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Abstract The present work attempts to devise an efficient method utilizing an on-grid photovoltaic-thermal heat pump water heater (PV-THPWH) integrated with a real-time variable frequency controller to achieve the goal of energy-efficient buildings. The prime focus is to reduce the grid's dependence on the compressor's energy-intensive operation by employing a feedback-controlled variable frequency drive (VFD). Additionally, the possibilities involved with addressing the electrical and thermal energy requirements of an energy-efficient building was investigated utilizing the proposed system. R-32 refrigerant in the photovoltaic-thermal (PV-T) evaporator coils of the heat pump assembly help to cool the photovoltaic (PV) panel while delivering the absorbed heat in the condenser to heat water contained inside the storage tank. Outdoor experiments and theoretical investigations of the combined system were carried out to appraise the dynamic behavior under varying solar irradiation and ambient temperature conditions. The observations conveyed that the PV-THPWH system succeeded in reducing the PV panel operating temperature by 25%, which resulted in a 20% increment in PV power output. Also, the performance indicators, such as the instantaneous energy efficiency and instantaneous PV efficiency, were found to increase by 15% and 34%, respectively, resulting in an average coefficient of performance of 6.4. For a clear sky day, the recorded total PV energy output was 4.67 units, while the VFD compressor consumption was 3.42 units, and the surplus 1.25 units were sent to the grid. Furthermore, the economic analysis reported a payback period of 2.3 years for the developed PV-THPWH system.

Algae production process is a key cost center in production of biofuels/bioproducts from microalgae. Decline in the growth of algae in outdoor ponds during non-optimal conditions is one of the hurdles for achieving consistently high algal production rates. An optimal controller can be used to overcome this limitation and provide reliable growth in outdoor conditions. A model predictive controller (MPC) was developed to optimize the algal growth, predicted by flux balance analysis, under natural disturbances, embedding within the cost function, the economic and environmental constraints associated with the process. The model, developed in MATLAB, was validated on a 30-L continuous algal culture under light, temperature and a combination of light and temperature disturbances. The MPC proved effective in minimization of a decrease in growth under these natural disturbances. The growth rates with MPC were observed to be 79-116% higher as compared to the non-MPC growth.

Abstract Date biomass is a carbon-rich renewable resource that can be considered a potential carbon-rich substrate for energy generation over anaerobic digestion (AD). However, due to its complex nature, appropriate pretreatment is necessary to achieve a higher methane yield. Hence, the current study was envisioned to evaluate the influence of three different pretreatment strategies, namely acid, alkali, and hydrothermal pretreatment on biochemical methane potential (BMP) of seven diverse sorts of Algerian date biomass, namely Pedicels, Fibrilium, Petiole, Fruit bunch, Spath, Palm, and its mixture. Among all the pretreatment conditions, alkaline pretreatment highly influenced the lignin composition of date biomass and showed higher BMP. Among all sorts of biomass, higher BMP was detected through Palm as 295.9 mL CH4/g-TS, whereas the lowest BMP values were recorded with Petiole as 226.74 mL CH4/g-TS. Among all the experimental variations, ammonium pretreated Palm biomass documented the highest substrate conversion efficiency (63.80%), which correlates well with the observed higher BMP values. Nevertheless, there was a very marginal improvement in BMP detected in the case of other pretreatment strategies compared to alkaline pretreatment. This might be due to the efficacy of the applied pretreatment method on delignification of date biomass.

Abstract The rapid increase in energy demand and the limited resources of fossil fuel as well as the environmentally damaging effects, drive the world to find new options for sustainable electricity generation, which is represented by renewable energies. Concentrating solar power (CSP) is one of the most promising technologies in the field of electricity generation to tackle this issue with a competitive cost in the future. This paper presents an investigation of the potential of implementation of CSP plants in Libya. The socio-economic context, current energy situation of the country and different types of CSP plants are discussed. Moreover, an assessment of site parameters required for CSP plants including solar resources, land use and topography, water resources and grid connections are investigated in detail. In addition, thermo-economic simulation of a 50 MW parabolic trough power plant is performed. The simulation is conducted based on meteorological data measured by the weather station installed at the Centre for Solar Energy Research and Studies (CSERS) in Tajoura city. The performance results are compared with the reference plant Andasol-1 in Spain. Even though the proposed plant is located on the North coast where solar resources are at their minimum compared with other regions of the country, the outcome of the study proves that Libya is not only suitable but it can be economically competitive in the implementation of CSP technology.

Abstract This study develops a novel sustainability assessment methodology for energy systems using life-cycle emission factors and sustainability indicators. Here, the global warming and environmental impact dimensions of the sustainability assessment methodology are examined in detail. A comparative analysis shows that a wind-battery system produces fewer potential global warming, stratospheric ozone depletion, air pollution, and water pollution impacts compared to a gas-fired system. The wind-battery system generates 13% of the life-cycle GHG emissions and 22% of the life-cycle ozone-depleting substance emissions of a gas-fired power plant. Nitrous oxide contributes more than 90% of the stratospheric ozone depletion potential of gas-fired and wind-battery systems.

Abstract This study demonstrates the possibility to use energy-cost optimal building designs based on life cycle approach. There is a lack of studies that cover the comprehensive assessment of both embodied energy (EE) and operational energy (OE) in a single optimization problem. The primary goal of the current study is to compare the optimized results of using OE+EE together and OE only. The optimization is performed on a case study building (townhouse) in Finland with three structural alternatives (i.e., reinforced concrete (RC); cross-laminated timber (CLT) and Steel). Different options for insulation thickness of external wall, roof, floor and window types were considered as decision variables as the scope of the present study is on building envelope. The objectives of the optimization are to minimize life cycle energy (LCE) and life cycle costs (LCC). The LCE difference between the most and least energy efficient solution on the pareto front is greater in case of the OE optimization, compared to OE+EE optimization. For all studied structures, the EE of the optimal solutions from OE+EE optimization ranges 16%–23% of LCE. Many of the non-dominated optimal solutions obtained from the OE+EE optimization shows a higher U-value for the building envelope components compared to the optimal solutions from the OE optimization. A relationship between both OE and EE with the overall thermal resistance of the building envelope is discussed to obtain a deeper understanding of such differences in U-value for the optimal solutions obtained from the OE+EE and OE optimization.

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 A forecast of transport activity, energy consumption and carbon dioxide emissions from transportation, carried out under ‘business as usual’ economic assumptions, is presented for the 10 countries of Central and Eastern Europe that have acquired the status of ‘accession countries’ to the European Union. Energy demand is projected under considerations of the dynamic evolution of transport modes and their use, the evolution of automotive fuel prices, which are assumed to gradually converge with Western European price levels within the current decade, and assumptions on efficiency improvements in all transport modes according to current technological trends and European regulations. The results, showing transportation energy demand to double and CO2 emissions to be 70% higher in 2030 compared to 2000, are compared with other published forecasts and discussed with a view to potential future energy and environmental impacts in these countries, outlining major policy implications.

Abstract Social acceptance of innovative technologies is a key element of an effective transition towards more sustainable energy economies. However, innovative technologies like genetic modification also tend to spark controversy and backlash. So far, efforts to inform the public about any risks and benefits of novel technologies not only have struggled to foster acceptance but also neglect the interdependent foundations of consumer decision-making. Through a controlled experiment with German consumers (N = 322), we examine whether consumer support and rejection of genetic modification in bioenergy crops is influenced by the statements and actions of actors throughout the supply chain. In specific, we show that the decision of energy companies to sell and support GM bioenergy positively impacts consumer decisions to support. To ensure that decision outcomes were specifically impacted by the expressions of corporate actors, we controlled for the content and valence of information by random assignment to one of three treatments in which participants received positive, negative, or balanced (risks and benefits) information. We find that negative messaging diminished support and increased rejection relative to the other treatments. Lastly, the statements and actions of corporate actors also exerted an indirect influence on consumer decisions through their interactions with social trust and labels, e.g. greater support by farmers had a positive influence only for those who are more generally trustworthy. Given these results, we anticipate more attention to the importance of actors such as farmers and energy companies for the social acceptance of novel technologies in the energy sphere.