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

Payam Nejat, Fatemeh Jomehzadeh, M. Taheri et al.

K. Gillingham, K. Palmer

Yuankai Wu, Huachun Tan, Jiankun Peng et al.

Abstract Hybrid electric vehicles offer an immediate solution for emissions reduction and fuel displacement under the current technique level. Energy management strategies are critical for improving fuel economy of hybrid electric vehicles. In this paper we propose a energy management strategy for a series-parallel plug-in hybrid electric bus based on deep deterministic policy gradients. Specifically, deep deterministic policy gradients is an actor-critic, model-free reinforcement learning algorithm that can assign the optimal energy split of the bus over continuous spaces. We consider that the buses are driving in a fixed bus line, where driving cycle is constrained by the traffic. The traffic information and number of passengers are also incorporated into the energy management system. The deep reinforcement learning based energy management agent is trained with a large amount of driving cycles that generated from traffic simulation. Experiments on the traffic simulation driving cycles show that the proposed approach outperforms conventional reinforcement learning approach and exhibits performance close to the global optimal dynamic programming. Moreover, it also has great generality to the standard driving cycles that are significantly different with the ones that it has been trained with. We also show some interesting attributes of learned energy management strategies through visualizations of the actor and critic. The main contribution of this study is to explore the incorporation of traffic information within hybrid electric vehicle energy managment through advanced intelligent algorithms.

Jacob J. Lamb, B. Pollet, O. Burheim

A. Shankar, A. Quinn, Katherine L. Dickinson et al.

Stove stacking (concurrent use of multiple stoves and/or fuels) is a poorly quantified practice in regions where efforts to transition household energy to cleaner stoves/or fuels are on-going. Using biomass-burning stoves alongside clean stoves undermines health and environmental goals. This review synthesizes stove stacking data gathered from eleven case studies of clean cooking programs in low/middle-income country settings. Analyzed data are from ministry and program records, research studies, and informant interviews. Thematic analysis identify key drivers of stove stacking behavior in each setting. Significant (28%-100%) stacking with traditional cooking methods was observed in all cases. Reason for traditional fuel use includes: costs of clean fuel; mismatches between cooking technologies and household needs; and unreliable fuel supply. National household surveys often focus on 'primary' cookstoves and miss stove stacking data. Thus more attention should be paid to discontinuation of traditional stove use, not solely adoption of cleaner stoves/fuels. Future energy policies and programs should acknowledge the realities of stacking and incorporate strategies at the design stage to transition away from polluting stoves/fuels. Seven principles for clean cooking system program design and policy are presented, focused on a shift toward "cleaner stacking" that could yield household air pollution reductions approaching WHO targets.

P. Smith, Pramod K. Singh, Vedant Ballal et al.

Climate change threatens biodiversity, water, food and human health and well‐being. Rapid, sustained mitigation and adaptation actions can benefit all these elements of the nexus. Key transitions in energy, land and marine ecosystems, urban areas, industry and society are essential for climate change mitigation, adaptation and sustainable development. These transitions require interdisciplinary research, policy support and societal engagement. Here we present an assessment of 69 response options, a subset of which (15) was used in the climate change chapter of the IPBES Nexus Assessment. We show that the majority of climate change response options for land, oceans and ecosystems, settlement and infrastructure, industrial and societal system transitions have broadly positive impacts across the nexus. However, energy system transitions show more apparent trade‐offs. Most of these impacts result from energy infrastructure that would also be required for fossil fuel‐based systems and should be compared to the far more damaging consequences of continued fossil fuel use. Transitioning to cleaner, renewable energy sources reduces these risks and offers significant improvements across the nexus by reducing climate change impacts. Of the 69 response options assessed, 59% have entirely positive effects, or at least no negative effects, across all nexus elements and can be considered as low‐risk, immediately actionable options. The remaining 41% show either negative or variable impacts on at least one nexus element. However, this does not render them unviable; rather, their implementation must be carefully managed. Where impacts are variable, strategies should be tailored to ensure positive outcomes; where trade‐offs are unavoidable, efforts should focus on minimising negative effects and maximising synergies. Our findings suggest that prioritising policies that address the interconnected challenges of climate change, biodiversity loss, land degradation, pollution, food insecurity, access to clean water, energy for all and sustainable development will deliver more effective and equitable climate action.

Cheng ZHANG, Yu CHEN, Can LI et al.

[Objective] At present, wind power generation has been widely used, but wind power is volatile and unstable, and the grid voltage fluctuation and network loss increase will be caused after wind farms are connected to the grid. To solve these problems, a multi-objective reactive power optimization model of distribution network considering the reactive power output of doubly fed induction generator is proposed. [Method] Based on the segmentation idea, the uncertain dynamic problem of wind power was transformed into a definite static problem, and the improved whale optimization algorithm was used to solve the mathematical model. In order to solve the problems of low precision, slow convergence speed and easy to fall into local optimality of the traditional whale optimization algorithm, a hybrid strategy was adopted to improve whale optimization algorithm, and some improved methods such as tent mapping initialization, adaptive weight and adaptive probability threshold were introduced. [Result] Taking the improved IEEE33 node distribution network as an example, the improved whale optimization algorithm can improve the global search ability and convergence speed comparing the particle swarm optimization and gray wolf optimizer. [Conclusion] The optimal reactive power output of wind farm optimized by the proposed strategy can reduce more system losses and improve the voltage stability of distribution network.

Bei CAO, Wenxiu BAI, Huan YAO et al.

[Objective] FeCrAl alloys have shown promise as candidate materials for accident tolerance fuel cladding because of their excellent high-temperature strength, irradiation resistance, and mature fabrication technology. There are fewer studies related to the thermal and irradiation creep of FeCrAl alloys due to the high cost, long cycle time and difficult testing of neutron irradiation. The thermal and irradiation creep behavior of FeCrAl alloys were examined. And, the effects of irradiation dose rate, temperature and stress on the creep rate and parameters of the creep constitutive equations were analyzed. [Method] The creep simulations were performed on several FeCrAl samples with different grain sizes over a wide range of temperature, stress, and irradiation dose rates, using LAMMPS molecular dynamics simulator. [Result] The results show that the irradiation creep rate is significantly lower, compared to the thermal creep rate. As stress rises, the thermal creep rate increases exponentially, and the stress exponent increases roughly from 0.9 to 2.0 at the turning point of 0.8 GPa. The irradiation creep rate increases linearly with stress and dose rate, that is, the exponents of both dose rate and stress for irradiation creep are very close to 1.0. Besides, higher temperatures accelerates the linear increase of irradiation creep rate with dose rate, and the irradiation creep pre-factor becomes larger. [Conclusion] The creep of FeCrAl alloys under conditions of high temperature and irradiation is mainly attributed to the thermal creep behavior. Higher temperatures and stresses accelerate the irradiation creep process.

I. B. Kantola, E. Blanc‐Betes, A. vonHaden et al.

ABSTRACT Six years after replacing a maize/soybean cropping system, perennial grasses miscanthus (Miscanthus × giganteus) and switchgrass (Panicum virgatum), and a 28‐species restored prairie increased particulate organic carbon in surface soils without increasing soil organic carbon (SOC). To resolve potential changes in the quantity and distribution of SOC, soils were resampled after seven to thirteen years to measure bulk density, carbon (C) content, and stable C isotopes to a depth of 1 m. SOC stocks increased between 1.75 and 2.5 Mg ha−1 year−1 in all perennial crops between 2008 and 2016 (nine growing seasons). Despite relatively low litter inputs and belowground biomass, the highest rate of SOC accrual was in restored prairie (2.5 Mg ha−1 year−1), followed by miscanthus (2.0 Mg ha−1 year−1) and switchgrass (1.75 Mg ha−1 year−1). The change in SOC in maize/soybean was not significant. After 2016, total SOC decreased in maize/soybean and miscanthus, resulting in slower overall rates of SOC accumulation over the full sampling period for miscanthus (0.8 Mg ha−1 year−1). The rate of SOC accumulation was greatest below 50 cm depth for restored prairie and switchgrass but in the top 10 cm for miscanthus. Stable isotope analysis showed 13C enrichment in all depths of switchgrass soils, an indication of new organic C accumulation, but mixed results in all other crops. Planting perennial crops on land formerly in an annual maize/soybean cropping system can slow or reverse soil carbon losses, with the greatest increases in SOC from species‐rich prairie.

Zhi Liu, Jinde Hao, Ronghua Yao et al.

Abstract The proton exchange membrane electrolysis cells (PEMECs) are electrochemical devices that efficiently produce high-purity hydrogen via electrical energy conversion, making them widely applicable in renewable energy storage and hydrogen infrastructure development. However, the external sodium ion (Na+) contamination can severely damage the catalyst layer and membrane in PEMEC, causing significant performance degradation. Therefore, a segmented diagnostic platform for PEMEC is developed to analyze the poisoning effects of Na+ contamination on a large scale PEMEC under various operating conditions. The results demonstrate that during the cycle test, the Na⁺ poisoning process is defined as three distinct stages of initial, sustained and stable contamination stages. An increased Na+ concentration enhances the occupations of active sites on the catalyst layer, resulting in significant voltage spike, dynamic voltage fluctuations, non-uniformity distributions of current density and temperature. Both the low water flow rate and high operating temperature improve the chemical reaction and PEMEC performance at high current density. The deionized water flushing will dissolve Na+ on the catalyst layer surface and realize 2.17% decrease in voltage at 2.0 A cm⁻2 after three cycles. This study is beneficial to consolidate the understanding of poisoning effects of sodium ion contamination in PEMEC under various operating conditions, thereby overcoming the obstacles for commercial application of green hydrogen production technology.

Gregor Papa, Rok Hribar, Gašper Petelin et al.

Abstract Background Achieving climate neutrality in cities is a major challenge, especially in light of rapid urbanization and the urgent need to combat climate change. This paper explores the role of advanced computational methods in the transition of cities to climate neutrality, with a focus on energy supply and transportation systems. Central to this are recent advances in artificial intelligence, particularly machine learning, which offer enhanced capabilities for analyzing and processing large, heterogeneous urban data. By integrating these computational tools, cities can develop and optimize complex models that enable real-time, data-driven decisions. Such strategies offer the potential to significantly reduce greenhouse gas emissions, improve energy efficiency in key infrastructures and strengthen the sustainability and resilience of cities. In addition, these approaches support predictive modeling and dynamic management of urban systems, enabling cities to address the multi-faceted challenges of climate change in a scalable and proactive way. Main text The methods, which go beyond traditional data processing, use state-of-the-art technologies such as deep learning and ensemble models to tackle the complexity of environmental parameters and resource management in urban systems. For example, recurrent neural networks have been trained to predict gas consumption in Ljubljana, enabling efficient allocation of energy resources up to 60 h in advance. Similarly, traffic flow predictions were made based on historical and weather-related data, providing insights for improved urban mobility. In the context of logistics and public transportation, computational optimization techniques have demonstrated their potential to reduce congestion, emissions and operating costs, underlining their central role in creating more sustainable and efficient urban environments. Conclusions The integration of cutting-edge technologies, advanced data analytics and real-time decision-making processes represents a transformative pathway to developing sustainable, climate-resilient urban environments. These advanced computational methods enable cities to optimize resource management, improve energy efficiency and significantly reduce greenhouse gas emissions, thus actively contributing to global climate and environmental protection.

Junhong Liu, Qinfei Long, Rong-Peng Liu et al.

The proliferation of distributed renewable energy triggers the peer-to-peer (P2P) energy market formations. To make profits, prosumers equipped with photovoltaic (PV) panels and even the energy storage system (ESS) can actively participate in the real-time P2P energy market and trade energy. However, in real situations, system states such as energy demands and renewable energy power generation are highly uncertain, making it difficult for prosumers to make optimal real-time decisions. Moreover, severe problems with the physical network can arise from the real-time P2P energy trading, such as bus voltage violations and line overload. To handle these problems, this work first formulates the real-time P2P energy trading problem as a spatio-temporally constrained stochastic optimization problem by considering ESS and the spatial physical network constraints. To deal with the uncertainties online, a modified Lyapunov optimization method is innovatively proposed to approximately reformulate the stochastic optimization problem into an online one by relaxing the time-coupling constraints. Compared with the state-of-the-art online methods, the proposed one renders more flexibility and better performance for the real-time P2P energy market operation. Additionally, to protect the prosumers' privacy, an online distributed algorithm based on the consensus alternating direction method of multipliers (ADMM) is developed to solve the reformulated online problem by decoupling the spatial constraints. The theoretical near-optimal performance guarantee of the proposed online distributed algorithm is derived, and its performance can be further improved by minimizing the performance gap. Simulation results demonstrate that the proposed online distributed algorithm can guarantee the fast, stable, and safe long-term operation of the real-time P2P energy market.

N. Alwaaritsy, Arista Romadani

Carbon pricing serves as an effective economic instrument to mitigate greenhouse gas emissions while fostering investment in renewable energy by reducing dependence on fossil fuels. This study examines the development of carbon pricing policies to accelerate the energy transition, focusing on the Industrial Processes and Product Use (IPPU) sector. The proposed scheme is based on the Emissions Trading Scheme (ETS), tailored to local regulations and industrial capacities. This research employs a systematic review and content analysis of successfully implemented carbon pricing policies in various countries. While carbon pricing has been applied in the energy and forestry sectors, existing studies often lack specificity regarding emission thresholds or quantified carbon values across different emission sources. The IPPU sector, despite being a significant emitter, remains underrepresented in current policy design and academic literature. The findings indicate that carbon commercialisation supports renewable energy transition projects and increases investment in the electricity sector. This study proposes a carbon credit scheme tailored to the Indonesian wood industry (referred to as Industry X), which has begun integrating biomass and bioenergy to compensate for fossil-based emissions. The novelty of this study lies in its targeted focus on the IPPU sector and the practical application of a carbon pricing framework for industrial decarbonisation. The results suggest that integrating carbon pricing with fiscal incentives and energy regulations enhances industrial competitiveness in transitioning to clean energy. This study provides policy recommendations to improve carbon pricing mechanisms, supporting renewable energy investment and sustainable industrial transformation.

Sothea Oum

Abstract The Lao PDR has experienced rapid growth and poverty reduction through its openness to trade, investment, and integration to the regional and world economy. The country has also progressed in providing access to electricity and aims to have a 95% national coverage of electricity by 2020. This paper focuses on assessing the extent of energy poverty, as well as its implications on the well-being of the people, such as in education and health, using the Lao Economic Consumption Survey (LECSs). While access to electricity has dramatically increased, a significant number of households still do not have access to electricity and cannot afford to meet both necessity and energy consumption. Energy-poor households are prevalent among those who have lower income, owning lesser durables, living in rural villages without electricity connection and are far from main roads. This paper also finds that energy poverty negatively impacts households’ average school years and health status. The findings would identify the vulnerable groups of people for targeted support. It argues that while ensuring access to electricity should be prioritised, it should be accompanied by policies promoting opportunities to generate income and reduce all forms of energy poverty.

Amjad Ali, Marc Audi, Yann Roussel

This article investigates the impact of renewable energy consumption and natural resource depletion on environmental degradation from 1990 to 2014. The analysis of this study is distributed into three parts, developing country analysis, developed country analysis and complete sample analysis. An insignificant relation has found between natural resource depletion and environmental degradation in the case of complete sample analysis and developing country analysis, but vica-versa in developed countries. Fossil fuel energy consumption has a positive and significant impact on environmental degradation in developing countries. Renewable energy consumption has negative impact on environmental degradation in the case of complete sample analysis and developed country analysis, but visa-versa in developing countries. Economic growth positively and significantly effecting environmental degradation in all the three cases, this mean for higher economic growth we have to bear some environmental degradation. But it is the need of the hour that we should find some threshold between economic growth and pollutant emissions, so that a healthy environment can be safe for coming generations. So, for a healthy environment, fossil fuel consumption should be reduced and consumption of renewable energy with merchandised trade and urbanization can be encouraged.

Olha Yatsenko, Olexander Iatsenko

The article aims to identify key trends, prospects, and features of international hydrogen trade, focusing on new barriers and challenges to global cooperation. It is determined that the current growth of interest in hydrogen is associated with incentives in developed countries to reduce greenhouse gas emissions and combat global warming. It is argued that international hydrogen trade is becoming an important factor in countries' energy and economic transformation, and the hydrogen energy global market will be actively developed and supported. Still, it will have to overcome technical limitations to achieve significant success. Based on theoretical and empirical generalizations, the author concludes that hydrogen has significant explicit and latent potential for international trade and sustainable development of global energy and is a key factor in achieving global decarbonization goals. Still, the main challenges remain high production and transportation costs and the need to invest in innovative technologies. The study emphasizes that the oil refining and fertilizer industries mainly generate the demand for hydrogen. However, experts argue that in the future, sectors that are heavily dependent on fossil fuels, such as heavy industry, long-haul transportation, and air transport, may benefit most from hydrogen energy. Currently, the largest importers of hydrogen are Asian countries, driven by the region's demand for chemicals and the transportation, iron, and steel sectors in China and India. The main exporters of hydrogen in the future may be the countries of Oceania, North America, and the Middle East. The main barriers and challenges in international hydrogen trade are identified, which can be classified into economic, political, technical and infrastructural. It is emphasized that different regions of the world use unique strategies to develop the hydrogen market, and some cases are presented. The study concludes that the prospects for international hydrogen trade and the future introduction of hydrogen into the global economy will depend on the factors that affect a country's ability to produce and export hydrogen, which is multifaceted and interdisciplinary and covers many areas. For example, a country's hydrogen production may be limited by its oil resources, renewable energy potential, water resources, or land area, and difficulties in producing or exporting hydrogen due to its infrastructure, financial capacity, political climate, and government policies.

Sagiraju Dileep Varma, Sarathbabu Duvvuri, Omkar Koduri et al.

The widespread integration of wind energy poses numerous challenges, including ride-through capability issues, stability concerns, and power quality issues within the utility grid. Additionally, the inherent non-linear nature of wind energy systems, coupled with internal dynamics like model uncertainties, non-linearities, parametric variations, modeling errors, and external disturbances, significantly impacts system performance. Therefore, developing a robust controller becomes imperative to address the complexity, non-linearity, coupling, time variation, and uncertainties associated with wind energy systems, aiming to enhance transient performance in the presence of external and internal disturbances. The research presented in this manuscript focuses on devising a robust control scheme for a grid-tied Permanent Magnet Synchronous Generator (PMSG) wind turbine. The objective is to improve the wind turbine's performance under both normal and abnormal grid conditions. The innovation in Active Disturbance Rejection Control (ADRC) lies in its capacity to offer robust, adaptive, and disturbance-rejecting capabilities without relying on precise mathematical models. This quality makes ADRC a valuable and innovative tool for addressing challenges in complex and dynamic real-world applications where system parameters evolve over time. The wind energy system is inherently non-linear, time-varying, cross-coupled, and highly uncertain. It is also susceptible to parameter uncertainties, parametric variations, and external grid disturbances, all of which significantly influence its performance. The effectiveness of the proposed control scheme is validated to enhance ride-through capability and extract maximum power under internal disturbances, external grid disturbances, and parametric variations. To assess the proposed controller's efficacy, a comparative analysis is conducted using the Integral Time Absolute Error (ITAE) index for all abnormal grid disturbances. This analysis is performed in comparison to a Proportional Resonant Controller and a PI controller, providing evidence of the proposed controller's effectiveness. In summary, the incorporation of an Active Disturbance Rejection Controller emerges as a promising solution for enhancing the Low Voltage Ride-Through (LVRT) and High Voltage Ride-Through (HVRT) capabilities of grid-tied Permanent Magnet Synchronous Generator (PMSG)-based wind energy systems.

Jiaxi Li, Zhuomin Zhou, Ming Wen et al.

The medium and long-term supply-demand imbalance of the power system in the context of the new power system is becoming more and more prominent due to the fluctuation and intermittency brought about by the high proportion of new energy sources connected to the grid. In this regard, a multi-objective power supply-demand balance optimization method considering the spatiotemporal correlation of source and load is proposed in this work. First, the autocorrelation and inter-correlation characteristics of source and load are analyzed. On this basis, a multi-dimensional scenario set construction method considering the spatiotemporal correlation of source and load is proposed. Then, the planning capacity of each regional power source and the system operation under each scenario are taken as the optimization variables. Renewable energy electricity curtailment, equivalent annual total cost, and inter-region transmission electricity are taken as the optimization objectives. Various constraints such as power source planning and operation, power balance, inter-region power transmission, and renewable energy power curtailment rate are considered comprehensively. The optimization method for the medium and long-term power supply and demand balance is proposed. Finally, the method is applied to Hunan Province, China to guide power planning. The results show that compared with traditional multi-dimensional correlation scene construction methods, the average probability density functions error of wind turbine output, photovoltaic output, and load constructed in this work decrease by 44.08 %, 73.64 %, and 57.54 %, respectively. It takes into account the regional, temporal, temporal autocorrelation, and inter-correlation of the source and load, and has similar characteristics to historical data. Compared with traditional planning that only considers economy, the optimization plan for power supply and demand balance in this work reduces electricity curtailment and inter-region transmission by 97.04 % and 72.71 %, respectively, balancing renewable energy consumption, economy, and regional independent balancing indicators.

محمد صادق ادیبیان, تقی ابراهیمی سالاری, هادی اسماعیل پور مقدم

عدم قطعیت­ها بخش جدایی ناپذیر اقتصاد هستند و تأثیرات اثبات شده‌ای بر ارکان گوناگون اقتصادی دارند. قیمت نفت علاوه بر آن­که به عنوان یک عامل کلیدی در بخش تولید محسوب می­شود، نشان­دهنده درآمدهای نفتی اقتصاد ایران است. هدف از این پژوهش بررسی تأثیر عدم قطعیت سیاست اقتصادی و عدم قطعیت ژئوپلیتیک با منشأ جهانی، چین، ایالات متحده و روسیه بر قیمت نفت خام ایران است. به این منظور از مدل افزایشی تعمیم یافته (گام) و بر اساس داده­های ماهیانه سال‌های 1997 الی 2022 استفاده شده است. نتایج نشان می‌دهد عدم قطعیت سیاست اقتصادی با منشأ جهانی، کشور چین و کشور روسیه تأثیر معنادار و غیرخطی بر قیمت نفت خام ایران دارد. هم­‌چنین عدم قطعیت ژئوپلیتیکی با منشاء جهانی، چین و روسیه تأثیر مستقیم و غیر خطی بر قیمت نفت خام ایران دارد در حالی که تأثیر عدم قطعیت ژئوپلیتیکی با منشأ ایالات متحده، تأثیر خطی و معکوس است. هم­‌چنین تأثیر عدم قطعیت­های همراه با منشأ یکسان، نشان می­دهد عدم قطعیت­های همزمان با منشأ جهانی، روسیه و ایالات متحده، دارای تأثیرگذاری معنادار و غیرخطی هستند. این نتیجه نشان دهنده ضرورت استفاده از مدل­های نوین با امکان بررسی توأمان متغیرهاست. نتایج می­تواند برای فعالان بازار نفت در بازار مالی و هم‌چنین سیاست‌مداران مورد استفاده قرار بگیرد.

Tamer Emre, Adnan Sözen

Abstract Energy poverty (EP), a pressing global concern, is uniquely manifested in regions like eastern Turkey due to intertwined socio-economic conditions and intricate energy consumption patterns. This study critically examines the electricity market dynamics, highlighting the direct impact on end-users, from households to entire communities facing challenges such as unauthorized consumption and waste. Our findings over 2 years period of 6 million customer invoices through 17 cities of 5 distribution companies underscore the limitations of traditional income-based measures in capturing the nuances of EP. In response, we introduce a novel metric—the power-cut index per consumer (PCPC)—spotlighting the prevalence of power interruptions due to non-payment as an actionable intervention metric. To address EP’s challenges, we present a mechanism encouraging consumers to reduce consumption, offering debt discounts as incentives. Our methodological approach, harnessing both the Monte Carlo simulation and optimization, promises flexible, actionable strategies tailored to diverse EP situations. Drawing parallels with the European Union’s energy transition efforts, this study proposes the adaptation of European frameworks to cater to Turkey’s unique landscape. By anchoring our insights in real stories of those affected by EP, we highlight the human dimension, emphasizing the urgency of stakeholder collaboration to ensure a future where energy facilitates prosperity rather than hindrance. The collective endeavors of infrastructure companies, governmental agencies, NGOs, and the public are pivotal in sculpting a brighter, equitable energy future.