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Microbial fuel cell (MFC), a bio-electrochemical device that exploits electroactive microbes, has gained more attention in developing countries, such as Indonesia. Unfortunately, studies related to bio-electrochemistry are often constrained due to the need for precise and high-cost instrumentation, such as data logger/acquisition or data logging-multimeter for continuously monitoring electricity generation of MFCs in the rigid time interval. This present work aimed at two issues: (1) to evaluate the use of a low-cost microcontroller-based data logger, the developed multi-channels Arduino UNO-based data logging system, for monitoring the electricity generation of ten MFC bioreactors simultaneously, and (2) to evaluate the electrochemical performance of MFCs biocatalysts by ten electroactive microbes isolated from aquaculture pond sediment in Indonesia. The monitoring system worked with a multi-channels Arduino UNO, a multiplexer, an external 16-bit ADC (analogue to digital converter) ADS1115, and a RTC (real time clock) module. The MFC performance was evaluated in the terms of open circuit voltage and close circuit voltage (polarization curve, power density, and losses). Statistical analysis confirmed the high accuracy of the developed system with the average of absolute and relative error values of 1.21 mV and 1.26%, respectively, comparable to traditional multimeter utilized for MFC electricity measurement. These results suggested that the developed data logging system could be a considerable option as a low-cost monitoring device for electrochemical studies of MFCs. Electrochemical performances of ten anodic biocatalysts were also evaluated, suggesting that there were three effective bacteria (isolate KCf2, KCf4, and KCf10) for producing relatively stable bioelectricity in the reactor of MFCs. These three electroactive microbes can produce power density of 0.069 W m−2, 0.021 W m−2, and 0.010 W m−2, respectively. [ABSTRACT FROM AUTHOR]

Summary: Due to the energy crisis and environmental concerns, wind power has seen a considerable increase in use over the past 10 years as a source of renewable energy. Since wind is intermittent and variable, it is obvious that as penetration levels rise, the influence of wind power generation on the electric power system must be considered. Wind power forecasting is essential because large‐scale wind power integration will make it more difficult to plan, operate, and control the power system. An accurate forecast is an efficient way to deal with the operational problems brought on by wind variability. To better utilize wind energy resources, it is essential to increase prediction accuracy. Frequently, the noise in the dataset causes the ramp events to be misclassified or overestimated. The main emphasis of this study is the pre‐processing of wind power data that produces precise time‐series data while reducing noise or artifact content and maintaining the swing feature of the original data. For this task, the data augmentation approach is proposed, where the augmented data (synthetic data) will be added up with the training data, in such a way as to make the strategy useful for real‐time applications. As the next step, the significant features, such as higher‐order statistical features and lower‐order statistical features are extracted. The extracted features act as the input to the recurrent neural network (RNN) classifier, the weights of which are tuned using the proposed honey badger crow (HBCro) optimization algorithm. The proposed HBCro optimization algorithm acts as the major contribution of the proposed model, and it is modeled with the integration of the concepts of the crow search optimization (CSO) algorithm and the honey badger optimization algorithm (HBA). The proposed system is simulated in MATLAB and the effectiveness of the proposed method is validated by comparison with other conventional methods in terms of Error measures. Furthermore, the developed HBCro‐based RNN obtained efficient performance in terms of MSE, MAE, RMSE, RMPSE, MAPE, MARE, MSRE, and RMSRE of 0.1578, 0.0442, 0.2102, 123.238, 124.72, 0.9944, 1.1799, and 1.0732, respectively. [ABSTRACT FROM AUTHOR]

PV(photovoltaic) systems have been deployed more in the recent years to support green energy generation. In the recent era, grid tied PV has been sparked by the emergence of the electricity market and offers an alternative solution to traditional fossil fuel-based electricity generation. A few of the potential impacts of solar PV on grid are false tripping of feeders, unwanted tripping, unnecessary islanding, and blind protection. In this research paper, different artificial intelligence techniques are tested in order to overcome the protection challenges. The PSCAD/EMTDC software package is used to analyze a section of the power system, and an algorithm has been constructed using Python v3.8 and MATLAB 2018. On an IEEE-9 BUS power system connected to a PV source, the Artificial Neural Network, Naive Bayes, Support Vector Machine, Random Forest, and Convolution Neural Network (CNN) algorithms are implemented to classify the faults. The suggested methods are proven effective for both in-zone and out-of-zone problems on power lines interconnected with solar park. The proposed techniques have been validated using total 16,320 internal and external fault cases with a wide range of system parameters alteration. In the proposed system, the effectiveness of several machine learning and deep learning techniques is compared. The obtained results demonstrate that CNN provides greater accuracy in the presence of a PV source, but at the same time, it is appropriate for a large number of data sets. The fault classification accuracy acquired is adequate and demonstrates the adaptability of the proposed approach. [ABSTRACT FROM AUTHOR]

Electrical power generation in Oman depends mainly on natural gas, while in rural areas it is based mainly on diesel fuel. Oman has committed to net-zero emissions by 2050, in line with the Paris Agreement's goal of limiting global warming to 1.5°C. The objective of this paper is to propose an optimal energy mix model for electricity generation from various energy sources, such as gas, diesel, wind, and photovoltaic, that considers more renewable sources in the energy mix. The optimization model minimizes various costs such as construction cost, operation cost, fuel cost, and carbon emissions, while satisfying the load demand. In this paper, Masirah Island is selected to perform our analysis. Several scenarios are contemplated, including grid extension to the island. The results found that gas-powered generators with 20% PV and storage are the best option in terms of the levelized cost of electricity. The grid extension is an economically feasible option if the existing load is more than doubled. [ABSTRACT FROM AUTHOR]

With increasing electricity demand, conventional centralized power generation systems encounter numerous challenges, including transmission and distribution losses, limited capacity, and high operational costs. In response, distributed energy systems have emerged as a promising solution by enabling electricity generation in close proximity to consumption points. These systems leverage renewable energy sources and minimize energy losses during transmission, presenting a more sustainable and efficient alternative. By utilizing diverse energy sources such as solar thermal panels, photovoltaic systems, geothermal energy, distributed energy systems enhance overall efficiency, and reduce power losses during transmission as well as greenhouse gas emissions. This research endeavor presents a novel approach employing mixed-integer linear programming to optimize distributed energy systems. The proposed model facilitates the determination of optimal dimensions of technologies, including combined heat and power systems, boilers, electric chillers, and absorption chillers, while simultaneously minimizing total costs and greenhouse gas emissions and adhering to real-world constraints. The findings of this study are validated through a real-world numerical example, confirming the model's efficiency in configuring and planning distributed energy systems optimally, thereby enhancing their operational performance. [ABSTRACT FROM AUTHOR]

The development of electricity generation from renewable sources, particularly photovoltaic energy (PV), as well as the significant growth of electric mobility with electric vehicles (EVs), leads us to contemplate the potential impacts of these components may have on an existing distribution electrical network. An electrical distribution network is designed to supply electrical loads in one specific direction while maintaining the quality of its technical parameters, such as current, voltage, and frequency. In this article, through a literature review, we will explore how the integration of each component, photovoltaic energy, and electric vehicles, individually and in combination, can impact the electrical distribution network. In addition, we will examine based on a literature review, the methods proposed by various authors to enhance the impacts occurring on the network due to this integration. [ABSTRACT FROM AUTHOR]

Climate change mitigation generally require rapid decarbonization in the power sector, including phase-out of fossil fuel-fired generators. Given recent technological developments, co-firing of hydrogen or ammonia, could help decarbonize fossil-based generators, but little is known about how its effects would play out globally. Here, we explore this topic using an energy system model. The results indicate that hydrogen co-firing occurs solely in stringent mitigation like 1.5 °C scenarios, where around half of existing coal and gas power capacity can be retrofitted for hydrogen co-firing, reducing stranded capacity, mainly in the Organization for Economic Co-operation and Development (OECD) countries and Asia. However, electricity supply from co-firing generators is limited to about 1% of total electricity generation, because hydrogen co-firing is mainly used as a backup option to balance the variable renewable energies. The incremental fuel cost of hydrogen results in lower capacity factor of hydrogen co-fired generators, whereas low-carbon hydrogen contributes to reducing emission cost associated with carbon pricing. While hydrogen co-firing may play a role in balancing intermittency of variable renewable energies, it will not seriously delay the phase-out of fossil-based generators. Effects of hydrogen and ammonia co-firing with fossil power generation on decarbonization scenario are assessed. Co-fired generation is limited to <1% because of higher cost of hydrogen. It will not delay the phase-out of fossil-based generators. [ABSTRACT FROM AUTHOR]

The present work deals with the preliminary design, the simulation, and the assessment of the thermodynamic performance of a polygeneration system for the simultaneous production of a range of valuable chemical products (namely, di-methyl-ether (DME), methanol (MeOH), H2-CH4 mixtures with an H2 content up to 30 % – usually referred to as “hythane”) alongside the generation of multiple energy carriers such as heating and power. The system included a biomass gasification step, a steam cycle for power generation, an oxyfuel combustor, a syngas-to-DME section and a methanation section. A sensitivity study on the gasification section showed that low pressure oxygen/steam gasification at 950°C yields a good quality syngas with an H2/(CO+CO2) ratio of 0.97. A simple graphical method for fixed-bed reactor dimensioning is also presented. [ABSTRACT FROM AUTHOR]

In this study, a contextual analysis of the CO2 reduction potential by using black pellets for energy production in Romania was performed. Black pellets have similar fuel properties to that of coal, thus representing a sustainable and environmentally friendly alternative for power generation. To assess the CO2 emissions reduction potential of the black pellet technology, two value chains for energy production were compared: one utilizing black pellets and the other using coal as the primary fuel source. The value chain of black pellets consists of biomass harvesting, the transportation of biomass from its source to the black pellets production plant, which incorporates pretreatment and steam explosion units, and finally, the utilization of black pellets for power production. The coal value chain encompasses coal mining, the transportation of the extracted coal to the power plant, and subsequent power generation. The total CO2 emissions for power generation in a 50 MW using black pellets and coal amounted to 16.27 and 272.10 kton/y, respectively. This substantial difference in emissions primarily stems from the higher emissions associated with coal extraction and the release of CO2 during coal combustion for power production. It is important to emphasize that power generation from black pellets results in net-zero emissions during combustion since biomass captures and stores CO2 throughout its lifecycle. The results of this analysis demonstrate the environmental advantages attainable by replacing coal with black pellets, thus promoting a more sustainable approach to energy production. [ABSTRACT FROM AUTHOR]

The EU's energy targets are to achieve at least 32% renewables in the energy mix by 2030. Part of the solution is strengthening consumer rights by empowering individuals to generate their own electricity. The aim of this study was to identify the most suitable energy system for electricity generation of up to 50 kW in the EU residential sector. Multi-Criteria Decision Analysis was used to compare four systems: proton exchange membrane fuel cell with photovoltaic panels, photovoltaic panels, biomass-powered Stirling engine, and solar-powered Stirling engine. Based on the results, the most beneficial system for household electricity generation is the biomass-fueled Stirling engine system due to its affordability, reliability, and low environmental impact. Governments and businesses can use these findings to improve information for the residential sector and enable the transition to renewable energy. [ABSTRACT FROM AUTHOR]

The development of public transportation is considered a vital issue in reducing traffic as well as urban pollution. City buses play an important role in the city transportation system. In Iran, due to the high average age of city buses, it is necessary to replace the old buses with new ones, To replace the old buses, diesel and CNG, hybrid, and electric buses are proposed as the main alternatives. Global warming and the energy crisis are now considered as two potential serious threats for the world. Therefore, energy consumption and CO2 emissions are examined as two outstanding criteria for comparing candidate buses in this paper. To make an accurate comparison, the amount of energy consumption and CO2 emissions have been calculated based on the well-to-wheel approach. The electric bus well-to-wheel analysis has been done for both electricity generation mix and renewable generation. To perform more accurate calculations and simulations, as a case study, a real driving cycle has been constructed for Tehran. For this approach, a modified micro trip method as a novel solution is presented to synthesize the driving cycle. The results show that due to the high share of fossil power plants (about 92%) in Iran, the use of electric buses in the bus fleet may not have much effect on reducing energy and CO2 eq emissions. By using renewable power plants, the amount of well-to-wheel energy consumption and CO2 emissions decrease significantly (about 56% and 93%, respectively) compared to that for the generation mix. [ABSTRACT FROM AUTHOR]

The purpose of the research to identify effect of service quality, the role of social media technology, and company reputation on increasing power sales. This research is an explanatory research using hypothesis testing methods and quantitative approaches. The goal is to explain the causal relationship between one variable that affects another variable, namely independent variables in the form of service quality, the role of social media technology and company reputation on the dependent variable that is increased sales. Based on the discussion in the previous chapters and answering the problem formulation, research objectives and referring to the process and results of data analysis in this study, the following conclusions can be drawn: There is a positive and significant influence between service quality and increased electricity sales at PLN UP3 Ponorogo. There is a positive and significant influence between the role of social media technology and the increase in electricity sales at PLN UP3 Ponorogo. There is a positive and significant influence between the company's reputation and the increase in electricity sales at PLN UP3 Ponorogo. [ABSTRACT FROM AUTHOR]

With the increasing scarcity of global energy, the rapid development of science and technology, and the growing demand for environmental protection, wind energy is receiving increasing attention as the cleanest source of energy. Due to its pollution-free nature and widespread availability, it has become a preferred source of electricity generation in many countries. However, wind speed prediction plays a vital role in wind power generation. Traditional prediction models, due to randomness and uncertainty, often produce unstable and inaccurate results, leading to power and economic losses. Therefore, this study proposes a hybrid prediction system based on an information processing strategy and a multi-objective optimization algorithm. By preprocessing the data and optimizing the combination of five individual models, the singularity of a single model is overcome, a Pareto-optimal solution is obtained, and accurate and stable prediction results are provided. To verify the effectiveness of the proposed combined model in predicting wind speed, various experiments on a wind speed series were conducted based on a wind power station located in Penglai, China. The results show that the combined model proposed in this study has better prediction performance than conventional models. [ABSTRACT FROM AUTHOR]

In this paper, we use the literature to help us better understand carbon capture costs and how these estimates fare against those of avoided costs, focusing on bioenergy carbon capture and storage (BECCS), carbon capture and storage (CCS), as well as direct air capture technologies. We approach these questions from a meta-analysis perspective. The analysis uses meta-analysis tools while applying them to numerical rather than statistical studies. Our analysis shows that avoided costs are, on average, 17.4% higher than capture costs and that the carbon intensity of the feedstock matters: the estimates for coal-based electricity generation capture costs are statistically smaller than those for natural gas or air. From a policy perspective, the literature suggests that the costs of CCS are like the 45Q subsidy of USD 50 per metric ton of carbon captured. [ABSTRACT FROM AUTHOR]

A novel dynamic economic model-predictive control strategy is presented that improves wind farm power production and reduces the additional demands of wake steering on yaw actuation when compared to an industry state-of-the-art reference controller. The novel controller takes a distributed approach to yaw control optimisation using a free-vortex wake model. An actuator-disc representation of the wind turbine is employed and adapted to the wind farm scale by modelling secondary effects of wake steering and connecting individual turbines through a directed graph network. The economic model-predictive control problem is solved on a receding horizon using gradient-based optimisation, demonstrating sufficient performance for realising real-time control. The novel controller is tested in a large-eddy simulation environment and compared against a state-of-the-art look-up table approach based on steady-state model optimisation and an extension with wind direction preview. Under realistic variations in wind direction and wind speed, the preview-enabled look-up table controller yielded the largest gains in power production. The novel controller based on the free-vortex wake produced smaller gains in these conditions while yielding more power under large changes in wind direction. Additionally, the novel controller demonstrated potential for a substantial reduction in yaw actuator usage. [ABSTRACT FROM AUTHOR]

To realize the projected increase in worldwide demand for floating offshore wind, numerical simulation tools must capture the relevant physics with a high level of detail while being numerically efficient. This allows engineers to have better designs based on more accurate predictions of the design driving loads, potentially enabling an economic breakthrough. The existing generation of offshore wind turbines is reaching a juncture, where traditional approaches, such as the blade element momentum theory, are becoming inadequate due to the increasing occurrence of substantial blade deflections. QBlade is a tool that includes a higher-fidelity aerodynamic model based on lifting-line theory, capable of accurately modeling such scenarios. In order to enable the simulation of offshore conditions in QBlade and to make use of this aerodynamic capability for novel offshore wind turbine designs, a hydrodynamic module called QBlade-Ocean was developed. In the present work, this module is validated and verified with two experimental campaigns and two state-of-the-art simulation frameworks on three distinct floating offshore wind turbine concepts. The results confirm the implementation work and fully verify QBlade as a tool to be applied in offshore wind turbine simulations. Moreover, a method aimed to improve the prediction of non-linear motions and loads under irregular wave excitation is analyzed in various conditions. This method results in a significant improvement in the surge and pitch degrees of freedom in irregular wave cases. Once wind loads are included, the method remains accurate in the pitch degree of freedom, while the improvements in the surge degree of freedom are reduced. A code-to-code comparison with the industry-designed Hexafloat concept highlights the coupled interactions on floating turbines that can lead to large differences in motion and load responses in otherwise identically behaving simulation frameworks. [ABSTRACT FROM AUTHOR]

The actuator line method (ALM) is increasingly being preferred to the ubiquitous blade element momentum (BEM) approach in several applications related to wind turbine simulation, thanks to the higher level of fidelity required by the design and analysis of modern machines. Its capability to resolve blade tip vortices and their effect on the blade load profile is, however, still unsatisfactory, especially when compared to other medium-fidelity methodologies such as the lifting line theory (LLT). Despite the numerical strategies proposed so far to overcome this limitation, the reason for such behavior is still unclear. To investigate this aspect, the present study uses the ALM tool developed by the authors for the ANSYS® Fluent® solver (v. 20.2) to simulate a NACA0018 finite wing for different pitch angles. Three different test cases were considered: high-fidelity blade-resolved computational fluid dynamics (CFD) simulations (to be used as a benchmark), standard ALM, and ALM with the spanwise force distribution coming from blade-resolved data (frozen ALM). The last option was included to isolate the effect of force projection, using three different smearing functions. For the postprocessing of the results, two different techniques were applied: the LineAverage sampling of the local angle of attack along the blade and state-of-the-art vortex identification methods (VIMs) to outline the blade vortex system. The analysis showed that the ALM can account for tip effects without the need for additional corrections, provided that the correct angle of attack sampling and force projection strategies are adopted. [ABSTRACT FROM AUTHOR]

Wind farm layout optimization is usually subjected to boundary constraints of irregular shapes. The analytical expressions of these shapes are rarely available, and, consequently, it can be challenging to include them in the mathematical formulation of the problem. This paper presents a new methodology to integrate multiple disconnected and irregular domain boundaries in wind farm layout optimization problems. The method relies on the analytical gradients of the distances between wind turbine locations and boundaries, which are represented by polygons. This parameterized representation of boundary locations allows for a continuous optimization formulation. A limitation of the method, if combined with gradient-based solvers, is that wind turbines are placed within the nearest polygons when the optimization is started in order to satisfy the boundary constraints; thus the allocation of wind turbines per polygon is highly dependent on the initial guess. To overcome this and improve the quality of the solutions, two independent strategies are proposed. A case study is presented to demonstrate the applicability of the method and the proposed strategies. In this study, a wind farm layout is optimized in order to maximize the annual energy production (AEP) in a non-uniform wind resource site. The problem is constrained by the minimum distance between wind turbines and five irregular polygon boundaries, defined as inclusion zones. Initial guesses are used to instantiate the optimization problem, which is solved following three independent approaches: (1) a baseline approach that uses a gradient-based solver; (2) approach 1 combined with the relaxation of the boundaries, which allows for a better design space exploration; and (3) the application of a heuristic algorithm, "smart-start", prior to the gradient-based optimization, improving the allocation of wind turbines within the inclusion polygons based on the potential wind resource and the available area. The results show that the relaxation of boundaries combined with a gradient-based solver achieves on average +10.2 % of AEP over the baseline, whilst the smart-start algorithm, combined with a gradient-based solver, finds on average +20.5 % of AEP with respect to the baseline and +9.4 % of AEP with respect to the relaxation strategy. [ABSTRACT FROM AUTHOR]

The mid-Atlantic will experience rapid wind plant development due to its promising wind resource located near large population centers. Wind turbines and wind plants create wakes, or regions of reduced wind speed, that may negatively affect downwind turbines and plants. We evaluate wake variability and annual energy production with the first yearlong modeling assessment using the Weather Research and Forecasting model, deploying 12 MW turbines across the domain at a density of 3.14 MW km -2 , matching the planned density of 3 MW km -2. Using a series of simulations with no wind plants, one wind plant, and complete build-out of lease areas, we calculate wake effects and distinguish the effect of wakes generated internally within one plant from those generated externally between plants. We also provide a first step towards uncertainty quantification by testing the amount of added turbulence kinetic energy (TKE) by 0 % and 100 %. We provide a sensitivity analysis by additionally comparing 25 % and 50 % for a short case study period. The strongest wakes, propagating 55 km, occur in summertime stable stratification, just when New England's grid demand peaks in summer. The seasonal variability of wakes in this offshore region is much stronger than the diurnal variability of wakes. Overall, yearlong simulated wake impacts reduce power output by a range between 38.2 % and 34.1 % (for 0 %–100 % added TKE). Internal wakes cause greater yearlong power losses, from 29.2 % to 25.7 %, compared to external wakes, from 14.7 % to 13.4 %. The overall impact is different from the linear sum of internal wakes and external wakes due to non-linear processes. Additional simulations quantify wake uncertainty by modifying the added amount of turbulent kinetic energy from wind turbines, introducing power output variability of 3.8 %. Finally, we compare annual energy production to New England grid demand and find that the lease areas can supply 58.8 % to 61.2 % of annual load. We note that the results of this assessment are not intended to make nor are they suitable to make commercial judgments about specific wind projects. [ABSTRACT FROM AUTHOR]

The climate emergency has prompted rapid and intensive research into sustainable, reliable, and affordable energy alternatives. Offshore wind has developed and exceeded all expectations over the last 2 decades and is now a central pillar of the UK and other international strategies to decarbonise energy systems. As the dependence on variable renewable energy resources increases, so does the importance of the necessity to develop energy storage and nonelectric energy vectors to ensure a resilient whole-energy system, also enabling difficult-to-decarbonise applications, e.g. heavy industry, heat, and certain areas of transport. Offshore wind and marine renewables have enormous potential that can never be completely utilised by the electricity system, and so green hydrogen has become a topic of increasing interest. Although numerous offshore and marine technologies are possible, the most appropriate combinations of power generation, materials and supporting structures, electrolysers, and support infrastructure and equipment depend on a wide range of factors, including the potential to maximise the use of local resources. This paper presents a critical review of contemporary offshore engineering tools and methodologies developed over many years for upstream oil and gas (O&G), maritime, and more recently offshore wind and renewable energy applications and examines how these along with recent developments in modelling and digitalisation might provide a platform to optimise green hydrogen offshore infrastructure. The key drivers and characteristics of future offshore green hydrogen systems are considered, and a SWOT (strength, weakness, opportunity, and threat) analysis is provided to aid the discussion of the challenges and opportunities for the offshore green hydrogen production sector. [ABSTRACT FROM AUTHOR]

The growing interest in floating offshore wind turbines (FOWTs) is rooted in the potential source of increased offshore energy production. As the technology is still in a pre-industrial state, several questions remain to be addressed where little field data are available. This study uses physical modelling at a reduced scale to investigate the signature of the floating motions into the wake spectral content of a simplified FOWT model. A wind turbine model based on the actuator disc concept is placed in an atmospheric boundary layer wind tunnel and subjected to a range of surge, heave and pitch motions. The signatures of idealised sinusoidal motion and realistic broadband motion on the model's wake at distances of 4.6 D (D being the disc diameter) and 8 D are measured through the use of a rake of single hot wires. The spectral analysis shows that harmonic motion leaves clear signatures in the far wake's energy spectra, mainly in the top tip region, while broadband motion does not leave easily detectable signatures. [ABSTRACT FROM AUTHOR]

High-fidelity flow modeling with data assimilation enables accurate representation of the wind farm operating environment under realistic, nonstationary atmospheric conditions. Capturing the temporal evolution of the turbulent atmospheric boundary layer is critical to understanding the behavior of wind turbines under operating conditions with simultaneously varying inflow and control inputs. This paper has three parts: the identification of a case study during a field evaluation of wake steering; the development of a tailored mesoscale-to-microscale coupling strategy that resolved local flow conditions within a large-eddy simulation (LES), using observations that did not completely capture the wind and temperature fields throughout the simulation domain; and the application of this coupling strategy to validate high-fidelity aeroelastic predictions of turbine performance and wake interactions with and without wake steering. The case study spans 4.5 h after midnight local time, during which wake steering was toggled on and off five times, achieving yaw offset angles ranging from 0 to 17°. To resolve nonstationary nighttime conditions that exhibited shear instabilities, the turbulence field was evolved starting from the diurnal cycle of the previous day. These background conditions were then used to drive wind farm simulations with two different models: an LES with actuator disk turbines and a steady-state engineering wake model. Subsequent analysis identified two representative periods during which the up- and downstream turbines were most nearly aligned with the mean wind direction and had observed yaw offsets of 0 and 15°. Both periods corresponded to partial waking on the downstream turbine, which had errors in the LES-predicted power of 4 % and 6 %, with and without wake steering. The LES was also able to capture conditions during which an upstream turbine wake induced a speedup at a downstream turbine and increased power production by up to 13 %. [ABSTRACT FROM AUTHOR]

In recent years, Electric Vehicles (EVs) are contributing a major share in Thailand and benefit the environment. Most of the EV charging stations are sourced from solar energy as it becomes a carbon-free source of energy production. Secondly, Thailand is rich in solar irradiance, and higher irradiance leads to higher power production. On the other hand, in tropical conditions, solar Photovoltaic (PV) module temperature increases following the solar irradiance due to high ambient temperature, resulting negative impact on the efficiency and lifespan of photovoltaic (PV) modules. Further, to increase PV power production, in this study, different rates of cooling strategies are proposed. The study found that reducing the temperature by 5% to 25% resulted in increased average power outputs of 5947.94W, 6021.43W, 6094.92W, 6168.41W, and 6241W, respectively. Notably, 25% of the cooling rate achieved higher production. However, it is lower than the nominal power production. Following that, economic analysis and environmental impacts are analyzed for Thailand's EV charging station using a different cooling rate of PV module. Overall, it is concluded that, depending on the economic viability of the EV charging station, cooling technology can be applied, and it will benefit the EV charging station both economically and environmentally. To further enhance the solar PV power production approach for EV charging stations in Thailand, it is imperative to prioritize future endeavors towards optimizing cooling technology, integrating energy storage, and implementing supportive policies. [ABSTRACT FROM AUTHOR]

The text examines the politics of water and access to ports in the Red Sea basin and the Indian Ocean, with a focus on the Great Ethiopian Renaissance Dam (GERD) and its impact on Egypt, Sudan, and Ethiopia. It explores the contested nature of water ownership and sovereignty, considering the influence of global capitalism and colonial legacies. The text also discusses the role of choke points in maritime trade and the potential for boycotts and strikes to challenge capitalist accumulation and foster solidarity. It offers a critical perspective on the relationship between land, sea, and power in the context of global maritime capitalism. Additionally, the text addresses the often overlooked labor of essential workers during the Covid-19 pandemic, particularly nurses, cashiers, cleaners, and waste collectors. It examines the vulnerabilities and proximity to death experienced by these workers, as well as the potential for imagining alternative economic, social, and medical systems. The text further explores the concept of water as a social space and blockage, particularly for brown and black people, and considers choke points and boycotts as spaces of potentiality and queer becoming. It emphasizes the need for critical reflection on dominant relations of rule and attention to alternative paths and routes. Finally, the text concludes by discussing the importance of granularity in understanding the invisible exchanges and environmental dynamics of capitalism. [Extracted from the article]

The current study aims to conduct a comprehensive analysis of the key parameters that affect the energy output of the Bagisli Hydropower Plant, located on the Zap River in the Dicle (Tigris) basin of Turkey. It considers the daily data for the time interval of 2016–2019 related to flow rate, precipitation, and temperature in relation to the generation of electricity. The relationship between energy output and flow rate is evident; however, the energy production is limited by the design flow rate. The largest flow rates were seen during the spring season after the occurrence of peak precipitation, which exhibited a shifting pattern. Similarly, energy generation also reaches its highest level during this time period. Another outcome of this study is that there is no apparent association between daily precipitation and daily energy generation. Moreover, a novel correlation with an R2 value of 0.89 has been proposed, in the deviation band of ±20%, to estimate energy generation when only flow rate data are available. [ABSTRACT FROM AUTHOR]

As the industry develops more and more, heat is produced during fabrication processes, resulting in an excess of heat. One of the ways to solve the problem can be the conversion of excess heat into electricity using a thermoelectric generator (TEG). The authors of this paper propose a method of using thin-film TEGs for electricity generation, a procedure that has been given little attention to in the literature. In this study, thin TEGs (about 50–100 nm thick) were obtained from Bi-Ni, using magnetron sputtering technology. This type of TEG can be used not only as a device that generates electricity, but also as a protective layer for various systems, protecting them from environmental influences. In addition, such TEGs can be formed on a complex, uneven surface, with various details changing their geometric shape. As shown from XRD studies, the obtained Bi-Ni layer is polycrystalline. XRD studies help to determine whether the layer obtained is composed of pure layers of Bi and Ni metals or whether metal oxides have formed (metal oxides have a negative effect on electrical conductivity). An increase in the temperature from 80 to 120 K, respectively, increases the voltage generated by the TEG from 0.01 to 0.03 V. Meanwhile, the efficiency of such TEG element changes from 1 to 4.5% when the temperature change increases from 30 to 119 K. [ABSTRACT FROM AUTHOR]

The paper presents a feasibility study for hybrid system operation of a hydroelectric power plant and a floating photovoltaic plant. Using the database of government agencies, it established the daily production of electrical energy and the corresponding water flow of the Ilha Solteira hydroelectric power plant in São Paulo, Brazil. The PVsyst software simulated the potential of 480 MWp of a floating photovoltaic plant in the hydroelectric power plant lake. The MATLAB software performed the mathematical modeling, analyzing 12 scenarios of weather conditions for hybrid electricity generation at the hydroelectric power plant and the floating photovoltaic plant. The data obtained in the analyzed scenarios show an average monthly reduction of 6% in hydroelectric power generation and 7% in the volume of water in the turbine, allowing the generation of electric energy from a floating photovoltaic plant, improving the reserves of waterenergy stock, reducing the production of greenhouse gases, and avoiding the emission of 55,000 tCO2/yr. The financial evaluation shows a cost of US$ 0.73/Wp, and 13 years for the floating photovoltaic plant system to start producing a profit. Yet the Floating Photovoltaic is advantageous because it shares the power transmission system of the hydroelectric plant, and it is not necessary to acquire large land areas. [ABSTRACT FROM AUTHOR]

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Under the background of "carbon peak" and "carbon neutral", carbon emissions in industrial linkages have become a current research hotspot. By screening key carbon reduction sectors in China at the provincial level and implementing corresponding industrial structure adjustment and optimization policies, the goal of carbon reduction can be accurately and efficiently achieved. This study is based on the multiple region input-output model in China, and uses the input-output method to construct an economic and carbon emission correlation model between provincial-level industries, and then analyzes the industrial sectors with significant carbon emission linkage nationwide. By using the method of industry correlation analysis, the changing trends of the influence coefficient and sensitivity coefficient between industrial sector economy and carbon emissions were explored, and key provincial-level carbon reduction departments in China were identified from the production and consumption sides, respectively. The main conclusions of this study indicated that at the national level, there are differences in the sectors with significant carbon emission correlations from different perspectives of backward and forward linkages. Specifically, on the supply side, the production and supply industries of electricity and heat are the sectors with the highest carbon emission correlation. On the consumption side, the construction industry is the sector with the highest carbon emission linkages. During the period 2010-2017, the production and supply industries of electricity and heat, as production side sectors, promoted the improvement of national carbon emission capacity and scale through backward linkage, but their contribution to the growth of national economic scale was relatively limited. The construction industry, as a consumer sector, has a significant impact on driving national carbon emissions through forward linkage rather than promoting the economy. At the provincial level, the key emission reduction sectors on the production side are mainly concentrated in the production and distribution of electric power and heat power in Hebei, Shanxi, Inner Mongolia, and the transportation and warehousing industry in Xinjiang. The key emission reduction sectors on the consumption side are mainly concentrated in the manufacture of non-metallic mineral products in Hebei, Inner Mongolia, Zhejiang, Jiangxi, Guangxi, Chongqing, Sichuan, Yunnan and Shaanxi, as well as the smelting and rolling processing of metals in Yunnan, and the transportation and warehousing industry in Xinjiang and Yunnan. Finally, this study proposes corresponding suggestions for different types of key carbon reduction provincial sectors in China based on the supply and consumption ends of the industrial chain. [ABSTRACT FROM AUTHOR]

Power density and efficiency typically dominate design approaches for power electronics. However, cost optimality is in no way guaranteed by these strategies. A design framework that minimizes the (i) levelized cost of electricity (LCOE), (ii) collection of light, and (iii) irradiance of the generation system is proposed as a solution to this flaw. From an improvement of the swarm behavior optimization model to get a minimum LCOE of solar panel, we design to optimize height, tilt angle, azimuth angle, and some parameters to solve the objective function and LCOE improvement problem to obtain the optimal design problem. In adaptive salp swarm optimization (ASSO), this change's proposed model producer swarm behavior is regarded as an adaptive process that keeps the algorithm from prematurely converging during exploration. The proposed algorithm's performance was confirmed using benchmark test functions, and the results were compared with those of the salp swarm optimization (SSO) and other efficient optimization algorithms. LCOE condition as far as "land‐related cost" and "module‐related cost" demonstrates that the optimal design of bifacial farms is determined by the interaction of these parameters. This proposed model can be used to evaluate visibility on building surfaces that are suitable for mining applications like crushing. Experimentation results show Minimum LCOE AS 0.05 (€/Kw)minimum irradiance and collection light as 336.23(w/m2) and 83.02%n proposed framework model. The swarm optimization method is contrasted with the optimal parameters derived from a conventional solver. [ABSTRACT FROM AUTHOR]

The renewable electricity quota standard (RES) policy plays an important role in achieving sustainable and green development targets. Thus, it is essential to measure the sustainability of the electric power sectors in the context of RES. In terms of the energy and environmental efficiency (EEE) measurements, few studies divided energy inputs into renewable and non-renewable energy or explored the restricted problem of minimizing resource summation. To fill these gaps, we propose an improved fix-sum energy input data envelopment analysis (FSIDEA) model based on the adjustment strategy of weighted sum minimization of renewable energy inputs. The assurance region (AR) restriction and renewable energy input sum constraint (IC) are, respectively, imposed on the FSIDEA model to achieve the common equilibrium effective frontier (EEF). Finally, this study assesses the EEE of the electric power sectors in China's 30 main regions based on the common EEF. The result reveals that Beijing and Shanghai can be selected as benchmarks after efficiency comparison. In addition, our proposed model can compressively rank all decision-making units (DMUs) compared with traditional efficiency models. [ABSTRACT FROM AUTHOR]

Most sub-Saharan African electricity generation is through renewable energy sources. However, the pace of renewable expansion is slow, mirrored by the region's low per capita electric power consumption and electricity access. The study examines the determinants of renewable electricity generation adoption in sub-Saharan Africa (SSA) countries using content description and a panel ARDL analysis. Findings from this study show that hydroelectric power is the long-standing renewable electricity source in the region. The deployment of non-hydro renewable electricity sources is slow despite its vast potential. In most evaluated countries, renewable electricity targets are below actual realization. Also, policies are ineffective in driving renewable electricity adoption, as indicated by the negative relationship between renewable electricity generation and policy enactments in SSA. Foreign direct investment and financial development significantly negatively impact renewable electricity adoption, suggesting that both factors do not expand renewable electricity generation. Feasible strategies for increasing non-hydro renewable electricity use include activating renewable energy support mechanisms and their uptake. In addition, governments in SSA should strengthen their legal and institutional frameworks and encourage lessening bottlenecks and bureaucracies associated with renewable electricity investment. [ABSTRACT FROM AUTHOR]

Russian hydrogen industry exists more than 100 years and is one of the biggest in the world. In 2021 Russia produced more than 5 mln tons of hydrogen (the 5th place in the world after China, US, EU-27, India), more than 1 mln tons of hydrogen were exported as hydrogen-contained production (ammonia, methanol, fertilizers). Following the global trends in the growth of production and use of hydrogen as an energy carrier, which plays the role of an important tool for reducing greenhouse gas emissions, decarbonization of energy, as well as the use of hydrogen in the transport sector and industry, the analysis of the current state and prospects for the development of hydrogen energy in Russia is carried out, the technologies of low-carbon hydrogen production at electric power, oil- and gas processing, logistics and technologies of transportation and storage of hydrogen, the world's leading and promising Russian developments are analyzed, the feasibility of their application in Russia is assessed. The main technology for hydrogen production in Russia remains SMR: by using this technology more than 95 % of hydrogen is produced. At the same time, electrolyzers are present in many industries (oil refineries, power generation, hydrometeorology, microelectronics, food industry etc.). Russian nuclear power plant giant Rosatom is seriously studying the possibility of producing hydrogen in nuclear power plants by using high-temperature technologies. There are no main hydrogen pipelines in Russia (only internal technological pipelines) because big industrial plants that use hydrogen construct their hydrogen facilities on-site. Smaller amounts of hydrogen are delivered to the customers in a compressed state and stored in steel cylinders or reservoirs. Currently, Russian companies and organizations process development in hydrogen transportation and storage in compressed (up to 700 bars, including polymer reservoirs), liquid and bound states. In addition to traditional hydrogen consumers (hydrocarbon refineries, chemical plants) and metallurgy (7 furnaces for iron production) Russian companies and organizations develop hydrogen energy storage units, and there are pilot projects in the commercial and heavy vehicles, buses, river boats). [ABSTRACT FROM AUTHOR]

This article provides a comprehensive overview of the performance evaluation of looped tube thermoacoustic power generators using numerical and experimental analysis. The study focuses on small-scale generators operating at atmospheric pressure and utilizing low-cost linear alternators. The analysis considers factors such as temperature variation, pressure fluctuation, volume flow rate, and acoustic power distribution. The results show that the generators produce maximum acoustic power at a frequency of 78 Hz, with an overall thermal to electric efficiency of approximately 8.3%. The article also includes references to other research papers and articles that cover various aspects of thermoacoustic engines and generators, providing valuable insights into the field. [Extracted from the article]

Electricity generation in Europe is undergoing a fundamental change. The aim is to increase sustainability by reducing emissions. Each country has a different electricity mix, and there is no established method for measuring environmental impacts of electricity production with a single monetary indicator, in a uniform manner, and with country-specific data. To address this gap, a model that measures the costs of 19 environmental externalities (usually, types of emissions) has been developed. Using country-specific technologies, electricity mixes, and external cost rates, the development of external costs of generating electricity in 27 European countries between 2010 and 2030 is assessed and analyzed. The simulation results show that the external costs vary heavily between 2.1 and 22.4 euro cents per kWh in this period. Despite the initiated transformation of the energy systems in many EU countries, external costs per kWh are decreasing in only eight of them. This fact underlines the need for a drastic change in national energy strategies. Overall, the results show that more far-reaching policy measures are needed in order to significantly reduce the external costs of the energy sector in Europe. The article raises the level of granularity of research on the external costs of electricity in Europe by combining extensive country-specific emission data and country-specific external cost rates. [ABSTRACT FROM AUTHOR]

As electricity systems become increasingly dominated by variable inverter-based generation (such as wind and solar photovoltaics (PV)), additional sources of variability appear, while the share of dispatchable thermal power plants decreases. Maintaining a stable grid frequency requires new sources of inertia to slow the frequency changes, as well as new sources of reserve power to counter the imbalances. This work uses a linear optimization modeling approach to analyze the reserve market of the electricity system during the transition to a carbon-free system with high shares of variable electricity generation. The modeling is performed for three regional contexts and with varying degrees of available flexibility technologies. As for the reserve supply, batteries, electrolyzers, electric boilers and heat pumps for district heating, curtailed wind and solar power, and hydropower and thermal power plants are all included. The results indicate that of these suppliers of reserves, the introduction of grid-scale batteries into the system drastically reduces the reserve market size. Only early in the transition is revenue from the reserve market greater than 5% of the total revenue for any technology. While the demand for reserves increases as the share of solar PV and wind power increases, the modeling reveals that access to flexible loads, storage units, and emulated inertia from wind power also increases. Depending on the choice of flexibility measures available, demand-side participation could play a major role in minimizing the cost of grid stability in the future. [ABSTRACT FROM AUTHOR]

A sustainable, affordable, and eco-friendly solution has been proposed to address water heating, electricity generation, space cooling, and photovoltaic (PV) cooling requirements in scorching climates. The photovoltaic thermal system (PV/T) and the direct expansion PV/T heat pump (PV/T DXHP) were numerically studied using MATLAB. A butterfly serpentine flow collector (BSFC) and phase change material (PCM) were assimilated in the PV system and MATLAB model was developed to evaluate the economic and enviroeconomic performance of the PV/T water system (PV/T-W), PV/T PCM water system (PV/T PCM-W), the PV/T DXHP system, and the PV/T PCM heat pump system (PV/T-PCM-DXHP). In this study, annual energy production, socioeconomic factors, enviro-economic indicators, and environmental characteristics are assessed and compared. Also, an economic, environmental, and enviro-economic analysis was conducted to assess the commercial viability of the suggested system. The PV/T PCM-DXHP demonstrated the highest electrical performance of 53.69%, which is comparatively higher than the other three configurations. The discounted levelized cost of energy (DLCOE) and payback period (DPP) of the PV/T PCM-DXHP were ₹2.87 per kW-h and 3–4 years, respectively, resulting in a total savings of ₹67,7403 over its lifetime. Furthermore, installing this system mitigated 280.72 tonnes of CO2 emissions and saved the mitigation cost by ₹329,700 throughout its operational lifecycle. [ABSTRACT FROM AUTHOR]

Renewable energy production is one of the most important strategies to reduce the emission of greenhouse gases. However, wind and solar energy especially depend on time-varying properties of the environment, such as weather. Hence, for the control and stabilization of electricity grids, the accurate forecasting of energy production from renewable energy sources is essential. This study provides an empirical comparison of the forecasting accuracy of electricity generation from renewable energy sources by different deep learning methods, including five different Transformer-based forecasting models based on weather data. The models are compared with the long short-term memory (LSTM) and Autoregressive Integrated Moving Average (ARIMA) models as a baseline. The accuracy of these models is evaluated across diverse forecast periods, and the impact of utilizing selected weather data versus all available data on predictive performance is investigated. Distinct performance patterns emerge among the Transformer-based models, with Autoformer and FEDformer exhibiting suboptimal results for this task, especially when utilizing a comprehensive set of weather parameters. In contrast, the Informer model demonstrates superior predictive capabilities for onshore wind power and photovoltaic (PV) power production. The Informer model consistently performs well in predicting both onshore wind and PV energy. Notably, the LSTM model outperforms all other models across various categories. This research emphasizes the significance of selectively using weather parameters for improved performance compared to employing all parameters and a time reference. We show that the suitability and performance of a prediction model can vary significantly, depending on the specific forecasting task and the data that are provided to the model. [ABSTRACT FROM AUTHOR]

The studies have focused on changes in CO2 emissions over different periods, including the COVID-19 pandemic. Even if CO2 emissions are temporarily reduced during the pandemic according to annual figures, this may be misleading. Considering annual figures is important to understand the overall trend, but using data with much higher frequency (e.g., daily) is much better suited to investigate dynamic relationships and external effects. Therefore, this study comprehensively analyzes the association between CO2 emissions and disaggregated electricity generation (EG) sources across the globe by employing the novel wavelet local multiple correlation (WLMC) approach on daily data from 1st January 2020 to 31st March 2023. The results demonstrate that (1) based on the main statistics, daily CO2 emissions range between 69 MtCO2 and 116 MtCO2, indicating that there is an oscillation, but no sharp changes over the analyzed period. (2) based on the baseline regression using the dynamic ordinary least squares (DOLS) approach, the constructed estimation models have a high predictive ability of CO2 emissions, reaching ~ 94%; (3) in the further analysis employing the WLMC approach, there are significant externalities between EG resources, which affect CO2 emissions. The results present novel insights about time- and frequency-varying effects as well as a disaggregated analysis of the effect of EG on CO2 emissions, demonstrating the significance of the energy transition towards clean sources around the world. [ABSTRACT FROM AUTHOR]

To achieve the Sustainable Development Goals by 2030, low-income sub-Saharan African countries urgently need to electrify. Biogas production from anaerobic digestion could make a contribution to a solution to improved electricity generation and access in these regions. This study evaluates its feasibility using Malawi as a case study. The aim is to provide households with a continuous supply of gas for cooking and electricity. The study examines different sizes of fixed dome reactors (3, 6, 12 m3) and assumes individual household ownership of 2, 4, and 6 cows. Several feedstocks and conditions are considered, such as cow dung alone, co-generation of cow dung with human faeces, cow dung with grass, and cow dung with maize residue. The economic benefits of selling biogas and fertilisers are calculated, and the cost of construction for different sizes of reactors is determined. Results show that co-generation of cow dung and grass silage in the reactor of 12 m3 with six cows has a positive net present value (NPV) of $8962, while for a small farm with a 6 m3 reactor capacity, co-digestion of cow dung with maize residue is preferable. The feasibility of the technology depends heavily on current national economic conditions, such as inflation, electricity prices, and construction material costs. A sensitivity analysis estimated that a 25% increase in the cost of electricity could increase the net present value (NPV) from − $3345 to $1526 for the generation of biogas from cow dung alone. Overall, this technology could have a significant impact on the lives of low-income households in sub-Saharan Africa by improving their access to electricity and providing a source of income through the sale of biogas and digestate. [ABSTRACT FROM AUTHOR]

The research on constructed wetland (CW) and microbial fuel cell (MFC) has been separate studies worldwide with crucial achievements being made in both fields. Due to environmentally friendly feature (of CW) and rich microbial population and excellent electrode catalytic activity (of MFC), CW and MFC have their own anticipated application prospect in wastewater purification and biological electricity generation. More significantly, the idea of embedding MFC into CW to form CW-MFC expands the scope for both of them and this has received much interest in recent years due to its striking features of sewage treatment efficiency, electricity generation, sustainability, and environmental friendliness. The increasing interest and the lack of soul of CW-MFC emerging to the new researchers reflect the need to recall the idea and summarize its development with regard to achieving its reality via some key issues This forms the basis of the paper. The paper also includes how to enhance the efficiency of electricity generation and supplement energy consumption, the degradation of emerging pollutants, and the degradation mechanism as well as the potential joint application of CW-MFC with other treatment technique. A mass of CW-MFC design parameters has been synthesized from the literature. Challenges and potential directions of CW-MFC in the future are prospected. It is expected that the paper can serve as a linkage for bridging knowledge gaps for further studies of CW-MFC. [ABSTRACT FROM AUTHOR]

This paper presents a numerical algorithm for environmental/economic load dispatch (EELD) with emissions constraints, which takes into account the emissions trading system's effect on electricity generation cost and is implemented using a Python computer program. The developed program is applied to a power system of six (6) fossil-fueled electricity generating units with NOx, SO2 and CO2 constraints and proved to be significantly beneficial not only for the environment but also for the power company and the consumers. The proposed algorithm uses multi-objective optimization and incorporates both fuel and emissions allowances costs. The schedule of generating units is calculated and the testing of all possible weighting factor combinations with resolution of 0.01 is carried out showing that the proposed algorithm is fast, cost effective and environmentally friendly. [ABSTRACT FROM AUTHOR]

The electrode played an essential role in the operation of CW-MFC system due to its synergistic effect, and the development of electrode strategy has promoted the application of CW-MFC since 2012. In this paper, according to the material and the quantity, the electrode types in CW-MFC were distinctly divided into unified model, composited model, modified model, and multi-electrodes model combined with non-conductive or conductive particle. Different electrode strategies were provided to improve the performance of CW-MFC towards electricity generation, removal of pollutants, and control of greenhouse gas emission, and the coordination mechanism was further reviewed. Furthermore, the development process of the electrode strategy was summarized, and the low-cost, sustainable, and innovated electrode materials were emphatically recommended. For the scale-up application, multi-electrode model was systematically reviewed based on the optimizing of the material, shape, spacing distance, and connection type of electrode. This review may provide guidance to maximize the advantages of CW-MFC applications. Highlights: • Electronic receiver and non-conductive or conductive particle was firstly classified. • The electrode application on electricity generation and pollutant removal was reviewed. • The application of emerging electrode materials in CW-MFC was summarized. • The multi-anode and multi-cathode strategy may facilitate the scaling-up of CW-MFC. • The development of electrode material was prospected to extend the function of CW-MFC. [ABSTRACT FROM AUTHOR]

Environmental pollution is becoming ubiquitous; it has a negative impact on ecosystem diversity and worsens the quality of human life. This review discusses the possibility of applying the plant microbial fuel cells (PMFCs) technology for concurrent processes of electricity generation and the purification of water and soil ecosystems from organic pollutants, particularly from synthetic surfactants and heavy metals. The review describes PMFCs' functioning mechanisms and highlights the issues of PMFCs' environmental application. Generally, this work summarizes different approaches to PMFC development and to the potential usage of such hybrid bioelectrochemical systems for environmental protection. [ABSTRACT FROM AUTHOR]

This study investigates the potential for renewable energy-based electricity generation using existing wave, wind, and solar energies in Türkiye. A significant part of Türkiye's energy needs is still met using fossil fuels. Considering the country's resources, renewable energy sources appear as an alternative source to meet these needs. The objective of this study is to find an effective, efficient, economical, environmentally friendly, and sustainable way to produce electricity to reach net-zero targets and transition towards low-carbon and carbon-free energy systems. To be able to make a deep investigation about the relevant issue, six provinces from different regions of Türkiye (Antalya, Çanakkale, İstanbul, İzmir, Kırklareli, and Muğla) are assessed in terms of wave, wind, and solar energy potential, including wave data, wind speeds, sunshine duration, and global radiation values. Wind, wave, and solar energy data of the selected regions were taken from the ERA5 database, which is the weather forecast model of the European Center for Medium-Term Weather Forecasts (ECMWF), and the Ministry of Energy and Natural Resources of the Republic of Türkiye and the General Directorate of Meteorology. Calculations were made using monthly data for the last 5 years. Considering the coastal lengths in the determined regions, the annual total electrical power produced from wave, solar, and wind energies was calculated. In these calculations, the coastal length parameter was assumed to be uniform across all cities, and the electrical power potential from these energy sources was analyzed. Within the framework of these analyses, the number of houses in the selected regions whose electricity needs can be met was calculated. As a result, the potential electrical power and the amount of affordable housing units in the selected regions were compared. As an important result of the studies, it was determined that the characteristic features of the selected regions, such as wavelength, wave height, and wind speed, were directly related to the applicable coast length. The power obtained from wave energy was higher than that from other renewable energy sources, considering the determined coast lengths. Wave energy was followed by parabolic solar collector, wind, and photovoltaic solar energy systems. According to the model, the power obtained from renewable energy systems was at the highest level in the Kırklareli/Demirköy province compared to other locations. Kırklareli was followed by İstanbul, Antalya, İzmir, Muğla, and Çanakkale. It was also found that the electricity needs of 763,578 houses were met in the Kırklareli/Demirköy region, and the electricity needs of 470,590 houses were met in the Çanakkale/Ayvacık region. The statistically optimized factors using the Response Surface Methodology (RSM) for wind, photovoltaic, parabolic solar collector, and wave power were reported as 995.278, 4529.743, 2264.546, and 276,495.09, respectively. The optimal factors aim to achieve a total electricity generation rate of 2.491 × 109 (kWh/year), a total number of houses of 682,590.55 (number/year), and a total cost of USD 813,940,876. In line with the results obtained, the Kırklareli/Demirköy region becomes favorable when considering wave and wave-integrated wind and solar energies. The proposed system has the potential to meet the entire electricity demand of the Kırklareli province based on data from the Republic of Türkiye Energy Market Regulatory Authority (EMRA). [ABSTRACT FROM AUTHOR]

To achieve sustainable development, the energy transition from lignite burning to renewable energy resources for electric power generation is essential for Greece. Wind and solar energy have emerged as significant sources in this transition. Surprisingly, numerous studies have examined the potential for onshore wind based on land eligibility, while few studies on open-field photovoltaic (PV) installations have been conducted. Therefore, based on the Specific Framework for Spatial Planning and Sustainable Development for Renewable Energy Sources (SFSPSD-RES), along with insights from previous relevant studies, this work conducts a land eligibility analysis of onshore wind and open-field PV installations in Greece using the software Geospatial Land Availability for Energy Systems (GLAES 1.2.1) and ArcGIS 10.2. Additionally, through an in-depth exploration of wind and solar PV energy potential in decommissioned lignite mines integrated with wind power density (WPD) and global horizontal irradiation (GHI) maps, this study compares the suitability of wind versus solar as energy sources for the decarbonization of Greece. Overall, despite the greater spatial eligibility for onshore wind turbines compared to open-field PV power plants, the relatively lower wind energy potential and operational limitations of wind turbines lead to the study's conclusion that solar energy (PV) is more suitable for the decarbonization of Greece. [ABSTRACT FROM AUTHOR]

Combined concentrated solar power with photovoltaics can provide electricity and heat at the same system while maximizing the power output with reduced losses. Spectral splitting is required in such systems to separate the infrared part of the solar spectrum towards the thermal system, while the visible and near-infrared radiation can be converted by the photovoltaic solar cell. The performance of concentrated solar power plants comprising reflective beam splitters for combined generation of electricity and heat is presented in this work. A 50 MW power plant is considered in this work as a case of study in Southern Crete, Greece. The solar power plant consists of parabolic trough collectors and utilizes beam splitters with varying reflectivity. The dynamic performance of the power plant is modeled, and the annual energy yield can be calculated. Up to 350 MWt of thermal power can be delivered to the photovoltaic system utilizing a 50% reflecting splitter. The penalty to the high-reflectivity system is limited to 16.9% and the annual energy yield is calculated as 53.32 GWh. During summer months, a higher energy yield by up to 84.8 MWh/month is produced at 80% reflectivity compared to 90% as a result of the number of parabolic troughs. The reported energy yields with reflectivity by dynamic modeling can highlight discrete points for improvement of the performance in concentrated solar power photovoltaics. [ABSTRACT FROM AUTHOR]

As an instrument supporting the realization of EU climate neutrality targets by 2050 and encouraging decarbonization outside its borders, the current proposed Carbon Border Adjustment Mechanism (CBAM) is facing opposition from some countries. Focusing on Brazil, this paper evaluates the impacts of the CBAM on the Brazilian economy through a comprehensive analysis of various scenarios based on the potential EU implementation of the CBAM and Brazil's climate scenarios. Results obtained in this research alleviate concerns of detrimental and competitiveness losses from Brazilian industries. Rather, the implementation of the EU CBAM improves the trade balance of Brazil's Energy-Intensive Industries (EII). The relatively low CO2 contents of Brazilian EII are elemental to this result, while contributions of carbon-free technologies in electricity generation are also critical factors in maximizing this trade surplus. Other consequential factors affecting these results are the contributions of CO2 removal from Brazil's forestry of land used, and homogeneity of CBAM-imposed products. [ABSTRACT FROM AUTHOR]

Summary: At present, the implementation of fuel cell power generation system in electric vehicles has been widely concerned. But the voltage produced by fuel cells is generally relatively low and cannot be supplied directly to the load or grid. To raise its output voltage, a new single‐switch dc‐dc boost topology is put forward in this article. That converter has some characteristics as below: (1) The common ground structure availably avoids electromagnetic interference and improves the reliability of the system. (2) All power semiconductor devices withstand inferior to half the output voltage. (3) The input current avoids pulsation and small number of switching devices that greatly prolong the service life of the fuel cell. The circuit working principle, steady‐state performance, the design of device parameters, and comparison with similar boost topologies are researched. Finally, a 100‐W experimental platform is set up to validate the above features and guarantee the infallibility of theoretical research. [ABSTRACT FROM AUTHOR]