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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.

(Abstract) This paper proposes a new power line communication (PLC) architecture for monitoring and remote control of Distributed Generators (DG) and Energy Storage Systems (ESS) connected to low voltage distribution networks. The final aim is to improve the performance of the PLC link in terms of robustness and efficiency in devices addressing. The proposed solution is based on a concentrator, to be installed in secondary substation, and a new PLC bridge, to be linked both to inverters and interface protection systems of DGs or ESSs. In this way, a communication link is obtained between distribution system operator (DSO) and DG or ESS owners. The proposed system is able to provide advanced functions for the remote control of DGs and ESSs inverters, not only in terms of remote disconnection but also in terms of adjusting the inverter operating modes.

An effective controller is proposed for the 'Photovoltaic(PV) - Battery - Diesel Generator(DG)' based hybrid standalone system in this article. A bidirectional DC to DC device which can allow power in both directions is integrated among the DC-link and battery bank to maintain contact voltage by maintaining power balance in the system. Further, a bidirectional inverter is also considered between point of common coupling (PCC) and DC-link for providing supply to AC loads as well as charging the battery from diesel generator based on requirement. However, the phenomenon of partial shading condition (PSC) commonly occurring on PV modules and also generated power from PV always fluctuates according to changes in weather. To achieve a superior performance of the system, a Takagi-Sugeno Fuzzy (TSF) based controllers are implemented in proposed control schemes. The novel control schemes are implemented on a bidirectional DC to DC converter as well as three phase bidirectional inverter. However, the proper deloading process of the PV system should be incorporated into the controller of the DC to DC converter to achieve power balance during light load conditions. Balanced quality voltages (3-phase) at PCC are achieved by inverter control which forces to maintain balanced currents generated by DG during the operation of unbalanced loads. Maintaining balanced DG currents can help to reduce the oscillations on the torque of the shaft which increases the fatigue life. Further the reactive power demanded at PCC is compensated by the inverter control, hence DG need not to provide it which results can reduce the consumption of diesel. Various case studies are examined by using MATLAB to present results and Real Time Digital Simulator (RTDS) based results are also provided in this paper.

This paper presents a control method based on active disturbance rejection control (ADRC) for both the primary and secondary control layers in a hybrid DC/AC microgrid (MG). A DC bus inside MG includes a wind turbine generator, photovoltaic panels, a fuel cell and battery energy storage. Maintaining the DC link voltage under various scenarios is made possible by applying an energy management system (EMS) based on the deviation in the state of charge of the battery and using a fuel cell as a backup. Through a voltage source inverter, the DC bus of the MG is connected to the AC side, which supplies AC loads. Using the proposed ADRC-based control strategy for the inverter, the voltage, frequency, and power flow within the MG would be effectively controlled. In order to demonstrate the effectiveness of the proposed method, a comparison between the ADRC and PI controller has also been implemented in different scenarios, proving the superiority of the suggested controller over classical approaches.

Investigations show that most simulations on solar parabolic trough collectors reported in the literature are one-dimensional or at least with a variety of simplifications. Indeed, for this collector type, due to the complex heat transfer elements as well as two-phase flow through the tubes, etc., such simplifications make the model fail to give an acceptable estimation of the circumferential temperature distribution of the walls, thermal stresses, heat losses, vapor volume fraction, etc. In this article, a detailed three-dimensional numerical modeling of solar parabolic trough collectors is presented. The results of this model are also compared to those given by an axisymmetric model and a one-dimensional nodal model to highlight the impacts of such a rigorous model on the accuracy of the final results. The results demonstrated that although the axisymmetric and nodal models show acceptable accuracy in predicting the temperature and enthalpy for the flow, they are quite incapable of precisely calculating the vapor volume fraction and heat loss rates. The discrepancy in the distribution of vapor volume fraction in different sections of the absorber tube causes significant temperature heterogeneity in the solid walls.

Electric vehicles (EVs) are considered a substitute for fossil-fueled vehicles due to rising fossil fuel prices and accompanying environmental concerns, and their use is predicted to increase dramatically shortly. However, the widespread use of EVs and their large-scale integration into the energy system will present several operational and technological hurdles. In the energy industry, an innovative solution known as the EVs smart parking lot (SPL) is introduced to handle EV charging and discharging electricity and energy supply challenges. This paper investigates social equity access and mobile charging stations (MCSs) for EVs, where the owner of MCSs is the EV parking lot. Accordingly, a new self-scheduling model for SPLs is presented in this paper that incorporates scheduling of the MCSs as temporary charging infrastructures while considering social equity access and optimizes SPL energy generation and storage schedule. The main objectives of this research are to (i) develop MCSs accessibility measures and quantify the equity impacts of MCSs locations by modeling prioritized demand based on several indices; (ii) determine the optimal set-points of SPL components (i.e., combined heat and power (CHP), photovoltaic system, electrical and heat-energy storage, and MCSs) to manage electrical peak demand and to maximize the economic benefits of SPLs. Results indicate that the proposed demand prioritization function model can meet the required EV charging demands for prioritized events, and the self-scheduling model for SPLs satisfies the charging demand of the EVs in the SPL location. Also, the social equity access to the EV charging stations is satisfied by analyzing the operation of MCSs around the prioritized demand of the prioritized events and social equity access indices.

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.

This article combines two neglected elements within the history of online news: public service news sites and weather reporting, and it does so by utilising web archives, which – surprisingly – do not figure very prominently in journalism history. The two elements have – in isolation and in combination – at least in Denmark, become increasingly important as the online news sections of the two public service institutions Denmark’s Radio (DR) and TV2 consistently are among the most visited news sites and since reporting on the weather has gained in prominence and more recently, at least on DR TV, has become increasingly educational in its linking to issues of climate change. This article focusses on online news and conducts a historical analysis of the weather reporting on DR.dk from 2005 to 2022. The analysis seeks to balance the coding of journalistic texts with considerations of the online form of journalism, which here broadly means reading the webpage as a text. A key focus in the analysis is how meteorological data have been woven into cultural and social narratives, some of which are linked to climate change.