• Energy Research
• Restricted close
• Embargo close
• 7. Clean energy close
• 2. Zero hunger close
• CN close
• IN close
• SA close

The present study is motivated by the need to decouple economic growth from environmental degradation given the new wave of chase for higher economic growth trajectories comes with its environmental cost implications, especially among developing blocs like the Emerging 7 (E7) countries. There is a consistent trade-off between economic growth versus environmental quality. Government apparatus are perpetually on the chase for low-carbon emission policies via the pursuit for green economy. To this end, this present study extends the conventional environmental Kuznets curve (EKC) argument by incorporating the role of institution in emerging industrialized economies (E7) and using second-generation panel analysis methods like mean group (MG), augmented mean group (AMG), common correlated effects mean group (CCEMG), and the Dumitrescu and Hurlin causality test for more robust estimates and inferences. To this end, we explore the long-run and causality relationship between economic growth, quadratic form of economic growth, institutional quality, trade flow, investment in energy sector, and financial development in an EKC environment. Empirical analysis established a long-run equilibrium relationship among the outlined variables over the study period. The long-run regression shows the presence of EKC in the E7. Thus, suggesting the preference for GDP growth over environmental quality at the earlier stage of growth curve. Interestingly, investment in energy, trade flow dynamics across the blocs, and financial development dampens the detrimental effect of environmental pollution as we observed negative relationship with the ecological footprint. On the contrary, quality of institution is weak as institutional quality increase (worsen) the quality of environment in the E7 economies. From a policy perspective, this current study proposed the need for more stringent environmental treaties and regulations and promotion of green economy without compromising economic growth. In the conclusion part of the study, more details and specifics about the policy blueprint are presented.

The presented article will describe an 'effect-cause' model for the purpose of simulating the energy consumption of DC fed light rail vehicles. The model will assess the advantages of hybrid vehicles in terms of energy consumption, network power and voltage variations, line current and losses; and will help sizing and designing a supercapacitor based energy storage system (ESS) for both on-board, and stationary applications. The proposed modeling needs to allow the ESS sizing according to the objective that needs to be achieved, being braking energy recovery, voltage drop compensation and peak power shaving the most common goals of ESS use in hybrid vehicles. The needed power and energy levels will vary in function of the vehicle features and the driving cycle followed. This all can be determined by the quasi-static simulation tool to ease the design process. Another objective of the modeling tool is to evaluate the behaviour of the vehicle power flow controller, which manages the power from/to the ESS in function of the state of several variables.

Plant-soil feedback (PSF) describes the process whereby plant species modify the soil environment, which subsequently impacts the growth of the same or another plant species. Our aim was to explore PSF by two maize varieties (a landrace and a hybrid variety) and three arbuscular mycorrhizal fungi (AMF) species (Funneliformis mosseae, Claroideoglomus etunicatum, Gigaspora margarita, and the mixture). We carried out a pot experiment with a conditioning and a feedback phase to determine PSF with different species of AMF and with a non-mycorrhizal control. Sterilized soil was conditioned separately by each variety, with or without AMF; in the feedback phase, each soil community was used to grow each in its "home" soil and in the "away" soil. Plant performance was assessed as shoot biomass, phosphorus (P) concentration and P content, and fungal performance was assessed as mycorrhizal colonization and hyphal length density. Both maize varieties were differentially influenced by AMF in the conditioning phase. In the feedback phase, PSF was generally negative for non-mycorrhizal plants or when plants were colonized by G. margarita, whereas PSF was positive in the other three AMF treatments. When plants were grown on home soil, hyphal length density was larger than on away soil. We conclude that different maize varieties can strengthen positive plant-soil feedback for themselves through beneficial mutualists for themselves, but not across the maize varieties.

This paper deals with the medium between two reconfigurable sensor nodes characterized by radio interfaces that support multiple channels for exchanging real-time messages under energy constraints. These constraints are violated if the consumed energy in transmission is higher than the remaining quantity of energy. A reconfiguration, i.e., any addition or removal of tasks in devices and consequently of messages on the medium, can cause the violation of real-time or energy constraints at run time. To achieve a feasible scheduling in time (i.e., message deadlines will be respected) and energy (i.e., there is available energy) on the medium, we propose new dynamic solutions: Balance, Dilute, and a Combination of them to manage any addition or removal of messages. The proposed approach utilizes the energy harvesting techniques and the PowerControl algorithm to reduce the nonharvested consumed energy. The proposed strategies achieve significant improvement over existing methods and provide the highest percentage of adding messages, with a lower average in response time and energy consumption. They reach a percentage of success in adding the highest priority messages while meeting deadlines up to 85%.

The potential of renewable energy should be fully exploited in the transportation sector to achieve a cleaner production. Therefore, this paper proposes an on-grid hybrid hydrogen refueling and battery swapping station powered by wind energy. This novel concept can promote the development of low-carbon emission vehicles including hydrogen-based vehicle and battery electric vehicle. During the daily operation of the station, the multiple uncertainties may lead to a higher operational cost. To address this problem, a hybrid stochastic/distributionally robust optimization method is proposed to handle different uncertainties for the energy management problem. The first type of uncertainties can be depicted by a certain distribution, i.e. electricity price and wind power, which is processed by a stochastic optimization method. The second type of uncertainties is associated with human behaviors and is difficult to find its probability distribution, i.e. the hydrogen demand of hydrogen-based vehicles, so the second type is processed by a distributionally robust optimization method. The overall objective is to minimize the total operational cost of the station, which also considers the battery swapping station overstock punishment. Because a reasonable battery swapping scheduling can reduce the waiting time of users and operational cost of the station. The results indicate that the proposed method can effectively address the conservatism of solutions as its total operational cost is 4.4% lower than that of the hybrid stochastic/robust optimization method under a high confidence level.

Abstract The implementation of energy efficiency measures is an effective way to gain energy savings in the Italian residential sector. This paper assesses the embodied energy impact related to the envelope insulation and evaluates the energy and carbon payback of the efficiency measures. The proposed method consists of (1) an estimation of the baseline operational energy consumption, (2) simulations of realistic retrofit solutions and, (3) the assessment of the ‘retrofitting’ embodied energy and the energy and carbon payback time calculation. The payback is based on the comparison between the saved operational energy and the embodied energy of the materials selected for insulation. Ten Italian cities are analysed, and the results show a deep dependence on the climate zone. In Northern Italian cities, envelope insulation gains relevance as the energy and carbon payback periods are shorter, about 3 years against the 84 years for the Southern city of Palermo. The optimal thickness is estimated for the city of Milan considering the building’s typology, the insulation materials, and the energy payback. This study shows how the total energy savings can be used as a criterion to obtain design indications.

Nanosecond-level transient electromagnetic disturbance (TED), including very fast transient overvoltage caused by operation of disconnectors, high-altitude electromagnetic pulse, and many other fast transients may interfere or even damage the electrical equipment. As one of the main overvoltage protective equipment, the protective performance of metal-oxide surge arresters (MOAs) under nanosecond-level TED should be investigated and then compared with that under microsecond-level TED, especially the lightning impulse. Based on a testing platform containing a 400-kV pulse generator with adjustable rise time from 5 to 100 ns, the behaviors of nonlinearity, fast impulse response, and converting impedances of three types of 10-kV MOAs under TED with different rise time were explored experimentally in this article. The peak residual voltages of 10-kV MOAs under TED with the rise time of 5 ns at 5 kA are 50.2–60.7% higher than those under the lightning impulse. The rise time of TED has significant influence on the peak voltage and impedance converting behaviors of MOAs. A circuit model of 10-kV MOAs under nanosecond-level TED is built and validated by experimental results, which can be applied in insulation coordination and design of protective devices against TED.