Traction power systems for electrified railways:evolution,state of the art,and future trends

Traction power systems(TPSs)play a vital role in the operation of electrified railways.The transformation of conventional railway TPSs to novel structures is not only a trend to promote the development of electrified railways toward high-efficiency and resilience but also an inevitable requirement to achieve carbon neutrality target.On the basis of sorting out the power supply structures of conventional AC and DC modes,this paper first reviews the characteristics of the existing TPSs,such as weak power supply flexibility and low-energy efficiency.Furthermore,the power supply structures of various TPSs for future electrified railways are described in detail,which satisfy longer distance,low-carbon,high-efficiency,high-reliability and high-quality power supply requirements.Meanwhile,the application prospects of different traction modes are discussed from both technical and economic aspects.Eventually,this paper introduces the research progress of mixed-system electrified railways and traction power supply technologies without catenary system,speculates on the future development trends and challenges of TPSs and predicts that TPSs will be based on the continuous power supply mode,employing power electronic equipment and intelligent information technology to construct a railway comprehensive energy system with renewable energy.

A Tutorial Review of the Solar Power Curve: Regressions, Model Chains, and Their Hybridization and Probabilistic Extensions

Owing to the persisting hype in pushing toward global carbon neutrality,the study scope of atmospheric science is rapidly expanding.Among numerous trending topics,energy meteorology has been attracting the most attention hitherto.One essential skill of solar energy meteorologists is solar power curve modeling,which seeks to map irradiance and auxiliary weather variables to solar power,by statistical and/or physical means.In this regard,this tutorial review aims to deliver a complete overview of those fundamental scientific and engineering principles pertaining to the solar power curve.Solar power curves can be modeled in two primary ways,one of regression and the other of model chain.Both classes of modeling approaches,alongside their hybridization and probabilistic extensions,which allow accuracy improvement and uncertainty quantification,are scrutinized and contrasted thoroughly in this review.

Weather-Driven Solar Power Forecasting Using D-Informer:Enhancing Predictions with Climate Variables

Precise forecasting of solar power is crucial for the development of sustainable energy systems.Contemporary forecasting approaches often fail to adequately consider the crucial role of weather factors in photovoltaic(PV)power generation and encounter issues such as gradient explosion or disappearance when dealing with extensive time-series data.To overcome these challenges,this research presents a cutting-edge,multi-stage forecasting method called D-Informer.This method skillfully merges the differential transformation algorithm with the Informer model,leveraging a detailed array of meteorological variables and historical PV power generation records.The D-Informer model exhibits remarkable superiority over competing models across multiple performance metrics,achieving on average a 67.64%reduction in mean squared error(MSE),a 49.58%decrease in mean absolute error(MAE),and a 43.43%reduction in root mean square error(RMSE).Moreover,it attained an R2 value as high as 0.9917 during the winter season,highlighting its precision and dependability.This significant advancement can be primarily attributed to the incorporation of a multi-head self-attention mechanism,which greatly enhances the model’s ability to identify complex interactions among diverse input variables,and the inclusion of weather variables,enriching the model’s input data and strengthening its predictive accuracy in time series analysis.Additionally,the experimental results confirm the effectiveness of the proposed approach.

The Correlation between the Power Quality Indicators and Entropy Production Characteristics of Wind Power+Energy Storage Systems

Power quality improvements help guide and solve the problems of inefficient energy production and unstable power output in wind power systems.The purpose of this paper is mainly to explore the influence of different energy storage batteries on various power quality indicators by adding different energy storage devices to the simulated wind power system,and to explore the correlation between systementropy generation and various indicators,so as to provide a theoretical basis for directly improving power quality by reducing loss.A steady-state experiment was performed by replacing the wind wheel with an electric motor,and the output power qualities of the wind power systemwith andwithout energy storagewere compared and analyzed.Moreover,the improvement effect of different energy storage devices on various indicatorswas obtained.Then,based on the entropy theory,the loss of the internal components of the wind power system generator is simulated and explored by Ansys software.Through the analysis of power quality evaluation indicators,such as current harmonic distortion rate,frequency deviation rate,and voltage fluctuation,the correlation between entropy production and each evaluation indicator was explored to investigate effective methods to improve power quality by reducing entropy production.The results showed that the current harmonic distortion rate,voltage fluctuation,voltage deviation,and system entropy production are positively correlated in the tests and that the power factor is negatively correlated with system entropy production.In the frequency range,the frequency deviationwas not significantly correlated with the systementropy production.

Rolling Decision Model of Thermal Power Retrofit and Generation Expansion Planning Considering Carbon Emissions and Power Balance Risk

With the increasing urgency of the carbon emission reduction task,the generation expansion planning process needs to add carbon emission risk constraints,in addition to considering the level of power adequacy.However,methods for quantifying and assessing carbon emissions and operational risks are lacking.It results in excessive carbon emissions and frequent load-shedding on some days,although meeting annual carbon emission reduction targets.First,in response to the above problems,carbon emission and power balance risk assessment indicators and assessment methods,were proposed to quantify electricity abundance and carbon emission risk level of power planning scenarios,considering power supply regulation and renewable energy fluctuation characteristics.Secondly,building on traditional two-tier models for low-carbon power planning,including investment decisions and operational simulations,considering carbon emissions and power balance risks in lower-tier operational simulations,a two-tier rolling model for thermal power retrofit and generation expansion planning was established.The model includes an investment tier and operation assessment tier and makes year-by-year decisions on the number of thermal power units to be retrofitted and the type and capacity of units to be commissioned.Finally,the rationality and validity of the model were verified through an example analysis,a small-scale power supply system in a certain region is taken as an example.The model can significantly reduce the number of days of carbon emissions risk and ensure that the power balance risk is within the safe limit.

Research on the MPPT of Photovoltaic Power Generation Based on Improved WOA and P&O under Partial Shading Conditions

Partial shading conditions(PSCs)caused by uneven illumination become one of the most common problems in photovoltaic(PV)systems,which can make the PV power-voltage(P-V)characteristics curve show multi-peaks.Traditional maximum power point tracking(MPPT)methods have shortcomings in tracking to the global maximum power point(GMPP),resulting in a dramatic decrease in output power.In order to solve the above problems,intelligent algorithms are used in MPPT.However,the existing intelligent algorithms have some disadvantages,such as slow convergence speed and large search oscillation.Therefore,an improved whale algorithm(IWOA)combined with the P&O(IWOA-P&O)is proposed for the MPPT of PV power generation in this paper.Firstly,IWOA is used to track the range interval of the GMPP,and then P&O is used to accurately find the MPP in that interval.Compared with other algorithms,simulation results show that this method has an average tracking efficiency of 99.79%and an average tracking time of 0.16 s when tracking GMPP.Finally,experimental verification is conducted,and the results show that the proposed algorithm has better MPPT performance compared to popular particle swarm optimization(PSO)and PSO-P&O algorithms.

Increasing the Efficiency and Level of Environmental Safety of Pro-Environmental City Heat Supply Technologies by Low Power Nuclear Plants

In connection with the current prospect of decarbonization of coal energy through the use of small nuclear power plants (SNPPs) at existing TPPs as heat sources for heat supply to municipal heating networks, there is a technological need to improve heat supply schemes to increase their environmental friendliness and efficiency. The paper proves the feasibility of using the heat-feeding mode of ASHPs for urban heat supply by heating the network water with steam taken from the turbine. The ratio of electric and thermal power of a “nuclear” combined heat and power plant is given. The advantage of using a heat pump, which provides twice as much electrical power with the same heat output, is established. Taking into account that heat in these modes is supplied with different potential, the energy efficiency was used to compare these options. To increase the heat supply capacity, a scheme with the use of a high-pressure heater in the backpressure mode and with the heating of network water with hot steam was proposed. Heat supply from ASHPs is efficient and environmentally friendly even in the case of significant remoteness of heat consumers.

Source-Load Coordinated Optimal Scheduling Considering the High Energy Load of Electrofused Magnesium and Wind Power Uncertainty

In fossil energy pollution is serious and the“double carbon”goal is being promoted,as a symbol of fresh energy in the electrical system,solar and wind power have an increasing installed capacity,only conventional units obviously can not solve the new energy as the main body of the scheduling problem.To enhance the systemscheduling ability,based on the participation of thermal power units,incorporate the high energy-carrying load of electro-melting magnesiuminto the regulation object,and consider the effects on the wind unpredictability of the power.Firstly,the operating characteristics of high energy load and wind power are analyzed,and the principle of the participation of electrofusedmagnesiumhigh energy-carrying loads in the elimination of obstructedwind power is studied.Second,a two-layer optimization model is suggested,with the objective function being the largest amount of wind power consumed and the lowest possible cost of system operation.In the upper model,the high energy-carrying load regulates the blocked wind power,and in the lower model,the second-order cone approximation algorithm is used to solve the optimizationmodelwithwind power uncertainty,so that a two-layer optimizationmodel that takes into account the regulation of the high energy-carrying load of the electrofused magnesium and the uncertainty of the wind power is established.Finally,the model is solved using Gurobi,and the results of the simulation demonstrate that the suggested model may successfully lower wind abandonment,lower system operation costs,increase the accuracy of day-ahead scheduling,and lower the final product error of the thermal electricity unit.

Transient AC Overvoltage Suppression Orientated Reactive Power Control of the Wind Turbine in the LCC-HVDC Sending Grid

High-voltage direct current(HVDC) transmission is a crucial way to solve the reverse distribution of clean energy and loads. The line commutated converter-based HVDC(LCCHVDC) has become a vital structure for HVDC due to its high technological maturity and economic advantages. During the DC fault of LCC-HVDC, such as commutation failure, the reactive power regulation of the AC grid always lags the DC control process, causing overvoltage in the AC sending grid, which brings off-grid risk to the wind power generation based on power electronic devices. Nevertheless, considering that wind turbine generators have fast and flexible reactive power control capability, optimizing the reactive power control of wind turbines to participate in the transient overvoltage suppression of the sending grid not only improves the operational safety at the equipment level but also enhances the voltage stability of the system. This paper firstly analyses the impact of wind turbine's reactive power on AC transient overvoltage. Then, it proposes an improved voltage-reactive power control strategy, which contains a reactive power control delay compensation and a power command optimization based on the voltage time series prediction. The delay compensation is used to reduce the contribution of the untimely reactive power of wind turbines on transient overvoltage, and the power command optimization enables wind turbines to have the ability to regulate transient overvoltage, leading to the variation of AC voltage, thus suppressing the transient overvoltage. Finally, the effectiveness and feasibility of the proposed method are verified in a ±800kV/5000MW LCC-HVDC sending grid model based on MATLAB/Simulink.

Review of Thermal Design of SiC Power Module for Motor Drive in Electrical Vehicle Application

In the current vehicle electric propulsion systems,the thermal design of power modules heavily relies on empirical knowledge,making it challenging to effectively optimize irregularly arranged Pinfin structures,thereby limiting their performance.This paper aims to review the underlying mechanisms of how irregularly arranged Pinfins influence the thermal characteristics of power modules and introduce collaborative thermal design with DC bus capacitor and motor.Literature considers chip size,placement,coolant flow direction with the goal of reducing thermal resistance of power modules,minimizing chip junction temperature differentials,and optimizing Pinfin layouts.In the first step,algorithms should efficiently generating numerous unique irregular Pinfin layouts to enhance optimization quality.The second step is to efficiently evaluate Pinfin layouts.Simulation accuracy and speed should be ensured to improve computational efficiency.Finally,to improve overall heat dissipation effectiveness,papers establish models for capacitors,motors,to aid collaborative Pinfin optimization.These research outcomes will provide essential support for future developments in high power density motor drive for vehicles.

Reinforcement Learning-Based Energy Management for Hybrid Power Systems:State-of-the-Art Survey,Review,and Perspectives

The new energy vehicle plays a crucial role in green transportation,and the energy management strategy of hybrid power systems is essential for ensuring energy-efficient driving.This paper presents a state-of-the-art survey and review of reinforcement learning-based energy management strategies for hybrid power systems.Additionally,it envisions the outlook for autonomous intelligent hybrid electric vehicles,with reinforcement learning as the foundational technology.First of all,to provide a macro view of historical development,the brief history of deep learning,reinforcement learning,and deep reinforcement learning is presented in the form of a timeline.Then,the comprehensive survey and review are conducted by collecting papers from mainstream academic databases.Enumerating most of the contributions based on three main directions—algorithm innovation,powertrain innovation,and environment innovation—provides an objective review of the research status.Finally,to advance the application of reinforcement learning in autonomous intelligent hybrid electric vehicles,future research plans positioned as“Alpha HEV”are envisioned,integrating Autopilot and energy-saving control.

Review of the Analysis and Suppression for High-frequency Oscillations of the Grid-connected Wind Power Generation System

High-frequency oscillation(HFO)of gridconnected wind power generation systems(WPGS)is one of the most critical issues in recent years that threaten the safe access of WPGS to the grid.Ensuring the WPGS can damp HFO is becoming more and more vital for the development of wind power.The HFO phenomenon of wind turbines under different scenarios usually has different mechanisms.Hence,engineers need to acquire the working mechanisms of the different HFO damping technologies and select the appropriate one to ensure the effective implementation of oscillation damping in practical engineering.This paper introduces the general assumptions of WPGS when analyzing HFO,systematically summarizes the reasons for the occurrence of HFO in different scenarios,deeply analyses the key points and difficulties of HFO damping under different scenarios,and then compares the technical performances of various types of HFO suppression methods to provide adequate references for engineers in the application of technology.Finally,this paper discusses possible future research difficulties in the problem of HFO,as well as the possible future trends in the demand for HFO damping.

International Competition and Cooperation of Artificial Intelligence from the Perspective of State-to-State Power Relations

2023 marks a key juncture for artificial intelligence(AI)to be deeply embedded in international relations.From a technical point of view,the rapid development of generative AI not only provides new carriers and capabilities for countries’foreign exchanges,but also brings new risks and challenges to national security.In terms of topics,AI has created a series of new agendas for international relations,such as security,ethics and development,which need to be accelerated under the framework of global governance.

Optimizing the power conversion processes in diluted donor/acceptor heterojunctions towards 19.4%efficiency all-polymer solar cells

All polymer solar cells(all-PSCs)promise mechanically-flexible and morphologically-stable organic photovoltaics and have aroused increased interests very recently.However,due to their disorderly conformation structures within the photoactive film,inefficient charge generation and carrier transport are observed which lead to inferior photovoltaic performance compared to smaller molecular acceptor-based photovoltaics.Here,by diluting PM6 with a cutting-edge polymeric acceptor PY-IT and diluting PY-IT with PM6 or D18,donor-dominating or acceptor-dominating heterojunctions were prepared.Synchrotron X-ray and multiple spectrometer techniques reveal that the diluted heterojunctions receive increased structural order,translating to enhanced carrier mobility,improved exciton diffusion length,and suppressed non-radiative recombination loss during the power conversion.As the results,the corresponding PM6+1%PY-IT/PY-IT+1%D18 and PM6+1%PY-IT/PY-IT+1%PM6 devices fabricated by layer-by-layer deposition received superior power conversion efficiency(PCE)of 19.4%and 18.8%respectively,along with enhanced operational lifetimes in air,outperforming the PCE of 17.5%in the PM6/PY-IT reference device.

Choice of the Best Production Prediction Model for the Zagtouli Solar Power Plant in Burkina-Faso

In this paper, we present a study on the prediction of the power produced by the 33 MWp photovoltaic power plant at Zagtouli in Burkina-Faso, as a function of climatic factors. We identified models in the literature, namely the Benchmark, input/output, Marion, Cristo-fri, Kroposki, Jones-Underwood and Hatziargyriou prediction models, which depend exclusively on environmental parameters. We then compared our linear model with these seven mathematical models in order to determine the most optimal prediction model. Our results show that the Hatziargyriou model is better in terms of accuracy for power prediction.

A Review on Technologies for the Use of CO2 as a Working Fluid in Refrigeration and Power Cycles

The use of carbon dioxide as a working fluid has been the subject of extensive studies in recent years, particularly in the field of refrigeration where it is at the heart of research to replace CFC and HCFC. Its thermodynamic properties make it a fluid of choice in the efficient use of energy at low and medium temperatures in engine cycles. However, the performance of transcritical CO2 cycles weakens under high temperature and pressure conditions, especially in refrigeration systems;On the other hand, this disadvantage becomes rather interesting in engine cycles where CO2 can be used as an alternative to the organic working fluid in small and medium-sized electrical systems for low quality or waste heat sources. In order to improve the performance of systems operating with CO2 in the field of refrigeration and electricity production, research has made it possible to develop several concepts, of which this article deals with a review of the state of the art, followed by analyzes in-depth and critical of the various developments to the most recent modifications in these fields. Detailed discussions on the performance and technical characteristics of the different evolutions are also highlighted as well as the factors affecting the overall performance of the systems studied. Finally, perspectives on the future development of the use of CO2 in these different cycles are presented.

IoT-Enabled Plant Monitoring System with Power Optimization and Secure Authentication

Global food security is a pressing issue that affects the stability and well-being of communities worldwide.While existing Internet of Things(IoT)enabled plant monitoring systems have made significant strides in agricultural monitoring,they often face limitations such as high power consumption,restricted mobility,complex deployment requirements,and inadequate security measures for data access.This paper introduces an enhanced IoT application for agricultural monitoring systems that address these critical shortcomings.Our system strategically combines power efficiency,portability,and secure access capabilities,assisting farmers in monitoring and tracking crop environmental conditions.The proposed system includes a remote camera that captures images of surrounding plants and a sensor module that regularly monitors various environmental factors,including temperature,humidity,and soil moisture.We implement power management strategies to minimize energy consumption compared to existing solutions.Unlike conventional systems,our implementation utilizes the Amazon Web Services(AWS)cloud platform for reliable data storage and processing while incorporating comprehensive security measures,including Two-Factor Authentication(2FA)and JSON Web Tokens(JWT),features often overlooked in current agricultural IoT solutions.Users can access this secure monitoring system via a developed Android application,providing convenient mobile access to the gathered plant data.We validate our system’s advantages by implementing it with two potted garlic plants on Okayama University’s rooftop.Our evaluation demonstrates high sensor reliabil-ity,with strong correlations between sensor readings and reference data,achieving determination coefficients(R2)of 0.979 for temperature and 0.750 for humidity measurements.The implemented power management strategies extend battery life to 10 days on a single charge,significantly outperforming existing systems that typically require daily recharging.Furthermore,our dual-layer security implementation utilizing 2FA and JWT successfully protects sensitive agricultural data from unauthorized access.

Conceptual Strategy for Mitigating the Risk of Hydrogen as an Internal Hazard in Case of Severe Accidents at Nuclear Power Plant Considering Existing Risks and Uncertainties Associated with the Use of Traditional Strategies

Hydrogen challenge mitigation stands as one of the main objectives in the management of severe accidents at Nuclear Power Plants (NPPs). Key strategies for hydrogen control include atmospheric inertization and hydrogen removal with Passive Autocatalytic Recombiners (PARs) being a commonly accepted approach. However, an examination of PAR operation specificity reveals potential inefficiencies and reliability issues in certain severe accident scenarios. Moreover, during the in-vessel stage of severe accident development, in some severe accident scenarios PARs can unexpectedly become a source of hydrogen detonation. The effectiveness of hydrogen removal systems depends on various factors, including the chosen strategies, severe accident scenarios, reactor building design, and other influencing factors. Consequently, a comprehensive hydrogen mitigation strategy must effectively incorporate a combination of strategies rather than be based on one strategy, taking into consideration the probabilistic risks and uncertainties associated with the implementation of PARs or other traditional methods. In response to these considerations, within the framework of this research it has been suggested a conceptual strategy to mitigate the hydrogen challenge during the in-vessel stage of severe accident development.

Research on uninterruptable power supply technology for auxiliary winding of electric locomotive while passing the neutral section

Purpose–Auxiliary power system is an indispensable part of the train;the auxiliary systems of both electric locomotives and EMUs mainly are powered by one of the two ways,which are either from auxiliary windings of traction transformers or from DC-link voltage of traction converters.Powered by DC-link voltage of traction converters,the auxiliary systems were maintained of uninterruptable power supply with energy from electric braking.Meanwhile,powered by traction transformers,the auxiliary systems were always out of power while passing the neutral section of power supply grid and control system is powered by battery at this time.Design/methodology/approach–Uninterrupted power supply of auxiliary power system powered by auxiliary winding of traction transformer was studied.Failure reasons why previous solutions cannot be realized are analyzed.An uninterruptable power supply scheme for the auxiliary systems powered by auxiliary windings of traction transformers is proposed in this paper.The validity of the proposed scheme is verified by simulation and experimental results and on-site operation of an upgraded HXD3C type locomotive.This scheme is attractive for upgrading practical locomotives with the auxiliary systems powered by auxiliary windings of traction transformers.Findings–This scheme regenerates braking power supplied to auxiliary windings of traction transformers while a locomotive runs in the neutral section of the power supply grid.Control objectives of uninterrupted power supply technology are proposed,which are no overvoltage,no overcurrent and uninterrupted power supply.Originality/value–The control strategies of the scheme ensure both overvoltage free and inrush current free when a locomotive enters or leaves the neutral section.Furthermore,this scheme is cost low by employing updated control strategy of software and add both the two current sensors and two connection wires of hardware.

Estimating the Input Power of a Power Plant Using the Efficiency of the Inverter

The study focuses on estimating the input power of a power plant from available data, using the theoretical inverter efficiency as the key parameter. The paper addresses the problem of missing data in power generation systems and proposes an approach based on the efficiency formula widely documented in the literature. In the absence of input data, this method makes it possible to estimate the plant’s input power using data extracted from the site, in particular that provided by the Ministry of the Environment. The importance of this study lies in the need to accurately determine the input power in order to assess the overall performance of the energy system.