Energy Generation Technologies Research Articles

Revealing the relaxation kinetics of curcumin based dye-sensitized solar cell

DSSCs have garnered significant attention as a promising technology for renewable energy generation. The carrier kinetics, or the dynamics of charge carriers, play a vital role in the efficiency of DSSC. However, numerous of its optoelectronics characteristics at low frequencies are highly contested. Here, we thoroughly investigated the carrier dynamics of curcumin-based sensitized cell using impedance spectroscopy and modulus spectroscopy under illumination and dark condition. It is revealed that the dielectric relaxation in curcumin-based DSSC follows the interfacial (Maxwell-Wagner type) polarization probably ascribed to the grain boundary effect. Moreover, the comparative evaluation of impedance and modulus spectra at lower frequencies demonstrates the localized type of charge-carrier relaxation in this curcumin-based sensitized cell, which has been related with the conductivity hopping phenomena. These results illustrate the potential of curcumin as a promising new sensitizer for DSSCs and highlight the importance of continued research into new and innovative materials for sustainable energy technology.

Unveiling the influence of ferromagnetic Gd-doped ZnO films on the performance of organic solar cells

Organic solar cells (OSCs) have emerged as a promising technology for renewable energy generation due to their low cost, lightweight, flexibility, and compatibility with roll-to-roll manufacturing. However, OSCs still face challenges in achieving high power conversion efficiency (PCE) due to various factors, including recombination loss. In this study, we investigated the effect of introducing a layer of eight atomic percent gadolinium-doped zinc oxide (Zn0.92Gd0.08O) between the poly(3-hexylthiophene) (P3HT): [6,6]-phenyl butyric acid methyl ester (PCBM) active layer and the fluorine-doped tin oxide (FTO) electrode of the OSC. The reference cell, which has an Au/P3HT:PCBM/ZnO/FTO structure, exhibits a PCE of 0.52%. Remarkably, when the Zn0.92Gd0.08O layer was inserted (Au/P3HT:PCBM/Zn0.92Gd0.08O/FTO), the PCE increased significantly to 3.42%, which is more than six times the increase. Through further analysis, we present that the insertion of the Zn0.92Gd0.08O layer induces spin polarization in the P3HT:PCBM layer, leading to enhanced charge transport and reducing the recombination rate. Based on the findings, it can be concluded that the Zn0.92Gd0.08O film can potentially improve OSC performance.

Energy Management and Environmental Protection in Industrial Parks: A Comparative Study of Central Taiwan Science Park and Silicon Glen

This manuscript focuses on analyzing the growth dynamics of the Central Taiwan Science Park (CTSP) and Silicon Glen in Scotland with a specific emphasis on their approaches to energy, environmental conservation, and economic management. The objective is to provide insights into their sustainable development strategies. In terms of energy, CTSP addresses Taiwan’s energy security and green transformation challenges, while Silicon Glen concentrates on Scotland’s wind energy generation technologies. Both regions prioritize the advancement of renewable energy sources and smart grid technologies. In the realm of environmental conservation, both CTSP and Silicon Glen prioritize environmental protection and sustainability by implementing rigorous environmental monitoring measures. Regarding economic management, CTSP and Silicon Glen serve as vital technology industry hubs in Taiwan and Scotland, respectively, attracting a multitude of high-tech and startup enterprises. This growth is facilitated through various means, including policy support, access to research resources, and robust infrastructure. This manuscript presents a comparative analysis of these two industrial parks, focusing on their environmental and economic management strategies. It aims to elucidate the principles underpinning the sustainable development and economic growth of industrial parks, offering valuable insights to decision-makers and stakeholders involved in the planning of sustainable industrial parks.

Active disturbance rejection control of photovoltaic microgrids based on disturbance compensation and feed-forward correction strategy

Photovoltaic microgrid (PV) is a promising direction of new energy generation technology. However, due to the performance of low-voltage side interface affected by complex disturbance, PV microgrid has the problem of output voltage fluctuation, which will make the power quality not guaranteed. In order to stabilize the low-voltage side load supply, the active disturbance rejection control strategy with disturbance compensation and feed-forward correction (ADRC-DCFC) is proposed. By expanding the conventional state observer (ESO) dimension, a feed-forward correction link for disturbance tracking compensation is added. In contrast, the internal deviations extracted from the system model are actively added to the disturbance compensation link. In addition, a theoretical analysis of its disturbance observation performance and noise suppression performance is presented. Experimental results on a 300-watt test platform verified the accuracy and effectiveness of the ADRC-DCFC.

Exploring the Synergy of Renewable Energy in the Circular Economy Framework: A Bibliometric Study

Over the past half-century, scientists from many different areas have been investigating how to switch to renewable energy, especially in the context of a circular economy. Numerous articles have discussed the scientific aspects of developing technology to support this process. This systematic literature review and bibliometric study aim to fill in research gaps by looking at trends, challenges, and possible future directions for the use of renewable energy in the context of a circular economy, especially in the fields of business, management, and economics. The study analyzed 294 peer-reviewed articles using the R Studio-Biblioshiny package version 4.1.2 software. The challenges of integrating renewable energy technologies within a circular economy include financial constraints, such as a high initial investment, the lack of an adequate regulatory framework and government support, the intermittent availability of renewable energy sources, the scarcity of resources and components for renewable energy generation technologies, relatively low energy conversion efficiency, the challenge of increasing consumer awareness, and the environmental impact of technological waste. The study suggests that future research should focus on financial models and policy incentives that can encourage businesses and investors to take advantage of renewable energy. The study also recommends exploring sustainable alternative fuel technologies, optimized waste-to-energy conversion, the increased efficiency of bioenergy conversion, more efficient solar panels, improved energy storage capacity, the life cycle management of solar panel devices, and the development of innovative business models to facilitate industrial symbiosis.

Renewable Energy Generation Technologies for Decarbonizing Urban Vertical Buildings: A Path towards Net Zero

Greenhouse gas (GHG) emissions, especially CO2, represent a global concern. Among those responsible for CO2 emissions, buildings stand out due to the consumption of energy from fossil fuels. In this sense, initiatives for the decarbonization of buildings and construction tends to contribute to the achievement of the target defined in the Paris Agreement of limiting the increase in global temperature to 1.5 degrees Celsius above pre-industrial levels, as well as in achieving the Sustainable Development Goals (SDG) and of the Triple Bottom Line (TBL). This article aimed to identify renewable energy generation technologies that can be applied in urban vertical constructions, contributing to the reduction of carbon emissions in the atmosphere. To this end, the following methodology was adopted: a survey of the Conferences of the Parties on climate change; identification of European Union Legislative Directives for the decarbonization of buildings; and a literature review to identify research that deals with renewable energy generation technologies that can be adopted in buildings. The results indicated that there seems to be a correlation between the growth in the number of articles that deal with the topic of decarbonizing buildings and the increase in world concerns about global warming. A hybrid microgrid proposal, combining different sources of renewable energy such as solar photovoltaic, wind, biomass, micro-hydroelectric, and others for vertical buildings with more than five floors, is presented as viable to achieve zero emissions in these buildings, contributing to future research, that can carry out quantitative analyses and feasibility studies, as well as for experiments and applications in existing buildings and the projects of new vertical constructions.

(Invited) Dynamics in the Electrocatalytic Reduction of CO2

Climate change concerns have spurred a growing interest in developing environmentally friendly technologies for energy generation, such as green H2 from water splitting. Moreover, the electrochemical reduction of CO2 (CO2RR) into value-added chemicals and fuels offers an additional possibility to store renewable energy into chemical bonds. It is therefore of particular interest to develop efficient, selective and durable electrocatalysts that can operate under mild reaction conditions. The latter however requires fundamental understanding of their structure and surface composition under reaction conditions. It should be kept in mind that even morphologically and chemically well-defined pre-catalysts will be susceptible to drastic modifications under operando conditions, especially when the reaction conditions themselves change periodically.This talk will illustrate how of a multi-technique in-situ/operando experimental approach is able provide in depth mechanistic insights into CO2RR1,2. A synergistic combination of LC-TEM, EC-AFM, NAP-XPS, XAS, XRD, GC/MS, and Raman Spectroscopy, coupled with machine learning-based data analysis, has been employed to investigate the time-dependent chemical and structural changes in mono and bimetallic CO2 electrocatalysts under reaction conditions.Some of the aspects that will be discussed here include: (i) the design of size- and shape-controlled catalytically active nanoparticle (NP) pre-catalysts (Cu2O cubes, ZnO@Cu2O cubic NPs), (ii) the understanding of the active state formation (e.g for well-defined Cu(100), Cu(111) surfaces) and the correlation between the dynamically evolving structure and composition of the electrocatalysts under operando reaction conditions and their activity and selectivity. Our studies are expected to open up new routes for the reutilization of CO2 through its direct conversion into industrially valuable chemicals and fuels such as ethylene and ethanol.

Optimal transition pathways toward carbon neutrality in Chinese power sector: Considering regional heterogeneity and technological change

Carbon emission reduction, cost-affordability and supply-reliability are all important for the power system transition. This study searches for optimal transition pathways toward carbon neutrality in Chinese power sector with a high spatial resolution model, coordinating deployments of power generation, transmission, and storage. It analyzes the impacts of regional heterogeneity, technological change, and low-carbon policies on the optimal transitions. The results show that renewable energy generation technologies, especially photovoltaic, might dominate the market in the latter planning period. With technological change and low-carbon policies, offshore wind and nuclear might replace fossil energy in coastal regions. Future electricity consumption would be dominated by local absorption and guaranteed by long-distance transmission. Storage capacity would be necessary to balance intermittent output with high penetration of renewable energy. This study also provides several policy implications related to improvement of grid flexibility, reprogramming of electricity transmissions, coordinated deployments of energy storage technologies, and implementation of low-carbon policies.

Examining the synergistic diffusion process of carbon capture and renewable energy generation technologies under market environment: A multi-agent simulation analysis

To achieve carbon neutrality, the power industry will vigorously promote renewable energy generation and carbon capture and storage (CCS) technologies. The diffusion of these technologies will vary depending on the incentive policies and market environments. Considering the progressive development of China's electricity market reform, this study constructs a multi-agent simulation model for the long-term low-carbon transformation of power systems, simulating the effects of different market environment and policy tools on the synergistic diffusion process of CCS and renewable energy generation technologies. According to the research results, when the price constraints in the electricity market are relaxed, opting for a differentiated clearing price demonstrates greater benefits for the diffusion of CCS technology and the reduction of carbon emissions compared to using a uniform clearing price. In this situation, the spread of renewable energy generation technologies aids in lowering the average market electricity price, thereby offsetting any potential price hikes resulting from the expansion of CCS technology. Moreover, in the presence of electricity price constraints, policy subsidies are necessary to incentivize the diffusion of CCS technology, with the suitable period for such incentives falling before 2040.

Energy recovery from produced water via reverse Electrodialysis: The role of heavy metals and soluble organics on process performance

Produced water (PW) is the largest by-product of oil and gas exploration, drilling and processing. PW salinity ranges from highly dilute solutions to saturated brines. This study investigates the potential use of salinity gradient power (SGP) for energy harvesting from PW generated from oil and gas exploration and processing. The study aims to evaluate the efficiency of reverse electrodialysis (RED) technology for harvesting SGP from PW and its dependence on various parameters such as feed concentration gradients, compositions, temperature and flow rate, as well as the presence of heavy metals and dissolved organic matter. Fourier transform infrared spectroscopy (FTIR) was used to study the interaction of phenol, nickel and zinc with the RED ion exchange membranes and their impact on power production. The study also explores the feasibility of utilizing the SGP of mixing PW streams for operating treatment processes such as nanofiltration (NF) and reverse osmosis (RO). According to our findings, when two PW streams with salinities of 150 g/L and 1 g/L are mixed, a maximum power output of nearly 8 kWh bbl−1 of PW can be achieved using 1000 cells and an active membrane area of 0.25 m2. Overall, this study provides valuable information for further research and development of RED technology for sustainable energy generation and management of PW by-products. Indeed, the energy extracted from the PW may be utilized to lessen the cost of its treatment and pave the way for its use in sustainable farming and landscaping.

High evaporation rate and electrical conductivity synergistically boosting porous rGO/CNT Film for water evaporation-driven electricity generation

Harvesting energy from natural water evaporation has attracted tremendous interest recently due to the advantages of independent operation in a wide range of environments and continuous direct current output. However, the currently reported power density is far lower than other renewable energy generation technologies. Herein, we demonstrate that an efficient water evaporation-driven generator (rGO/CNT-EPG) utilizes the synergistic effect of high water evaporation rate and electrical conductivity to achieve a spectacular continuous power output as high as 0.53 W m−2 and a high current density of 267 µA cm−2 under optimal conditions, which is the highest power density among the reported water evaporation-induced generators thus far. Remarkably, even in outdoor environment, the rGO/CNT generator performed a stable power density of 0.6 W m−2 with a high current density of 257.8 µA cm−2 through optical focusing, demonstrating its huge potential for practical applications. This work not only puts deep insights into the effect of electrical conductivity on water evaporation-induced electricity generation but also provides significant guidance to develop high-performance hydrovoltaic devices.

Experimental test of a building thermal system for preventive maintenance based on thermoeconomic analysis

An analysis of the sectorial structure of energy consumption shows that residential and tertiary sector buildings are the third-highest consumers, responsible for 29.5% of a city’s final energy consumption. The Building Quality Control Laboratory of the Basque Government aims to promote quality, innovation, and sustainability in buildings. To accomplish this goal, it has constructed an experimental facility with different energy generation technologies and a very versatile control system for testing different energy systems and operation modes. In this study, we tested a facility for supplying domestic hot water and heating for a multi-family house by means of a condensing boiler and an aerothermal heat pump (together with the corresponding control). This installation could reproduce the thermal demands required to be satisfied by the generation equipment through a programmed operation of the installation based on real demands. Additionally, this installation was analyzed using thermoeconomics (TE) to solve problems unable to be solved using traditional energy analyses based on the First Law of Thermodynamics. These problems include: (1) Determining the costs of the products of the installation based on physical criteria, (2) detecting the places where losses actually occur, evaluating their costs, and proposing cost-effective improvements, and (3) diagnosing issues in the installation. As a result, this paper suggests a solution to the preventive maintenance problems confronting the technical maintenance personnel for thermal installations in buildings by applying TE knowledge and using real data collected from sensors.

Directed Message Passing Neural Network for Predicting Power Conversion Efficiency in Organic Solar Cells.

Organic solar cells (OSCs) have emerged as a promising technology for renewable energy generation, and researchers are constantly exploring ways to improve their efficiency. For prediction of photovoltaic properties in OSCs, many machine learning models have been used in the past. All the models are used with fixed molecular descriptors and molecular fingerprints as input for power conversion efficiency (PCE) prediction. Recently, the graph neural network (GNN), which can model graph structures of the molecule, has received increasing attention as a method that could potentially overcome the limitations of fixed descriptors by learning the task-specific representations using graph convolutions. In this study, we have used the directed message passing neural network (D-MPNN), an emerging type of GNN for predicting PCE of organic solar cells, and the results are compared for the same train and test set with fixed descriptors and fingerprints. The excellent performance demonstrated by the D-MPNN model in this investigation highlights its potential for predicting PCE, surpassing the limitations of conventional fixed descriptors.

Perovskite Solar Module: Promise and Challenges in Efficiency, Meta‐Stability, and Operational Lifetime

AbstractPerovskite photovoltaics (PVs) are an emerging solar energy generation technology that is nearing commercialization. Despite the unprecedented progress in increasing power conversion efficiency (PCE) for perovskite solar cells (PSCs), up‐scaling lab‐made cells to solar modules remains a challenge. In this work, the recent progress of making perovskite mini‐modules is reviewed. In particular, a database summarizing the module size, performance, hysteresis, and operational lifetimes reported in the literature is built. After analyzing the performance losses from scaling PSCs to mini‐modules based on the data collected from the literature, the current key to high‐performance perovskite mini‐modules is found to be the coating method optimization. If the perovskite layer quality is well reserved, a >24% mini‐module efficiency is projected by only considering the losses from lateral resistivity and laser scribing area. Next, performance characteristics are explored including hysteresis and meta‐stable power outputs that must be overcome to correctly characterize perovskite modules. Finally, current challenges associated with the long‐term stability of perovskite modules are examined and the importance of such durability for commercialization is discussed. It is hoped that the findings in this review provide a bridge for the development of perovskite modules that will lead to commercialization in the near future.

Exploratory analysis of a real wind turbine dataset, using AI tools to cluster and classify data, for condition monitoring and fault detection

In recent years there has been an increase in wind generation, driven by environmental factors and the incentive offered for the development of clean and sustainable technologies for energy generation. However, due to the rapid growth of this technology, concerns about the safety and reliability of wind turbines are increasing, especially due to the associated risks and financial costs. Therefore, health monitoring and fault detection for wind turbines has become an important research focus. Thus, the objective of this work was to realize an exploratory study of real data from a wind turbine, using AI tools that help to group the different behaviors, according to the similarity of resources and characteristics of the data. For this, unsupervised learning methods were used to cluster the data and a model was proposed to train and test, using a multilayer perceptron network, to classify these clusters. The differential of this work is the use of real data from CHESF's wind turbines. Another important contribution is in relation to permanent magnet wind turbines, as there are not many studies in this field, therefore a great potential to be explored.

A review on BIPV-induced temperature effects on urban heat islands

Urban Heat Islands (UHI) occur in and around cities, leading to warmer temperatures than in surrounding rural areas. The UHI effect increases energy demand, air pollution levels, and heat-related illness and mortality. Solar energy is one of the most widely adopted renewable energy generation technologies in the built environment. Solar photovoltaic (PV) systems, integrated into building envelopes, can form a cohesive design, construction and energy solution for buildings, namely, building-integrated photovoltaic system (BIPV). However, the BIPV panels might potentially exacerbate the UHI intensity by trapping more heat in urban areas. This review paper uses a detailed literature survey of over 100 sources to evaluate whether the uptake of BIPV systems in urban areas contributes to an aggravation of the UHI effect. The survey found both direct and indirect impacts of BIPV systems on UHI, which also identified the fundamental causes of UHI such as the albedo effect and heat dispersion and how this would be embodied in the BIPV installations. Furthermore, this paper discusses how to mitigate the impact of BIPV systems on the UHI, as well as the future research directions around this concern in relation to the urban design.

One-pot synthesis of crystalline structure: Nickel-iron phosphide and selenide for hydrogen production in alkaline water splitting

Electrocatalytically active nanocomposites play a vital role in energy generation, conversion, and storage technologies. Transition metal-based catalysts such as nickel and iron and their pnictide (phosphide), and chalcogenide (selenide) compounds exhibit good activity for hydrogen evolution reaction (HER) in the alkaline environment. In this study, transition metals-based catalysts (Ni-P-Se, Fe-P-Se, and Ni-Fe-P-Se) solutions were prepared using a simple one-pot method. Prepared solutions were deposited on Ni foam, and different characterization techniques were used to determine the composition, structure, and morphology of as-prepared catalysts. Furthermore, it was found that Ni-Fe-P-Se as a cathode material showed better HER performance compared to other investigated materials with the overpotential value of 316 mV at 10 mA cm-2 current density and 89 mV dec-1 Tafel slope value. The stability tests of the as-prepared catalyst confirmed that the synergistic effect between various elements enhances the electrocatalytic performance for up to 24 hours, providing a fair, stable nature of Ni-Fe-P-Se based sample.

Attaining multiple sustainable development goals through storage hydropower development amidst community vulnerabilities

AbstractEvery energy generation technology, including hydropower, has its own strengths and shortcomings. We carried out vulnerability assessment (VA) applying a bottom‐up multi‐disciplinary indicator‐based method considering people's perception of five dimensions of a storage type (ST) “national pride” hydropower project–1200 MW Budhi Gandaki Hydropower Project (BGHP) in Nepal. We also examined how ST projects can contribute to sustainable development goals (SDGs) overcoming the vulnerabilities. Primary data on people's perception were collected through focus group discussions and 200 household questionnaire surveys conducted within the most vulnerable areas. People perceived the “Physical” dimension as the most impactful. The local community is optimistic about some infrastructure development, but issues related to compensation, resettlement and physical stressors were found to be very sensitive for the effective implementation of the project. Expectations of the local people and proposed plans by the government are concurrent in some issues but not in all. Our analysis shows that the BGHP has the potential to be multi‐dimensionally beneficial (to eight SDGs) for Nepal, provided that supportive policies are formulated and implemented stringently. Extending the project as multi‐purpose, pumped storage and other improvements such as floatovoltaics are some of the plausible recommendations for harnessing maximum benefits from this important project while minimizing threats. Moreover, the methodological framework can be conveniently replicated for conducting VA of hydropower projects under comparable physical and socio‐economic conditions.

A Review of Cybersecurity Concerns for Transactive Energy Markets

Advances in energy generation and distribution technology have created the need for new power management paradigms. Transactive energy markets are integrated software and hardware systems that enable optimized energy management and direct trading between prosumers. This literature review covers unresolved security and privacy vulnerabilities in the proposed implementations of such markets. We first performed a coarse search for such implementations. We then combed the resulting literature for references to privacy concerns, security vulnerabilities, and attacks that their system was either vulnerable to or sought to address. We did so with a particular focus on threats that were not mitigated by the use of blockchain technology, a commonly employed solution. Based on evidence from 28 peer-reviewed papers, we synthesized 14 categories of concerns and their proposed solutions. We found that there are some concerns that have been widely addressed, such as protecting trading history when using a public blockchain. Conversely, there were serious threats that are not sufficiently being considered. While a lack of real-world deployment has limited information about which attacks are most likely or feasible, there are clear areas of priority that we recommend to address going forward, including market attacks, false data injection attacks, single points of failure, energy usage data leakage, and privacy.

Development of hybrid ANFIS-GAN-XGBOOST models for accurate prediction of material removal rates from PCB-polluted concrete surfaces using laser technology for sustainable energy generation

This study presents a hybrid machine learning approach for predicting material removal rates from polychlorinated biphenyl (PCB)-polluted concrete surfaces using laser technology. An adaptive neural fuzzy inference system (ANFIS) with XGBoost and generative adversarial networks (GANs) was employed as a hybrid model (ANFISGAN- XGBoost) to classify the numerous input variables for material removal rates based on process factors. Four input parameters, including annealing temperature, scanning speed, frequency, and laser power, were evaluated to calculate the ablation effectiveness and material removal rates. The study demonstrated that the hybrid ANFIS-GAN-XGBoost model applied to laser ablation on concrete surfaces polluted with PCBs accurately predicts the ablation depth. The experimental findings revealed that 96.66% of the PCBs were removed from the concrete surface, and 88.43% of them were decomposed during the laser decontamination procedure. A surface ablation ratio of roughly 7.2 m2/h was achieved, indicating the potential of using laser technology for sustainable energy generation by removing pollutants from concrete surfaces. The findings of this study contribute to the development of sustainable energy generation strategies and could be used in the cleanup of concrete surfaces polluted with PCBs in various settings, including nuclear power plants and polluted buildings. The hybrid ANFIS-GAN-XGBoost model is a valuable tool for predicting material removal rates based on process factors and can be used in the optimization of the laser-based decontamination process for PCB-polluted concrete surfaces. This study highlights the potential of using advanced machine learning models in environmental cleanup efforts, paving the way for future research in this field.