With the rapid development of cloud computing,edge computing,and smart devices,computing power resources indicate a trend of ubiquitous deployment.The traditional network architecture cannot efficiently leverage these...With the rapid development of cloud computing,edge computing,and smart devices,computing power resources indicate a trend of ubiquitous deployment.The traditional network architecture cannot efficiently leverage these distributed computing power resources due to computing power island effect.To overcome these problems and improve network efficiency,a new network computing paradigm is proposed,i.e.,Computing Power Network(CPN).Computing power network can connect ubiquitous and heterogenous computing power resources through networking to realize computing power scheduling flexibly.In this survey,we make an exhaustive review on the state-of-the-art research efforts on computing power network.We first give an overview of computing power network,including definition,architecture,and advantages.Next,a comprehensive elaboration of issues on computing power modeling,information awareness and announcement,resource allocation,network forwarding,computing power transaction platform and resource orchestration platform is presented.The computing power network testbed is built and evaluated.The applications and use cases in computing power network are discussed.Then,the key enabling technologies for computing power network are introduced.Finally,open challenges and future research directions are presented as well.展开更多
There is a growing need to explore the potential of coal-fired power plants(CFPPs)to enhance the utilization rate of wind power(wind)and photovoltaic power(PV)in the green energy field.This study developed a load regu...There is a growing need to explore the potential of coal-fired power plants(CFPPs)to enhance the utilization rate of wind power(wind)and photovoltaic power(PV)in the green energy field.This study developed a load regulation model for a multi-power generation system comprising wind,PV,and coal energy storage using realworld data.The power supply process was divided into eight fundamental load regulation scenarios,elucidating the influence of each scenario on load regulation.Within the framework of the multi-power generation system with the wind(50 MW)and PV(50 MW)alongside a CFPP(330 MW),a lithium-iron phosphate energy storage system(LIPBESS)was integrated to improve the system’s load regulation flexibility.The energy storage operation strategy was formulated based on the charging and discharging priority of the LIPBESS for each basic scenario and the charging and discharging load calculation method of LIPBESS auxiliary regulation.Through optimization using the particle swarm algorithm,the optimal capacity of LIPBESS was determined to be within the 5.24-4.88 MWh range.From an economic perspective,the LIPBESS operating with CFPP as the regulating power source was 49.1% lower in capacity compared to the renewable energy-based storage mode.展开更多
Against the backdrop of global energy shortages and increasingly severe environmental pollution,renewable energy is gradually becoming a significant direction for future energy development.Power electronics converters...Against the backdrop of global energy shortages and increasingly severe environmental pollution,renewable energy is gradually becoming a significant direction for future energy development.Power electronics converters,as the core technology for energy conversion and control,play a crucial role in enhancing the efficiency and stability of renewable energy systems.This paper explores the basic principles and functions of power electronics converters and their specific applications in photovoltaic power generation,wind power generation,and energy storage systems.Additionally,it analyzes the current innovations in high-efficiency energy conversion,multilevel conversion technology,and the application of new materials and devices.By studying these technologies,the aim is to promote the widespread application of power electronics converters in renewable energy systems and provide theoretical and technical support for achieving sustainable energy development.展开更多
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 ...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.展开更多
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 attent...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.展开更多
In this study,the present situation and characteristics of power supply in remote areas are summarized.By studying the cases of power supply projects in remote areas,the experience is analyzed and described,and the ap...In this study,the present situation and characteristics of power supply in remote areas are summarized.By studying the cases of power supply projects in remote areas,the experience is analyzed and described,and the applicability of related technologies,such as grid-forming storage and power load management,is studied,including grid-connection technologies,such as grid-forming converters and power load management.On this basis,three power-supply modes were proposed.The application scenarios and advantages of the three modes were compared and analyzed.Based on the local development situation,the temporal sequences of the three schemes are described,and a case study was conducted.The study of the heavy-load power supply mode in remote areas contributes to solving the problem of heavy-load green power consumption in remote areas and promoting the further development of renewable energy.展开更多
Converters rely on passive filtering as a crucial element due to the high-frequency operational characteristics of power electronics.Traditional filtering methods involve a dual inductor-capacitor(LC)cell or an induct...Converters rely on passive filtering as a crucial element due to the high-frequency operational characteristics of power electronics.Traditional filtering methods involve a dual inductor-capacitor(LC)cell or an inductor-capacitor-inductor(LCL)T-circuit.However,capacitors are susceptible to wear-out mechanisms and failure modes.Nevertheless,the necessity for monitoring and regular replacement adds to an elevated cost of ownership for such systems.The utilization of an active output power filter can be used to diminish the dimensions of the LC filter and the electrolytic dc-link capacitor,even though the inclusion of capacitors remains an indispensable part of the system.This paper introduces capacitorless solid-state power filter(SSPF)for single-phase dc-ac converters.The proposed configuration is capable of generating a sinusoidal ac voltage without relying on capacitors.The proposed filter,composed of a planar transformer and an H-bridge converter operating at high frequency,injects voltage harmonics to attain a sinusoidal output voltage.The design parameters of the planar transformer are incorporated,and the impact of magnetizing and leakage inductances on the operation of the SSPF is illustrated.Theoretical analysis,supported by simulation and experimental results,are provided for a design example for a single-phase system.The total harmonic distortion observed in the output voltage is well below the IEEE 519 standard.The system operation is experimentally tested under both steady-state and dynamic conditions.A comparison with existing technology is presented,demonstrating that the proposed topology reduces the passive components used for filtering.展开更多
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...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.展开更多
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 e...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.展开更多
To reduce carbon emissions,clean energy is being integrated into the power system.Wind power is connected to the grid in a distributed form,but its high variability poses a challenge to grid stability.This article com...To reduce carbon emissions,clean energy is being integrated into the power system.Wind power is connected to the grid in a distributed form,but its high variability poses a challenge to grid stability.This article combines wind turbine monitoring data with numerical weather prediction(NWP)data to create a suitable wind power prediction framework for distributed grids.First,high-precision NWP of the turbine range is achieved using weather research and forecasting models(WRF),and Kriging interpolation locates predicted meteorological data at the turbine site.Then,a preliminary predicted power series is obtained based on the fan’s wind speed-power conversion curve,and historical power is reconstructed using variational mode decomposition(VMD)filtering to form input variables in chronological order.Finally,input variables of a single turbine enter the temporal convolutional network(TCN)to complete initial feature extraction,and then integrate the outputs of all TCN layers using Long Short Term Memory Networks(LSTM)to obtain power prediction sequences for all turbine positions.The proposed method was tested on a wind farm connected to a distributed power grid,and the results showed it to be superior to existing typical methods.展开更多
With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable ener...With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.展开更多
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,...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.展开更多
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.Traditiona...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.展开更多
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 un...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.展开更多
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 ...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.展开更多
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, ...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.展开更多
基金supported by the National Science Foundation of China under Grant 62271062 and 62071063by the Zhijiang Laboratory Open Project Fund 2020LCOAB01。
文摘With the rapid development of cloud computing,edge computing,and smart devices,computing power resources indicate a trend of ubiquitous deployment.The traditional network architecture cannot efficiently leverage these distributed computing power resources due to computing power island effect.To overcome these problems and improve network efficiency,a new network computing paradigm is proposed,i.e.,Computing Power Network(CPN).Computing power network can connect ubiquitous and heterogenous computing power resources through networking to realize computing power scheduling flexibly.In this survey,we make an exhaustive review on the state-of-the-art research efforts on computing power network.We first give an overview of computing power network,including definition,architecture,and advantages.Next,a comprehensive elaboration of issues on computing power modeling,information awareness and announcement,resource allocation,network forwarding,computing power transaction platform and resource orchestration platform is presented.The computing power network testbed is built and evaluated.The applications and use cases in computing power network are discussed.Then,the key enabling technologies for computing power network are introduced.Finally,open challenges and future research directions are presented as well.
基金supported by the Natural Science Foundation of China(Grant Nos.52076079,52206010)Natural Science Foundation of Hebei Province,China(Grant No.E2020502013)the Fundamental Research Funds for the Central Universities(2021MS076,2021MS079).
文摘There is a growing need to explore the potential of coal-fired power plants(CFPPs)to enhance the utilization rate of wind power(wind)and photovoltaic power(PV)in the green energy field.This study developed a load regulation model for a multi-power generation system comprising wind,PV,and coal energy storage using realworld data.The power supply process was divided into eight fundamental load regulation scenarios,elucidating the influence of each scenario on load regulation.Within the framework of the multi-power generation system with the wind(50 MW)and PV(50 MW)alongside a CFPP(330 MW),a lithium-iron phosphate energy storage system(LIPBESS)was integrated to improve the system’s load regulation flexibility.The energy storage operation strategy was formulated based on the charging and discharging priority of the LIPBESS for each basic scenario and the charging and discharging load calculation method of LIPBESS auxiliary regulation.Through optimization using the particle swarm algorithm,the optimal capacity of LIPBESS was determined to be within the 5.24-4.88 MWh range.From an economic perspective,the LIPBESS operating with CFPP as the regulating power source was 49.1% lower in capacity compared to the renewable energy-based storage mode.
文摘Against the backdrop of global energy shortages and increasingly severe environmental pollution,renewable energy is gradually becoming a significant direction for future energy development.Power electronics converters,as the core technology for energy conversion and control,play a crucial role in enhancing the efficiency and stability of renewable energy systems.This paper explores the basic principles and functions of power electronics converters and their specific applications in photovoltaic power generation,wind power generation,and energy storage systems.Additionally,it analyzes the current innovations in high-efficiency energy conversion,multilevel conversion technology,and the application of new materials and devices.By studying these technologies,the aim is to promote the widespread application of power electronics converters in renewable energy systems and provide theoretical and technical support for achieving sustainable energy development.
基金supported in part by the Scientific Foundation for Outstanding Young Scientists of Sichuan under Grant No.2021JDJQ0032in part by the National Natural Science Foundation of China under Grant No.52107128in part by the Natural Science Foundation of Sichuan Province under Grant No.2022NSFSC0436.
文摘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.
基金supported by the National Natural Science Foundation of China(project no.42375192),and the China Meteorological Administration Climate Change Special Program(CMA-CCSPproject no.QBZ202315)+2 种基金supported by the National Natural Science Foundation of China(project no.42030608)supported by the National Research,Development and Innovation Fund,project no.OTKA-FK 142702by the Hungarian Academy of Sciences through the Sustainable Development and Technologies National Programme(FFT NP FTA)and the János Bolyai Research Scholarship.
文摘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.
文摘In this study,the present situation and characteristics of power supply in remote areas are summarized.By studying the cases of power supply projects in remote areas,the experience is analyzed and described,and the applicability of related technologies,such as grid-forming storage and power load management,is studied,including grid-connection technologies,such as grid-forming converters and power load management.On this basis,three power-supply modes were proposed.The application scenarios and advantages of the three modes were compared and analyzed.Based on the local development situation,the temporal sequences of the three schemes are described,and a case study was conducted.The study of the heavy-load power supply mode in remote areas contributes to solving the problem of heavy-load green power consumption in remote areas and promoting the further development of renewable energy.
文摘Converters rely on passive filtering as a crucial element due to the high-frequency operational characteristics of power electronics.Traditional filtering methods involve a dual inductor-capacitor(LC)cell or an inductor-capacitor-inductor(LCL)T-circuit.However,capacitors are susceptible to wear-out mechanisms and failure modes.Nevertheless,the necessity for monitoring and regular replacement adds to an elevated cost of ownership for such systems.The utilization of an active output power filter can be used to diminish the dimensions of the LC filter and the electrolytic dc-link capacitor,even though the inclusion of capacitors remains an indispensable part of the system.This paper introduces capacitorless solid-state power filter(SSPF)for single-phase dc-ac converters.The proposed configuration is capable of generating a sinusoidal ac voltage without relying on capacitors.The proposed filter,composed of a planar transformer and an H-bridge converter operating at high frequency,injects voltage harmonics to attain a sinusoidal output voltage.The design parameters of the planar transformer are incorporated,and the impact of magnetizing and leakage inductances on the operation of the SSPF is illustrated.Theoretical analysis,supported by simulation and experimental results,are provided for a design example for a single-phase system.The total harmonic distortion observed in the output voltage is well below the IEEE 519 standard.The system operation is experimentally tested under both steady-state and dynamic conditions.A comparison with existing technology is presented,demonstrating that the proposed topology reduces the passive components used for filtering.
基金supported by the Shenzhen Science and Technology Plan,Sustainable Development Technology Special Project (Dual-Carbon Special Project),Research and Development of Intelligent Virtual Power Plant Technology (KCXST20221021111402006)the Science and Technology project of Tianjin,China (No.22YFYSHZ00330).
文摘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.
基金Supported by the National Natural Science Foundation of China(No.51966013)Inner Mongolia Natural Science Foundation Jieqing Project(No.2023JQ04)+1 种基金the National Natural Science Foundation of China(No.51966018)the Natural Science Foundation of Inner Mongolia Autonomous Region(No.STZC202230).
文摘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.
基金funded by National Key Research and Development Program of China (2021YFB2601400)。
文摘To reduce carbon emissions,clean energy is being integrated into the power system.Wind power is connected to the grid in a distributed form,but its high variability poses a challenge to grid stability.This article combines wind turbine monitoring data with numerical weather prediction(NWP)data to create a suitable wind power prediction framework for distributed grids.First,high-precision NWP of the turbine range is achieved using weather research and forecasting models(WRF),and Kriging interpolation locates predicted meteorological data at the turbine site.Then,a preliminary predicted power series is obtained based on the fan’s wind speed-power conversion curve,and historical power is reconstructed using variational mode decomposition(VMD)filtering to form input variables in chronological order.Finally,input variables of a single turbine enter the temporal convolutional network(TCN)to complete initial feature extraction,and then integrate the outputs of all TCN layers using Long Short Term Memory Networks(LSTM)to obtain power prediction sequences for all turbine positions.The proposed method was tested on a wind farm connected to a distributed power grid,and the results showed it to be superior to existing typical methods.
基金supported by State Grid Corporation of China Project“Research and Application of Key Technologies for Active Power Control in Regional Power Grid with High Penetration of Distributed Renewable Generation”(5108-202316044A-1-1-ZN).
文摘With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.
基金supported by Science and Technology Project of State Grid Anhui Electric Power Co.,Ltd. (No.B6120922000A).
文摘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.
基金supported in part by the Natural Science Foundation of Jiangsu Province under Grant BK20200969(L.Z.,URL:http://std.jiangsu.gov.cn/)in part by Basic Science(Natural Science)Research Project of Colleges and Universities in Jiangsu Province under Grant 22KJB470025(L.R.,URL:http://jyt.jiangsu.gov.cn/)in part by Social People’s Livelihood Technology Plan General Project of Nantong under Grant MS12021015(L.Q.,URL:http://kjj.nantong.gov.cn/).
文摘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.
基金funded by the National Key R&D Program of China,Grant Number 2019YFB1505400.
文摘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.
文摘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.
文摘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.
