Power Harmonic Emission Level Evaluation Based on Principal Component Analysis Regression Method

24 - Power Quality — Hamonics in Power Systems

The penetration of distributed generation (DG) scheme in modern power system is progressively increasing because of the call for environmental friendly energy resources. Photovoltaic (PV) has been identified as one of such energy resources which can provide reliable and efficient power supply when integrated with distribution network. The installation of a single site PV module is modelled in a bus bar of the 31-bus 330kV network of Power Holding Company of Nigeria (PHCN) to characterize and predict harmonic pattern therein and also to assess bus voltage disturbance in the network due to increase in harmonic emission level. The simulation results obtained using PCFLO version 6 programme platform indicates that the system voltage variation is dependent on harmonic emission level. In a bus bar the highest and constant non-sinusoidal current Total Harmonic Distortion (THD) of 29% flows in the neutral of the apparatus in the candidate bus where the non-linear load is installed irrespective of harmonic current source magnitude.

The development of the shipbuilding industry involves increasing the competitiveness of manufactured products, replacing obsolete electrical equipment, and increasing the efficiency of power supply systems. The introduction of the latest technologies reduces the weight and size of equipment, expands their functionality, but these technologies are based on nonlinear and asymmetrical power consumers, which causes a negative impact on the power grid. The power supply system of the Baltic Shipyard "Yantar" is characterized by a significant share of nonlinear, asymmetrical loads, often single-phase. An integrated approach to the analysis of the plant's power supply system included experimental studies of nonlinear power consumers, during which a high level of higher current harmonics (3rd, 5th and 7th orders) was established. One of the effective methods for reducing zero-sequence voltage asymmetry is to replace a transformer with a Y/Y0 winding connection diagram with a Δ/Y0 diagram. Circuit and technological solutions (separation of nonlinear loads to a separate bus system; increasing the phase of semiconductor converters; connecting a nonlinear load to a system with greater short-circuit power) and filtering devices (narrow-band filters, filter-balancing devices and active filters) are used to increase the efficiency of the power supply system when it operates under conditions of increasing distorting loads.

To ensure the functioning of the energy system, coordination and increase the efficiency of its parts need new control mechanisms. Generation, transmission and consumption of electricity needed control mechanisms that include integration of self-organizing power and heat supply systems, built on multi-agent principle. Also they must correspond intellectual basis, monitoring and accumulation. This includes effectiveness assessment of the state and analysis of technical, technological and organizational management mechanisms. One of the main parts is interaction principles of energy systems in accordance with European Community policy at various levels at liberalized electricity market. In most developed countries, demand management programs are widely used as a means of harmonizing the modes of generation and consumption in the power supply system. The main direct methods are set in the form of electricity tariffs. Indirect methods are set in the form of programs to manage electricity demand and the possibility of their application to manage electricity demand. Methods for estimating the unevenness of the daily schedule of electricity consumption and the factors influencing the technological environment are presented. The work aims at scientific and applied problem – finding methods of estimation and features of managing the demand for electricity. The use of the proposed estimation methods of electricity consumption influence non-uniformity on the level of power supplies system losses based on Frize QF power and optimization of consumers’ operation modes in the power supply system is considered. Approaches and optimization mechanisms of the daily electricity consumption on the example of a residential complex with the possibility of energy accumulation are offered

Principal Component Analysis (PCA) is a widely used dimensional reduction method that aims to find a low dimension sub space of highly correlated data for its major information to be used in further analysis. Machine learning methods based on PCA are popular in high dimensional data analysis, such as video and image processing. In video processing, the Robust PCA (RPCA), which is a modified method of the traditional PCA, has good properties in separating moving objects from the background, but it may have difficulties in separating those when light intensity of the background varies significantly in time. To overcome the difficulties, a modified PCA method, called Regression PCA (RegPCA), is proposed. The method is developed by combining the traditional PCA and regression approaches together, and it can be easily combined with RPCA for video processing. We focus the presentation of RegPCA with the combination of RPCA on video processing and find that it is more reliable than RPCA only. We use RegPCA to separate moving object from the background in a color video and get a better result than that given by RPCA. In the implementation, we first derive the explanatory variables by the background information. we then process a number of frames of the video and use those as a set of response variables. We remove the impact of the background by regressing the response against the explanatory variables by a regression model. The regression model provides a set of residuals, which can be further analyzed by RPCA. We compare the results of RegRPCA against those of RPCA only. It is evident that the moving objects can be completely removed from the background using our method but not in RPCA. Note that our result is based on a combination of RegPCA with RPCA. Our proposed method provides a new implementation of RPCA under the framework of regression approaches, which can be used to account for the impact of risk factors. This problem cannot be addressed by the application of RPCA only.

In this paper, a method for estimating the system harmonic impedance and harmonic emission level based on the pan-normal impedance cloud is presented. First of all, based on the basic principle of fluctuation method, it can be obtained that the key to estimate the system harmonic impedance is how to identify fluctuation ratio samples closer to the true value through theoretical analysis; Secondly, through the study of the probability distribution of fluctuation ratio, this paper proposes the characteristic of the pan-normal distribution meets the applicable conditions of normal cloud model, which can be used to calculate the digital features of impedance cloud by backward cloud generator; Finally, based on the 3En' Rules of cloud model, the filtering threshold of impedance is determined, then the system harmonic impedance and harmonic emission level can be estimated by filtering qualified samples. It proves the accuracy and effectiveness of the proposed method by the simulation of theoretical model and calculation of practical engineering examples.

Due to the widespread applications of new energy and the power electronic residential loads in the distribution network, it is very necessary to assess the harmonic current emission level since the impact of the collective harmonics cannot be ignored. The calculation of the harmonic impedance is a crucial task to determine the harmonic responsibilities at the point of common coupling (PCC). This paper presents a method to quantify the harmonic current responsibilities of the system side and customer side based on the impedance gathering trend, and then to calculate the emission level of the residential loads. This study has a sparked phenomenon on the evaluation of current emission level of the residential loads and can reflect the residential load harmonic emission characteristic precisely.

An individual power supply source is usually used for each group of identical magnetic elements in accelerators of charge particles. We discuss the power supply and control system on the basis of additional current shunts applied for the simultaneous supply of several groups of magnets in the positron storage ring of the Low-Energy Particle Toroidal Accumulator (LEPTA). Data on the use of the shunt of the linear and key converter are given. The option of the device of a power supply system with the transformation of the recuperated energy in the storage battery and supply from it of the precision power supply sources of the LEPTA correcting magnets is considered. A channel of the individual digital transformation of power supply system elements is given which allows one to build, together with a reverse precision converter, effective intellectual balanced power supply systems.

To solve the problems of high functional requirement, complex structure and poor versatility of manned spacecraft power supply and distribution ground test equipment, a modular universal ground power supply system (PSS) is designed. The functions of the system cover the functions of wire instruction opening, parameter measurement and state detection of the interface between the manned spacecraft and the ground equipment, and realize the universal and extensible configuration. This paper provides a general architecture design method for complex manned spacecraft power supply and distribution ground test system.

Robust principal component regression is development of principal component regression that applies robust method at principal component analysis and principal component regression analysis. Robust principal component regression does not only overcome multicollinearity problems, but also overcomes outlier problems. The robust methods used in this research are Minimum Covariance Determinant (MCD) that is applied when doing principal component analysis and Least Trimmed Squares (LTS) that is applied when doing principal component regression analysis. The case study in this research is Human Development Index (HDI) in Central Java in 2017 which is influenced by labor force participation rates, school enrollment rates, percentage of poor population, population aged 15 years and over who are employed, health facilities, gross enrollment rates, and net enrollment rates. The model of HDI in Central Java in 2017 using robust principal component regression MCD-LTS provides the most effective result for handling multicollinearity and outliers with Adjusted R2 value of 0.6913 and RSE value of 0.469. Keywords: Robust Principal Component Regression, Multicollinearity, Outliers, Minimum Covariance Determinant (MCD), Least Trimmed Squares (LTS), Human Development Index (HDI).

Robust principal component regression s-estimator is principal component regression that applies robust approach method at principal component analysis and s-estimator at principal component regression analysis. The aim of robust principal component regression s-estimator is to overcome multicollinearity problems in multiple linier regression Ordinary Least Square (OLS) and to overcome outlier problems in principal component regression so get the most effective model. Minimum Volume Ellipsoid (MVE) is one of the robust approach methods that applied when doing principal component analysis and S-Estimator is one of the estimation methods that applied when doing principal component regression analysis. The case in this study is the factors that influence the Number of Unemployment in Central Java in 2017. The model that provides the most effective result to handling multicolliniearity and ouliers in the case study Number of Unemployment in Central Java in 2017 is using robust principal component regression MVE-(S-Estimator) with Adjusted R2 value of 0.9615 and RSE value of 0.4073. Keywords: Robust Principal Component Regression S-Estimator, Multicollinearity, Outliers, Minimum Volume Ellipsoid (MVE), Number of Unemployment.

A severe interference problem caused by a large rectifier installation is studied. The interaction between harmonic emission level and power system impedance matching is described. An elegant solution involving corrective measures on each of the plants???customer, power system and communication circuits???are proposed. The dangers of creating new problems with single approaches are stressed, and the use of power current phase angles is illustrated in the analysis.

With the rapid growth of urban power transmission cable scale, the harmonic pollution in the high-voltage power grid is more transmitted to other power grids of different voltage levels, which makes the harmonic transmission more complicated, increases the harmonic emission level, and makes it difficult to quantitatively analyze and study the allowable value of users’ electrical pollution emission. Therefore, in this paper, by establishing the harmonic conduction model of the urban high-voltage power grid and considering the equivalent circuit of transformer and transmission cable in the urban power grid, the parameters of transmission cable harmonic transfer coefficient and the allowable emission value of power quality pollution of the urban power grid are deduced and quantitatively analyzed. Then the harmonic transmission and mutual influence of urban power network harmonics in power transmission cable are analyzed through examples, which is helpful to determine the allowable value of harmonic pollution emission scientifically and reasonably.

The threat of harmonic pollution has become increasingly serious with the rapid increase in the scale and complexity of distribution networks. However, the harmonic source variety of distribution networks and the phenomena about harmonic characteristics become vague after harmonic mixture because harmonic governance and responsibility division cause much inconvenience. To address this point, a distribution network mixed-harmonic separation method based on characteristic vector is developed in this study. This method realizes the division of the current working state, harmonic emission levels, and harmonic governance responsibility of each harmonic source by equivalent analysis and reverse thinking. The results are verified through an experiment.

Study on the prediction of stock price has great theoretical significance and application value. Traditional stock forecasting methods cannot fit and analysis highly nonlinear, multi-factors of stock market well, there are problems such as the prediction accuracy is not high, the slow training speed etc. In order to improve the accuracy of stock price forecasting, this paper proposes a prediction method of Elman neural network model based on principal component analysis method. In order to better compare results, establish structure same BP network and Elman network, forecast for stock data; then using principal component analysis filter factors of significant effect on stock prices, Elman neural network model based on principal component analysis method, and compared with single Elman network and BP networks prediction results. Result shows BP network convergence is relatively slow, train for a long time, and could converge to a local minimum; Elman network training time is short, the error bars for smoother and more stable performance; Elman neural network model based on principal component analysis with higher accuracy, faster network speeds.