Hasil untuk "Renewable energy sources"

Omran Moradlou, Mohammad Qorbani, Amr Sabbah et al.

A strategy is presented to mitigate copper surface reconstruction during electrochemical CO2 reduction reaction (EC‐CO2RR) by conformally coating copper microcubes (CuMCs) with an ultrathin (≈2 nm) polydopamine (PDA) layer. The formation of nanocubes (30–50 nm in size) at the surface of microcubes at the early stages of the EC‐CO2RR contributes to suppressed surface reconstruction and sustained Faradaic efficiency (FE) for C2 products. Furthermore, PDA coating effectively stabilizes adsorbed COatop and CObridge intermediates and promotes CC coupling. As a result, the FE for C2 products increases from 52.0 ± 4.0% for unmodified CuMCs to 81.6 ± 2.8% for PDA‐coated CuMCs at −1.18 V versus reversible hydrogen electrode (VRHE). The PDA coating effectively slows down the surface evolution process of the catalyst during electrolysis. After 18 h of continuous operation at −0.88 VRHE, the CuMCs retain their original framework owing to a tightly adhered PDA layer that effectively stabilizes the surface and enhances catalyst durability. In situ surface‐enhanced infrared absorption spectroscopy confirms the presence of adsorbed COatop, CObridge, and OCCOH intermediates on PDA/CuMCs surface, which are believed to boost CC coupling. This work highlights the potential of polymer film to stabilize the catalyst surface and steer product distribution in CO2 electroreduction.

Shevchenko S., Danylchenko D., Hanus R. et al.

The article discusses methods for calculating the moisture discharge voltage of insulators under various operating conditions (pollution, humidity, etc.) to identify patterns of environmental influence on operational characteristics, as well as to improve the reliability and safety of power grids. The main aim of the study is to compare two approaches to calculating the moisture discharge characteristics of insulators: the classical method based on the Tepler formula and an alternative approach that utilizes generalized parameters. These parameters can be easily obtained from the technical characteristics of insulators or design standards for automated calculations. To achieve this goal, the authors addressed several important tasks. First, a comprehensive analysis of the behavior of electrical discharges on the surface of insulators under various operating conditions, including standard and adverse environments, was conducted. Second, an automated tool was developed to quickly and accurately determine the values of moisture discharge voltage. Third, the proposed method was experimentally validated using the LK 70-110 insulator. The tests revealed a discharge voltage of 549 kV and an electric field intensity of 2.1 kV/cm, confirming the accuracy of the calculation method. The key findings of the study highlight the importance of considering factors such as the properties of insulator surfaces and the degree of contamination, especially in underground substations where humidity and pollution exhibit specific characteristics. The proposed approach proved effective both in standard and challenging operating conditions. The significance of the results lies in the creation of a tool that simplifies the calculation of moisture discharge characteristics of insulators.

Mahmoud Alsharkawy, Ahmed Hamdy, Mohamed Marzouk

This research presents a methodology for assessing the contractor's abidance towards preserving the environment during the construction phase. This goal is achieved by the indication of the most prevalent factors. Based on a thorough literature review and experts' review, a list of forty factors is presented, which are grouped into nine categories. These categories are: Solid Waste Management; Water Management; Energy Efficiency; Pollutants Control; Traffic Management; Site Arrangement; Procurement; Awareness Leverage & Education; and Social Governance. Firstly, a two-step questionnaire survey is conducted in this research to review and assess the factors list extracted from the literature review. Upon completing the questionnaire survey, statistical analysis is applied, including the Analysis of Variance (ANOVA) test, Exploratory Factors Analysis (EFA), and the Cronbach's Alpha test for reliability, resulting in thirty-two final factors list after eliminating eight factors. Using the weights calculated by the Best-Worst Method (BWM) and the assessment benchmarks set for each factor, the environmental scoring sheet is generated along with the overall scoring evaluation thresholds to indicate the holistic environmental performance grade. Finally, the application of the proposed research methodology is presented by applying the scoring tool through a case study.

Hannah Bossi, Yi Chen, Yu-Chen Chen et al.

Quantum Chromodynamics (QCD) is a remarkably rich theory exhibiting numerous emergent degrees of freedom, from flux tubes to hadrons. Their description in terms of the underlying quarks and gluons of the QCD Lagrangian remains a central challenge of modern physics. Colliders offer a unique opportunity to probe these phenomena experimentally: high energy partons produced from the QCD vacuum excite these emergent degrees, imprinting their dynamics in correlations in asymptotic energy flux. Decoding these correlations requires measurements with exceptional angular resolution, beyond that achieved in previous measurements. Recent progress has enabled precision calculations of energy flux on charged particles alone, allowing data-theory comparisons for measurements using high resolution tracking detectors. In this Letter, we resurrect thirty-year-old data from the ALEPH tracker, and perform a high angular resolution measurement of the two-point correlation of energy flux, probing QCD over three orders of magnitude in scale in a single measurement. Our measurement unveils for the first time the full spectrum of the correlator, including light-ray quasi-particle states, flux-tube excitations, and their transitions into confined hadrons. We compare our measurement with record precision theoretical predictions, achieving percent level agreement, and revealing interesting new phenomena in the confinement transitions. More broadly, we highlight the immense potential of this newly unlocked archival data set, the so called "recycling frontier", and emphasize synergies with ongoing and future collider experiments.

Joanna Jałocha, Łukasz Bratek

We investigate the dynamical behavior of strange quark matter (SQM) objects, such as stars and planets, when subjected to radial oscillations induced by tidal interactions in stellar systems. Our study demonstrates that SQM objects can efficiently convert mechanical energy into hadronic energy due to the critical mass density at their surfaces of 4.7*10^{14} g/cm^3, below which SQM becomes unstable and decays into photons, hadrons, and leptons. We show that even small-amplitude radial oscillations, with a radius change of as little as 0.1%, can result in significant excitation energies near the surface of SQM stars. This excitation energy is rapidly converted into electromagnetic energy over short timescales approximately 1 ms, potentially leading to observable astrophysical phenomena. Higher amplitude oscillations may cause fragmentation or dissolution of SQM stars, which has important implications for the evolution of binary systems containing SQM objects and the emission of gravitational waves.

Carla Goncalves, Ricardo J. Bessa, Tiago Teixeira et al.

Accurate power forecasting from renewable energy sources (RES) is crucial for integrating additional RES capacity into the power system and realizing sustainability goals. This work emphasizes the importance of integrating decentralized spatio-temporal data into forecasting models. However, decentralized data ownership presents a critical obstacle to the success of such spatio-temporal models, and incentive mechanisms to foster data-sharing need to be considered. The main contributions are a) a comparative analysis of the forecasting models, advocating for efficient and interpretable spline LASSO regression models, and b) a bidding mechanism within the data/analytics market to ensure fair compensation for data providers and enable both buyers and sellers to express their data price requirements. Furthermore, an incentive mechanism for time series forecasting is proposed, effectively incorporating price constraints and preventing redundant feature allocation. Results show significant accuracy improvements and potential monetary gains for data sellers. For wind power data, an average root mean squared error improvement of over 10% was achieved by comparing forecasts generated by the proposal with locally generated ones.

Tiago Fonseca, Clarisse Sousa, Ricardo Venâncio et al.

The electrification of transportation and the increased adoption of decentralized renewable energy generation have added complexity to managing Renewable Energy Communities (RECs). Integrating Electric Vehicle (EV) charging with building energy systems like heating, ventilation, air conditioning (HVAC), photovoltaic (PV) generation, and battery storage presents significant opportunities but also practical challenges. Reinforcement learning (RL), particularly MultiAgent Deep Deterministic Policy Gradient (MADDPG) algorithms, have shown promising results in simulation, outperforming heuristic control strategies. However, translating these successes into real-world deployments faces substantial challenges, including incomplete and noisy data, integration of heterogeneous subsystems, synchronization issues, unpredictable occupant behavior, and missing critical EV state-of-charge (SoC) information. This paper introduces a framework designed explicitly to handle these complexities and bridge the simulation to-reality gap. The framework incorporates EnergAIze, a MADDPG-based multi-agent control strategy, and specifically addresses challenges related to real-world data collection, system integration, and user behavior modeling. Preliminary results collected from a real-world operational REC with four residential buildings demonstrate the practical feasibility of our approach, achieving an average 9% reduction in daily peak demand and a 5% decrease in energy costs through optimized load scheduling and EV charging behaviors. These outcomes underscore the framework's effectiveness, advancing the practical deployment of intelligent energy management solutions in RECs.

Abhishek Kumar, Jyoti, Shweta Tomer et al.

Transition metal oxide films (TMO) as passivating contacts with improved opto-electronic characteristics play an important role in improving the silicon solar cell device efficiency. In this report, the effect of sputtering power on the optical properties of MoOx and the quality of MoOx/n-Si interface for its application in a silicon solar cell as carrier selective contacts has been reported. The optical transmittance of the film greater than 80 % in the visible and near infrared region of the spectrum is observed, which further improved with sputtering power. The creation of oxygen ion vacancies, which acts as positively charged structural defects able to capture one or two electrons led to the decrease of optical band gap from 3.70 eV to 3.23 eV at higher power. The oxygen vacancies occupied by electrons acts as donor centers, which lies close to the valence band, were responsible for modulation in electrical properties. The electrical properties of MoOx/n-Si interface was analyzed using current-voltage (I-V) measurements for its application as selective contact. A significant change in the selectivity parameters, like barrier height, I0 and series resistance of MoOx, has been observed with dc power. These extracted parameters showed that the sputtering power has a great influence on the selectivity of the charge carriers.

Shoya Ohsumi, Yoshiki J. Sato, Ryuji Okazaki

Materials with axis-dependent conduction polarity are known as p×n-type or goniopolar conductors that can be used for transverse thermoelectric devices, allowing the longitudinal thermal current to be converted into the transverse electrical current. Here, we have performed experimental and computational studies on the transport properties of WSi_{2} single crystals, in which such axis-dependent conduction polarity of the thermopower and the Hall coefficient have recently been reported, and demonstrated the transverse thermoelectric effect by applying the temperature gradient in a direction rotated 45^{∘} from the crystallographic axis. We have observed strongly sample-dependent transport properties, which have also been observed in previous studies, and together with first-principles calculations we show that such sample-dependent transport properties originate from the band-dependent scattering rates of carriers. The calculated band-resolved Peltier conductivity shows that the mixed-dimensional electronic structure consisting of a quasi-one-dimensional electron Fermi surface and a quasi-two-dimensional hole surface is a key property for the axis-dependent conduction polarity. The directly obtained transverse thermoelectric figure of merit is comparable to that of the anomalous Nernst materials, implying that the present material is a potential candidate for transverse thermoelectric conversion.

Bumanis Girts, Bajare Diana

Thermal insulation materials used in civil engineering have been developing throughout time. One of the latest thermal insulation used in construction sites with gained popularity is EPS aggregate and mineral binder-based composite. Waste recycling potential, low cost, and ease of installation have brought popularity to the material. This research investigates such material which is formulated by EPS aggregates and pure Portland cement binder thus making EPS aggregate concrete (EAC). Many contractors use such untested and uncertified EAC material due to the low cost of the raw materials. In this research, EAC was taken directly from the construction site. Material physical and mechanical properties are evaluated and compared to commercial counterparts. The drying of the material was investigated, following the practice in the construction sites where upper covering layers are built according to the time schedule ignoring material drying process. Results were compared with commercial EAC. Results indicate that rapid construction schedule with layer-to-layer covering of wet EAC results in dramatically slow drying of such composites, which is one of the main problems for safe use in civil engineering. EAC density from 113 to 169 kg/m3 was measured with an average compressive strength of 49 kPa. The thermal conductivity of the tested EAC was from 0.050 to 0.055 W/(mK).

Sobti Rajeev, Anjaneyulu M.

The paper examines the use of genetic algorithm (GA) methods to optimize hybrid renewable energy microgrids by merging various renewable sources and energy storage technologies. An examination of meteorological data over many days reveals fluctuations in solar irradiance ranging from 4.8 kW/m² to 5.5 kW/m² and wind speed oscillating between 3.9 m/s and 4.5 m/s, indicating the presence of dynamic weather conditions. An analysis of energy generating capabilities reveals a wide range of potentials, with solar capacities varying from 80 kW to 150 kW and wind capacities ranging from 60 kW to 120 kW across different sources. An analysis of Energy Storage System (ESS) specifications shows a range of values for maximum capacities, charge/discharge efficiencies (ranging from 85% to 96%), and maximum charge/discharge rates (from 60 kW to 100 kW), highlighting the need for flexible energy storage systems. The examination of microgrid load profiles reveals the presence of diverse energy needs, with residential loads oscillating between 48 kW and 55 kW, commercial loads ranging from 40 kW to 47 kW, and industrial loads spanning from 30 kW to 36 kW. A percentage change study reveals the ability to adapt, with solar irradiance and wind speed showing mild fluctuations of roughly 14% and nearly 15% respectively. In contrast, renewable source capacity demonstrate significant percentage changes ranging from around 40% to 50%. These results highlight the ever-changing characteristics of renewable energy sources, underlining the need for strong optimization tactics in microgrid systems. The study emphasizes the potential of GA-based approaches in developing efficient microgrids, promoting sustainable and dependable energy solutions in the face of changing environmental circumstances and varied energy requirements.

Mohammad Reza Karimi Gharigh, Lamia Varawala, Mohammad Reza Hesamzadeh et al.

The impact of energy production significantly affects system sustainability, which has enabled a shift towards renewable energy sources. Thus, producer behavior is crucial in electricity markets to achieve sustainability goals. In this paper, we address two key challenges comprising electricity markets and generation investment. Firstly, electricity markets typically are operated with competitive market clearing and merit-order dispatch, which neglects negative externalities from pollution. A Pigouvian tax is proposed in order to investigate the impacts of these externalities on electricity prices and resolve this issue. Secondly, renewable energy sources entail low operational costs, which result in lower system prices and reduced profits for producers. Furthermore, producers face high investment costs when moving into renewable energy resources, which leads to strategic investment decisions. In order to mitigate this strategic behavior, subsidies are proposed equal to producers' contribution to consumer surplus. These subsidies incentivize producers to decrease prices and increase consumer surplus, so, producers would be motivated to invest in socially optimal generation capacity. Finally, we demonstrate that implementing the proposed tax and subsidy does not increase the regulator's information burden.

Nonthawat Khortsriwong, Promphak Boonraksa, Terapong Boonraksa et al.

Recently, deep learning techniques have become popular and are widely employed in several research areas, such as optimization, pattern recognition, object identification, and forecasting, due to the advanced development of computer programming technologies. A significant number of renewable energy sources (RESs) as environmentally friendly sources, especially solar photovoltaic (PV) sources, have been integrated into modern power systems. However, the PV source is highly fluctuating and difficult to predict accurately for short-term PV output power generation, leading to ineffective system planning and affecting energy security. Compared to conventional predictive approaches, such as linear regression, predictive-based deep learning methods are promising in predicting short-term PV power generation with high accuracy. This paper investigates the performance of several well-known deep learning techniques to forecast short-term PV power generation in the real-site floating PV power plant of 1.5 MWp capacity at Suranaree University of Technology Hospital, Thailand. The considered deep learning techniques include single models (RNN, CNN, LSTM, GRU, BiLSTM, and BiGRU) and hybrid models (CNN-LSTM, CNN-BiLSTM, CNN-GRU, and CNN-BiGRU). Five-minute resolution data from the real floating PV power plant is used to train and test the deep learning models. Accuracy indices of MAE, MAPE, and RMSE are applied to quantify errors between actual and forecasted values obtained from the different deep learning techniques. The obtained results show that, with the same training dataset, the performance of the deep learning models differs when testing under different weather conditions and time horizons. The CNN-BiGRU model offers the best performance for one-day PV forecasting, while the BiLSTM model is the most preferable for one-week PV forecasting.

Dongwei Zhao, Audun Botterud, Marija Ilic

This paper evaluates market equilibrium under different pricing mechanisms in a two-settlement 100%-renewables electricity market. Given general probability distributions of renewable energy, we establish game-theoretical models to analyze equilibrium bidding strategies, market prices, and profits under uniform pricing (UP) and pay-as-bid pricing (PAB). We prove that UP can incentivize suppliers to withhold bidding quantities and lead to price spikes. PAB can reduce the market price, but it may lead to a mixed-strategy price equilibrium. Then, we present a regulated uniform pricing scheme (RUP) based on suppliers' marginal costs that include penalty costs for real-time deviations. We show that RUP can achieve lower yet positive prices and profits compared with PAB in a duopoly market, which approximates the least-cost system outcome. Simulations with synthetic and real data find that under PAB and RUP, higher uncertainty of renewables and real-time shortage penalty prices can increase the market price by encouraging lower bidding quantities, thereby increasing suppliers' profits.

Pawel Robert Smolinski, Joseph Januszewicz, Barbara Pawlowska et al.

Poland is currently undergoing substantial transformation in its energy sector, and gaining public support is pivotal for the success of its energy policies. We conducted a study with 338 Polish participants to investigate societal attitudes towards various energy sources, including nuclear energy and renewables. Applying a novel network approach, we identified a multitude of factors influencing energy acceptance. Political ideology is the central factor in shaping public acceptance, however we also found that environmental attitudes, risk perception, safety concerns, and economic variables play substantial roles. Considering the long-term commitment associated with nuclear energy and its role in Poland's energy transformation, our findings provide a foundation for improving energy policy in Poland. Our research underscores the importance of policies that resonate with the diverse values, beliefs, and preferences of the population. While the risk-risk trade-off and technology-focused strategies are effective to a degree, we advocate for a more comprehensive approach. The framing strategy, which tailors messages to distinct societal values, shows particular promise.

Jasmin-Clara Bürger, Serin Lee, Aubrey Penn et al.

Full utilization of the high storage capacity of conversion electrode materials as tin oxide (SnO2) in lithium‐ion batteries is hindered by the high volumetric expansion due to the high lithium storability which can lead to major cell damage and consequent safety issues. To overcome this issue, two promising approaches, nanostructures and buffer layers, are combined and evaluated. SnO2 nanowires (NWs) are coated with an aluminum oxide (Al2O3) buffer layer to investigate the combination SnO2–Al2O3. Strong differences in the crystallinity after cycling between the SnO2/Al2O3 core/shell NW‐based heterostructure and uncoated SnO2 NWs based on detailed structural analysis are shown via transmission electron microscopy (TEM) and determination of the elemental distribution of tin, oxygen, lithium, and aluminum via energy‐dispersive X‐Ray spectroscopy and energy‐filtered TEM in the as‐prepared and postmortem nanostructures. The core/shell NWs exhibit two different states after charge/discharge cycling, amorphous or crystalline, depending on the NW diameter; for the uncoated SnO2 NWs, only an amorphous postmortem structure is found. Additionally, differences in the elemental distribution for the amorphous and crystalline postmortem SnO2/Al2O3 core/shell NWs, especially for tin, are measured. Consequently, the structures and effects of the Al2O3 coating on the lithiation behavior of SnO2 NW‐based heterostructures are discussed.

Bo Wang, Deyou Yang, Guowei Cai et al.

An ambient modal framework for inertia estimation using synchrophasor data is proposed in this letter. Specifically, an analytical formulation is developed for the estimation of inertia based on the frequency and damping ratio modes extracted from ambient data. An advantage of the proposed framework is that it can rely on synchronized ambient data under non-disturbed conditions for online estimation and tracking of inertia. Ultimately, numerical simulation studies and physical experiments demonstrate the feasibility of the proposed approach.

Cunzhi Zhao, Xingpeng Li

The total electricity consumption from offshore oil/gas platforms is around 16 TWh worldwide in 2019. The majority offshore platforms are powered by the diesel generators while the rest mainly uses gas turbines, which emits large amounts of CO2 per year. The fast development of offshore wind turbines (WT) can potentially replace traditional fossil fuel based resources to power offshore loads. Thus, a novel offshore hybrid renewable energy sources (OHRES) system is proposed to enable a zero CO2 emission offshore platform mitigating climate change. Battery energy storage system (BESS) and hydrogen energy storage system (HESS) are considered to mitigate the fluctuation of wind power in the proposed OHRES system. Resilience models are designed to enhance the resilience of the proposed OHRES system with extra energy stored in BESS and/or HESS. Case studies demonstrate the feasibility of the proposed OHRES system to power offshore platforms. The economic analysis reports the planning cost for the proposed OHRES system under different resilience levels, which may benefit the decision to balance the carbon emission and investment cost.

Keifa Vamba Konneh, Hasan Masrur, Mohammad Lutfi Othman et al.

The concept of introducing hybrid off-grid systems has made electricity accessible to areas that are far or have no access to grid network. This paper evaluates the techno-economic and environmental characteristics of a hybrid renewable energy system considering three different scheduling approaches, four different solar tracking systems, two different PV modules and eight scheduling scenarios to supply sustainable electricity to a rural community in Sierra Leone. Each scenario consists of a solar tracking system, a specific type of PV module and a scheduling approach. The aim is to find the most efficient and cost-effective scenario that meets the electrical demands of the village. Results revealed that the &#x2018;Two axis tracking system&#x2019; generated the highest PV power, 28.8&#x0025; additional power compared to the &#x2018;No tracking system&#x2019; confirming the superiority of using a tracking system though it comes with initial cost repercussions. Also, systems that employed the use of Canadiasolar Dymond CS6K-285M-FG PV module tend to be more efficient and cost-effective than those that employed Sharp ND-250QCS PV module even with the same solar tracking technology and scheduling approach. From the best scheduling approach (third scheduling), Scenario 7 (SC&#x0023;7) gives the lowest net present cost (NPC) of <inline-formula> <tex-math notation="LaTeX">$ \$ $ </tex-math></inline-formula>1.53M with <inline-formula> <tex-math notation="LaTeX">$ \$ $ </tex-math></inline-formula>0.173/kWh cost of energy (COE) and CO₂ emission of 8.54 kg/yr making it the optimum scenario. A daily operation of the optimum scenario on both a sunny and rainy day confirms that the system is capable of supplying the required electricity for both rainy and dry seasons. Sensitivity analyses explain the high reliance of the system cost on the erratic inflation rate, discount rate and PV derating factor. Maintaining a healthy and sustainable environment depends on the minimum load ratio of both the biogas and diesel generators.

Takahiro Sudoh, Tim Linden, Dan Hooper

The HAWC Collaboration has observed gamma rays at energies above 56 TeV from a collection of nine sources. It has been suggested that this emission could be hadronic in nature, requiring that these systems accelerate cosmic-ray protons or nuclei up to PeV-scale energies. In this paper, we instead show that the spectra of these objects favor a leptonic (inverse Compton) origin for their emission. More specifically, the gamma-ray emission from these objects can be straightforwardly accommodated within a model in which $\sim \mathcal{O}(10\%)$ of the host pulsar's spindown power is transferred into the acceleration of electrons and positrons with a power-law spectrum that extends to several hundred TeV or higher. The spectral break that is observed among these sources is naturally explained within the context of this simple model, and occurs at the energy where the timescale for energy losses matches the age of the pulsar. In contrast, this spectral feature cannot be straightforwardly accommodated in hadronic scenarios. Furthermore, hadronic models predict that these sources should produce more emission at GeV-scale energies than is observed. In light of these considerations, we conclude that HAWC's highest energy sources should be interpreted as TeV halos or pulsar wind nebulae, which produce their emission through inverse Compton scattering, and are powered by the rotational kinetic energy of their host pulsar.