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

Yansheng Huang, Atthapol Ngaopitakkul, Suntiti Yoomak

Abstract As the world’s energy structure is gradually changing, the automotive industry is shifting its focus to new energy vehicles in an effort to improve the performance and service life of the charging pile. To solve the problem that traditional models tend to fall into locally optimal solutions (i.e., the model optimization process stays in the non-optimal regional minimum) in complex parameter space, the study innovatively proposes a hybrid prediction model that combines the whale optimization algorithm with the gated recurrent unit-long short-term memory neural network. By introducing the whale optimization mechanism to globally optimize the key parameters of the neural network, the method improved the model’s ability to model complex time series data. Moreover, the method also effectively avoided the problem of traditional methods falling into local optimal solutions, thus improving the training efficiency and generalization ability while maintaining the model accuracy. It took only 21 s to complete the training of 600 samples, and the prediction accuracy was as high as 91%. In the four classes of fault classification experiments, the proposed model performs well in classification accuracy in all classes, showing strong multi-class fault recognition capability. Therefore, the fault prediction model developed in this study can accurately and effectively identify and predict charging pile faults, and shows high performance. This not only provides a strong theoretical foundation for the application of deep learning in charging pile fault prediction, but is also of great significance in terms of reducing operation and maintenance costs, supporting energy structure transformation, and promoting green development.

Jin Guo, Tetsuji Tanaka, Xiufang Wang

The rapid growth of US ethanol production, driven by the Energy Policy Act of 2005 and the Energy Independence and Security Act of 2007, has raised questions about intensifying price linkages between energy and food markets. This is based on the premise that higher crude oil prices incentivize ethanol producers to increase production, thereby boosting corn demand. This study explores the impact of biofuel policies by testing the hypothesis that increased U.S. ethanol production has strengthened these linkages. Previous literature overlooked the fact that both fuel and food goods tend to move together with the commodity price index, which can often change in response to interest rates, monetary supply, or the U.S. dollar index. To overcome this deficiency, we filter out the 'noises' from the commodity price index by controlling for the index with the partial wavelet transform and present more accurate relationships between crude oil and corn prices. Our primary finding reveals significant mid- and long-term correlations between crude oil and corn prices from 2007. This suggests that U.S. biofuel policies could strengthen the connectivity between crude oil and corn prices.

Onyinyechi Nnamchi, Cyprian Tom, Godwin Akpan et al.

As the world transitions towards green energy sources solar drying has become a vital technology for sustainable agricultural production, offering a cleaner, more efficient alternative to traditional drying methods. Solar drying has been demonstrated to be a sustainable and eco-friendly drying process for drying and preserving agricultural products, offering advantages over traditional methods that include faster drying rates, improved product quality, and reduced energy costs. This review examines the mechanisms and methods applicable to solar drying, including indirect and direct solar drying, hybrid systems combining solar drying with other heating sources, and thermal storage materials to address challenges such as intermittent solar radiation. The designs of solar drying systems include various solar collector configurations, drying chamber geometries, and air conveyance mechanisms crucial for efficient drying. This review therefore explores different design approaches and their effects on drying performance, highlighting the importance of understanding the complex interactions between system components. Additionally, the approach for Energy and exergy analysis of solar drying systems was explored, providing insights into energy utilization and efficiency. Finally, this review elucidates the complex transport phenomena governing solar drying, including moisture diffusion, heat and mass transfer, and airflow patterns. It identifies knowledge gaps in existing models and future research directions in transport modelling phenomena to advance sustainable, efficient, and scalable solar drying techniques.

K. Anderson, J. Broderick, Isak Stoddard

ABSTRACT The Paris Agreement establishes an international covenant to reduce emissions in line with holding the increase in temperature to ‘well below 2°C … and to pursue … 1.5°C.’ Global modelling studies have repeatedly concluded that such commitments can be delivered through technocratic adjustments to contemporary society, principally price mechanisms driving technical change. However, as emissions have continued to rise, so these models have come to increasingly rely on the extensive deployment of highly speculative negative emissions technologies (NETs). Moreover, in determining the mitigation challenges for industrialized nations, scant regard is paid to the language and spirit of equity enshrined in the Paris Agreement. If, instead, the mitigation agenda of ‘developed country Parties’ is determined without reliance on planetary scale NETs and with genuine regard for equity and ‘common but differentiated responsibilities and respective capabilities’, the necessary rates of mitigation increase markedly. This is evident even when considering the UK and Sweden, two nations at the forefront of developing ‘progressive’ climate change legislation and with clear emissions pathways and/or quantitative carbon budgets. In both cases, the carbon budgets underpinning mitigation policy are halved, the immediate mitigation rate is increased to over 10% per annum, and the time to deliver a fully decarbonized energy system is brought forward to 2035-40. Such a challenging mitigation agenda implies profound changes to many facets of industrialized economies. This conclusion is not drawn from political ideology, but rather is a direct consequence of the international community’s obligations under the Paris Agreement and the small and rapidly dwindling global carbon budget. Key Policy Insights Without a belief in the successful deployment of planetary scale negative emissions technologies, double-digit annual mitigation rates are required of developed countries, from 2020, if they are to align their policies with the Paris Agreement’s temperature commitments and principles of equity. Paris-compliant carbon budgets for developed countries imply full decarbonization of energy by 2035-40, necessitating a scale of change in physical infrastructure reminiscent of the post-Second World War Marshall Plan. This brings issues of values, measures of prosperity and socio-economic inequality to the fore. The stringency of Paris-compliant pathways severely limits the opportunity for inter-sectoral emissions trading. Consequently aviation, as with all sectors, will need to identify policies to reduce emissions to zero, directly or through the use of zero carbon fuels. The UK and Swedish governments’ emissions pathways imply a carbon budget of at least a factor of two greater than their fair contribution to delivering on the Paris Agreement’s 1.5-2°C commitment.

Brigitte Astrid Medjo Nouadje, Pascalin Tiam Kapen, Victorin Chegnimonhan et al.

The current electricity challenges in Africa have spurred the interest of governments in incorporating renewable energy sources into the energy mix. The use of hybrid solar energy systems has become a practical choice for electrification. The novelty of the paper is threefold: (i) The Grid/Fuel Cell/PV/Electrolyzer hybrid system is modeled, simulated, and optimized in for some communities of the nineteen countries of the African and Malagasy Council for Higher Education (CAMES) for the very first time; (ii) The levelized costs of hydrogen and energy were evaluated and compared; (iii) PV, fuel cell, grid purchases, and grid sales power productions were determined and compared. The study findings showed a levelized cost of energy varying between US$ 0.238/kWh (in Madagascar) and US$ 0.344/kWh (in Gabon). Subsequently, among the West, Central, and East African countries of CAMES, Mali, Chad, and Burundi were the countries with the smallest LCOE respectively. Also, the levelized cost of hydrogen ranged between US$ 1.84/kg (in Madagascar) and US$ 2.17/kg (in Gabon and Equatorial Guinea). The computation of the net present cost indicated a variation between 183,536 US$ (in Madagascar) and 216,115 US$ (in Gabon). The PV, fuel cell, grid purchases, and grid sales power productions were between 34,044 kWh/year (in Gabon) and 53,176 kWh/year (in Mali) for PV productions; between 43,526 kWh/year (in the Democratic Republic of Congo) and 43,784 kWh/year (in Chad) for fuel cell productions; between 29,976 kWh/year (in Senegal) and 30,700 kWh/year (in the Congo Republic) for grid purchases power productions; and between 11,604 kWh/year (in Gabon) and 29,608 kWh/year (in Mali) for grid sales productions respectively. It was concluded that the PV power production was the highest power generated by the hybrid system when compared with fuel cell, grid sales, and grid purchases power productions. Concerning the PV penetration, it varied between 54.2 % (in Gabon) and 84.7 % (in Mali). The present work is aimed at decision-makers so that they become aware of the need to urgently develop the renewable energy sector in the countries for a successful energy transition in Africa.

Dušan Prodanović, Damjan Ivetić, Predrag Vojt et al.

Kontinualno merenje protoka na brojnim turbinama hidroelektrana se standardno radi nekom od relativnih metoda (na primer Winter-Kennedy). Umesto da se meri složeno polje brzina u jednoj proticajnoj ravni i da se njenom integracijom dobije protok, meri se samo jedna karakteristična veličina a na fizičkom modelu se odrede parametri preslikavanja vrednosti te veličine u trenutni protok. Najčešće se koristi Winter-Kennedy metoda gde se merenjem razlike pritisaka dobija relativna (indeksna) vrednost protoka. Merna nesigurnost tako određenog protoka je znatno veća od nesigurnosti merenja ostalih relevantnih veličina za određivanje optimalnih radnih uslova turbine. Da bi se smanjila merna nesigurnost, potrebno je „apsolutnim merenjima“ celog polja brzina odrediti trenutni protok i preračunati, u realnim uslovima, korekcije indeksne metode. To se posebno odnosi na hidroelektrane čija dispozicija nije „idealna“ kao što je bila na fizičkom modelu, kao što je HE „Đerdap 2“ sa poznatim problemom „kosog dostrujavanja“. Sa ciljem bolje procene hidrauličke efikasnosti turbina i prikupljanja podataka o realnim uslovima rada turbina i ulazne rešetke, a zbog planiranih radova na revitalizaciji, projektovan je i primenjen inovativni sistem za apsolutno merenje protoka koji je prikazan u ovom radu. Na pokretni ram, pozicioniran na ulazu u turbinu uzvodno od grube rešetke, postavljeno je 15 elektromagnetnih (EM) senzora u jednoj horizontalnoj ravni, zajedno sa dva redudantna akustična Doppler senzora. Svaki od senzora meri sve tri komponente brzina. Ram se podiže duž cele visine proticajnog preseka snimajući celo polje brzina. Položaj rama se prati pomoću dva enkodera, dok se dva senzora pritiska koriste za merenje dubine vode. Merenja su sinhronizovana sa lokalnim SCADA sistemom odakle se preuzimaju podaci o radu turbine. Uvažavajući specifičnosti mernog sistema, novorazvijenih EM sondi i postojećih hidrauličkih uslova, razvijena je adekvatna procedura za procenu nesigurnosti izmerenog protoka. U ovom radu je prikazana merna metoda i dati su neki rezultati merenja na agregatima HE „Đerdap 2“.

C. Bataille, H. Waisman, Y. Briand et al.

Abstract This synthesis paper presents the objectives, approach and cross-cutting results of the Latin American Deep Decarbonization Pathways project (DDP-LAC). It synthesizes and compares detailed national and sectoral deep decarbonization pathways (DDPs) to 2050 compatible with the Paris Agreement objectives and domestic development priorities in Argentina, Colombia, Costa Rica, Ecuador, Mexico and Peru. The first five countries analysed in detail the energy system and agriculture, forestry and land use (AFOLU) at a high level, while Peru focussed on a detailed analysis of AFOLU given its predominance in its GHG emissions. While economy-wide results were produced, this paper focuses on the electricity, passenger transport, and AFOLU results because of their current emissions, potential to grow, and identification of successful strategies for decarbonization (e.g. switching to clean electricity and other net-zero emissions fuels across the economy; urban planning, mode shifting, and electrification in passenger transport; and intensive sustainable agriculture, assignment of land use rights and their enforcement and afforestation in AFOLU). It also highlights where significant emissions remain in 2050, notably in industry, AFOLU, freight, and oil and gas production, all areas for future research. It derives insights for the design of domestic policy packages and identifies priorities for international cooperation. This analysis provides critical information for Long-Term Strategies, Nationally Determined Contributions and Global Stocktaking in the context of the Paris Agreement.

D. McCollum, Charlie Wilson, M. Bevione et al.

Felix Schreyer, Gunnar Luderer, Renato Rodrigues et al.

Given their historic emissions and economic capability, we analyze a leadership role for representative industrialized regions (EU, US, Japan, and Australia) in the global climate mitigation effort. Using the global integrated assessment model REMIND, we systematically compare region-specific mitigation strategies and challenges of reaching domestic net-zero carbon emissions in 2050. Embarking from different emission profiles and trends, we find that all of the regions have technological options and mitigation strategies to reach carbon neutrality by 2050. Regional characteristics are mostly related to different land availability, population density and population trends: While Japan is resource limited with respect to onshore wind and solar power and has constrained options for carbon dioxide removal (CDR), their declining population significantly decreases future energy demand. In contrast, Australia and the US benefit from abundant renewable resources, but face challenges to curb industry and transport emissions given increasing populations and high per-capita energy use. In the EU, lack of social acceptance or EU-wide cooperation might endanger the ongoing transition to a renewable-based power system. CDR technologies are necessary for all regions, as residual emissions cannot be fully avoided by 2050. For Australia and the US, in particular, CDR could reduce the required transition pace, depth and costs. At the same time, this creates the risk of a carbon lock-in, if decarbonization ambition is scaled down in anticipation of CDR technologies that fail to deliver. Our results suggest that industrialized economies can benefit from cooperation based on common themes and complementary strengths. This may include trade of electricity-based fuels and materials as well as the exchange of regional experience on technology scale-up and policy implementation.

Bangzhu Zhu, B. Su, Yingzhu Li

Abstract India is the second largest developing country and fourth largest carbon emitter in the world. It has registered the rapid economic growth (7–9%) in the last decade. However, both its total carbon emissions and emission intensity (CO2 emissions per GDP) kept increasing during period 2007–2013. There are few studies using input-output (I-O) analysis for India’s energy/emissions in the literature. This paper tries to fill in the gap by using I-O framework to study India’s total emissions and intensity changes and its driving forces with the latest data available and newly proposed techniques. The results show that India’s carbon emission were mainly driven by private consumption (50–55%), followed by investment (25–26%) and exports (14–19%). During period 2007/08–2013/14, India’s total emissions increased by 56.6%, where total final demand change resulted in emissions increasing and the shift of demand from raw material industry to high-value added manufacturing industry helped to reduce the emissions. When measuring India’s relative emission efficiency, its aggregate embodied intensity (AEI) indicator in aggregate was mainly determined by private consumption (47–49%), followed by investment (23–24%) and exports (15–18%). From 2007/08 to 2013/14, the AEI values in aggregate and by final demand category all increased except the AEI of inventory change, mainly caused by production structure change. The emission efficiency improvements helped to reduce India’s total emissions and carbon intensity, but the contributions were small. The policy implications of our findings are also discussed.

M. Wei, C. McMillan, Stephane de la Rue du Can

Zongnan Zhang, Jun Du, Kudashev Sergey Fedorovich et al.

Promoting the efficient use of renewable energy and realizing the low-carbon operation of the integrated energy system has become an important direction for the reform of the integrated energy system. In this paper, we firstly construct a microgrid model containing electricity, heat and gas multi-energy synergy, consider the optimal operation mechanism of carbon trading with reward and punishment ladder, and improve the model of CHP units by adding carbon capture system and power-to-gas facility to reduce carbon emissions. Then, a cooperative operation model of multi-microgrid electric energy sharing is established, which is then decomposed into the subproblem of maximizing the benefits of microgrid alliances and the subproblem of distributing cooperative benefits, and the alternating direction multiplier method is selected for distributed solution, so as to effectively protect the privacy of each subject. In the cooperative benefit distribution subproblem, a method is proposed to quantify the contribution size of each participating entity by a nonlinear energy mapping function, and each microgrid negotiates with each other by the size of its electric energy contribution in the cooperation as the bargaining power to achieve a fair distribution of cooperative benefits. Finally, the simulation results verify the effectiveness of the proposed method. The results show that the benefits of the microgrid alliance are maximized by the proposed multi-microgrid power sharing method; moreover, the cooperative benefits of the microgrid alliance are equitably distributed based on the magnitude of the energy contribution of each microgrid; in terms of carbon emissions, the results demonstrate that the carbon capture joint power-to-gas system, as well as the energy sharing method among microgrids, can effectively reduce the carbon emissions during the microgrid operation.

Haijin Wang, Caomingzhe Si, Guolong Liu et al.

Abstract Non‐intrusive load monitoring (NILM) is essential for understanding consumer power consumption patterns and may have wide applications such as in carbon emission reduction and energy conservation. Determining NILM models requires massive load data containing different types of appliances. However, inadequate load data and the risk of power consumer privacy breaches may be encountered by local data owners when determining the NILM model. To address these problems, a novel NILM method based on federated learning (FL) called Fed‐NILM is proposed. In Fed‐NILM, instead of local load data, local model parameters are shared among multiple data owners. The global NILM model is obtained by averaging the parameters with the appropriate weights. Experiments based on two measured load datasets are performed to explore the generalization capability of Fed‐NILM. In addition, a comparison of Fed‐NILM with locally trained NILM models and the centrally trained NILM model is conducted. Experimental results show that the Fed‐NILM exhibits superior performance in terms of scalability and convergence. Fed‐NILM out performs locally trained NILM models operated by local data owners and approaches the centrally trained NILM model, which is trained on the entire load dataset without privacy protection. The proposed Fed‐NILM significantly improves the co‐modelling capabilities of local data owners while protecting the privacy of power consumers.

Ziwei Xu, Wenxuan Hou, Brian G. M. Main et al.

Abstract This study revisits the question of “whether firms are doing well by doing good?”. We examine shareholders-sponsored corporate socially responsible (CSR) proposals related to Environmental, Social, and Governance (ESG) that are voted to pass or fail by a small margin. The adoption of those “close call” proposals is regarded as equivalent to a random assignment of CSR policies and, therefore, provides a quasi-experimental setting to capture the causal influence of CSR on firm performance. We apply the regression discontinuity design (RDD) and find that CSR proposals’ passage leads to a significant positive abnormal return on the voting day. The results are robust with both parametric and nonparametric approaches of RDD and different polynomial orders. However, we fail to identify a significant change in financial performance in the long-term. One possible reason is that passing a CSR proposal could be symbolic, rather than substantial.

Babatunde Odetayo, Michael Walsh

Julia M. Puaschunder

: The future leadership on the Green New Deal (GND) will depend on teaching core concepts of the economics of the environment and evaluating the success of the transition implementation by monitoring and evaluation. The GND operates within the framework of the United Nations Environment Programme (UNEP) since 2008 to create jobs in green industries, thus boosting the world economy and curbing climate change at the same time. In 2019 over 600 organizations submitted a letter to the U.S. Congress declaring support for policies to reduce greenhouse gas emissions. This includes ending fossil fuel extraction and subsidies, transitioning to 100% clean renewable energy by 2035, expanding public transportation, and strict emission reductions rather than reliance on carbon emission trading. This paper describes the implementation of the GND but also underlying efforts to teach GND components for building a cadre of future environmental economists.

Kai Strunz, Xuanyuan Wang, Qinglai Guo et al.

Thomas Wolgast, Eric MSP Veith, Astrid Nieße

Abstract Future smart grids can and will be subject of systematic attacks that can result in monetary costs and reduced system stability. These attacks are not necessarily malicious, but can be economically motivated as well. Emerging flexibility markets are of interest here, because they can incite attacks if market design is flawed. The dimension and danger potential of such strategies is still unknown. Automatic analysis tools are required to systematically search for unknown strategies and their respective countermeasures. We propose deep reinforcement learning to learn attack strategies autonomously to identify underlying systemic vulnerabilities this way. As a proof-of-concept, we apply our approach to a reactive power market setting in a distribution grid. In the case study, the attacker learned to exploit the reactive power market by using controllable loads. That was done by systematically inducing constraint violations into the system and then providing countermeasures on the flexibility market to generate profit, thus finding a hitherto unknown attack strategy. As a weak-point, we identified the optimal power flow that was used for market clearing. Our general approach is applicable to detect unknown attack vectors, to analyze a specific power system regarding vulnerabilities, and to systematically evaluate potential countermeasures.

MENG Hao, TIAN Liang

[Introduction] In order to reduce the influence of the positioning accuracy of the electric actuator by the change of its internal parameters, and to reduce the maintenance frequency of the electric actuator. [Method] After the model of the electric actuator was improved, the influence factors of the steady-state error were obtained through simulation experiments. The compensation loop was further added to reduce the steady-state error. The parameters of the compensation loop were obtained by utilizing the BP neural network algorithm. [Result] The simulation result shows that the steady-state error of the electric actuator is related to the width of the dead zone of the controller, the backlash width of the reducer and the sign of the input signal. After adding the compensation circuit, the absolute value of the steady-state error can be guaranteed to fluctuate within 0.1% when the controller dead zone width and reducer backlash width change. [Conclusion] It solves the contradiction between the positioning accuracy and stability of electric actuator, and the problem of positioning accuracy being reduced due to the wear of reducer.