Sustainable All-Day Thermoelectric Power Generation From the Hot Sun and Cold Universe.

Energy conversion from the environment into electricity is the most direct and effective electricity source to sustainably power off-grid electronics, once the electricity requirement exceeds the capability of traditional centralized power supply systems. Normally photovoltaic cells have enabled distributed power generation during the day, but do not work at night. Thus, efficient electricity generation technologies for a sustainable all-day power supply with no necessity for energy storage remain a challenge. Herein, an innovative all-day power generation strategy is reported, which self-adaptively integrates the diurnal photothermal and nocturnal radiative cooling processes into the thermoelectric generator (TEG) via the spectrally dynamic modulated coating, to continuously harvest the energy from the hot sun and the cold universe for power generation. Synergistic with the optimized latent heat phase change material, the electricity generation performance of the TEG is dramatically enhanced, with a maximum power density exceeding 1000 mW m-2 during the daytime and up to 25 mW m-2 during the nighttime, corresponding to an improvement of 123.1% and 249.1%, compared with the conventional strategy. This work maximizes the utilization of ambient energy resources to provide an environmentally friendly and uninterrupted power generation strategy. This opens up new possibilities for sustained power generation both daytime and nighttime.

Copper-Nanoparticle-Decorated Hydrothermal Carbonaceous Carbon-Polydimethylsiloxane Nanocomposites: Unveiling Potential in Simultaneous Light-Driven Interfacial Water Evaporation and Power Generation.

This study introduces a hydrothermal synthesis method that uses glucose and Cu2+ ions to create a Cu-nanoparticle (NP)-decorated hydrothermal carbonaceous carbon hybrid material (Cu-HTCC). Glucose serves both as a reducing agent, efficiently transforming Cu2+ ions into elemental Cu nanostructures, and as a precursor for HTCC microstructures. An enhanced plasmon-induced electric field resulting from Cu NPs supported on microstructure matrices, coupled with a distinctive localized π-electronic configuration in the hybrid material, as confirmed by X-ray photoelectron spectroscopic analysis, lead to the heightened optical absorption in the visible-near-infrared range. Consequently, flexible nanocomposites of Cu-HTCC/PDMS and Cu-HTCC@PDMS (PDMS = polydimethylsiloxane) are designed as 2 and 3D structures, respectively, that exhibit broad-spectrum solar absorption. These composites promise efficient photo-assisted thermoelectric power generation and water evaporation, demonstrating commendable mechanical stability and flexibility. Notably, the Cu-HTCC@PDMS composite sponge simultaneously exhibits commendable efficiency in both water evaporation (1.47 kg m-2 h-1) and power generation (32.1 mV) under 1 sunlight illumination. These findings unveil new possibilities for innovative photothermal functional materials in diverse solar-driven applications.

A Review of Automation and Sensors: Parameter Control of Thermal Treatments for Electrical Power Generation.

This review delves into the critical role of automation and sensor technologies in optimizing parameters for thermal treatments within electrical power generation. The demand for efficient and sustainable power generation has led to a significant reliance on thermal treatments in power plants. However, ensuring precise control over these treatments remains challenging, necessitating the integration of advanced automation and sensor systems. This paper evaluates the pivotal aspects of automation, emphasizing its capacity to streamline operations, enhance safety, and optimize energy efficiency in thermal treatment processes. Additionally, it highlights the indispensable role of sensors in monitoring and regulating crucial parameters, such as temperature, pressure, and flow rates. These sensors enable real-time data acquisition, facilitating immediate adjustments to maintain optimal operating conditions and prevent system failures. It explores the recent technological advancements, including machine learning algorithms and IoT integration, which have revolutionized automation and sensor capabilities in thermal treatment control. Incorporating these innovations has significantly improved the precision and adaptability of control systems, resulting in heightened performance and reduced environmental impact. This review underscores the imperative nature of automation and sensor technologies in thermal treatments for electrical power generation, emphasizing their pivotal role in enhancing operational efficiency, ensuring reliability, and advancing sustainability in power generation processes.

Forecasting a Short-Term Photovoltaic Power Model Based on Improved Snake Optimization, Convolutional Neural Network, and Bidirectional Long Short-Term Memory Network.

The precision of short-term photovoltaic power forecasts is of utmost importance for the planning and operation of the electrical grid system. To enhance the precision of short-term output power prediction in photovoltaic systems, this paper proposes a method integrating K-means clustering: an improved snake optimization algorithm with a convolutional neural network-bidirectional long short-term memory network to predict short-term photovoltaic power. Firstly, K-means clustering is utilized to categorize weather scenarios into three categories: sunny, cloudy, and rainy. The Pearson correlation coefficient method is then utilized to determine the inputs of the model. Secondly, the snake optimization algorithm is improved by introducing Tent chaotic mapping, lens imaging backward learning, and an optimal individual adaptive perturbation strategy to enhance its optimization ability. Then, the multi-strategy improved snake optimization algorithm is employed to optimize the parameters of the convolutional neural network-bidirectional long short-term memory network model, thereby augmenting the predictive precision of the model. Finally, the model established in this paper is utilized to forecast photovoltaic power in diverse weather scenarios. The simulation findings indicate that the regression coefficients of this method can reach 0.99216, 0.95772, and 0.93163 on sunny, cloudy, and rainy days, which has better prediction precision and adaptability under various weather conditions.

What is China's efficient power generation portfolio under carbon neutrality target? An empirical analysis considering flexibility and system cost.

Variable renewable energy (VRE) is the most promising form of primary generation under a carbon neutrality target due to its environmental benefits, incentive policy, and technological progress. However, the increasing proportion of VRE generation, such as solar and wind power, has sharply increased integration cost and reduced power grid stability. This study uses portfolio theory to investigate China's optimal power generation portfolio by 2050 considering flexibility constraint and system cost, including technical and integration costs. The results demonstrate that non-fossil-fuel power generation technologies have cost and emission reduction advantages over fossil-fuel-based technologies. VRE generation technologies must be developed in synergy with other forms of power generation when considering flexibility requirement and integration cost. A complete phase-out of fossil-fuel power generation technologies in China appears unlikely in the study period. Gas-fired and coal-fired power generation are the pillar forms of power generation to meet future flexibility needs.

A H2O2 Self-Charging Zinc Battery with Ultrafast Power Generation and Storage.

Self-charging power systems are considered as promising alternatives for off-grid energy devices to provide sustained electricity supply. However, the conventional self-charging systems are severely restricted by the energy availability and time-consuming charging process as well as insufficient capacity. Herein, we developed an ultrafast H2O2 self-charging aqueous Zn/NaFeFe(CN)6 battery, which simultaneously integrates the H2O2 power generation and energy storage into a battery configuration. In such battery, the chemical energy conversion of H2O2 can generate electrical energy to self-charge the battery to 1.7 V through the redox reaction between H2O2 and NaFeFe(CN)6 cathode. The thermodynamically and kinetically favorable redox reaction contributes to the ultrafast H2O2 self-charging rate and the extremely short self-charging time within 60 seconds. Moreover, the rapid H2O2 power generation can promptly compensate the energy consumption of battery to provide continuous electricity supply. Impressively, this self-charging battery shows excellent scalability of device architecture and can be designed to a H2O2 single-flow battery of 7.06 Ah to extend the long-term energy supply. This work not only provides a route to design self-charging batteries with fast charging rate and high capacity, but also pushes forward the development of self-charging power systems for advanced large-scale energy storage applications.

[Bayesian network prediction study on the impact of occupational health psychological factors on insomnia among thermal power generation workers].

Objective: To explore the risk factors of insomnia among employees in the thermal power generation industry and the network relationships between their interactions, and to provide scientific basis for personalized interventions for high-risk groups with insomnia. Methods: In November 2022, 860 employees of a typical thermal power generation enterprise were selected as the research subjects by cluster sampling. On-site occupational health field surveys and questionnaire surveys were used to collect basic information, occupational characteristics, anxiety, depression, stress, occupational stress, and insomnia. The interaction between insomnia and occupational health psychological factors was evaluated by using structural equation model analysis and Bayesian network construction. Results: The detection rates of anxiety, depression and stress were 34.0% (292/860), 32.1% (276/860) and 18.0% (155/860), respectively. The total score of occupational stress was (445.3±49.9) points, and 160 workers (18.6%) were suspected of insomnia, and 578 workers (67.2%) had insomnia. Structural equation model analysis showed that occupational stress had a significant effect on the occurrence of insomnia in thermal power generation workers (standardized load coefficient was 0.644), and occupational health psychology had a low effect on insomnia (standardized load coefficient was 0.065). However, the Bayesian network model further analysis found that anxiety and stress were the two parent nodes of insomnia, with direct causal relationships, the arc strength was-8.607 and -15.665, respectively. The model prediction results showed that the probability of insomnia occurring was predicted to be 0 in the cases of no stress and anxiety, low stress without anxiety, and no stress with low anxiety. When high stress with low anxiety and low stress with high anxiety occurred, the predicted probability of insomnia occurring were 0.38 and 0.47, respectively. When both high stress and high anxiety occurred simultaneously, the predicted probability of insomnia occurring was 0.51. Conclusion: Bayesian network risk assessment can intuitively reveal and predict the insomnia risk of thermal power generation workers and the network interaction relationship between the risks. Anxiety and stress are the direct causal risks of insomnia, and stress is the main risk of individual insomnia of thermal power generation workers. The occurrence of insomnia can be reduced based on scientific intervention of stress conditions.

Electrodeposited MOFs Membrane with In Situ Incorporation of Charged Molecules for Osmotic Energy Harvesting.

Ion-selective membranes are considered as the promising candidates for osmotic energy harvesting. However, the fabrication of highly perm-selective membrane is the major challenge. Metal-organic frameworks (MOFs) with well-defined nanochannels along functional charged groups show great importance to tackle this problem. Here, a series of dense sodium polystyrene sulfonate (PSS) incorporated MOFs composite membranes (PSS@MOFs) on a porous anodic aluminum oxide (AAO) membrane via in situ anodic electrodeposition process are developed. Benefiting to the novel structural design of the confined Ag layer, PSS@MOFs dense composite membrane with less defects formed. The sulfonated nanochannels of the PSS@MOFs composite membrane provided rapid and selective transport of cations due to the enhanced electrostatic interaction between the permeating ions and MOFs. While osmotic energy conversion, 860 nm thick negatively charged PSS@MOFs composite membrane achieves an ultrahigh cation transfer number of 0.993 and energy conversion efficiency of 48.8% at a 100-fold salinity gradient. Moreover, a large output power of 2.90 µW has been achieved with an ultra-low internal resistance of 999 Ω, employing an effective area of 12.56 mm2 . This work presents a promising strategy to construct a high-performance MOFs-based osmotic energy harvesting system for practical applications.

Moisture-Enabled Germination of Heat-Activated Bacillus Endospores for Rapid and Practical Bioelectricity Generation: Toward Portable, Storable Bacteria-Powered Biobatteries.

Small-scale battery-like microbial fuel cells (MFCs) are a promising alternative power source for future low-power electronics. Controllable microbial electrocatalytic activity in a miniaturized MFC with unlimited biodegradable energy resources would enable simple power generation in various environmental settings. However, the short shelf-life of living biocatalysts, few ways to activate the stored biocatalysts, and extremely low electrocatalytic capabilities render the miniature MFCs unsuitable for practical use. Here, heat-activated Bacillus subtilis spores are revolutionarily used as a dormant biocatalyst that can survive storage and rapidly germinate when exposed to special nutrients that are preloaded in the device. A microporous, graphene hydrogel allows the adsorption of moisture from the air, moves the nutrients to the spores, and triggers their germination for power generation. In particular, forming a CuO-hydrogel anode and an Ag2 O-hydrogel cathode promotes superior electrocatalytic activities leading to an exceptionally high electrical performance in the MFC. The battery-type MFC device is readily activated by moisture harvesting, producing a maximum power density of 0.4 mW cm-2 and a maximum current density of 2.2 mA cm-2 . The MFC configuration is readily stackable in series and a three-MFC pack produces enough power for several low-power applications, demonstrating its practical feasibility as a sole power source.

Microbial fuel cell: Interplay of energy production, wastewater treatment, toxicity assessment with hydraulic retention time.

Microbial fuel cell (MFC) operation under similar conditions to conventional methods will support the use of this technology in large-scale wastewater treatment. The operation of scaled-up air-cathode MFC (2 L) fed with synthetic wastewater (similar to domestic) in a continuous flow was evaluated using three different hydraulic retention times (HRT), 12, 8, and 4 h. We found that electricity generation and wastewater treatment could be enhanced under an HRT of 12 h. Additionally, the longer HRT led to greater coulombic efficiency (5.44%) than MFC operating under 8 h and 4 h, 2.23 and 1.12%, respectively. However, due to the anaerobic condition, the MFC was unable to remove nutrients. Furthermore, an acute toxicity test with Lactuca sativa revealed that MFC could reduce wastewater toxicity. These outcomes demonstrated that scaled-up MFC could be operated as a primary effluent treatment and transform a wastewater treatment plant (WWTP) into a renewable energy producer.

Does China's green power trading policy play a role? - Evidence from renewable energy generation enterprises.

Green power trading is an institutional innovation proposed by China to promote green and sustainable development. This policy aims to relieve the serious debt pressure of renewable energy generation enterprises, thus laying the foundation for achieving carbon reduction targets. This paper empirically examines the role of green power trading by constructing the difference-in-differences (DID) model. Our findings indicate that green power trading significantly reduces the debt levels of policy-covered generation enterprises. This effect is more pronounced for state-owned enterprises, companies with better ESG performance, companies in regions with higher degree of marketization and companies specializing in renewable energy power generation. Further research discusses the impact mechanism of green power trading in terms of external and internal environmental channels. We find that a strong green development atmosphere, especially the external atmosphere, will significantly reinforce the weakening effect of green power trading on corporate debt. Our research provides empirical evidence for the success of green power trading policy in its pilot phase.

Application of a membrane-less air cathode microbial fuel cell to treat municipal waste composting leachate.

The adverse effects of high strength wastewaters on the microbial activities have created a challenge to biological treatments. Microbial fuel cell has been considered as a promising process because the electrical potential generation can stimulate microorganisms and overcome the inhibitory effect. However, several issues (e.g., scalability, high costs and maintenance) have prevented the process from the industrial applications. Elimination of the proton exchange membrane has been suggested as a remedy to the mentioned problems. In this work, a membrane-less microbial fuel cell was modified by putting the cathode within a thin sand layer (instead of the proton exchange membrane) to treat a high strength wastewater sample. The influences of the feed organic load and time of treatment in the modified system were studied in batch and continuous operations. It was revealed that the batch operation efficiency was higher for the lower feed loadings as a 5-day batch treatment removed 66 ± 4% of the 15,000 ± 500 mg/L initial chemical oxygen demand while the continuous process efficiency with 9-day hydraulic residence time was slightly more than 50%. However, the efficiency of the continuous operation for treatment of higher initial loading values was better than the batch mode with the removal efficiency of 41 ± 2% versus 12 ± 2% for a more concentrated leachate feed (45,000 ± 1000 mg/L). Finally, it was disclosed that the modified membrane-less MFC employed in this work can be effective in treatment of high strength wastewaters in larger scales with lower costs.

Electroactive Microorganisms in Advanced Energy Technologies.

Large-scale production of green and pollution-free materials is crucial for deploying sustainable clean energy. Currently, the fabrication of traditional energy materials involves complex technological conditions and high costs, which significantly limits their broad application in the industry. Microorganisms involved in energy production have the advantages of inexpensive production and safe process and can minimize the problem of chemical reagents in environmental pollution. This paper reviews the mechanisms of electron transport, redox, metabolism, structure, and composition of electroactive microorganisms in synthesizing energy materials. It then discusses and summarizes the applications of microbial energy materials in electrocatalytic systems, sensors, and power generation devices. Lastly, the research progress and existing challenges for electroactive microorganisms in the energy and environment sectors described herein provide a theoretical basis for exploring the future application of electroactive microorganisms in energy materials.

Suitability evaluation and potential estimation of photovoltaic power generation and carbon emission reduction in the Qinghai-Tibet Plateau.

The expansion of power development industry is facing enormous pressure to reduce carbon emissions in the context of global decarbonization. Using solar energy instead of traditional fossil energy to adjust energy structure is one of the important means for reducing carbon emissions. Existing research focuses on the evaluation of the generation potential of centralized or distributed photovoltaic power plants, rather than the comprehensive evaluation of multi-type power plants. Based on multi-source remote sensing data for information extraction and suitability evaluation, this paper develops a method to comprehensively evaluate the construction potential of multi-type photovoltaic power stations and determine the potential of photovoltaic power generation and carbon emission reduction on the Qinghai-Tibet Plateau (QTP). The results showed that estimating the power generation potential of only single-type photovoltaic power stations cannot accurately reflect the photovoltaic power generation potential of QTP. It is also demonstrated that the emission reduction effect of the photovoltaic power generation in all prefecture-level cities of QTP can meet national emission reduction targets, showing high annual power generation potential, of which 86.59% is concentrated in Qinghai province's Guoluo, Yushu, and Haixi. An accurate estimation of the photovoltaic power generation potential in QTP can provide a useful theoretical basis for developing carbon-saving and emission reduction strategies for clean energy in China.

Toward Scalable Nanofluidic Osmotic Power Generation from Hypersaline Water Sources with a Metal-Organic Framework Membrane.

Nanofluidic membranes have shown great promise in harvesting osmotic energy but its scalablity remains challenging since most studies only tested with a membrane area of ≈10-2  mm2 or smaller. We demonstrate that metal-organic-framework membranes with subnanometer pores can be used for scalable osmotic power generation from hypersaline water sources. Our membrane can be scaled up to a few mm2 , and the power density can be stabilized at 1.7 W m-2 . We reveal that the key is to improve the out-of-membrane conductance while keeping the membrane's charge selectivity, contradicting the previous conception that the ionic conductivity of the membrane plays the dominating role. We highlight that subnanometer pores are essential to ensure the charge selectivity in hypersaline water sources. Our results suggest the importance to engineer the interplay between the in-membrane and out-of-membrane ion transport properties for scalable osmotic power generation.

Developing Flexible Quinacridone-Derivatives-Based Photothermal Evaporaters for Solar Steam and Thermoelectric Power Generation.

Solar-driven interfacial vaporization by localizing solar-thermal energy conversion to the air-water interface has attracted tremendous attention. In the process of converting solar energy into heat energy, photothermal materials play an essential role. Herein, a flexible solar-thermal material di-cyan substituted 5,12-dibutylquinacridone (DCN-4CQA)@Paper was developed by coating photothermal quinacridone derivatives on the cellulose paper. The DCN-4CQA@Paper combines desired chemical and physical properties, broadband light-absorbing, and shape-conforming abilities that render efficient photothermic vaporization. Notably, synergetic coupling of solar-steam and solar-electricity technologies by integrating DCN-4CQA@Paper and the thermoelectric devices is realized without trade-offs, highlighting the practical consideration toward more impactful solar heat exploitation. Such solar distillation and low-grade heat-to-electricity generation functions can provide potential opportunities for fresh water and electricity supply in off-grid or remote areas.

A Novel Constructed Wetland Combined with Microbial Desalination Cells and its Application.

Wastewater recycling can alleviate the shortage of water resources. Saline water is seldom treated with biological processes, and its recycling rate is low. Constructed wetland (CW) is a safe, economical, and ecological water treatment method. However, the saline water treatment performance of CW is not good. Microbial desalination cells (MDC) utilizing a bioelectrochemical approach achieve functions of desalination and power generation. In this study, MDC was used to strengthen CW to form a composite system, MDC-CW. Through optimization of design parameters, MDC-CW was applied in the treatment of salt-containing water. The average total nitrogen removal rate in MDC-CW-P1 reached 87.33% and the average COD removal rate was 92.79%. The average desalination rate of MDC-CW-P1 was 55.78% and the average voltage of MDC-CW-P1 reached 0.40 mV. Planting Canna indica in the MDC-CW was conducive to the functions of desalination and power generation. The above results were also verified by the microbial analysis results of gravels in the substrate, plant rhizosphere, and electrodes. In addition, the decontamination of the device mainly depended on the function of the bacteria commonly used in water treatment, such as Proteobacteria and Bacteroidetes, whereas the generation of power depended on the function of Geobacter. Salt ions moved spontaneously to the cathode and anode under the influence of current generation so that the desalination function was realized under the selective isolation function of exchange membranes. The device design and laboratory applications of MDC-CW experimentally achieved the electrochemical function and broadened the treatment scale of CW.

Resistance matching materials nanoarchitectonics for better performances in water evaporation-driven generators.

The improvement of electricity production for water evaporation-driven generators (WEGs) remains a challenge. Herein, two types of WEGs were designed to study the resistance matching for improving the electricity production using the method of nanoarchitectonics. One type of reduced graphene oxide/carbon nanotube (RGO/CNT) WEG was constructed using RGO with adjustable resistances as working material and CNTs with fixed resistance as electrode material. The other type of graphene oxide (GO)/RGO WEG was constructed using RGO with adjustable resistance as electrode material and GO with fixed resistance was used as working material. The open circuit voltage of RGO/CNT increased from 15 to 56 mV and then decreased to 22 mV with increasing RGO resistance. The short circuit current of RGO/CNT also first increased and then decreased. The performance of GO/RGO was similar with that of RGO/CNT. Typically, the RGO/CNT and GO/RGO WEG showed the highest performance when the working material to electrode material resistance ratio was 2272 and 2365, respectively. It showed that the best resistance ratio of working material to electrode material was in the range of 2000-2500, which helped to improve about 2-5 times of electricity efficiency in the WEG. The present work provides a new direction for optimizing performance of WEGs.

Biodiversity Loss from Freshwater Use for China's Electricity Generation.

Electricity generation has two major, under-investigated impacts on freshwater biodiversity due to its water use: the consumption of freshwater and thermal emissions to freshwater. Here, we analyze the spatiotemporal freshwater biodiversity impacts of China's electric power system and the driving factors for these impacts. We show that between 2008 and 2017, the freshwater consumption of electricity generation peaked in 2013 (13.6 Gm3). Meanwhile, the freshwater consumption factor of China's electricity generation decreased from 3.2 to 2.0 L/kWh. However, due to increasing thermal emissions, the biodiversity loss via freshwater use increased from 1.1 × 108 in 2008 to 1.6 × 108 PDF m3 year. The overall biodiversity loss per unit of electricity generation decreased from 3.2 × 10-5 to 2.5 × 10-5 PDF m3 year/kWh. Biodiversity loss from thermal pollution is 60% higher than that driven by water consumption. Electricity transmission results in the shifting of biodiversity impacts across regions. The results show that 15% of total biodiversity loss was embedded in transmission networks. In terms of electrical power system drivers of biodiversity loss, the total generation was the main driving factor of the increase in loss (rather than shifts in generation type, for example). Our results indicate the necessity of assessing the biodiversity impacts of electricity generation and incorporating them into energy system planning.

Dynamic Life Cycle Assessment of Energy Technologies under Different Greenhouse Gas Concentration Pathways.

Global warming potential (GWP) has been widely used in the life cycle assessment (LCA) to quantify the climate impacts of energy technologies. Most LCAs are static analyses without considering the dynamics of greenhouse gas (GHG) emissions and changes in background GHG concentrations. This study presents a dynamic approach to analyze the life-cycle GWP of energy technologies in different timeframes and representative GHG concentration pathways. Results show that higher atmospheric GHG concentrations lead to higher life-cycle GWP for long-term analysis. The impacts of background GHG concentrations are more significant for technologies with large operational emissions or CH4 emissions than technologies with low operational emissions. The case study for the U.S. electricity sector in 2020-2050 shows the impacts of background GHG concentrations and different LCA methods on estimating national climate impacts of different energy technology scenarios. Based on the results, it is recommended for future LCAs to incorporate temporal effects of GHG emissions when (1) the technology has large operational GHG emissions or CH4 emissions; (2) the analysis time frame is longer than 50 years; (3) when LCA results are used for policymaking or technology comparisons for mitigating climate change.