in this field, such as how real-life multidimensionality can be considered in sustainable development-related decision-making, or what are the effects of the VUCA in sustainable development considering the circular economy and waste management intersection.

The upsurge in higher education is considered a key determinant for enhancing green growth. Moreover, ICT development is also the main catalyst of green growth. This research explores the role of higher education and ICT on green growth for China from 1995 to 2020. The study employs auto-regressive distributive lag (ARDL) approach for short-run and long-run estimates of green growth. The effect of higher education and ICT on green growth is significantly positive in the long run and short run. The outcomes of the empirical models reveal that financial inclusion is positively associated with green growth in both long run and short run. Moreover, renewable energy consumption is found to have a positive impact on green growth. The findings thus point to the need for policies that promote human capital and ICT infrastructure as a way of accelerating green growth.

Abstract Closed-Loop Supply Chain (CLSC) focuses on acquiring the cores/product returns from consumers, recovering their residual value, and remarketing them. Extant literature on core acquisition management suggests that researchers have not considered behavioral aspect of consumers. On the other hand, marketing literature suggests that researchers neglected technical issues related to core acquisition in a CLSC while discussing consumers' disposition behaviors. We propose a conceptual framework that extends the existing CLSC setting by introducing consumers’ disposition behavior. We develop eleven research propositions based on which we design a survey. The survey was sent to decision making executives of different remanufacturing industries to solicit their perception. Participants were also asked to make paired comparisons using the Analytic Hierarchy Process (AHP), based on which an action oriented framework is developed. Firms that have CLSC operation can use our framework to ensure enhanced quality product returns which in turn increase profitability. Finally, possible future extensions are discussed.

In the light of The Paris Agreement (COP 21), global leaders reached a consensus to curtail the increase in global temperature up to 2.0 °C ideally 1.5 °C pre-industrial level. Likewise, it has become a pathway to accomplish long-term goals of achieving carbon neutrality. In this regard, this paper aims to explore the role of green process innovation and environmental orientation toward environmental performance for achieving the long-term goal of carbon neutrality. In addition, this paper also discovers a mediating role of green competitive advantage in said context. Using data from a survey among managers of equipment manufacturing sector, the study employed structural equation modeling technique and found that green process innovation, environmental orientation and green competitive advantage significantly influence environmental performance. Subsequently, mediation analysis indicated that green competitive advantage partially mediates the relation from green process innovation and environmental orientation to environmental performance. In light of the carbon neutrality targets, the study highlight that improving environmental performance through green process innovation and environmental orientation can be a way-forward for manufacturing sector to play its role to achieve carbon neutrality. The study concludes with theoretical and practical implications.

In this paper, a novel algorithm for calculating distribution load flow (DLF) for smart grid is presented. The algorithm can provide a DLF solution in a specific area of interest in the distribution system without the necessity of including all of the distribution system laterals in the DLF problem. The system laterals excluded from the DLF solution are replaced by equivalent loads using a proposed lumping technique. The proposed DLF zooming method thus reduces the size of the DLF problem and hence minimizes the effect of system size on the DLF solution time. The construction of the DLF problem is based on a novel automated recursive process, which enables fast accommodation of changes in the network topology of smart grid. The simulation results validate the accuracy of the proposed DLF zooming algorithm and provide a favorable evaluation of its performance for smart grid operation.