The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,...The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,photovoltaic power generation is unstable and random,resulting in a low utilization rate and directly affecting the stability of the power grid.To solve this problem,this paper proposes a coordinated control strategy for a newenergy power generation system with a hybrid energy storage unit based on the lithium iron phosphate-supercapacitor hybrid energy storage unit.Firstly,the variational mode decomposition algorithm is used to separate the high and low frequencies of the power signal,which is conducive to the rapid and accurate suppression of the power fluctuation of the energy storage system.Secondly,the fuzzy control algorithm is introduced to balance the power between energy storage.In this paper,the actual data is used for simulation,and the simulation results show that the strategy realizes the effective suppression of the bus voltage fluctuation and the accurate control of the internal state of the energy storage unit,effectively avoiding problems such as overshoot and over-discharge,and can significantly improve the stability of the photovoltaic power generation systemand the stability of the Direct Current bus.It is of great significance to promote the development of collaborative control technology for photovoltaic hybrid energy storage units.展开更多
As cataract surgery progresses from “restoration of sight” to “refractive correction”, precise prediction of intraocular lens (IOL) power is critical for enhancing postoperative visual quality in patients. IOL pow...As cataract surgery progresses from “restoration of sight” to “refractive correction”, precise prediction of intraocular lens (IOL) power is critical for enhancing postoperative visual quality in patients. IOL power calculation methods have evolved and innovated throughout time, from early theoretical and regression formulas to nonlinear formulas for estimating effective lens position (ELP), multivariable formulas, and innovative formulas that use optical principles and AI-based online formulas. This paper thoroughly discusses the development and iteration of traditional IOL calculation formulas, the emergence of new IOL calculation formulas, and the selection of IOL calculation formulas for different patients in the era of refractive cataract surgery, serving as a reference for “personalized” IOL implantation in clinical practice.展开更多
This paper deals with quasilinear elliptic equations of singular growth like-Δu-uΔ(u^(2))=a(x)u^(-1).We establish the existence of positive solutions for general a(x)∈L^(p)(Ω),p>2,whereΩis a bounded domain inℝ...This paper deals with quasilinear elliptic equations of singular growth like-Δu-uΔ(u^(2))=a(x)u^(-1).We establish the existence of positive solutions for general a(x)∈L^(p)(Ω),p>2,whereΩis a bounded domain inℝ^(N)with N≥1.展开更多
Thermal power plants are present in the Brazilian electrical matrix (8% in 2022) and worldwide (61.5% in 2021). Combustion engines are used to drive generators in most thermal power plants, serving as the main sources...Thermal power plants are present in the Brazilian electrical matrix (8% in 2022) and worldwide (61.5% in 2021). Combustion engines are used to drive generators in most thermal power plants, serving as the main sources of atmospheric emissions. This study aims to present a model that allows for the pre-selection of these engines, identifying those most suitable to the recommended standards for obtaining environmental licenses. Data from twelve engine models were used to evaluate the studied alternatives. Computational resources were utilized through the R program for statistical analysis of the data. Simulations with the Screen View software enabled the investigation of atmospheric dispersion scenarios. The study showed that dispersion presented significant correlations with the following variables: emission rate, with a significance of 0.60, and chimney height, with a significance of −0.57. It was possible to conclude that for wind speeds equal to or greater than the local annual average of 2.1 m/s, a distance of 1800 meters to the community (location of the thermal power plant), a flue gas exit speed of 35 m/s, and the analyzed engine standards and design, engines with a NOx emission rate of up to 3.0 g/kWh showed good dispersion values, below 200 mg/Nm3 of NOx, the standard required by Brazilian environmental legislation. Thus, only four engine models meet this condition.展开更多
In light of the increasing recognition of the necessity to evaluate and mitigate the environmental impact of human activities, the aim of this study is to assess the greenhouse gases emitted in 2022 by the Kossodo the...In light of the increasing recognition of the necessity to evaluate and mitigate the environmental impact of human activities, the aim of this study is to assess the greenhouse gases emitted in 2022 by the Kossodo thermal power plant as a consequence of its electricity production. The specific objective was to identify the emission sources and quantify the gases generated, with the purpose of proposing effective solutions for reducing the plant’s ecological footprint. In order to achieve the objectives set out in the study, the Bilan Carbone® method was employed. Following an analysis of the plant’s activities, seven emission items were identified as requiring further investigation. The data was gathered from the plant’s activity reports, along with measurements and questionnaires distributed to employees. The data collected was subjected to processing in order to produce the sought activity data. The Bilan Carbone® V7.1 spreadsheet was employed to convert the activity data into equivalent quantities of CO2. The full assessment indicates that the majority of the power plant’s emissions come from the combustion of HFO and DDO, accounting for 96.11% of the Kossodo power plant’s total GHG emissions in 2022. The plant produced 280,585,676 kilowatt-hours (kWh), resulting in emissions of 218,492.785 ± 10,924.639 tCO2e, which yielded an emission factor of 0.78 kgCO2e/kWh for the year 2022. In order to reduce this rate, recommendations for improved energy efficiency have been issued to management and all staff.展开更多
Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationship...Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.展开更多
This paper presents an optimized strategy for multiple integrations of photovoltaic distributed generation (PV-DG) within radial distribution power systems. The proposed methodology focuses on identifying the optimal ...This paper presents an optimized strategy for multiple integrations of photovoltaic distributed generation (PV-DG) within radial distribution power systems. The proposed methodology focuses on identifying the optimal allocation and sizing of multiple PV-DG units to minimize power losses using a probabilistic PV model and time-series power flow analysis. Addressing the uncertainties in PV output due to weather variability and diurnal cycles is critical. A probabilistic assessment offers a more robust analysis of DG integration’s impact on the grid, potentially leading to more reliable system planning. The presented approach employs a genetic algorithm (GA) and a determined PV output profile and probabilistic PV generation profile based on experimental measurements for one year of solar radiation in Cairo, Egypt. The proposed algorithms are validated using a co-simulation framework that integrates MATLAB and OpenDSS, enabling analysis on a 33-bus test system. This framework can act as a guideline for creating other co-simulation algorithms to enhance computing platforms for contemporary modern distribution systems within smart grids concept. The paper presents comparisons with previous research studies and various interesting findings such as the considered hours for developing the probabilistic model presents different results.展开更多
Virtual Power Plants(VPPs)are integral to modern energy systems,providing stability and reliability in the face of the inherent complexities and fluctuations of solar power data.Traditional anomaly detection methodolo...Virtual Power Plants(VPPs)are integral to modern energy systems,providing stability and reliability in the face of the inherent complexities and fluctuations of solar power data.Traditional anomaly detection methodologies often need to adequately handle these fluctuations from solar radiation and ambient temperature variations.We introduce the Memory-Enhanced Autoencoder with Adversarial Training(MemAAE)model to overcome these limitations,designed explicitly for robust anomaly detection in VPP environments.The MemAAE model integrates three principal components:an LSTM-based autoencoder that effectively captures temporal dynamics to distinguish between normal and anomalous behaviors,an adversarial training module that enhances system resilience across diverse operational scenarios,and a prediction module that aids the autoencoder during the reconstruction process,thereby facilitating precise anomaly identification.Furthermore,MemAAE features a memory mechanism that stores critical pattern information,mitigating overfitting,alongside a dynamic threshold adjustment mechanism that adapts detection thresholds in response to evolving operational conditions.Our empirical evaluation of the MemAAE model using real-world solar power data shows that the model outperforms other comparative models on both datasets.On the Sopan-Finder dataset,MemAAE has an accuracy of 99.17%and an F1-score of 95.79%,while on the Sunalab Faro PV 2017 dataset,it has an accuracy of 97.67%and an F1-score of 93.27%.Significant performance advantages have been achieved on both datasets.These results show that MemAAE model is an effective method for real-time anomaly detection in virtual power plants(VPPs),which can enhance robustness and adaptability to inherent variables in solar power generation.展开更多
The release of a new artificial intelligence(AI)model,ironically,evokes a biblical memory.What has transpired in the past few days echoes the biblical story of David versus Goliath,in which the massive and wellarmed G...The release of a new artificial intelligence(AI)model,ironically,evokes a biblical memory.What has transpired in the past few days echoes the biblical story of David versus Goliath,in which the massive and wellarmed Goliath is defeated by the comparatively puny David,who comes to the battle with only his staff and sling.展开更多
The release of a new artificial intelligence(AI)model,ironically,evokes a biblical memory.What has transpired in the past few days echoes the story of David versus Goliath,in which the massive and well-armed Goliath i...The release of a new artificial intelligence(AI)model,ironically,evokes a biblical memory.What has transpired in the past few days echoes the story of David versus Goliath,in which the massive and well-armed Goliath is defeated by the comparatively puny David,who comes to the battle with only his staff and sling.展开更多
The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward...The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward-looking information of key wind farms in a cluster under different weather conditions is an effective method to improve the accuracy of ultrashort-term cluster power forecasting.To this end,this paper proposes a refined modeling method for ultrashort-term wind power cluster forecasting based on a convergent cross-mapping algorithm.From the perspective of causality,key meteorological forecasting factors under different cluster power fluctuation processes were screened,and refined training modeling was performed for different fluctuation processes.First,a wind process description index system and classification model at the wind power cluster level are established to realize the classification of typical fluctuation processes.A meteorological-cluster power causal relationship evaluation model based on the convergent cross-mapping algorithm is pro-posed to screen meteorological forecasting factors under multiple types of typical fluctuation processes.Finally,a refined modeling meth-od for a variety of different typical fluctuation processes is proposed,and the strong causal meteorological forecasting factors of each scenario are used as inputs to realize high-precision modeling and forecasting of ultra-short-term wind cluster power.An example anal-ysis shows that the short-term wind power cluster power forecasting accuracy of the proposed method can reach 88.55%,which is 1.57-7.32%higher than that of traditional methods.展开更多
In order to increase the stability of the Mongolia power system, a single-phase automatic reclosing device (SPAR) was introduced on double-circuit power lines built with a size of 330 kV, operating on a voltage of 220...In order to increase the stability of the Mongolia power system, a single-phase automatic reclosing device (SPAR) was introduced on double-circuit power lines built with a size of 330 kV, operating on a voltage of 220 kV and a length of 250 km. These overhead power lines (L-213, L-214) connect the 220/110/35 kV “Songino” substation with the “Mandal” substation and form system networks. This paper presents the challenges encountered when implementing single-phase automatic reclosing (SPAR) devices and compares the changes in power system parameters before and after SPAR deployment for a long 220 kV line. Simulations and analyses were carried out using DIgSILENT PowerFactory software, focusing on rotor angle stability, and the overall impact on the power system during short-circuit faults. The evaluation also utilized measurement data from the Wide Area Monitoring System (WAMS) to compare system behavior pre- and post-implementation of SPAR. The findings reveal that SPAR significantly enhances system reliability and stability, effectively mitigating the risk of oscillations and stability loss triggered by short circuits. This improvement contributes to a more resilient power system, reducing the potential for disturbances caused by faults.展开更多
The integration of cognitive radio and energy has enhanced the utilization efficiency of the spectrum and promoted the application of green energy.To begin with,this paper presents the architecture of green energy-eff...The integration of cognitive radio and energy has enhanced the utilization efficiency of the spectrum and promoted the application of green energy.To begin with,this paper presents the architecture of green energy-efficient communication and network models.It incorporates the distributed network model and the heterogeneous two-tier network model into the green cognitive radio power control and channel allocation model.The primary focus of this research lies in energy conservation at the physical layer.To mitigate the interference with primary users and address the peak constraint in secondary user power allocation,the article analyzes the system model of the cognitive radio network and subsequently elaborates on the dynamic throughput maximization allocation algorithm.Eventually,through experimental analysis and verification,the distinctiveness and comprehensiveness of the optimal power control for this subject are illustrated.展开更多
This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy dema...This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy demands,and the adoption of smart grid technologies,power systems are undergoing a rapid transformation,making the need for efficient,reliable,and sustainable distribution networks increasingly critical.In this paper,the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms.Among these advanced search algorithms,the Bonobo Optimizer(BO)has demonstrated superior performance in handling the complexities of unbalanced power distribution network optimization.The study is structured around four distinct scenarios:(Ⅰ)improving mean voltage profile and minimizing active power loss,(Ⅱ)minimizing Voltage Unbalance Index(VUI)and Current Unbalance Index(CUI),(Ⅲ)optimizing key reliability indices using both Line Oriented Reliability Index(LORI)and Customer Oriented Reliability Index(CORI)approaches,and(Ⅳ)employing multi-objective optimization using the Pareto front technique to simultaneously minimize active power loss,average CUI,and System Average Interruption Duration Index(SAIDI).The study aims to contribute to the development of more efficient,reliable,and sustainable energy systems by addressing voltage profiles,power losses,reduction of imbalance,and the enhancement of reliability together.展开更多
For thermal power enterprises,the traditional business model of scale expansion and a single product line restricts the development of electricity marketing.Therefore,to achieve the transformation and upgrading of the...For thermal power enterprises,the traditional business model of scale expansion and a single product line restricts the development of electricity marketing.Therefore,to achieve the transformation and upgrading of their electricity marketing,this study starts from the current situation of the electricity market and introduces in detail the market-oriented electricity marketing strategies of thermal power enterprises from four aspects:product strategy,price strategy,channel strategy,and promotion strategy.The analysis finds that a market-oriented electricity marketing strategy is not only an inevitable choice for thermal power enterprises to respond to current challenges but also an essential path for them to move toward high-quality development.Through continuous innovation and upgrading,thermal power enterprises will maintain a leading position in fierce market competition,achieve sustainable development,and make greater contributions to the prosperity and development of the energy industry.展开更多
To promote energy conservation,emission reduction,and sustainable development in thermal power enterprises,this study conducted a detailed analysis of the problems existing in measurement management in these enterpris...To promote energy conservation,emission reduction,and sustainable development in thermal power enterprises,this study conducted a detailed analysis of the problems existing in measurement management in these enterprises and explored targeted solutions.The analysis found that,faced with increasingly stringent environmental protection requirements and urgent needs to improve energy efficiency,thermal power enterprises must address the current issues in energy measurement management.They should actively respond to the national call for energy conservation and emission reduction,continuously optimize energy measurement management processes,improve energy utilization efficiency,reduce unnecessary energy consumption and emissions,and lay a solid foundation for the green transformation and sustainable development of the industry.展开更多
In this study,the power generation difference between the east-west and the north-south orientation of the vertically installed heterojunction solar cell(HJT)modules was deeply discussed.East-west oriented HJT module ...In this study,the power generation difference between the east-west and the north-south orientation of the vertically installed heterojunction solar cell(HJT)modules was deeply discussed.East-west oriented HJT module has 30%higher power generation,especially in desert photovoltaic(PV)with a bimodal distribution.While the south-north one has a single peak,the same as normal PV modules.Vertical power generation technology of HJT also has less land occupation,which is of great significance for optimizing the design of photovoltaic systems.展开更多
基金supported by the State Grid Corporation of China Science and Technology Project,grant number 52270723000900K.
文摘The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,photovoltaic power generation is unstable and random,resulting in a low utilization rate and directly affecting the stability of the power grid.To solve this problem,this paper proposes a coordinated control strategy for a newenergy power generation system with a hybrid energy storage unit based on the lithium iron phosphate-supercapacitor hybrid energy storage unit.Firstly,the variational mode decomposition algorithm is used to separate the high and low frequencies of the power signal,which is conducive to the rapid and accurate suppression of the power fluctuation of the energy storage system.Secondly,the fuzzy control algorithm is introduced to balance the power between energy storage.In this paper,the actual data is used for simulation,and the simulation results show that the strategy realizes the effective suppression of the bus voltage fluctuation and the accurate control of the internal state of the energy storage unit,effectively avoiding problems such as overshoot and over-discharge,and can significantly improve the stability of the photovoltaic power generation systemand the stability of the Direct Current bus.It is of great significance to promote the development of collaborative control technology for photovoltaic hybrid energy storage units.
文摘As cataract surgery progresses from “restoration of sight” to “refractive correction”, precise prediction of intraocular lens (IOL) power is critical for enhancing postoperative visual quality in patients. IOL power calculation methods have evolved and innovated throughout time, from early theoretical and regression formulas to nonlinear formulas for estimating effective lens position (ELP), multivariable formulas, and innovative formulas that use optical principles and AI-based online formulas. This paper thoroughly discusses the development and iteration of traditional IOL calculation formulas, the emergence of new IOL calculation formulas, and the selection of IOL calculation formulas for different patients in the era of refractive cataract surgery, serving as a reference for “personalized” IOL implantation in clinical practice.
基金Supported by National Science Foundation of China(11971027,12171497)。
文摘This paper deals with quasilinear elliptic equations of singular growth like-Δu-uΔ(u^(2))=a(x)u^(-1).We establish the existence of positive solutions for general a(x)∈L^(p)(Ω),p>2,whereΩis a bounded domain inℝ^(N)with N≥1.
文摘Thermal power plants are present in the Brazilian electrical matrix (8% in 2022) and worldwide (61.5% in 2021). Combustion engines are used to drive generators in most thermal power plants, serving as the main sources of atmospheric emissions. This study aims to present a model that allows for the pre-selection of these engines, identifying those most suitable to the recommended standards for obtaining environmental licenses. Data from twelve engine models were used to evaluate the studied alternatives. Computational resources were utilized through the R program for statistical analysis of the data. Simulations with the Screen View software enabled the investigation of atmospheric dispersion scenarios. The study showed that dispersion presented significant correlations with the following variables: emission rate, with a significance of 0.60, and chimney height, with a significance of −0.57. It was possible to conclude that for wind speeds equal to or greater than the local annual average of 2.1 m/s, a distance of 1800 meters to the community (location of the thermal power plant), a flue gas exit speed of 35 m/s, and the analyzed engine standards and design, engines with a NOx emission rate of up to 3.0 g/kWh showed good dispersion values, below 200 mg/Nm3 of NOx, the standard required by Brazilian environmental legislation. Thus, only four engine models meet this condition.
文摘In light of the increasing recognition of the necessity to evaluate and mitigate the environmental impact of human activities, the aim of this study is to assess the greenhouse gases emitted in 2022 by the Kossodo thermal power plant as a consequence of its electricity production. The specific objective was to identify the emission sources and quantify the gases generated, with the purpose of proposing effective solutions for reducing the plant’s ecological footprint. In order to achieve the objectives set out in the study, the Bilan Carbone® method was employed. Following an analysis of the plant’s activities, seven emission items were identified as requiring further investigation. The data was gathered from the plant’s activity reports, along with measurements and questionnaires distributed to employees. The data collected was subjected to processing in order to produce the sought activity data. The Bilan Carbone® V7.1 spreadsheet was employed to convert the activity data into equivalent quantities of CO2. The full assessment indicates that the majority of the power plant’s emissions come from the combustion of HFO and DDO, accounting for 96.11% of the Kossodo power plant’s total GHG emissions in 2022. The plant produced 280,585,676 kilowatt-hours (kWh), resulting in emissions of 218,492.785 ± 10,924.639 tCO2e, which yielded an emission factor of 0.78 kgCO2e/kWh for the year 2022. In order to reduce this rate, recommendations for improved energy efficiency have been issued to management and all staff.
基金funded by the Inner Mongolia Nature Foundation Project,Project number:2023JQ04.
文摘Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.
文摘This paper presents an optimized strategy for multiple integrations of photovoltaic distributed generation (PV-DG) within radial distribution power systems. The proposed methodology focuses on identifying the optimal allocation and sizing of multiple PV-DG units to minimize power losses using a probabilistic PV model and time-series power flow analysis. Addressing the uncertainties in PV output due to weather variability and diurnal cycles is critical. A probabilistic assessment offers a more robust analysis of DG integration’s impact on the grid, potentially leading to more reliable system planning. The presented approach employs a genetic algorithm (GA) and a determined PV output profile and probabilistic PV generation profile based on experimental measurements for one year of solar radiation in Cairo, Egypt. The proposed algorithms are validated using a co-simulation framework that integrates MATLAB and OpenDSS, enabling analysis on a 33-bus test system. This framework can act as a guideline for creating other co-simulation algorithms to enhance computing platforms for contemporary modern distribution systems within smart grids concept. The paper presents comparisons with previous research studies and various interesting findings such as the considered hours for developing the probabilistic model presents different results.
基金supported by“Regional Innovation Strategy(RIS)”through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(MOE)(2021RIS-002)the Technology Development Program(RS-2023-00266141)funded by the Ministry of SMEs and Startups(MSS,Republic of Korea).
文摘Virtual Power Plants(VPPs)are integral to modern energy systems,providing stability and reliability in the face of the inherent complexities and fluctuations of solar power data.Traditional anomaly detection methodologies often need to adequately handle these fluctuations from solar radiation and ambient temperature variations.We introduce the Memory-Enhanced Autoencoder with Adversarial Training(MemAAE)model to overcome these limitations,designed explicitly for robust anomaly detection in VPP environments.The MemAAE model integrates three principal components:an LSTM-based autoencoder that effectively captures temporal dynamics to distinguish between normal and anomalous behaviors,an adversarial training module that enhances system resilience across diverse operational scenarios,and a prediction module that aids the autoencoder during the reconstruction process,thereby facilitating precise anomaly identification.Furthermore,MemAAE features a memory mechanism that stores critical pattern information,mitigating overfitting,alongside a dynamic threshold adjustment mechanism that adapts detection thresholds in response to evolving operational conditions.Our empirical evaluation of the MemAAE model using real-world solar power data shows that the model outperforms other comparative models on both datasets.On the Sopan-Finder dataset,MemAAE has an accuracy of 99.17%and an F1-score of 95.79%,while on the Sunalab Faro PV 2017 dataset,it has an accuracy of 97.67%and an F1-score of 93.27%.Significant performance advantages have been achieved on both datasets.These results show that MemAAE model is an effective method for real-time anomaly detection in virtual power plants(VPPs),which can enhance robustness and adaptability to inherent variables in solar power generation.
文摘The release of a new artificial intelligence(AI)model,ironically,evokes a biblical memory.What has transpired in the past few days echoes the biblical story of David versus Goliath,in which the massive and wellarmed Goliath is defeated by the comparatively puny David,who comes to the battle with only his staff and sling.
文摘The release of a new artificial intelligence(AI)model,ironically,evokes a biblical memory.What has transpired in the past few days echoes the story of David versus Goliath,in which the massive and well-armed Goliath is defeated by the comparatively puny David,who comes to the battle with only his staff and sling.
基金funded by the State Grid Science and Technology Project“Research on Key Technologies for Prediction and Early Warning of Large-Scale Offshore Wind Power Ramp Events Based on Meteorological Data Enhancement”(4000-202318098A-1-1-ZN).
文摘The development of wind power clusters has scaled in terms of both scale and coverage,and the impact of weather fluctuations on cluster output changes has become increasingly complex.Accurately identifying the forward-looking information of key wind farms in a cluster under different weather conditions is an effective method to improve the accuracy of ultrashort-term cluster power forecasting.To this end,this paper proposes a refined modeling method for ultrashort-term wind power cluster forecasting based on a convergent cross-mapping algorithm.From the perspective of causality,key meteorological forecasting factors under different cluster power fluctuation processes were screened,and refined training modeling was performed for different fluctuation processes.First,a wind process description index system and classification model at the wind power cluster level are established to realize the classification of typical fluctuation processes.A meteorological-cluster power causal relationship evaluation model based on the convergent cross-mapping algorithm is pro-posed to screen meteorological forecasting factors under multiple types of typical fluctuation processes.Finally,a refined modeling meth-od for a variety of different typical fluctuation processes is proposed,and the strong causal meteorological forecasting factors of each scenario are used as inputs to realize high-precision modeling and forecasting of ultra-short-term wind cluster power.An example anal-ysis shows that the short-term wind power cluster power forecasting accuracy of the proposed method can reach 88.55%,which is 1.57-7.32%higher than that of traditional methods.
文摘In order to increase the stability of the Mongolia power system, a single-phase automatic reclosing device (SPAR) was introduced on double-circuit power lines built with a size of 330 kV, operating on a voltage of 220 kV and a length of 250 km. These overhead power lines (L-213, L-214) connect the 220/110/35 kV “Songino” substation with the “Mandal” substation and form system networks. This paper presents the challenges encountered when implementing single-phase automatic reclosing (SPAR) devices and compares the changes in power system parameters before and after SPAR deployment for a long 220 kV line. Simulations and analyses were carried out using DIgSILENT PowerFactory software, focusing on rotor angle stability, and the overall impact on the power system during short-circuit faults. The evaluation also utilized measurement data from the Wide Area Monitoring System (WAMS) to compare system behavior pre- and post-implementation of SPAR. The findings reveal that SPAR significantly enhances system reliability and stability, effectively mitigating the risk of oscillations and stability loss triggered by short circuits. This improvement contributes to a more resilient power system, reducing the potential for disturbances caused by faults.
文摘The integration of cognitive radio and energy has enhanced the utilization efficiency of the spectrum and promoted the application of green energy.To begin with,this paper presents the architecture of green energy-efficient communication and network models.It incorporates the distributed network model and the heterogeneous two-tier network model into the green cognitive radio power control and channel allocation model.The primary focus of this research lies in energy conservation at the physical layer.To mitigate the interference with primary users and address the peak constraint in secondary user power allocation,the article analyzes the system model of the cognitive radio network and subsequently elaborates on the dynamic throughput maximization allocation algorithm.Eventually,through experimental analysis and verification,the distinctiveness and comprehensiveness of the optimal power control for this subject are illustrated.
基金supported by the Scientific and Technological Research Council of Turkey(TUBITAK)under Grant No.124E002(1001-Project).
文摘This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy demands,and the adoption of smart grid technologies,power systems are undergoing a rapid transformation,making the need for efficient,reliable,and sustainable distribution networks increasingly critical.In this paper,the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms.Among these advanced search algorithms,the Bonobo Optimizer(BO)has demonstrated superior performance in handling the complexities of unbalanced power distribution network optimization.The study is structured around four distinct scenarios:(Ⅰ)improving mean voltage profile and minimizing active power loss,(Ⅱ)minimizing Voltage Unbalance Index(VUI)and Current Unbalance Index(CUI),(Ⅲ)optimizing key reliability indices using both Line Oriented Reliability Index(LORI)and Customer Oriented Reliability Index(CORI)approaches,and(Ⅳ)employing multi-objective optimization using the Pareto front technique to simultaneously minimize active power loss,average CUI,and System Average Interruption Duration Index(SAIDI).The study aims to contribute to the development of more efficient,reliable,and sustainable energy systems by addressing voltage profiles,power losses,reduction of imbalance,and the enhancement of reliability together.
文摘For thermal power enterprises,the traditional business model of scale expansion and a single product line restricts the development of electricity marketing.Therefore,to achieve the transformation and upgrading of their electricity marketing,this study starts from the current situation of the electricity market and introduces in detail the market-oriented electricity marketing strategies of thermal power enterprises from four aspects:product strategy,price strategy,channel strategy,and promotion strategy.The analysis finds that a market-oriented electricity marketing strategy is not only an inevitable choice for thermal power enterprises to respond to current challenges but also an essential path for them to move toward high-quality development.Through continuous innovation and upgrading,thermal power enterprises will maintain a leading position in fierce market competition,achieve sustainable development,and make greater contributions to the prosperity and development of the energy industry.
文摘To promote energy conservation,emission reduction,and sustainable development in thermal power enterprises,this study conducted a detailed analysis of the problems existing in measurement management in these enterprises and explored targeted solutions.The analysis found that,faced with increasingly stringent environmental protection requirements and urgent needs to improve energy efficiency,thermal power enterprises must address the current issues in energy measurement management.They should actively respond to the national call for energy conservation and emission reduction,continuously optimize energy measurement management processes,improve energy utilization efficiency,reduce unnecessary energy consumption and emissions,and lay a solid foundation for the green transformation and sustainable development of the industry.
文摘In this study,the power generation difference between the east-west and the north-south orientation of the vertically installed heterojunction solar cell(HJT)modules was deeply discussed.East-west oriented HJT module has 30%higher power generation,especially in desert photovoltaic(PV)with a bimodal distribution.While the south-north one has a single peak,the same as normal PV modules.Vertical power generation technology of HJT also has less land occupation,which is of great significance for optimizing the design of photovoltaic systems.
