As the intermittency and uncertainty of photovoltaic(PV)power generation poses considerable challenges to the power system operation,accurate PV generation estimates are critical for the distribution operation,mainten...As the intermittency and uncertainty of photovoltaic(PV)power generation poses considerable challenges to the power system operation,accurate PV generation estimates are critical for the distribution operation,maintenance,and demand response program implementation because of the increasing usage of distributed PVs.Currently,most residential PVs are installed behind the meter,with only the net load available to the utilities.Therefore,a method for disaggregating the residential PV generation from the net load data is needed to enhance the grid-edge observability.In this study,an unsupervised PV capacity estimation method based on net metering data is proposed,for estimating the PV capacity in the customer’s premise based on the distribution characteristics of nocturnal and diurnal net load extremes.Then,the PV generation disaggregation method is presented.Based on the analysis of the correlation between the nocturnal and diurnal actual loads and the correlation between the PV capacity and their actual PV generation,the PV generation of customers is estimated by applying linear fitting of multiple typical solar exemplars and then disaggregating them into hourly-resolution power profiles.Finally,the anomalies of disaggregated PV power are calibrated and corrected using the estimated capacity.Experiment results on a real-world hourly dataset involving 260 customers show that the proposed PV capacity estimation method achieves good accuracy because of the advantages of robustness and low complexity.Compared with the state-of-the-art PV disaggregation algorithm,the proposed method exhibits a reduction of over 15%for the mean absolute percentage error and over 20%for the root mean square error.展开更多
Currently a large effort is being done with the intention to educate people about how much energy each electrical appliance uses in their houses, since this knowledge is the fundamental basis of energy efficiency prog...Currently a large effort is being done with the intention to educate people about how much energy each electrical appliance uses in their houses, since this knowledge is the fundamental basis of energy efficiency programs that can be managed by the household owners. This paper presents a simple yet functional non-intrusive method for electric power measurement that can be applied in energy efficiency programs, in order to provide a better knowledge of the energy consumption of the appliances in a home.展开更多
Metering technology is one of the core technologies of the smart power grid. The overall metering solution and related products have a wide market space in the whole process of power production, which bring new opport...Metering technology is one of the core technologies of the smart power grid. The overall metering solution and related products have a wide market space in the whole process of power production, which bring new opportunities for power distribution development from automation to intelligentialize, and provide technical supports for the power metering system platform. Because of the importance of metering products and their market demand, this paper focuses on the design of a simple power metering chip with low-cost, low-precision and non-invasive, so as to lay the foundation for the development and practical technology accumulation of power metering products. The design achieves low cost by reducing the acquisition accuracy, simplifying the collection and sampling methods. This paper studies the chip accuracy, sampling methods, collection methods, and the inference of the chip characteristics requirements.展开更多
Mobile power meters allow for cyclists to monitor power output （PO） during training and competition. The Garrnin Vector power meter （VPM） measures PO at the pedal compared to the crank and has been tested in only ...Mobile power meters allow for cyclists to monitor power output （PO） during training and competition. The Garrnin Vector power meter （VPM） measures PO at the pedal compared to the crank and has been tested in only a few limited studies. The purpose of this study was to determine the validity and reproducibility of the VPM by comparing it to the SRM. The VPM validity was tested by （1） a submaximal incremental test, （2） submaximal constant power test, （3） sprint test, and （4） a field test. The reliability of the VPM was tested by repeating the laboratory tests 10 times over a 6 week span. Significant differences （P = 0.046） were found between the mean POSRM （178 ± 1.8 W） and POVPM （163.5 ± 14.7 W） for the submaximal constant-power test. No significant differences were found between the POMAX SRM and the POMAx VPM. The reproducibility of the VPM was lower than the SRM （CV = 8.52 ±4.0 vs 3.48 ± 1.9, 10.66% vs 5.50%, and 67.7% vs 55.3% for the submaximal incremental test, submaximal constant-power test, and field test respectively）. The POVPM appears to underestimate the POSRM and is less valid and reliable across various cycling efforts.展开更多
This paper analyzes the main reasons of abnormal power metering device, discusses the monitoring method of abnormal state of power metering device, studies the abnormal detection measures of power metering device, in ...This paper analyzes the main reasons of abnormal power metering device, discusses the monitoring method of abnormal state of power metering device, studies the abnormal detection measures of power metering device, in order to promote the stable development of power metering device.展开更多
In recent years, in order to achieve further development, the State Grid has further increased the intelligent management of measurement assets with the construction of electric energy information collection as the co...In recent years, in order to achieve further development, the State Grid has further increased the intelligent management of measurement assets with the construction of electric energy information collection as the core and the construction of intelligent warehouse as the pillar, and taken active measures to further increase the application of the monitoring system in daily life, work and operation. In this way, the internal assets of the power enterprise are effectively controlled in an all-round way during the actual operation process, so as to further enable the related work of measurement management to be more healthy and orderly and develop continuously.展开更多
Recent advancements in smart-meter technology are transforming traditional power systems into intelligent smart grids.It offers substantial benefits across social,environmental,and economic dimensions.To effectively r...Recent advancements in smart-meter technology are transforming traditional power systems into intelligent smart grids.It offers substantial benefits across social,environmental,and economic dimensions.To effectively realize these advantages,a fine-grained collection and analysis of smart meter data is essential.However,the high dimensionality and volume of such time-series present significant challenges,including increased computational load,data transmission overhead,latency,and complexity in real-time analysis.This study proposes a novel,computationally efficient framework for feature extraction and selection tailored to smart meter time-series data.The approach begins with an extensive offline analysis,where features are derived from multiple domains—time,frequency,and statistical—to capture diverse signal characteristics.Various feature sets are fused and evaluated using robust machine learning classifiers to identify the most informative combinations for automated appliance categorization.The bestperforming fused features set undergoes further refinement using Analysis of Variance(ANOVA)to identify the most discriminative features.The mathematical models,used to compute the selected features,are optimized to extract them with computational efficiency during online processing.Moreover,a notable dimension reduction is secured which facilitates data storage,transmission,and post processing.Onward,a specifically designed LogitBoost(LB)based ensemble of Random Forest base learners is used for an automated classification.The proposed solution demonstrates a high classification accuracy(97.93%)for the case of nine-class problem and dimension reduction(17.33-fold)with minimal front-end computational requirements,making it well-suited for real-world applications in smart grid environments.展开更多
随着多变的分布式可再生能源的大规模接入,配电系统将逐步从单纯接受和分配电能的传统电力网络,转变为能量交换网络。近年来,我国智能配电网的建设步伐正在加快。在开展配电网现代化的其他方面工作之前,应该首先做好配电网体系结构设计...随着多变的分布式可再生能源的大规模接入,配电系统将逐步从单纯接受和分配电能的传统电力网络,转变为能量交换网络。近年来,我国智能配电网的建设步伐正在加快。在开展配电网现代化的其他方面工作之前,应该首先做好配电网体系结构设计,即配电网最顶层模型的设计。虽然所谓的总配电系统运营商(total distribution system operator,DSO)模型是最可取方案,但在实践中尚未得到重视。为此,该文在已经过科学论证的电网分层和集群体系结构的框架下对这一问题进行论述,揭示总DSO模式的科学性和其实施的重要意义,并指出由不同局部配电网内的部分分布式能源所集成的虚拟电厂模式的弊端。进而,阐释了与实施DSO模式相关的几个战略性问题,包括重新定义配电服务、开放电表市场、激励新型电力需求和分布式电源的增长,树立新的电网设计理念等,以期大幅降低电网现代化建设的巨额花费。展开更多
智能电能表在复杂电网环境下的计量精度易受非线性误差影响。为提高其准确性,提出一种融合非线性自回归外生输入(nonlinear auto-regressive with exogenous inputs,NARX)模型与畸变功率的误差校正方法。利用NARX模型构建电能表的非线...智能电能表在复杂电网环境下的计量精度易受非线性误差影响。为提高其准确性,提出一种融合非线性自回归外生输入(nonlinear auto-regressive with exogenous inputs,NARX)模型与畸变功率的误差校正方法。利用NARX模型构建电能表的非线性误差模型,以捕捉其动态特性;从测量数据中分离基波与谐波电能,并计算谐波电能比差以量化谐波影响;引入畸变功率概念,构建以谐波电能比差和畸变功率为输入的误差校正模型,对非线性误差进行补偿。实验结果表明:经所提方法校正后,在不同谐波含量(5%、10%、20%)条件下,智能电能表的最大计量误差由校正前的2.4%、3.1%、10.3%均降至0.5%左右,同时非线性误差预测结果的拟合度得到了提升,有效提高了谐波环境下的计量精度。展开更多
基金supported by the Science and Technology Project of State Grid Corporation of China(No.5400-202112507A-0-5-ZN)the National Nature Science Foundation for Young Scholars of China(No.52107120).
文摘As the intermittency and uncertainty of photovoltaic(PV)power generation poses considerable challenges to the power system operation,accurate PV generation estimates are critical for the distribution operation,maintenance,and demand response program implementation because of the increasing usage of distributed PVs.Currently,most residential PVs are installed behind the meter,with only the net load available to the utilities.Therefore,a method for disaggregating the residential PV generation from the net load data is needed to enhance the grid-edge observability.In this study,an unsupervised PV capacity estimation method based on net metering data is proposed,for estimating the PV capacity in the customer’s premise based on the distribution characteristics of nocturnal and diurnal net load extremes.Then,the PV generation disaggregation method is presented.Based on the analysis of the correlation between the nocturnal and diurnal actual loads and the correlation between the PV capacity and their actual PV generation,the PV generation of customers is estimated by applying linear fitting of multiple typical solar exemplars and then disaggregating them into hourly-resolution power profiles.Finally,the anomalies of disaggregated PV power are calibrated and corrected using the estimated capacity.Experiment results on a real-world hourly dataset involving 260 customers show that the proposed PV capacity estimation method achieves good accuracy because of the advantages of robustness and low complexity.Compared with the state-of-the-art PV disaggregation algorithm,the proposed method exhibits a reduction of over 15%for the mean absolute percentage error and over 20%for the root mean square error.
文摘Currently a large effort is being done with the intention to educate people about how much energy each electrical appliance uses in their houses, since this knowledge is the fundamental basis of energy efficiency programs that can be managed by the household owners. This paper presents a simple yet functional non-intrusive method for electric power measurement that can be applied in energy efficiency programs, in order to provide a better knowledge of the energy consumption of the appliances in a home.
文摘Metering technology is one of the core technologies of the smart power grid. The overall metering solution and related products have a wide market space in the whole process of power production, which bring new opportunities for power distribution development from automation to intelligentialize, and provide technical supports for the power metering system platform. Because of the importance of metering products and their market demand, this paper focuses on the design of a simple power metering chip with low-cost, low-precision and non-invasive, so as to lay the foundation for the development and practical technology accumulation of power metering products. The design achieves low cost by reducing the acquisition accuracy, simplifying the collection and sampling methods. This paper studies the chip accuracy, sampling methods, collection methods, and the inference of the chip characteristics requirements.
文摘Mobile power meters allow for cyclists to monitor power output （PO） during training and competition. The Garrnin Vector power meter （VPM） measures PO at the pedal compared to the crank and has been tested in only a few limited studies. The purpose of this study was to determine the validity and reproducibility of the VPM by comparing it to the SRM. The VPM validity was tested by （1） a submaximal incremental test, （2） submaximal constant power test, （3） sprint test, and （4） a field test. The reliability of the VPM was tested by repeating the laboratory tests 10 times over a 6 week span. Significant differences （P = 0.046） were found between the mean POSRM （178 ± 1.8 W） and POVPM （163.5 ± 14.7 W） for the submaximal constant-power test. No significant differences were found between the POMAX SRM and the POMAx VPM. The reproducibility of the VPM was lower than the SRM （CV = 8.52 ±4.0 vs 3.48 ± 1.9, 10.66% vs 5.50%, and 67.7% vs 55.3% for the submaximal incremental test, submaximal constant-power test, and field test respectively）. The POVPM appears to underestimate the POSRM and is less valid and reliable across various cycling efforts.
文摘This paper analyzes the main reasons of abnormal power metering device, discusses the monitoring method of abnormal state of power metering device, studies the abnormal detection measures of power metering device, in order to promote the stable development of power metering device.
文摘In recent years, in order to achieve further development, the State Grid has further increased the intelligent management of measurement assets with the construction of electric energy information collection as the core and the construction of intelligent warehouse as the pillar, and taken active measures to further increase the application of the monitoring system in daily life, work and operation. In this way, the internal assets of the power enterprise are effectively controlled in an all-round way during the actual operation process, so as to further enable the related work of measurement management to be more healthy and orderly and develop continuously.
文摘Recent advancements in smart-meter technology are transforming traditional power systems into intelligent smart grids.It offers substantial benefits across social,environmental,and economic dimensions.To effectively realize these advantages,a fine-grained collection and analysis of smart meter data is essential.However,the high dimensionality and volume of such time-series present significant challenges,including increased computational load,data transmission overhead,latency,and complexity in real-time analysis.This study proposes a novel,computationally efficient framework for feature extraction and selection tailored to smart meter time-series data.The approach begins with an extensive offline analysis,where features are derived from multiple domains—time,frequency,and statistical—to capture diverse signal characteristics.Various feature sets are fused and evaluated using robust machine learning classifiers to identify the most informative combinations for automated appliance categorization.The bestperforming fused features set undergoes further refinement using Analysis of Variance(ANOVA)to identify the most discriminative features.The mathematical models,used to compute the selected features,are optimized to extract them with computational efficiency during online processing.Moreover,a notable dimension reduction is secured which facilitates data storage,transmission,and post processing.Onward,a specifically designed LogitBoost(LB)based ensemble of Random Forest base learners is used for an automated classification.The proposed solution demonstrates a high classification accuracy(97.93%)for the case of nine-class problem and dimension reduction(17.33-fold)with minimal front-end computational requirements,making it well-suited for real-world applications in smart grid environments.
文摘随着多变的分布式可再生能源的大规模接入,配电系统将逐步从单纯接受和分配电能的传统电力网络,转变为能量交换网络。近年来,我国智能配电网的建设步伐正在加快。在开展配电网现代化的其他方面工作之前,应该首先做好配电网体系结构设计,即配电网最顶层模型的设计。虽然所谓的总配电系统运营商(total distribution system operator,DSO)模型是最可取方案,但在实践中尚未得到重视。为此,该文在已经过科学论证的电网分层和集群体系结构的框架下对这一问题进行论述,揭示总DSO模式的科学性和其实施的重要意义,并指出由不同局部配电网内的部分分布式能源所集成的虚拟电厂模式的弊端。进而,阐释了与实施DSO模式相关的几个战略性问题,包括重新定义配电服务、开放电表市场、激励新型电力需求和分布式电源的增长,树立新的电网设计理念等,以期大幅降低电网现代化建设的巨额花费。
文摘智能电能表在复杂电网环境下的计量精度易受非线性误差影响。为提高其准确性,提出一种融合非线性自回归外生输入(nonlinear auto-regressive with exogenous inputs,NARX)模型与畸变功率的误差校正方法。利用NARX模型构建电能表的非线性误差模型,以捕捉其动态特性;从测量数据中分离基波与谐波电能,并计算谐波电能比差以量化谐波影响;引入畸变功率概念,构建以谐波电能比差和畸变功率为输入的误差校正模型,对非线性误差进行补偿。实验结果表明:经所提方法校正后,在不同谐波含量(5%、10%、20%)条件下,智能电能表的最大计量误差由校正前的2.4%、3.1%、10.3%均降至0.5%左右,同时非线性误差预测结果的拟合度得到了提升,有效提高了谐波环境下的计量精度。
