Pollution of water by plastic contaminants has received increasing attention, owing to its negative effects on ecosystems. Small plastic particles propagate in water and can travel long distances from the source of pollution. In order to research the settling motion of particles in water flow, a small-scale experiment was conducted, whereby spherical plastic particles of varying diameters were released in an open-channel flow. Three approaches were investigated to numerically simulate the motion of particles. The numerical simulation results were compared and validated with experimental data. The presented methods allow for deeper insight into particle motion in fluid flow and could be extended to a larger scale to predict the propagation of mesoplastics in natural environments.

Supercritical carbon dioxide (SCO2) is widely used in many fields of energy and power engineering, such as nuclear reactors, solar thermal power generation systems, and refrigeration systems. In practical applications, SCO2 undergoes a cooling process significantly when it is cooled near the pseudo−critical point. Because of the drastic variations in thermo−physical properties, the heat transfer characteristics fluctuate, affecting the heat exchange and overall cycle performance. This paper summarizes extensive experiments and numerical simulations on the cooling process of SCO2 in various application scenarios. The effects of various working conditions, such as mass flow, working pressure, pipe diameter, flow direction, and channel shapes, are reviewed. The applicability and computational results using different numerical methods under different working conditions are also summarized. Furthermore, empirical correlations obtained in experiments at different conditions are included. The... [more]

In the context of carbon neutrality, the development of new digital infrastructure (NDI) and the improvement of digital capabilities are essential, in order to speed up the transformation of the energy structure. Based on the balanced panel data of 30 provinces in China from 2008 to 2019, we empirically analyzed the impact of NDI on the structural transformation of energy in China and its mechanisms of action. The results demonstrated that (1) NDI had a positive impact on China’s energy transition, and the empirical results were robust. (2) The mediating effect showed that NDI had a positive impact on the transformation of energy structure, through improving green total factor productivity and green finance. (3) The heterogeneity analysis indicated that NDI made a more significant contribution to the transformation of the energy structure in regions with lower pollution levels and in those with energy cooperation policies. This study provides a policy reference for Chinese energy trans... [more]

In recent years, with the rapid development of distributed photovoltaic systems (DPVS), the shortage of data monitoring devices and the difficulty of comprehensive coverage of measurement equipment has become more significant, bringing great challenges to the efficient management and maintenance of DPVS. Virtual collection is a new DPVS data collection scheme with cost-effectiveness and computational efficiency that meets the needs of distributed energy management but lacks attention and research. To fill the gap in the current research field, this paper provides a comprehensive and systematic review of DPVS virtual collection. We provide a detailed introduction to the process of DPVS virtual collection and identify the challenges faced by virtual collection through problem analogy. Furthermore, in response to the above challenges, this paper summarizes the main methods applicable to virtual collection, including similarity analysis, reference station selection, and PV data inference.... [more]

This paper reports on a review on combined heat and power (CHP). A historical examination points out that combined heat and power was primarily used for hot heat valorizing (CHHP). The technological aspects evolved with this configuration first in industrial size. More recently, configuration with cold heat and power production (CCHP) appeared. Then, the immediate extension of this configuration led to trigeneration configuration, providing three useful effects: power and hot and cold heat. We suggest in the paper that progress regarding this last approach remains to be achieved towards the extension of trigeneration to polygeneration, whatever the form of energy and substance (water uses, for example). More generally, we consider that the goal, regarding the energy uses, is the integration of all needs in the design stage of the whole system (design optimization). Then, the evolution of the system in time should be considered, this being the purpose of control command of the optimized... [more]

Due to the uncertainty of the nodal power caused by the varying renewable energies and the variety of loads, the line power of the distribution network (DN) is uncertainty also. In extreme scenarios, the line power may exceed the loading limits and incur overload violations. In this paper, a risk analysis specifically for overload violations based on the security region of the DN is established. This method takes the N-0 security of the DN as the reference to determine the bidirectional security region and violation distances. The calculation of the probability distribution of the overload violation in the distribution lines is established according to the distribution of node injections of the DN by using the semi-invariant algorithm. By referring to the security boundaries, the optimization model of the anti-violation strategy to minimize the cost of anti-violation is derived, by which the severity of violation risk events is obtained accordingly. Assessment of the risk cost is built... [more]

Building electricity load forecasting plays an important role in building energy management, peak demand and power grid security. In the past two decades, a large number of data-driven models have been applied to building and larger-scale energy consumption predictions. Although these models have been successful in specific cases, their performances would be greatly affected by the quantity and quality of the building data. Moreover, for older buildings with sparse data, or new buildings with no historical data, accurate predictions are difficult to achieve. Aiming at such a data silos problem caused by the insufficient data collection in the building energy consumption prediction, this study proposes a building electricity load forecasting method based on a similarity judgement and an improved TrAdaBoost algorithm (iTrAdaBoost). The Maximum Mean Discrepancy (MMD) is used to search similar building samples related to the target building from public datasets. Different from general Boos... [more]

This paper presents a power distribution system that prioritizes the reliability of power to critical loads within a community. The proposed system utilizes reinforcement learning methods (Q-learning) to train multi-port power electronic interface (MPEI) systems within a community of microgrids. The primary contributions of this article are to present a system where Q-learning is successfully integrated with MPEI to reduce the impact of power contingencies on critical loads and to explore the effectiveness of the subsequent system. The feasibility of the proposed method has been proven through simulation and experiments. It has been demonstrated that the proposed method can effectively improve the reliability of the local power system—for a case study where 20% of the total loads are classified as critical loads, the system average interruption duration index (SAIDI) has been improved by 75% compared to traditional microgrids with no load schedule.

Bifacial technology is attracting the attention of the photovoltaic community. Although considered premature, research and development activities still need to be carried out to improve bPV performance. In addition, the need for a standard test reference will aid bankability and increase confidence in this technology. This article describes the state of the art of bifacial technology, going through the bPV cell and its difference compared to conventional monofacial cells and listing the different sources of limitations, with an identification of different parameters that characterize the performance of the bifacial. Then, the paper reviews the different modeling methods that allow predicting the performance of bPV systems, and ends with the most important applications, whether for dual use of land to produce energy and food (agrivoltaic) or for placing bPV modules on water bodies instead of on the ground (aquavoltaics), or for vertical use as solar fences, acoustic barriers, or buildin... [more]

Power generation forecasts for wind farms, especially with a short-term horizon, have been extensively researched due to the growing share of wind farms in total power generation. Detailed forecasts are necessary for the optimization of power systems of various sizes. This review and analytical paper is largely focused on a statistical analysis of forecasting errors based on more than one hundred papers on wind generation forecasts. Factors affecting the magnitude of forecasting errors are presented and discussed. Normalized root mean squared error (nRMSE) and normalized mean absolute error (nMAE) have been selected as the main error metrics considered here. A new and unique error dispersion factor (EDF) is proposed, being the ratio of nRMSE to nMAE. The variability of EDF depending on selected factors (size of wind farm, forecasting horizons, and class of forecasting method) has been examined. This is unique and original research, a novelty in studies on errors of power generation for... [more]

Battery degradation is a main concern for electric vehicle (EV) users, and a reliable capacity estimation is of major importance. Every EV battery management system (BMS) provides a variety of information, including measured current and voltage, and estimated capacity of the battery. However, these estimations are not transparent and are manufacturer-specific, although measurement accuracy is unknown. This article uses extensive measurements from six diverse EVs to compare and assess capacity estimation with three different methods: (1) reading capacity estimation from the BMS through the central area network (CAN)-bus, (2) using an empirical capacity estimation (ECE) method with external current measurements, and (3) using the same method with measurements coming from the BMS. We show that the use of BMS current measurements provides consistent capacity estimation (a difference of approximately 1%) and can circumvent the need for costly experimental equipment and DC chargers. This dat... [more]

With the rapid expansion of new energy in China, the large-scale grid connection of new energy is increasing, and the operating safety of the new energy power system is being put to the test. The static security and stability region (SSSR) with hyper-plane expression is an effective instrument for situational awareness and the stability-constrained operation of power systems. This paper proposes a hybrid improved particle swarm optimization (IPSO) and recursive least square (RLS) approach for rapidly approximating the SSSR boundary. Initially, the operating point data in the high-dimensional nodal injection space is examined using the IPSO algorithm to find the key generators, equivalent search space, and crucial points, which have a relatively large impact on static stability. The RLS method is ultimately utilized to fit the SSSR border that best suits the crucial spots. Consequently, the adopted algorithm technique was used to rapidly approximate the SSSR border in power injection sp... [more]

State of charge (SOC) is one of the most important parameters in battery management systems, and the accurate and stable estimation of battery SOC for real-world electric vehicles remains a great challenge. This paper proposes a long short-term memory network based on grid search and cross-validation optimisation to estimate the SOC of real-world battery systems. The real-world electric vehicle data are divided into parking charging, travel charging, and finish charging cases. Meanwhile, the parameters associated with the SOC estimation under each operating condition are extracted by the Pearson correlation analysis. Moreover, the hyperparameters of the long short-term memory network are optimised by grid search and cross-validation to improve the accuracy of the model estimation. Moreover, the gaussian noise algorithm is used for data augmentation to improve the accuracy and robustness of SOC estimation under the working conditions of the small dataset. The results indicate that the a... [more]

Biomass is one of the most important sources of renewable energy in the energy industry. It is assumed that by 2050 the global energy deposit could be covered in 33−50% of biomass combustion. As with conventional fuels, the combustion of biomass produces combustion by-products, such as fly ash. Therefore, along with the growing interest in the use of biomass as a source of energy, the production of ash as a combustion by-product increases every year. It is estimated that approximately 476 million tons of ashes per year can be produced from biomass combustion. For example, the calorific value of dry wood mass tends to be between 18.5 MJ × kg−1 and 19.5 MJ × kg−1, while the ash content resulting from thermal treatment of wood is from 0.4 to 3.9% of dry fuel mass. However, biomass ash is a waste that is particularly difficult to characterize due to the large variability of the chemical composition depending on the biomass and combustion technology. In addition, this waste is, on the one h... [more]

Methane hydrate applications in gas storage and desalination have attracted increasing attention in recent years. In the present work, the effect of isopentane (IP), sodium dodecyl sulfate (SDS), and IP/SDS blends as promoters on methane hydrate formation kinetics, in terms of the pressure−temperature (P-T) profile, gas uptake, hydrate induction time (HIT), and water-to-hydrate conversion ratio (WHCR), were studied for distilled water and seawater samples with an IP/water sample ratio of 3:10 (by volume) and an SDS/water sample ratio of 1:1000 (by mass). Each solution was tested in a stirred tank at 600 rpm at a temperature and pressure of 2 °C and 5.2−5.3 MPa. In the case of methane hydrate formation in distilled water, the highest WHCR attained was 9.97% without additives, and 45.71% and 72.28% for SDS and isopentane additives, respectively. However, when using seawater at a salinity of 3.9%, the highest WHCR attained was 2.26% without additives and 9.89% and 18.03% for SDS and IP pr... [more]

Blockchain technology is currently evolving rapidly, and smart contracts are the hallmark of the second generation of blockchains. Currently, smart contracts are gradually being used in power system networks to build a decentralized energy system. Security is very important to power systems and attacks launched against smart contract vulnerabilities occur frequently, seriously affecting the development of the smart contract ecosystem. Current smart contract vulnerability detection tools suffer from low correct rates and high false positive rates, which cannot meet current needs. Therefore, we propose a smart contract vulnerability detection system based on the Siamese network in this paper. We improved the original Siamese network model to perform smart contract vulnerability detection by comparing the similarity of two sub networks with the same structure and shared parameters. We also demonstrate, through extensive experiments, that the model has better vulnerability detection perfor... [more]

The Paris Agreement requires a drastic reduction of global carbon emissions towards the net zero transition by mid-century, based on the large-scale transformation of the global energy system and major emitting sectors. Aviation and shipping emissions are not on a trajectory consistent with Paris goals, driven by rapid activity growth and the lack of commercial mitigation options, given the challenges for electrification of these sectors. Large-scale models used for mitigation analysis commonly do not capture the specificities and emission reduction options of international shipping and aviation, while bottom-up sectoral models do not represent their interlinkages with the entire system. Here, I use the global energy system model PROMETHEUS, enhanced with a detailed representation of the shipping and aviation sector, to explore transformation pathways for these sectors and their emission, activity, and energy mix impacts. The most promising alternative towards decarbonizing these secto... [more]

The bidirectional dc-dc converter is a critical component for extending the use of renewable energy and improving the efficiency of high-power electronic systems. This paper presents the analysis of the stray inductance of a commutation loop and the commutation behavior of IGBT devices in a flying capacitor three-level bidirectional DC-DC converter (FC-3L-BDC) phase-leg power electronic building block (PEBB). An FC-3L-BDC phase-leg PEBB was designed as an example, which can be used to build 400 kW to MW-grade light rail train chargers, battery energy storage interface converters, or metro regenerative braking energy recovery converters with a single PEBB or several PEBBs interleaved parallel. In order to optimize the stray inductance of commutation paths and realize snubberless operation, a five-layer laminated bus bar was carefully designed, and the stray inductance of the bus bar was extracted by three-dimensional finite element analysis simulation. To obtain higher accuracy, the str... [more]

The dynamic performance of the DC bus significantly influences the impedance characteristics of MMC and the system stability in a high-voltage direct current system. However, most of the existing MMC-HVDC system stability research simplifies the DC side as an ideal voltage source and ignores the impacts of voltage feedforward control, which affects the accuracy and practicability of stability analysis. In this paper, a sequence impedance model considering both DC voltage control and voltage feedforward control is developed, and the necessity of considering DC control and voltage feedforward control for MMC-HVDC stability analysis is illustrated. Then, the impact of control parameters on MMC-HVDC impedance is discussed, and the boundary conditions of control parameters are also derived. Finally, a method of control parameters design and impedance optimization for MMC-HVDC based on the stability boundary is proposed. Compared to the traditional optimization method, the system stability i... [more]

Nuclear power plants have a complex structure and changeable operation mode, which induces low setting calculation efficiency. After analyzing the technology, architecture, and functional logic of a variety of relay protection setting calculation systems and combining the characteristics of the setting calculation of nuclear power plants, the relay protection setting calculation system in nuclear power plants based on B/S architecture and cloud computing is studied in this paper. The system adopts three-tier B/S architecture, applies two key technologies, the cloud computing task distribution synchronization mechanism and the cloud component automatic assembly mechanism, and introduces a particle swarm optimization algorithm to provide technical support for nuclear power plant setting calculation; the running example of the nuclear power plant system fully proves the efficiency and reliability of the relay protection setting calculation system of the nuclear power plant, which has high... [more]

The key goal of this research was to figure out the short and long run relationship between environmental degradation caused by carbon dioxide (CO2) emissions and energy consumption, the level of GDP economic growth, and urbanization in the Visegrad Region countries (V4). The study used data from the years 1996−2020. In the methodological area, ARDL bound test, and ARDL and ECM models were used to determine the directions and strength of interdependence. The results show that in the case of some V4 countries (Poland, Slovakia, and Hungary), changes in the urbanization rate affect CO2 emissions. Moreover, it was confirmed that the phenomenon of urbanization influences the enhanced energy consumption in the studied countries. In the case of individual countries, these relationships were varied, both unidirectional and bidirectional. Their nature was also varied—there were both long and short-term relationships. These findings suggest that the V4 countries should increase renewable and ec... [more]

Transient electromagnetic (TEM) surveys constitute an important element in exploration projects and can be successfully used in the search for oil and gas. Different modifications of the method include shallow (sTEM), 2D, 3D, and 4D (time-lapse) soundings. TEM data allow for solving a large scope of problems for estimating resources and reserves of hydrocarbons, discriminating reservoir rocks, detecting tectonic features, and characterizing drilling conditions. TEM surveys are applicable at all stages, from initial prospecting to production, and are especially efficient when combined with seismic surveys. Each stage has its specific objectives: estimation of net pay thickness, porosity, and fluid type during prospecting, optimization of well placement and prediction of drilling conditions in exploration, and monitoring of flooding during production. Electromagnetic soundings resolve permafrost features well and thus have a high potentiality for exploration in the Arctic petroleum provi... [more]

Energy deposition for flow and flight control has received significant interest in the past several decades due to its potential application to high-speed flow and flight control. This paper reviews recent progress and recommends future research.

In this paper, the transient state analysis of a Line-Start Permanent Magnet Synchronous Motor (LSPMSM) and the optimum design for high efficiency were studied. In the case of an LSPMSM, aluminum bars and permanent magnets are inserted in the rotor. Since it has aluminum bars, it can be directly started on-line without closed-loop control at the time of starting, like an induction motor. Furthermore, once driven, it rotates at a synchronous speed due to the permanent magnets in the steady state. Theoretically, since the rotor bars have no induced current, copper loss does not occur in the rotor bars. Further, because of the inserted permanent magnets, an LSPMSM has a higher power density than an induction motor with the same output power. However, since it is driven directly on-line, the transient state is longer than that of a synchronous motor driven by an inverter. Therefore, it is important to analyze the characteristics of the transient state depending on the rotor shape in the LS... [more]

An important feature of this research is the investigation of the de-alloyed catalysts based on the nanoparticles with a simple structure (alloy) and a complex structure (gradient). The resulting samples exhibit the 2−4 times higher mass activity in the ORR compared with the commercial Pt/C. The novelty of this study is due to the application of the express-electrochemical experiment to register the trend of changes in the ORR activity caused by rearranging the structure of bimetallic nanoparticles. The state-of-the-art protocol makes it possible to establish the dependence of properties of the de-alloyed catalysts on the nanoparticles’ structure obtained at the stage of the material’s synthesis. The study shows the possibility of determining the rate of the ongoing reorganization of bimetallic nanoparticles with different architectures. The PtCu/C electrocatalysts for proton-exchange membrane fuel cells presented in this work are commercially promising in terms of both the high functi... [more]