Hasil untuk "Energy industries. Energy policy. Fuel trade"

Md. Sayed Hossain

The performance of the Bangladesh Atomic Energy Commission (BAEC) TRIGA Research Reactor (BTRR) was significantly improved by addressing signal integrity issues related to the NLW-1000 logarithmic power channel. The PA-1000 signal, which suffered from strength loss due to the unavoidable transmission line distance, was restored by installing a line driver between the PA-1000 and NLW-1000. Therefore, reactor power and period are visualized in the console in logarithmic scale from the well-acquisition of both pulse count and current signals. By addressing another wiring anomaly, the in activeness of the optocouplers in the FC-ISO-D and FC-ISO-C was resolved, a prestart checklist was performed, and it was found that the apparent “count rate low” failure arose from a mis-specified HMI message condition while the core logic correctly passed the test so further corrective action is needed for the HMI message. Presently, the BTRR functions up to 3MWth and the power is displayed in the CSC monitor. According to the user demand, the signal integrity is sufficiently enhanced and there is no error within the DACS & CSC. Intermediate circuitry between the PA-1000 and logarithmic module can be omitted in the upcoming advanced logarithmic power monitoring channel to get better performance. The present study underscores the efficacy of signal enhancement methodologies in elevating reactor functionality and delineates a trajectory for sustained progress in nuclear research infrastructure.

Praveen Kumar Singh, Amit Saraswat, Yogesh Gupta

The increasing concerns about the environmental impact of fossil fuels have emphasized the importance of clean solar energy, which offers a pollution-free alternative for meeting growing energy needs. However, the accurate prediction of solar photovoltaic (SPV) based power generation is a very challenging task because of its inherent variability and uncertainty. To address this challenging problem, this paper applies several machine-learning, deep-learning, and their hybrid models such as: One-Dimensional Convolutional Neural Network (1D CNN), Bi-Directional Long Short-Term Memory (Bi-LSTM), Stacked LSTM, Artificial Neural Network (ANN), Linear Regression (LR), Support Vector Regression (SVR), XGBoost, and a hybrid CNN-LSTM model. These models are examined and compared on four different data sequences of DKASC Alice Springs dataset. The prediction performances of all these models are evaluated based on various error metrics: MAE (mean absolute error), explained variance, RMSE (root mean square error), R², and sMAPE (symmetric mean absolute percentage error). The simulation results demonstrates that Stacked LSTM model outperforms all other benchmark forecasting models and able to obtains average values of performance metrics i.e. MAE of 1.1157, RMSE of 2.3408, an Explained Variance of 0.8998, R² of 0.9004, and sMAPE of 1.1795 as evaluated across all four different data sequences. Moreover, a comprehensive statistical analysis, using Diebold Mariano Test and boxplots, confirms the further superiority of Stacked-LSTM model to efficiently address inherent uncertainty of solar power generation.

Shoyeb Ahmed, Abdullah Al-Faruk, Ahmad Sharifian

Energy crisis due to fast globalization and the negative effects of global warming compels a greater need for nonconventional energy sources. Solar and wind power are the primary sources of renewable energy used to meet the power demand. Savonius rotor, a kind of vertical-axis wind turbine, whose operation is dependent upon drag force, has many benefits, including low operating speeds, good self-starting ability, ease of installation, design simplicity, and wind direction independence. However, the low efficiency of the turbine caused by the negative torque it produces on the returning blade limits the applicability of the turbine. The present work experimentally investigated the possibility of performance improvement of the turbine by incorporating inner blades. A 3-bladed configuration of the turbine containing 2 inner blades and an outer semi-circular blade was designed and constructed for performance assessment using an open circuit wind tunnel. Three turbine configurations with 160º inner blade angle and 2 cm spacing between the blades were tested for optimal performance. The performance was evaluated for different wind velocities by fixing the test setup at the wind tunnel outlet. The rotational speed and torque were measured using a rope break dynamometer and tachometer, respectively. The result indicated that using 1 inner arc blade improved the maximum power coefficient and torque coefficient of the rotor by 33.17% and 8.89%, respectively, compared to the conventional configuration. However, using 2 inner blades reduced the maximum power coefficient and torque coefficient by 37.43% and 46.67%, respectively. The maximum value of the power coefficient was found at tip speed ratios (TSRs) between 0.25 and 0.45, whereas the torque coefficient declined with the increase of TSR for all 3 configurations. Moreover, the maximum power coefficient and torque were observed at lower wind speeds.

Stephanie M. Juice, Melannie D. Hartman, Adam C. vonHaden et al.

ABSTRACT Plant strategies to acquire nutrients from limited environments help shape ecosystem carbon (C) and nitrogen (N) cycling and response to environmental change. The effects of plant strategies on ecosystem dynamics are largely uncharacterized in bioenergy agroecosystems, where the impacts could determine bioenergy's ability to meet its sustainability goals of storing C and reducing N loss. We used FUN‐BioCROP (Fixation and Uptake of Nitrogen‐Bioenergy Carbon, Rhizosphere, Organisms and Protection), a plant–microbe interaction model of coupled plant nutrient uptake and soil organic matter decomposition, to simulate the effects of nutrient acquisition strategies on soil microbial activity and ecosystem nutrient cycling in bioenergy feedstocks miscanthus (Miscanthus × giganteus) and sorghum (Sorghum bicolor (L.) Moench). We examined the model's ability to reproduce the relative effects of belowground nutrient uptake on microbial activity using a reanalysis of empirical data showing that miscanthus root exudation provoked a larger soil microbial response than sorghum. From baseline model simulations, we found that the ability of miscanthus to retranslocate N resulted in higher N uptake at a lower C cost than the sorghum/soybean rotation and that soil C and N pools increased under perennial (miscanthus) and decreased under annual (sorghum/soybean) cultivation. The model also predicted that greater root exudation increased soil C accumulation, highlighting the role of roots in forming stable soil C. Overall, the baseline model was unable to reproduce field observations of miscanthus root exudation stimulating microbial activity more than sorghum. To improve the model, we updated the soil microbial parameters in miscanthus to have faster decomposition, a higher C/N ratio, and greater carbon use efficiency. These changes improved the simulated soil microbial response to miscanthus root exudation, supporting the hypothesis that miscanthus soils foster a microbial community that is more responsive to root exudation than that of sorghum.

Matthew D. Fuchs

Policies are designed to distinguish between correct and incorrect actions; they are types. But badly typed actions may cause not compile errors, but financial and reputational harm We demonstrate how even the most complex ABAC policies can be expressed as types in dependently typed languages such as Agda and Lean, providing a single framework to express, analyze, and implement policies. We then go head-to-head with Rego, the popular and powerful open-source ABAC policy language. We show the superior safety that comes with a powerful type system and built-in proof assistant. In passing, we discuss various access control models, sketch how to integrate in a future when attributes are distributed and signed (as discussed at the W3C), and show how policies can be communicated using just the syntax of the language. Our examples are in Agda.

Nan Wu, Zetian Yan

We introduce a fourth-order Willmore-type problem for closed four-dimensional submanifolds immersed in $\mathbb{R}^n$ and establish a connected sum energy reduction for the general fourth-order Willmore energy, analogous to the seminal result of Bauer and Kuwert \cite{Bauer-Kuwert03}.

Keerthana Rajan Lathika

The High Energy Cosmic-Radiation Detection (HERD) facility has been proposed as a leading experiment on China's Space Station (CSS). Scheduled for installation around 2027, HERD is expected to operate for at least a decade. The main scientific objectives include indirect detection of dark matter with unprecedented sensitivity, studying the cosmic-ray spectrum and composition up to the knee, and observing all-sky gamma rays with energies above 100 MeV. HERD is designed as a large-acceptance telescope with a unique design aimed at maximizing its efficiency. It comprises a central 3D imaging calorimeter (CALO) made of LYSO crystals, encircled by four complementary subdetectors on its top and four lateral faces: the scintillating fiber tracking detector (FIT), the plastic scintillator detector (PSD), the silicon charge detector (SCD), and a transition radiation detector (TRD) on one lateral side. To fully harness HERD gamma-ray detection capabilities down to 100 MeV, an advanced ultra-low-energy gamma-ray (ULEG) trigger system has been developed. We present an extensive overview of the design, performance, and optimization of the gamma-ray trigger system supported by software simulations and preliminary results from the successful implementation of the HERD prototype at CERN's PS and SPS beam test campaigns in Fall 2023.

Clara Tanghe, Senne Van Wellen, Kobe Vergaerde et al.

We propose and experimentally demonstrate a method to directly measure energy dissipation for a linearly driven superfluid confined in a harmonic trap. The method relies on a perturbed version of the harmonic-potential theorem, according to which a potential perturbation - effectively acting as a stirrer - converts center-of-mass motional energy into internal energy. Energy conservation then enables a direct, quantitative determination of the dissipated energy from measurements of the macroscopic center-of-mass observables. Applying this method to a perturbed, driven Bose-Einstein condensate, we observe dissipation curves characteristic of superfluid flow, including a critical velocity that depends on the stirrer strength, consistent with previous studies. Our results are supported by mean-field simulations, which corroborate both the theoretical framework and the experimental findings.

Mohammed khan, Rai Sujit Nath Sahai

The research aimed to create a composite material for the floaters used in floating solar power plants. High-density polyethylene (HDPE) was combined with 1, 1.5, 2, and 2.5% of carbon black (CB) and 1,2,and 3% of zinc oxide (ZnO). Mechanical tests were carried out after accelerated weathering for 311, 634, 954, 1403, and 2878 hours in dry (out of water) and wet (sample floating in water) conditions. HDPE loses tensile strength, impact resistance, and elongation at break after 634 hours and 954 hours of weathering. The Shore D hardness did not show any significant change. The best performance was observed in batches D4 and W4, which contain 2% CB and 1% ZnO, in dry and wet conditions. The SEM (scanning electron microscope) shows the external morphology of D1 and W1 (pure HDPE) and D4 and W4 (composite) and revealed that pure HDPE was more degraded compared to the composite. Thermal properties and stability were analyzed using TGA (Thermogravimetric analysis). A further increase in CB and ZnO will reduce the strength of the composite.It was found that HDPE with 2% CB and 1% ZnO was a good composite material for developing the floaters used in floating solar power plants.

Robert Herding, Emma Ross, Wayne R. Jones et al.

This work examines the daily bidding problem of a grid-connected microgrid with locally deployed resources for electricity generation, storage and its own electricity demand. Trading electricity in energy markets may offer economic incentives but exposes the microgrid to financial risk caused by market commitments. Hence, a multi-objective, two-stage stochastic mixed integer linear programming (MILP) model is formulated, extending prior work of a risk-neutral microgrid bidding approach. The multi-objective model minimises both expected total cost of day-ahead microgrid operations and financial risk from bidding measured by conditional value-at-risk (CVaR). Bidding curves derived as first stage decisions are always feasible under present market rules – including a limitation on the number of break points per submitted curve – while being near optimal for the microgrid’s day-ahead recourse schedule. The proposed optimisation model is embedded in a variant of the ɛ-constrained method to generate bidding curve candidates with different trade-offs between the two conflicting objectives. Moreover, scenario reduction is used to compromise accuracy of the uncertainty set for better computational performance. Particularly, the marginal relative probability distance between initial and reduced scenario set is suggested to make a decision on the extent of scenario reduction. The proposed solution procedure is tested in a computational study to demonstrate its applicability to generate optimal microgrid bidding curve candidates with different emphasis between total cost and CVaR in reasonable computational time.

Yanhong Ma, Feng Li, Hong Zhang et al.

Accurate photovoltaic (PV) power forecasting ensures the stability and reliability of power systems. To address the complex characteristics of nonlinearity, volatility, and periodicity, a novel two-stage PV forecasting method based on an optimized transformer architecture is proposed. In the first stage, an inverted transformer backbone was utilized to consider the multivariate correlation of the PV power series and capture its non-linearity and volatility. ProbSparse attention was introduced to reduce high-memory occupation and solve computational overload issues. In the second stage, a weighted series decomposition module was proposed to extract the periodicity of the PV power series, and the final forecasting results were obtained through additive reconstruction. Experiments on two public datasets showed that the proposed forecasting method has high accuracy, robustness, and computational efficiency. Its RMSE improved by 31.23% compared with that of a traditional transformer, and its MSE improved by 12.57% compared with that of a baseline model.

Zoltán Bajnok, János Balog, István Vona

Perturbation theory in asymptotically free quantum field theories is asymptotic. The factorially growing perturbative coefficients carry information about non-perturbative corrections, which can be related to renormalons and instantons. Using the Wiener-Hopf technique we determine the full analytic solution for the free energy density in the two dimensional $O(N)$ sigma models. For $N>3$ there are no instantons, and we found that the perturbative series carries all the information about the non-perturbative corrections. However, in the $O(3)$ case, we identify several non-perturbative sectors that are not related to the asymptotics of the perturbative series. The number of sectors depends on the observables: for the ground-state energy density we identify three sectors, which we attribute to instantons. For the free energy density in the running perturbative coupling we found infinitely many sectors.

Sneha Pradhan, Raja Solanki, P. K. Sahoo

The article investigates cosmological applications of $f(Q)$ theories in a non-coincident formalism. We explore a new $f(Q)$ theory dynamics utilizing a non-vanishing affine connection involving a non-constant function $γ(t)=-a^{-1}\dot{H}$, resulting in Friedmann equations that are entirely distinct from those of $f(T)$ theory. In addition, we propose a new parameterization of the Hubble function that can consistently depicts the present deceleration parameter value, transition redshift, and the late time de-Sitter limit. We evaluate the predictions of the assumed Hubble function by imposing constraints on the free parameters utilizing Bayesian statistical analysis to estimate the posterior probability by employing the CC, Pantheon+SH0ES, and the BAO samples. Moreover, we conduct the AIC and BIC statistical evaluations to determine the reliability of MCMC analysis. Further, we consider some well-known corrections to the STEGR case such as an exponentital $f(Q)$ correction, logarithmic $f(Q)$ correction, and a power-law $f(Q)$ correction and then we find the constraints on the parameters of these models via energy conditions. Finally, to test the physical plausibility of the assumed $f(Q)$ models we conduct the thermodynamical stability analysis via the sound speed parameter.

S. Davood Sadatian, S. Mohamad Reza Hosseini

We investigate wormhole solutions using the modified gravity model $f(Q,T)$ with viscosity and aim to find a solution for the existence of wormholes mathematically without violating the energy conditions. We show that there is no need to define a wormhole from exotic matter and analyze the equations with numerical analysis to establish weak energy conditions. In the numerical analysis, we found that the appropriate values of the parameters can maintain the weak energy conditions without the need for exotic matter. Adjusting the parameters of the model can increase or decrease the rate of positive energy density or radial and tangential pressures. According to the numerical analysis conducted in this paper, the weak energy conditions are established in the whole space if $α< 0$, $12.56 < β< 25.12$ or $α> 0$, $β> 25.12$. The analysis also showed that the supporting matter of the wormhole is near normal matter, indicating that the generalized $f(Q,T)$ model with viscosity has an acceptable parameter space to describe a wormhole without the need for exotic matter.

Sanjay Johnson, Piyush Sabharwall, Youssef Ballout

In 2021, the United States declared its Nationally Determined Contribution (NDC) in preparation for the COP26 climate summit, setting goals to achieve zero emission electricity by 2035, and reducing net emissions by 50–52% compared to 2005 levels. The current U.S. energy policies were found to not be adequate to meet these goals, thus it is necessary to draft a pathway to achieving these goals through policy changes. This study focused on foreign energy policies to analyze the most effective policies in a host of sectors. By identifying the most ambitious and effective policies from around the world in each sector, this study was able to suggest a policy pathway that can potentially achieve both of the goals set in the NDC. In guiding the development of the proposed policy pathway, this study analyzed policies from Australia, Canada, California, China, Denmark, France, Germany, Japan, Russia, South Korea, Sweden, the United Kingdom, and the United States. This study found that the most drastic CO2 reductions came from low-carbon electricity policy, but contributions were also made from carbon capture, reforestation, hydrogen, energy efficiency, and climate smart agriculture.

Dunja Grujić, Miloš Kuzman, Željko Đurišić

Prošlo je nekoliko godina od uvođenja instituta kupca-proizvođača u pravni sistem Republike Srbije. Razvoj regulatornog okvira i tehnologija fotonaponskih panela, kao i pad investicionih troškova i porast cene električne energije, rezultovali su velikim interesovanjem za izgradnju fotonaponskih sistema na komercijalnim i rezidencijalnim objektima u Republici Srbiji. Svedoci smo sve većeg broja zahteva za priključenje kupaca-proizvođača na distributivni sistem električne energije i generalno sve većeg ukupno instalisanog kapaciteta za proizvodnju električne energije iz obnovljivih izvora od kog određen deo čine kupci-proizvođači. Postojećom zakonskom regulativom utvrđen je način obračuna električne energije kupaca-proizvođača. Regulativom je jasno uređen i način balansiranja električne energije kupaca-proizvođača, kao i odnos kupca-proizvođača sa snabdevačem odnosno operatorom distributivnog sistema električne energije. U stručnim krugovima česte su debate o tome da li je moguće izvršiti unapređenje postojećeg modela obračuna električne energije kupaca-proizvođača i puta na koji je ovo unapređenje moguće izvršiti. U ovom radu će biti prikazan novi model obračuna električne energije kupaca-proizvođača. Biće analizirana i postojeća zakonska regulativa kako bi se omogućilo unapređenje regulatornog okvira u svrhu implementacije predloženih rešenja. U okviru rada biće analiziran konkretan primer potrošnje električne energije prosečnog domaćinstva. Izvršiće se i analiza mogućnosti posmatranog domaćinstva za sticanje statusa kupca-proizvođača. Biće prikazan i uporedni prikaz obračuna električne energije kupcima-proizvođačima po postojećem zakonskom modelu obračuna električne energije kao i po modelu koji je prikazan u okviru ovog rada. Na kraju će biti analiziran uticaj predloženog alternativnog modela na kupca-proizvođača, snabdevača, balansno odgovorne strane i operatora distributivnog sistema kao i na njihove međusobne odnose.

Jinyu Liu, Hongye Guo, Qinghu Tang et al.

With the growing penetration of renewable energy resource, electricity market prices have exhibited greater volatility. Therefore, it is important for Energy Storage Systems(ESSs) to leverage the multidimensional nature of energy market bids to maximize profitability. However, current learning methods cannot fully utilize the high-dimensional price-quantity bids in the energy markets. To address this challenge, we modify the common reinforcement learning(RL) process by proposing a new bid representation method called Neural Network Embedded Bids (NNEBs). NNEBs refer to market bids that are represented by monotonic neural networks with discrete outputs. To achieve effective learning of NNEBs, we first learn a neural network as a strategic mapping from the market price to ESS power output with RL. Then, we re-train the network with two training modifications to make the network output monotonic and discrete. Finally, the neural network is equivalently converted into a high-dimensional bid for bidding. We conducted experiments over real-world market datasets. Our studies show that the proposed method achieves 18% higher profit than the baseline and up to 78% profit of the optimal market bidder.

Shiqi Ou, Xu Hao, Zhenhong Lin et al.

Abstract The fast-growing light-duty plug-in electric vehicle (PEV) market in China has important implications for both the global vehicle market and energy policies. From the perspective of demand pull-supply push, this study examines China's PEV market by reviewing sales, product performance, and government policies from the last decade; and by comparing it with the market in the United States, the study attempts to generate market dynamics insights to the Chinese PEV market. On the demand side, inexpensive, small-sized PEVs have contributed the most to the recent rapid increase in sales, but this trend is diminishing. The majority of Chinese PEV sales in recent years occurred in economically prosperous regions or cities that are able to supply lucrative monetary incentives and otherwise PEV purchasing and driving privileges to consumers. On the supply side, expansion of the PEV market, incentivized by government policies, enable young, privately-owned automakers to compete with the established automakers. Overall, the PEV market concentration ratio is still small: hundreds of PEV models and new PEV automakers are competing in China; but when it comes to some major local markets, PEV sales are commonly dominated by the local automakers. In the U.S. market, except for Tesla, the vast majority of PEV models are manufactured by established manufacturers of conventional vehicles. Demand-pull policies (e.g. direct monetary purchase incentives) are being transitioned to supply-push policies (e.g. special fuel economy credits for PEVs and PEV sales mandate) which will be major government measures to further stimulate PEV sales with less fiscal burden.

D. Ismukurnianto

International concern is now focused on reducing green house gas (GHG) emissions which drive climate change. The use of fossil fuels, either flaring natural gas and burning fossil fuels, are predicted contributing GHG emissions. As a consequence, International cooperation through United Nation Framework Convention on Climate Change (UNFCCC) has pointed to increase policy interest in developing CO2 and GHG emission trading system. The system would allow the countries who have opportunities to reduce CO2 and GHG emission (generally developing countries) and sell or trade GHG emission reduction to the countries (generally developed countries). The second part of this paper will be emphasized on oil and gas reserves, production, refineries,and utilization. Indonesia oil resource as of January 1st, 2006 amounts to about 56.60 BBO, while gas resources as of January 1st, 2006 is about 334.5 TSCF. Indonesia has nine refineries owned by PT Pertamina (Persero) and six refineries owned by private. Indonesia has also voluntary participated in reducing GHG emissions by formulating energy policy, doing research on carbon capture and storage (CCS), and developing innovative projects. This paper will highlight the energy policy, research program and innovative projects for reducing GHG emission from oil and gas activities in Indonesia

Łukasz Chmielewski

Abstract The aim of the article is to present the supply and demand situation on the market of rapeseed oil and maize used for fuel purposes in Poland, as well as analyze the relationship between their prices and production, as well as the consumption of gasoline and diesel fuel. The analysis covered the 2015–2020 period and was based on data from statistics Poland, the National Support Center for Agriculture, and the Polish Oil Industry and Trade Organization. Statistical analysis showed that between 2015 and 2020 the dynamics of the usage of raw materials to produce biofuels exceeded the growth rate of their production and harvest. The assessment of the relationship between production and consumption of fuels in Poland showed that the demand from the fuel sector had a dominant influence on the prices of rapeseed oil and maize during the period under consideration, and fuel production had a less significant share in shaping wholesale prices of rapeseed oil and purchase prices of maize. Biofuels are an important and topical issue both in the context of the new energy policy of the European Union (EU) and Poland until 2040 and Russia’s invasion of Ukraine, with one of the consequences being the energy crisis and the announcement of the EU becoming independent from Russian energy. In such a situation, biofuels and raw materials for their production may turn out to be an important element of improving energy security.