Line Loss Calculation Research Articles

Line Loss Calculation and Optimization in Low Voltage Lines with Photovoltaic Systems Using an Analytical Model and Quantum Genetic Algorithm

Line Loss Calculation and Optimization in Low Voltage Lines with Photovoltaic Systems Using an Analytical Model and Quantum Genetic Algorithm

Line loss calculation model of low-voltage distribution network under harmonic and three-phase unbalance disturbances and its experimental validation

With the grid integration of distributed power sources and traction loads, the power quality problem of the power system has become more and more serious, aggravating the distribution network line losses, so it is important to study the calculation model of distribution network line loss under power quality disturbance in order to find loss reduction measures. This paper first theoretically derives the calculation model of line loss of low-voltage distribution network under separate disturbance of 2 common power quality problems, namely, harmonics and three-phase unbalance. Then, using the composite power quality disturbance decoupling method, the calculation model of line loss of low-voltage distribution network under the disturbance of harmonics and three-phase unbalance is derived, which improves the accuracy of line loss calculations. Finally, experiments are conducted for each part by Matlab/Simulink simulation tool to verify the correctness of the theoretical derivation.

Theoretical line loss calculation method for low-voltage distribution network via matrix completion and ReliefF-CNN

Line loss is directly responsible for the management profitability of the grid company. The traditional method of calculating the theoretical line loss for Low Voltage Distribution Networks (LVDN) necessitates more electrical parameters. which cannot be obtained easily. Besides, due to the backward communication conditions of LVDN, the problem of smart meter data missing is significant, which poses a challenge to an exact theoretical line loss calculation. In an attempt to solve the issues above, a theoretical line loss computation approach via matrix completion and ReliefF-convolutional neural network (CNN) for LVDN is proposed. Firstly, a feature weighting algorithm based on ReliefF is presented to analyze the relevance of the electrical parameters, which can be obtained easily. Secondly, a theoretical line loss calculation method is proposed for CNN-based. In the view of the data missing problem, a matrix completion method based on singular value thresholding (SVT) is introduced to obtain the high-precision data, in order to enhance the calculation accuracy of the theoretical line loss calculation. Finally, the proposed method is tested on the data sample of 789 LVDNs. The results show that comparing with CNN, back-propagation and other methods, the mean absolute percentage error (MAPE) of the presented method can reduce by more than 90%. When data missing, the MAPE of the proposed method can reduce by more than 95% compared with the method without considering the data completion.

New Approach to Evaluate the Energy Efficiency of Overhead Power Transmission Lines: Results of Theoretical and Experimental Research

This article describes a new approach to evaluating energy efficiency of overhead power transmission lines which is based on power transmission line losses calculation taking into account induction currents and heating in the supporting elements. We present the results of theoretical and experimental research of induction currents and heating evaluation in pylons of the overhead power transmission line. To find the flux linkage for induction currents, calculations using the Poisson equation for vector magnetic potential were carried out. The limiting values of induction currents and heating temperature are estimated using a graphical approach. The analysis of the power losses balance for a 500-kV power transmission line demonstrates considerable energy-saving benefits. The update of the previous conference paper is implying to compare energy efficiency of the overhead power transmission line for thermal and electric energy losses associated with induced currents and to conclude about their interchangeability. Additionally, it is resumed which using technical assumptions in the study. The research work might be of interest for design and modernization of overhead power transmission lines.

Distribution Network Line Loss Calculation Method Considering Distributed Photovoltaic Access

With access to a high proportion of distributed photovoltaics, the power quality and line loss of distribution networks have become the focus of power grid enterprises. Traditional line loss management does not consider the impact of distributed photovoltaic access, which leads to incomplete line loss calculation methods and management means of distribution network. Therefore, this paper establishes a simulation analysis model of high proportion distributed generation connected to the distribution network and puts forward the overall loss method of the distribution network through theoretical analysis. On this basis, the IEEE 34-node system is used to calculate the impact of different capacities and locations of distributed access on the voltage distribution and line loss of the entire distribution network. The example shows that there is a corresponding relationship between the access capacity of DG and the lowest network loss. When the access capacity of distributed generation is too large, the system’s network loss will increase. Therefore, it is necessary to reasonably select the access capacity of distributed generation. The method proposed in this paper is accurate, and can also take the actual limitations of existing photovoltaic access and developable photovoltaic capacity into account, so it has strong engineering practicability.

A Modular Hardware Design of an Intelligent Distributed Feeder Terminal Unit

The development of a new power system is proposing new requirements for the function of the feeder terminal unit (FTU), which is the core equipment of the distribution automation system. At the same time, the improvement of FTU intelligence brings a new solution to the problem of line loss calculation. Aiming at the problems of complex structure and low measurement accuracy of current FTU, a hardware scheme combining ADC sampling chip and high-performance MCU is proposed in this paper to realize the integrated application of energy measurement function. Moreover, it is equipped with a line loss calculation module to achieve high precision line loss calculation when the metering chip cannot meet the precision requirements. At the same time, the modular design effectively improves the operation reliability and function expansion of the terminal.

Monthly Probability Theoretical Line Loss Calculation Method of Low Voltage Distribution Network Based on Simultaneous Power and Electricity

Monthly Probability Theoretical Line Loss Calculation Method of Low Voltage Distribution Network Based on Simultaneous Power and Electricity

A real-time three-phase line loss calculation method for distribution network based on feeder terminal unit

Combined with the monitoring data of the new distribution network Feeder Terminal Unit (FTU), an innovative three-phase real-time line loss calculation method based on the feeder segment rather than the entire feeder as the basic calculation unit is proposed. This method uses the variable structure dissipative network theory, divides the feeder into feeder segments, and conducts mathematical modeling for each equipment in the segment based on the feeder segment. The detailed line loss of each equipment makes the line loss distribution in the system clear at a glance, which is convenient for operation and maintenance personnel to scientifically manage and carry out distribution network line loss analysis and calculation, and provides a favorable basis for further optimization of the distribution network system.

Continuous Line Loss Calculation Method for Distribution Network Considering Collected Data of Different Densities

In order to find the causes of statistical line loss abnormalities and propose better loss reduction strategies, it is necessary to improve the accuracy of theoretical line loss calculations. Since Distributed Generation (DG) access to the distribution network causes variability of power flow in the distribution network within a short period, the error of the traditional line loss calculation method increases. For the line loss calculation of medium-voltage distribution networks containing DGs with high-density collection data, a continuous line loss calculation method for the distribution network was proposed, aiming at improving the accuracy compared with the traditional line loss calculation method. The proposed method makes full use of the high-density collection data on the dispatch side and DG side, distributing the supply power to each load node by power to calculate real-time power flow, thus obtaining a more credible line loss value. The effectiveness and accuracy of the proposed method were verified in the IEEE 17-node distribution system.

Line Loss Interval Algorithm for Distribution Network with DG Based on Linear Optimization under Abnormal or Missing Measurement Data

Data collection is more difficult in distribution network than transmission networks since the structure of distribution networks is more complex. As a result, data could be partly abnormal or missing, which cannot completely describe the operation status of distribution network. In addition, access of distributed generation (DG) to distribution network further aggravates the variability of power flow in distribution network. The traditional deterministic line loss calculation method has some limitations in accurately estimating the line loss of distribution network with DG. A line loss interval calculation method based on power flow calculation and linear optimization is proposed, considering abnormal data collection and distribution network power flow variability. The linear optimization model is established according to sensitivity of line loss to the injected power and sensitivity of transmission power of first branch to the injected power. Introducing the scheduling information into the optimization model, a reliable line loss fluctuation interval can be obtained which actual line loss locates. The effectiveness of the proposed algorithm is verified in IEEE 33-bus distribution network system.

Research on Short-Term Low-Voltage Distribution Network Line Loss Prediction Based on Kmeans-LightGBM

Due to the lack of data quality in real production environment, the traditional line loss calculation method cannot be applied, thus through the investigation of various information systems’ operation in power supply enterprises, a short-term low-voltage distribution network line loss prediction algorithm based on Kmeans-LightGBM is proposed. Operating data quality evaluation system of low-voltage distribution network was set up based on Hadoop platform, the feature dimensions were expanded by feature engineering, then those with no multicollinearity and high correlation with the line loss were selected, data normalization was again performed, Kmeans clustering algorithm was used to cluster the area and then, LightGBM algorithm was used to predict the classes within the area of line loss. Finally, the line loss of the numerical inverse normalization was found and validated with Beijing Power Grid of a low-voltage distribution network. By comparison, the model’s prediction accuracy is found to be higher than BPNN, FOA-SVR and traditional LightGBM.

Line Loss Prediction of Distribution Network Based on BP Neural Network

Distribution network line loss calculation refers to the calculation of the electrical energy loss, which is generated by all components in a distribution network system in a given period of time. Distribution network, as the end of the power network, is directly connected with users; there are many equipment on the network; the system has impedance, electric energy in the process of conversion, transmission and distribution with a lot of loss, so the calculation of distribution network line loss has very important economic significance. In addition, with the development of power network construction, the rationality of distribution network topology design and the comparison of practical effects of various measures need the guidance of line loss calculation. Line loss and line loss rate is one of the main criteria to reflect the operation of distribution system. Reducing line loss of distribution system is very important for the effective use of power and economic operation of distribution system. In order to better find the effective reduction method and lay the foundation for the scientific establishment of linear contraction targets. This study uses a line loss calculation method based on BP neural network. The method uses the super matching property of the network to map the complex nonlinear relationship between the line loss and the characteristic variables and stores the evolution of the line loss changes with the changes of the structural and operational variables of the distribution line. On the basis of analyzing the theoretical methods, management methods, and various loss reduction measures of power loss calculation, this study also analyzes the status quo and existing problems of line loss analysis and calculation and collects data from line loss calculation and theoretical line loss calculation methods. This study discusses in detail the method and idea of the application of the improved neural network in the estimation of distribution network line loss, and it is used to predict the line loss in a certain area, and the prediction result is good.

Application Research of BP Neural Network Algorithm in Power Line Loss Calculation

In recent years, it is still a difficult problem to calculate the line loss of distribution system. The main reason is that China’s power system data is not perfect, the components are huge, the management function does not exist, the network structure is directly connected. Therefore, reducing the loss rate of power system has become an urgent problem for energy companies to solve. Developing effective methods for line loss reduction evidence and line loss assessment requires careful calculation and analysis of line loss, which ultimately contributes to and guides line loss management.

Loss reduction strategy and evaluation system based on reasonable line loss interval of transformer area

As the wiring of distribution network becomes more and more complex, it is difficult to calculate the theoretical line loss of low-voltage distribution transformer area and the evaluation index of transformer line loss is extensive. In this paper, a reasonable interval calculation model of line loss is established based on the data of electricity information acquisition system. Firstly, the collected data are processed in the image format, and then the line loss calculation model is established based on the convolutional neural network. This model can estimate the reasonable line loss interval according to the operation data of different transformers. On this basis, the line loss evaluation system is established and the loss reduction strategy of abnormal transformer is formed. The method in this paper can be used to evaluate the line loss level of distribution transformer area more accurately. It also can improve the quality and efficiency of line loss lean management and produce certain effect for electric energy conservation and improving economic benefit of power supply.

An online identification system of 10kV medium voltage line-variation relationship

The 10kV medium-voltage line transformer relation refers to the connection relation between the transformer (station area) and the 10kV distribution line. The real-time and accuracy of the 10kV medium-voltage line transformer relation is the premise to realize the accurate calculation of the line loss of 10kV line and the basis for the operation control of 10kV line. In this paper, an online identification system of 10kV mid-voltage line transformer relationship is proposed. Through the identification terminal of mid-voltage line transformer relationship, the analysis machine of mid-voltage line transformer relationship and the main station of line-transformer relationship identification, the relationship of 10kV mid-voltage line transformer can be accurately identified online and real-time, providing reliable basis for accurate calculation and operation control of line loss of 10kV line.

A Line Loss Calculation Method Based on Big Data and Load Curve

In this paper, a new technique line loss calculation method based on load curve is presented. First, the data is preprocessed and the outliers are removed. Then the load curve is analyzed, and the load current per day is fitted by polynomial approximation method, and the load current curve is obtained by nine-order fitting. Considering that the current at different time points may affect the fitting of the data, time sequencing is carried out to improve the fitting accuracy. Then for the resistance calculation, the voltage difference between the platform side and the user side and the platform side current are used to calculate, avoiding the use of line length which is difficult to measure in practice. This method makes full use of the available power network data, rearranges it, calculates it according to the continuous load curve, and gets more accurate and reliable results.

Comprehensive Analysis of Power Grid Energy Saving and Loss Reduction Based on Power Big Data Platform

Whether the original power data is accurate and complete is a key factor affecting the accuracy of line loss calculations. This research is based on a big data platform to obtain the distribution network model data, topology data, and operating data required for theoretical line loss calculation and technical high loss analysis. The power system analysis algorithm is combined with the big data analysis algorithm to automatically check the distribution network. To locate the high-loss links of the power grid to assist grid planners in their energy-saving and loss-reducing planning and transformation work.

A research on line loss calculation based on BP neural network with genetic algorithm optimization

In order to realize the calculation of the line loss of the distribution network with complex structure and low-voltage station area, this paper presents a line loss calculation method based on BP neural network with genetic algorithm optimization. The proposed method is based on the actual operation data of the distribution network. Firstly, build an error back propagation (BP) neural network model to compute the theoretical line loss of the distribution network, then use genetic algorithm (GA) to optimize the neural network and establish the GA-BP model. Based on the proposed model, the calculation demonstrates that the neural network line loss rate calculation model with genetic algorithm optimization shows better performance than the single BP neural network model, such as better nonlinear fitting ability and higher calculation accuracy. Therefore, the line loss calculation method proposed in this paper based on the BP neural network with the genetic algorithm optimization can improve the accuracy of the distribution network line loss rate calculation model.

Monitoring Technology of Power System Operation State Based on Stereo Sensing

In recent years, the development of computer technology, automation control technology and communication technology has provided new hardware and software support for the implementation of distribution network operation monitoring. In the daily production of the oil field, the reliability and stability of the power supply are the key links to ensure the completion of the production tasks of the oil field. This paper studies the problem of scene depth reconstruction in panoramic technology. On this basis, the panoramic depth map is combined with the panoramic image, and the three-dimensional panoramic characteristics are reconstructed from the visual and environmental aspects of the stereo perception model suitable for its performance. This paper develops an oilfield distribution network operation monitoring system based on stereo perception, and develops corresponding system management software. This paper first determines the mathematical model of the distribution network line loss calculation, and introduces the principle of GPRS technology to formulate a specific network plan for distribution network operation monitoring. Finally, based on the terminal data collection method of CDD-IDT / GPRS, the development of terminal system management software is finally completed. Field test results show that the stereoscopic perception-based oil field distribution network operation monitoring system developed in this paper has high accuracy of accident prediction, strong real-time performance, stable and reliable operation, and the average transmission time of each data in the stereoscopic perception based monitoring network transmission It is 1.88 seconds, which can be displayed immediately after pre-loading.

OPTİMAL AKTİF GÜÇ DAĞITIMI İÇİN KARŞIT ÖĞRENME TABANLI DİFERANSİYEL GELİŞİM ALGORİTMASI

The optimum operation problem of electrical energy generation systems is a difficult problem to solve with numeric methods in terms of the constraints it includes. Various optimization algorithms are frequently used in order to be able to obtain the acceptable solutions of these kinds of problems in short times. In recent years it is very common to improve these kinds of algorithms in order to be able to obtain more decisive and better solutions. In this study Opposite-based learning concept has been integrated into Differential Evolution Algorithm, which was applied to the solution of many problems successfully before, in two different ways. Two different problem solutions have been done in order to test the performances and the decisiveness of the developed algorithms. The first of these problems is the optimization of six multimodal test functions, and the second is the solution of the optimum power dispatch problem. IEEE 30 bus 6 generator system has been selected as the sample for the solution of the problem. The calculation of transmission line losses have been done by doing AC load flow with Newton Raphson method. Finally, the values obtained from the solutions of the two problems have been compared with the performances of the algorithms and the effects of the opposite-based learning concept on the optimization algorithms have been discussed.