Researchers are now focusing on inorganic halide-based cubic metal perovskites that are not toxic as they strive to commercialize optoelectronic products and solar cells derived from perovskites. This study explores the properties of new lead-free compounds, specifically GaGeX3 (where X = Cl, Br, and I), by executing first-principles Density Functional Theory (DFT) to analyze their optical, electronic, mechanical, and structural characteristics under pressure. Assessing the reliability of all compounds is done meticulously by applying the criteria of Born stability and calculating the formation energy. As discovered through elastic investigations, these materials showed anisotropic behavior, flexibility, and excellent elastic stability. The electronic band structures, calculated using both HSE06 and GGA-PBE functionals at 0 GPa, reveal fascinating behavior. However, computed band structures with non-zero pressures using GGA-PBE. Here, the conduction band moved to the lower energy when the halide Cl was changed with Br or I. In addition, the application of hydrostatic pressure can lead to tunable band gap properties in all compounds such as from 0.779 eV to 0 eV for GaGeCl3, from 0.462 eV to 0 eV for GaGeBr3 and from 0.330 eV to 0 eV for GaGeI3, resulting transformation from semiconductor to metallic. Understanding the origins of bandgap changes can be illuminated by examining the partial and total density of states (PDOS & TDOS). When subjected to pressure, all the studied compounds showed an impactful increase in absorption coefficients and displayed exceptional optical conductivity in both the visible and UV zones. Yet, GaGeCl3 is a more effective UV absorber because it absorbs light more strongly in the UV area. Moreover, GaGeI3 stands out among the compounds examined due to its impressive visible absorption and optical conductivity, which remain consistent under varying pressure conditions. Besides, GaGeI3 exhibits higher reflectivity when subjected to pressure making them suitable for UV shielding applications. At last, these metal cubic halide perovskites without lead present promising opportunities for advancing optoelectronic technologies. With their tunable properties and favorable optical characteristics, these materials are highly sought after for their potential in solar cells, multi-junctional solar cells, and different optoelectronic functions.

We consider the scheduling of battery charging of electric vehicles (EVs) integrated with renewable power generation. The increasing adoption of EVs and the development of renewable energies contribute importance to this research. The optimization of charging scheduling is challenging because of the large action space, the multi-stage decision making, and the high uncertainty. To solve this problem is time-consuming when the scale of the system is large. It is urgent to develop a practical and efficient method to properly schedule the charging of EVs. The contribution of this work is threefold. First, we provide a sufficient condition on which the charging of EVs can be completely self-sustained by distributed generation. An algorithm is proposed to obtain the optimal charging policy when the sufficient condition holds. Second, the scenario when the supply of the renewable power generation is deficient is investigated. We prove that when the renewable generation is deterministic there exists an optimal policy which follows the modified least laxity and longer remaining processing time first (mLLLP) rule. Third, we provide an adaptive rule-based algorithm which obtains a near-optimal charging policy efficiently in general situations. We test the proposed algorithm by numerical experiments. The results show that it performs better than the other existing rule-based methods.

CO2 capture from coal power plants is an important and necessary solution to realizing carbon neutrality in China, but CCS demonstration deployment in power sector is far behind expectations. Hence, the reduction potential of energy consumption and cost for CCS and its competitiveness to renewable powers are very important to make roadmaps and policies toward carbon neutrality. Unlike the popular recognition that capturing CO2 from flue gases is technically and commercially mature, this paper notes that it has been proved to be technically feasible but far beyond technology maturity and high energy penalty leads to its immaturity and therefore causes high cost. Additionally, the potential energy penalty reduction of capture is investigated thermodynamically, and future CO2 avoidance cost is predicted and compared to renewable power (solar PV and onshore wind power). Results show that energy penalty for CO2 capture can be reduced by 48%-57%. When installation capacity reaches a similar scale to that of solar PV in China (250 GW), CO2 capture cost in coal power plants can be reduced from the current 28-40 US$/ton to 10-20 US$/ton, and efficiency upgrade contributes to 67%-75% in cost reduction for high coal price conditions. In China, CO2 capture in coal power plants can be cost competitive with solar PV and onshore wind power. But it is worth noting that the importance and share of CCS role in CO2 emission reduction is decreasing since renewable power is already well deployed and there is still a lack of large-scale CO2 capture demonstrations in China. Innovative capture technologies with low energy penalties need to be developed to promote CCS. Results in this work can provide informative references for making roadmaps and policies regarding CO2 emission reductions that contribute towards carbon neutrality.

High conversion ratio dc-dc converters have received significant attention in renewable energy systems, primarily due to their necessary high-gain characteristics. This research proposes a high step-up ratio full-bridge resonant cascaded (FBRC) dc-dc converter designed for use in photovoltaics (PV), fuel cells (FC), electric vehicles (EV), and other low-voltage output energy sectors to achieve high voltage gain. This converter contains a full-bridge cell with a boost input inductor, a diode-capacitor cascaded stage that replaces the transformer as a voltage multiplier and an inductor-capacitor (LC) parallel-series resonant network across the FB terminal. One of the strategic features of the converter is its high voltage step-up characteristic combined with lower duty cycle operation that limits the maximum current through the active devices, making it particularly suitable for systems that generate low output voltage. In addition, zero-voltage switching (ZVS) is achieved during the turn-off and turn-on operation of the FB switches from 25% to full load, thereby lessening the switching losses. Moreover, the diminished necessity for passive components and the decreased voltage stress on both active and passive devices lead to the use of smaller and more cost-effective components. The theoretical analysis of the proposed converter is validated using a 500 W laboratory-scale prototype wherein high-performance SiC-based MOSFETs have been utilized as switching devices. It offers reduced ripples, with input current ripple at 5% and output voltage ripple at 0.76%. When the load is 400 W and 60 V as the input voltage, the maximum efficiency is found 95.8% at 400 V output voltage. The proposed dc-dc converter, with its high voltage gain and reduced component stress, shows significant promise for application in renewable energy systems.

This study presents a novel approach to integrating combined cooling, heating, and power (CCHP) systems with water desalination for enhanced energy and water management in educational buildings. Two distinct layouts for CCHP and desalination systems are introduced: one prioritizing efficient power generation to meet electricity demands while providing waste heat for desalination, and the other focusing on balancing cooling and heating loads alongside water desalination. Both layouts are tailored to meet the building\'s energy and water demands while considering operational efficiency. Optimization of these layouts against traditional systems using the bat search algorithm emphasizes economic viability and the gas engine\'s operational flexibility, which are crucial for partial load operation. In addition, an environmental assessment compares the proposed CCHP-desalination systems with conventional setups, assessing CO2 emission reductions and overall sustainability. The evaluation encompasses key environmental metrics, such as resource consumption and the integration of renewable energy sources. Results highlight significant CO2 emission reductions across various gas engine capacities, with notable enhancements in economic and environmental performance achieved by selecting a 3,250 kW gas engine within the CCHP-desalination system. This choice not only maximizes the annual profit but also reduces CO2 emissions by 57% compared to conventional systems, underscoring the system\'s sustainability benefits.

Assessing and analyzing the complementary characteristics of renewable energy (RE) is crucial for designing, operating, and optimizing multi-energy complementary systems (MECSs). However, unified and precise quantitative descriptions of the complementary and stability characteristics among various energy outputs in MECSs have lacked attention and research. Here, this study innovatively proposed a mathematical model for the multi-energy complementarity index (MECI), which considers the complementarity rates of multiple energy outputs during zero and non-zero output periods, and a mathematical model for the multi-energy volatility index (MEVI), which accounts for fluctuation thresholds and the overall volatility of output processes. An evaluation system for multi-energy complementarity characteristics qualitative analysis has been established. The natural output processes of RE at three MECSs in China were applied in the case calculations and verification. Results show that the hydropower rated discharge (Qrating) has a significant negative correlation with MECI, with the MECI decreasing by an average of 0.0046 for every 5 m³/s increase in Qrating. The relationship between the Qrating and MEVI shows an overall negative correlation with local fluctuations. Notably, The MECI of the BeiPan River MECSs exhibits significant seasonal characteristics, with the MEVI in summer (0.378) and autumn (0.395) higher than those in spring (0.132) and winter (0.160), closely related to the natural seasonal variations of the three energy sources: water, wind, and solar. We believe that the study can assist in evaluating and making decisions on the multi-energy complementarity characteristics of RE bases in the future, making a significant contribution to achieving dual carbon goals.

In today\'s world, where the dramatic effects of climate change continue to increase, it is critical to turn from fossil fuels to renewable energy sources to achieve the CO2 emission reduction targets that countries have committed at the Paris Climate Agreement and COP 27 conference. This study analyzes the effects of macroeconomic factors, including economic growth, investments, and unemployment, on the transition to renewable energy in OECD countries. From 1996 to 2020, long-run relationships between variables were examined using advanced econometric methodologies for empirical analysis. For this purpose, panel data analysis, second-generation panel unit root tests, cross-sectional dependence tests, and panel cointegration tests were applied. Economically, in the long run, according to panel CCEMG and AMG estimator, while economic growth enhances the renewable energy transitions, investment does not statistically promote an impact on the renewable energy transitions. Renewable energy transition increases with unemployment. Moreover, the role of the considered variables in the renewable energy transition varies among country-specific. Within the framework of the results obtained, it has been proven that before determining policies for renewable energy transformation, it is necessary to do the necessary groundwork in the economy to increase economic growth and investments and reduce unemployment.

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The Royal Society and UK Department for International Development supported a consortium of three universities across sub-Saharan Africa and Imperial College London with the aim of developing new knowledge on direct-steam-generation concentrated solar power (CSP) plants and supporting relevant capacity building across the Universities of Lagos, Mauritius and Pretoria. Key research findings from the programme include an improved flow-classification scheme for two-phase, liquid-liquid flows; testing of advanced surfaces with much-improved steady-state heat transfer performance-the commercial nanoFLUX surface showed up to 200% higher heat-transfer coefficients (HTCs) in pool boiling compared with other surfaces with R-134a/R-245fa; first-of-a-kind measurements of transient flow boiling HTCs, which were up to 30% lower in step perturbations than quasi-steady-state expectations in horizontal pipes with R-245fa; error estimation and corrections for laser-induced fluorescence (LIF) measurements, leading to the development of an adapted planar LIF technique with uncertainty <10% for local, instantaneous film thickness measurements in annular flows, and the application of such diagnostic methods to pool, falling-film and flow boiling in pipes; and predictions of an ~80% increase in the net present value of a case-study CSP plant when integrated with solid storage media.

The economic management of lignocellulosic biomass from semi-natural grasslands is now a challenge across Europe. The abandonment of mowing these grasslands leads to the gradual degradation of these ecosystems. This study investigates how chemical and biological factors affect the suitability of biomass from abandoned grasslands for biogas production. We sampled 30 mown and 30 abandoned grassland sites in the Sudetes Mountains (Poland and Czechia). The cover contribution of short herbs was found to be significantly higher in mown grasslands (p < 0.001), while that of tall herbs was more prevalent in abandoned grasslands (p < 0.01). The specific biogas yield (SBY, NL kg-1 volatile solids) is negatively affected by an increased percentage of herbs in the biomass of mown and abandoned grasslands. This is due to the inhibitory effect of herbs on biodegradation, the increase in lignin content and the decrease in cellulose. This study highlights the importance of individual plant species in assessing grassland biomass for area biogas yield (ABY, m3 ha-1) and provides new insights into a field that has not yet been extensively investigated. In mown grasslands, ABY was most positively correlated with grass species (Arrhenatherum elatius, Trisetum flavescens and Festuca pratensis). In abandoned grasslands, the ABY was most correlated with herbaceous species (Galium aparine, Urtica dioica and Chaerophyllum aromaticum) and grasses (A. elatius and Elymus repens). Mown grasslands had significantly higher species richness (p < 0.001) compared to abandoned grasslands, but the number of species sampled did not correlate with SBY and ABY. This study contributes to the development of a sustainable bio-economy by highlighting the need for efficient use of grassland biomass. This approach helps protect semi-natural ecosystems and facilitates sustainable management of renewable resources.