Abstract The need to put in place alternative energy policies stems from the awareness that fossil fuels are exhaustible and harmful to the environment. For this reason, during the last decades the scientific world has focused on systems able to use and convert renewable energy sources, particularly solar radiation. Nowadays, solar thermal collectors use solar energy to distribute low-cost domestic and industrial heating. In this review a comprehensive analysis of peer-reviewed journals and relevant papers on solar thermal collectors is provided. Descriptions of the different types of solar collectors are provided. Theoretical analyses, latest developments related to the functional elements, and hybrid systems have been considered throughout this analysis. Performance test methods for solar thermal collectors and standards are discussed. This cross-review aims to assist researchers, engineers and manufacturers in keeping them abreast of latest developments in the field of solar thermal collectors.
Drawing on panel data encompassing 31 Chinese provinces during the period from 2007 to 2019 and employing a panel fixed-effects model, this study examines the influence of bank-dominated financial systems on the development of renewable energy alongside its specific operational mechanisms. The findings indicate that, compared to a market-dominated financial system, a bank-dominated financial system plays a significantly positive role in promoting renewable energy development. Heterogeneity analyses reveal that a bank-dominated financial system is particularly effective in fostering renewable energy development in provinces with lower levels of green finance, weaker environmental regulations, and lagging renewable energy sectors. Mechanism tests further demonstrate that a bank-dominated financial system can enhance the development of renewable energy by optimizing industrial structures and improving the level of green innovation. Ultimately, the study's conclusions underscore the pivotal role of bank-dominated financial systems in propelling the evolution of renewable energy within the Chinese context.
Use of Geographic Information System (GIS) mapping in tandem with Multi-Criteria Decision Analysis (MCDA) has become increasingly common as a means of determining the optimal location and design of renewable energy projects. However, to date, no attempt has been made to synthesise the location and design specific criteria currently evaluated within GIS-MCDA studies on renewable energy technologies. This study thus conducts a systematic literature review, using the Search Appraisal, Synthesis and Analysis (SALSA) framework, in order to gain better understanding about the breadth of design and location-specific assessment criteria employed in GIS-MCDA studies relating to renewable energy projects. It addresses three renewable energy technologies: hydropower, geothermal, and onshore wind power. This focus has a particular policy relevance as these renewable energy options are the types implemented in Iceland, where there is a Master Plan for Nature Protection and Utilization that determines strategic suitability. The study's results, which derive from a total of 57 articles, are that geothermal studies currently focus mostly on resource prospectivity, economic returns, and minimisation of risk and cost. Hydropower projects mostly address productive capacity issues, similarly to the geothermal GIS-MCDA studies, however, there was greater focus on providing a broader set of information for decision-makers about the legal, technical, environmental, and social consequences of projects. GIS-MCDA studies on onshore wind demonstrated evidence of methodological innovation and novelty, with consideration of not only the issues of productive capacity, but also environmental impacts, land use designations, and social acceptance. The application of GIS mapping in Icelandic decision-making concerning proposed energy projects would help to rationalise the determination of suitable locations and designs carried out by Iceland's Master Plan, providing a broader set of information for decision-makers about legal, technical, environmental, and social consequences.
[Objective] This paper aims to explore dynamic modeling methods for airborne wind energy systems (AWEs) and trajectory tracking control methods for stable trajectories of kite trains and between kite trains when subjected to longitudinal disturbances in high-altitude wind fields. [Method] Taking a 25 MW-level kite-based AWEs as an example, this study investigated the mechanical response characteristics of kite arrays and constructed a multi-rigid body dynamic model of the kite-based system. In a simulated environment replicating high-altitude wind fields subjected to longitudinal disturbances, the study employed kite attitude control to design synchronous control laws, enabling trajectory tracking and ensuring operational safety of the kite-based system.[Result] The results demonstrate that adjusting the effective windward area of the kite can mitigate longitudinal disturbances caused by variations in high-altitude wind fields, leading to the convergence of errors between the actual and desired trajectories of the kite-based system. Moreover, based on the synchronous control laws designed, synchronization among multiple kite- based systems has been achieved, thereby ensuring collision-free and safe operation. [Conclusion] Using kite attitude control as a basis, a synchronous control strategy can be designed for the operation of kite-based AWEs, thereby achieving the objective of safe and efficient operation control in dynamic high-altitude wind environments.
Savan K. Raj, Khushbu Sharma, Vartika Sharma
et al.
The design and synthesis of a silicon-integrated MXene-based nanoflower (Si@NFs) architecture using a simple hydrothermal method and thermal treatment are reported in this study. The resulting hierarchical structure creates a multidimensional conductive network by fusing the superior conductivity and mechanical stability of MXenes with the high capacity of nanosilicon. Due to effective ion transport, interfacial contact, and volume expansion buffering, Si@NFs exhibit better cycling stability, as demonstrated by structural and electrochemical characterisation. The strong interface and structural integrity of the nanoflowers indicate high promise for future integration into all-solid-state lithium-ion battery systems, even though solid-state electrolytes are not directly incorporated in this study.
Energy industries. Energy policy. Fuel trade, Renewable energy sources
Manoj Mandal, Sabyasachi Pal, G. K. Jaisawal
et al.
We report the broadband timing and spectral properties of the neutron star low-mass X-ray binary Aql X-1 during the 2024 outburst with NICER, NuSTAR, and Swift observatories. We detected six thermonuclear X-ray bursts during the NICER and NuSTAR observations, with the observed X-ray burst profiles exhibiting a strong energy dependence. The time-resolved burst spectra indicate the presence of soft excess during the burst, which can be modeled by using a variable persistent emission method ($f_a$ method), or the relxillNS reflection model. We found that the reflection model can contribute $\sim$20% of total emission as observed during the NICER burst. The reflection and blackbody component fluxes are strongly correlated as observed during a burst. The excess emission is possible due to the enhanced mass accretion rate to the neutron star due to the Poynting-Rodertson drag and a fraction of burst emission may be reflected from the disk. The bursts did not show photospheric radius expansion during the peak. Moreover, we examined the burst-free accretion emission in the broadband range with NuSTAR, NICER, and Swift at two epochs of the outburst. The persistent emission showed X-ray reflection feature, which can be well modeled with the relativistic reflection model relxillCp. The inner disk radius (R$_{in}$) is found to be nearly 22 and 10 times $\rm R_{g}$ for two observations, respectively. Assuming that the inner disk is truncated at the magnetospheric radius, the magnetic field strength at the poles of the neutron star is estimated to be $(0.6-1.9) \times 10^9$ G.
The collaborative development of the electricity and carbon markets can reduce transaction costs, stimulate energy conservation and emission reductions, and accelerate the social transition to low carbon. In this paper, we present a comprehensive review of the current state and policy challenges of electricity-carbon trading and present an in-depth analysis of key research directions and technical details of electricity-carbon collaboration in the context of large-scale access to renewable energy. Then, by constructing a multi-agent behavioral decision-making model, we refine the decision-making mechanism of electricity-carbon synergy, simulated market clearing outcomes under different mechanisms, and proposed policies and incentive mechanisms to promote electricity-carbon trading. Furthermore, leveraging the massive data in energy systems, we design a carbon measurement method and carbon emission flow tracking method for low-carbon energy companies, achieving real-time carbon accounting for the power system. We establish a collaborative simulation model of the electricity and carbon markets, enabling an accurate prediction of the day-ahead carbon emission intensity. This study provides a new research framework and complete technical route for electricity-carbon coordination, which can further promote the low-carbon transformation of the energy system.
Background: In the midst of the controversy over bioenergy or biofuels as a driving factor for global deforestation, Indonesia is dependent on its palm oil commodities which have been built for years and consume millions of hectares of land. Indonesia's dependence on these commodities to meet domestic and foreign markets is regulated by the biodiesel policy or ESDM Ministerial Decree No. 12 of 2015 concerning the Provision, Utilization and Trading Administration of Vegetable Fuels (Biofuel) as Other Fuels, which states that the use of biodiesel levels in the future will continue to increase, from B20 to B30, then to B40 and so on. However, to be able to meet these policy targets, there is a risk of land clearing. This policy paper discusses what important issues from an economic, social and environmental perspective are related to the development of the palm oil biodiesel industry in Indonesia and what needs to be prioritized in determining future government policy to ensure that sustainable development can be pursued and emission reductions reach targets. Methods: The research method used in this paper is a qualitative approach and descriptive analysis of data collected from literature study. Findings: Apart from that, there are various issues regarding palm oil management, both from a social, economic and environmental perspective, that still need to be addressed, considering that Indonesia is internationally committed to reducing its greenhouse gas emissions by 30% by 2030. Conclusion: Overall In short, there are five recommendations for palm oil biodiesel policy for the future, namely: 1. There is a need for clear data that can support policy decision making; 2. Indonesia needs to evaluate fossil fuel subsidy policies from developing countries that have succeeded in developing their renewable energy sectors; 3. There is a need for intensification, technological improvisation and sustainable agricultural practices on existing oil palm plantation land to meet national bioenergy needs; 4. Prioritizing collaboration between sectors in developing the industry; and 5. The government must be firm in determining a consistent future palm oil biodiesel policy so as not to harm many parties.
Smart cities depend highly on an intelligent electrical networks to provide a reliable, safe, and clean power supplies. A smart grid achieves such aforementioned power supply by ensuring resilient energy delivery, which presents opportunities to improve the cost-effectiveness of power supply and minimize environmental impacts. A systematic evaluation of the comprehensive benefits brought by smart grid to smart cities can provide necessary theoretical fundamentals for urban planning and construction towards a sustainable energy future. However, most of the present methods of assessing smart cities do not fully take into account the benefits expected from the smart grid. To comprehensively evaluate the development levels of smart cities while revealing the supporting roles of smart grids, this article proposes a model of smart city development needs from the perspective of residents’ needs based on Maslow’s Hierarchy of Needs theory, which serves the primary purpose of building a smart city. By classifying and reintegrating the needs, an evaluation index system of smart grids supporting smart cities was further constructed. A case analysis concluded that smart grids, as an essential foundation and objective requirement for smart cities, are important in promoting scientific urban management, intelligent infrastructure, refined public services, efficient energy utilization, and industrial development and modernization. Further optimization suggestions were given to the city analyzed in the case include strengthening urban management and infrastructure constructions, such as electric vehicle charging facilities and wireless coverage.
Energy conservation, Energy industries. Energy policy. Fuel trade
Understanding the acceleration of Ultra High Energy Cosmic Rays is one of the great challenges of contemporary astrophysics. In this short review, we summarize the general observational constraints on their composition, spectrum and isotropy which indicate that nuclei heavier than single protons dominate their spectra above $\sim 5\,{\rm EeV}$, that they are strongly suppressed above energies $\sim50\,{\rm EeV}$, and that the only significant departure from isotropy is a dipole. Constraints based upon photopion and photodisintegration losses allow their ranges and luminosity density to be estimated. Three general classes of source model are discussed - magnetospheric models (including neutron stars and black holes), jet models (including Gamma Ray Bursts, Active Galactic Nuclei and Tidal Disruption Events) and Diffusive Shock Acceleration models (involving large accretion shocks around rich clusters of galaxies). The value of constructing larger and more capable arrays to measure individual masses at the highest energies and probably identifying their sources is emphasized.
This paper presents a novel probabilistic data-driven approach to trip-level energy consumption estimation of battery electric vehicles (BEVs). As there are very few electric vehicle (EV) charging stations, EV trip energy consumption estimation can make EV routing and charging planning easier for drivers. In this research article, we propose a new driver behaviour-centric EV energy consumption estimation model using probabilistic neural networks with model uncertainty. By incorporating model uncertainty into neural networks, we have created an ensemble of neural networks using Monte Carlo approximation. Our method comprehensively considers various vehicle dynamics, driver behaviour and environmental factors to estimate EV energy consumption for a given trip. We propose relative positive acceleration (RPA), average acceleration and average deceleration as driver behaviour factors in EV energy consumption estimation and this paper shows that the use of these driver behaviour features improves the accuracy of the EV energy consumption model significantly. Instead of predicting a single-point estimate for EV trip energy consumption, this proposed method predicts a probability distribution for the EV trip energy consumption. The experimental results of our approach show that our proposed probabilistic neural network with weight uncertainty achieves a mean absolute percentage error of 9.3% and outperforms other existing EV energy consumption models in terms of accuracy.
The environmental variations compel global countries for restructuring economic growth policies to ensure reliable energy usage. Ecological sustainability is a leading concern of the world for adequate and smooth survival of human beings. The inefficiency of technology is a focal hindrance to attaining the sustainable environment goal. This research aims to probe the cointegration and causal relationship among information communication technology, CO2 emission, economic development, trade, and total population for GCC countries, namely, the United Arab Emirates, Saudi Arabia, Qatar, Oman, Kuwait, and Bahrain, from 2000 to 2018. This research approached the unit-root tests, cointegration test, and FMOLS and DOLS test to determine stationarity of data series, cointegration relationship among variables, and the short- and long-run relationship among variables, respectively. The results of the analytical procession by employing FMOLS and DOLS confirmed that CO2 emission, ICT, and ED are positively significant, while POP was negatively substantial at a 1% level. No relation has been observed between trade and CO2 emission. The long-run relationship among variables is confirmed by FMOLS and DOLS analyses. A negative relationship between population growth and CO2 emission is observed. It is ideal for enhancing environmental sustainability by awareness of people’s importance to the environment. The GCC countries should transform or divide their economic growth sectors instead of only the fossil fuel sector. This research also enlightened the way to reduce environmental destruction by the attraction of foreign investments in other sectors compared to entire fossil fuel industries, and the information communication technologies also move toward green technology using environmentally friendly energy resources.
Abstract The distributed integrated multi‐energy system (DIMS) has many advantages in terms of the utilisation of renewable energy sources and clean energy. Operation strategies for the DIMS based on a real‐time profile have been extensively studied. In a DIMS online optimisation problem, besides fluctuations in the renewable energy output and load, inconsistent time scales of the transport dynamics of different energy flows and non‐ideal communication (involving communication uncertainty and latency) result in suboptimal operation in dispatch scheduling. An online multi‐time‐scale optimal operation strategy is proposed for the DIMS to respond to the above challenges, using a hybrid algorithm comprising a model predictive control method and distributed collaborative consensus algorithm (CCA). The approach is based on a hierarchy, comprising rolling optimisation and adjustment. A rolling optimisation is established to schedule operations according to the latest forecast and status information. The rolling dispatch is then adjusted according to the ultrashort‐term adjustment using the CCA. Meanwhile, the effect of the information transmission environment on real‐time scheduling is considered, and the robust CCA is improved for the implementation of strategies under non‐ideal communication conditions. Case studies and results are presented and discussed to show the effectiveness of the proposed approach with the better matching between demand and supply.
Production of electric energy or power. Powerplants. Central stations, Energy industries. Energy policy. Fuel trade
Jiantao Wu, Fabrizio Orlandi, Tarek AlSkaif
et al.
In a decentralized household energy system comprised of various devices such as home appliances, electric vehicles, and solar panels, end-users are able to dig deeper into the system's details and further achieve energy sustainability if they are presented with data on the electric energy consumption and production at the granularity of the device. However, many databases in this field are siloed from other domains, including solely information pertaining to energy. This may result in the loss of information (e.g. weather) on each device's energy use. Meanwhile, a large number of these datasets have been extensively used in computational modeling techniques such as machine learning models. While such computational approaches achieve great accuracy and performance by concentrating only on a local view of datasets, model reliability cannot be guaranteed since such models are very vulnerable to data input fluctuations when information omission is taken into account. This article tackles the data isolation issue in the field of smart energy systems by examining Semantic Web methods on top of a household energy system. We offer an ontology-based approach for managing decentralized data at the device-level resolution in a system. As a consequence, the scope of the data associated with each device may easily be expanded in an interoperable manner throughout the Web, and additional information, such as weather, can be obtained from the Web, provided that the data is organized according to W3C standards.
Gregory P. Trencher, Noel Healy, Koichi Hasegawa
et al.
Abstract Achieving temperature targets under the Paris Agreement requires urgent measures to curb construction of coal-fired power plants (CFPPs) and expediate the retirement of existing assets. As the world's fourth largest coal consumer, Japan's efforts to reduce coal usage are critical for international climate mitigation. Policies introduced after the Fukushima nuclear disaster have led to a rapid increase in solar. However deregulation of the electricity market has also prompted a rush of new CFPP constructions by new market entrants and incumbent utilities. In parallel, Japanese state agencies and industry are actively exporting CFPP technologies to developing countries. Although these domestic and international actions harbour serious consequences for global climate mitigation efforts, greater understanding of the factors driving Japan's coal dependency is needed to limit further lock-in of future carbon emissions. Filling this gap, this study critically examines narratives employed by actors in government and industry to sustain Japan's domestic and international coal industry. Our analysis shows how Japan's fossil fuel regime is employing recurring narratives to promote continuation of the current coal-based energy system and to mobilise further investments in high-efficiency coal power technologies. We conclude by recommending various policy pathways and institutional reform measures aimed at encouraging wider diffusion of renewable electricity sources while reducing coal dependency.