Consideration of the influence of supports in modeling the electromagnetic fields of 25 kV traction networks under emergency conditions

Single-phase 25 kV traction networks of electrified alternating current(AC)railways create electromagnetic fields(EMFs)with significant levels of intensity.The most intense magnetic fields occur when short circuits exist between the contact wire and rails or ground.Despite the short duration of exposure,they can adversely affect electronic devices and induce significant voltages in adjacent power lines,which is dangerous for operating personnel.Although numerous investigations have focused on modeling the EMF of traction networks and power lines,the challenge of determining the three-dimensional electromagnetic fields near metal supports during the flow of a short-circuit current through them is yet to be resolved.In this case,the field has a complex spatial structure that significantly complicates the calculations of intensities.This study proposes a methodology,algorithms,software,and digital models for determining the EMF in the described emergency scenarios.During the modeling process,the objects being studied were represented by segments of thin wires to analyze the distribution of the electric charge and calculate the intensities of the electric and magnetic fields.This approach was implemented in the Fazonord software,and the modeling results show a substantial increase in EMF levels close to the support,with a noticeable decrease in the levels as the distance from it increases.The procedure implemented in the commercial software Fazonord is universal and can be used to determine electromagnetic fields at any electrical power facility that includes live parts of limited length.Based on the proposed procedure,the EMF near the supports of overhead power lines and traction networks of various designs could be determined,the EMF levels at substations can be calculated,and the influence of metal structures located near traction networks,such as pedestrian crossings at railway stations,can be considered.

The Application of Combination Forecasting Model in Forecasting the Total Power of Agricultural Machinery in Heilongjiang Province

Agricultural machinery total power is an important index to reflect and evaluate the level of agricultural mechanization. Firstly,we respectively made use of exponential model,grey forecasting and BP neural network to construct models depending on historical data of agricultural machinery total power of Heilongjiang Province; secondly,we constructed the combined forecasting models that respectively based on divergence coefficient method,quadratic programming and weight distribution of Shapley value. Fitting results showed that the various combination forecasting model is superior to the single models. Finally,we applied the combination forecasting model which based on the weight distribution method of Shapley value to forecast Heilongjiang agricultural machinery total power,and it would provide some reference to the development and program for power of agriculture machinery.

Mathematical model of electric hydraulic and powered support control system at a plough mining face

Given the actual working of a fully mechanized plough at a mining face, we have proposed a formula for running constraints between powered supports and a coal plough under assumed geological conditions of the coal face and, on this basis, established an automatic control model of powered supports for the coal plough face. We introduced the working principle of the powered support control system of the plough at the mining face. We established three advanced characteristics of this control system： response speed, reliability and easy maintenance of the system. As well, we briefly introduced, the principal function of primary and subordinate controllers and the realization of the communication system by a Single Bus. Ten controllers were constructed and tested in our laboratorium. The results show that the control model is practical and meets actual conditions. It provides a theoretical basis for designing a comouter control system for a oowered support system of a plough at a mining face.

EMS Supporting System for Dispatching Automation in Northeast Power Network

The EMS supporting system of thesecond phase extension project for NortheastElectric Network dispatching automationsystem, co-developed by Electric PowerResearch Institute. Ministry of ElectricPower, and Northeast China Electric PowerGroup, is an open type, object oriented CC-2000 EMS/DMS supporting system withChinese proprietary copyright and anadvanced international level. It passed thetechnical appraisal of Ministry of ElectricPower in Oct. 1996. This EMS supportingsystem includes four parts f managementenvironment of the system operation.database management system. big object forpower system, man-machine interface. Theexperience of developing and operationindicates that the EMS supporting system haspowerful functions, the performance index isvery high, the operation is stable and reliable.the ability of supporting EMS/DMS is morepowerful than the first phase system. Thedevelopment work of the super applicationsoftware of Northeast Power Network EMS(Energy Management System) will befinished in 1997 on the supporting system.thereby an integrated and open EMS of ourcountry’s own copyright will be completed.

A Multi-mode Electronic Load Sensing Control Scheme with Power Limitation and Pressure Cut-off for Mobile Machinery

In mobile machinery,hydro-mechanical pumps are increasingly replaced by electronically controlled pumps to improve the automation level,but diversified control functions(e.g.,power limitation and pressure cut-off)are integrated into the electronic controller only from the pump level,leading to the potential instability of the overall system.To solve this problem,a multi-mode electrohydraulic load sensing(MELS)control scheme is proposed especially considering the switching stability from the system level,which includes four working modes of flow control,load sensing,power limitation,and pressure control.Depending on the actual working requirements,the switching rules for the different modes and the switching direction(i.e.,the modes can be switched bilaterally or unilaterally)are defined.The priority of different modes is also defined,from high to low:pressure control,power limitation,load sensing,and flow control.When multiple switching rules are satisfied at the same time,the system switches to the control mode with the highest priority.In addition,the switching stability between flow control and pressure control modes is analyzed,and the controller parameters that guarantee the switching stability are obtained.A comparative study is carried out based on a test rig with a 2-ton hydraulic excavator.The results show that the MELS controller can achieve the control functions of proper flow supplement,power limitation,and pressure cut-off,which has good stability performance when switching between different control modes.This research proposes the MELS control method that realizes the stability of multi-mode switching of the hydraulic system of mobile machinery under different working conditions.

Characteristics and prospect of geothermal industry in China under the“dual carbon”target

Geothermal energy utilization in China had been promoted actively during the 13^(th)Five-Year Plan period(2016-2020),with resultant achievements showing unique Chinese characteristics.Buildings(measured by areas)heated/cooled by intermediate-to-deep geothermal energy increased more rapidly than those by shallow geothermal energy.Geothermal power generation was restricted by the distribution of the resource and the sufficiency of local power supply.With the proposition of“dual carbon goal”by the central government of China and the coming era of great development of renewable energy,geothermal energy will be provided more development opportunities in room heating/cooling and power generation in the country ever than before.However,tackling technology bottlenecks and introduction of appropriate policy support are still urgently needed for nurturing a healthy environment for geothermal industry.Analysis suggests that a near-to medium-term development of geothermal energy shall be focused on a comprehensive and efficient utilization both through heating/cooling and power generation.Room heating/cooling by intermediate-to-deep and shallow geothermal energy shall be promoted nationwide according to local resource endowment and economic conditions.Geothermal power generation in Yunnan and Tibet shall be pushed forward in an orderly way.For medium-and long-term development,focus shall be put on power generation by using low to medium temperature geothermal energy and hot dry rocks.The"hot spring+"model shall be adapted in steps on a regular basis.To achieve these,measures including attaching importance to tackling key technologies,promoting standards for geothermal energy development and utilization,strengthening geothermal energy exploration and evaluation,and seeking for necessary policy support shall be taken.

Weather Prediction With Multiclass Support Vector Machines in the Fault Detection of Photovoltaic System

Since the efficiency of photovoltaic(PV) power is closely related to the weather,many PV enterprises install weather instruments to monitor the working state of the PV power system.With the development of the soft measurement technology,the instrumental method seems obsolete and involves high cost.This paper proposes a novel method for predicting the types of weather based on the PV power data and partial meteorological data.By this method,the weather types are deduced by data analysis,instead of weather instrument A better fault detection is obtained by using the support vector machines(SVM) and comparing the predicted and the actual weather.The model of the weather prediction is established by a direct SVM for training multiclass predictors.Although SVM is suitable for classification,the classified results depend on the type of the kernel,the parameters of the kernel,and the soft margin coefficient,which are difficult to choose.In this paper,these parameters are optimized by particle swarm optimization(PSO) algorithm in anticipation of good prediction results can be achieved.Prediction results show that this method is feasible and effective.

Predicting of Power Quality Steady State Index Based on Chaotic Theory Using Least Squares Support Vector Machine

An effective power quality prediction for regional power grid can provide valuable references and contribute to the discovering and solving of power quality problems. So a predicting model for power quality steady state index based on chaotic theory and least squares support vector machine (LSSVM) is proposed in this paper. At first, the phase space reconstruction of original power quality data is performed to form a new data space containing the attractor. The new data space is used as training samples for the LSSVM. Then in order to predict power quality steady state index accurately, the particle swarm algorithm is adopted to optimize parameters of the LSSVM model. According to the simulation results based on power quality data measured in a certain distribution network, the model applies to several indexes with higher forecasting accuracy and strong practicability.

The Effect of Structural Empowerment on Psychological Empowerment in Private Health Care in Biskra, Algeria

The approach of employees empowerment is one of the modem approaches in the field of human resources management. According to many studies, it has dimensions and can not be separated structural empowerment on psychological empowerment. This study aimed to recognize effect of structural empowerment in motivating psychological empowerment for employees in the private health sector in Biskra （Okba Ben Nail Clinic, Errazi Clinic, ziadinne Clinic, Ennoor Clinic, Ibn Sina Clinic, AI-Quds clinic, Elihsen clinic, Ibn Rushd clinic, Chifa clinic, ziben clinic, and elkothben clinic）. The study problem is concentrated to find answers of the following questions： what is the level of structural and psychological empowerment practiced by employees of private health sector in Biskra, how much impact structural empowerment （opportunity, support, and formal power） has on psychological empowerment （meaning, competence, self-determination, and impact） in private health sector in Biskra？ To achieve the objectives of this study and answers on it questions, data were collected through questionnaire, in all （59） participants answered it. The results here, which form part of a larger stud）＇, suggest that only opportunity and formal power had significant effect on psychological empowerment, when the availability of all subscales of structural empowerment have no effect on meaning of work.

Forecasting the Demand of Short-Term Electric Power Load with Large-Scale LP-SVR

This research studies short-term electricity load prediction with a large-scalelinear programming support vector regression (LP-SVR) model. The LP-SVR is compared with other three non-linear regression models: Collobert’s SVR, Feed-Forward Neural Networks (FFNN), and Bagged Regression Trees (BRT). The four models are trained to predict hourly day-ahead loads given temperature predictions, holiday information and historical loads. The models are trained on-hourly data from the New England Power Pool (NEPOOL) region from 2004 to 2007 and tested on out-of-sample data from 2008. Experimental results indicate that the proposed LP-SVR method gives the smallest error when compared against the other approaches. The LP-SVR shows a mean absolute percent error of 1.58% while the FFNN approach has a 1.61%. Similarly, the FFNN method shows a 330 MWh (Megawatts-hour) mean absolute error, whereas the LP-SVR approach gives a 238 MWh mean absolute error. This is a significant difference in terms of the extra power that would need to be produced if FFNN was used. The proposed LP-SVR model can be utilized for predicting power loads to a very low error, and it is comparable to FFNN and over-performs other state of the art methods such as: Bagged Regression Trees, and Large-Scale SVRs.

Methods for measuring and calculating the external load of powered supports

Taking the chock shield supports as the object of study, methods formeasuring and calculating the external load of powered supports were discussed. Selecting the angleparameters as variables, the simple formulae of interactive computation with respect to the workangles of a powered support were deduced and verified by an example. Furthermore, the formulaedetermining the magnitude, direction and action point of the external load were put forward. Theinvestigation results have provided a sound basis for the software design of the intelligentinstrument for load measuring of powered supports.

Upper Lillooet River Hydroelectric Project： The Challenges of Constructing a Power Tunnel for Run-of-River Hydro Projects in Mountainous British Columbia

The Upper Lillooet River Hydroelectric Project （ULHP） is a run-of-river power generation scheme located near Pemberton, British Columbia, Canada, consisting of two separate hydroelectric facilities （HEFs） with a combined capacity of 106.7 MW. These HEFs are owned by the Upper Lillooet River Power Limited Partnership and the Boulder Creek Power Limited Partnership, and civil and tunnel construction was completed by CRT-ebc. The Upper Lillooet River HEF includes the excavation ofa 6 m wide by 5.5 m high and approximately 2500 m long tunnel along the Upper Lillooet River Valley. The project is in a moun- tainous area; severe restrictions imposed by weather conditions and the presence of sensitive wildlife species constrained the site operations in order to limit environmental impacts. The site is adjacent to the Mount Meager Volcanic Complex, the most recently active volcano in Western Canada. Tunneling conditions were very challenging, including a section through deposits associated with the most recent eruption from Mount Meager Volcanic Complex （-2360 years before the present）. This tunnel section included welded breccia and unconsolidated deposits composed of loose pumice, organics （that represent an old forest floor）, and till, before entering the underlying tonalite bedrock. The construction of this section of the tunnel required cover grouting, umbrella support, and excavation with a combination of road header, hydraulic hammer, and drilling-and-blasting method. This paper provides an overview of the project, a summary of the key design and construction schedule challenges, and a description of the successful excavation of the tunnel through deposits associated with the recent volcanic activity.

A Decision Support System for Selection of Solar Power Plant Locations by Applying Fuzzy AHP and TOPSIS: An Empirical Study

The objective of this research is to propose a decision support system for avoiding flood on solar power plant site selection. Methodologically, the geographic information system (GIS) is used to determine the optimum site for a solar power plant. It is intended to integrate the qualitative and quantitative variables based upon the adoption of the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model. These methods are employed to unite the environmental aspects and social needs for electrical power systematically. Regarding a case study of the choice of a solar power plant site in Thailand, it demonstrates that the quantitative and qualitative criteria should be realized prior to analysis in the Fuzzy AHP-TOPSIS model. The fuzzy AHP is employed to determine the weights of qualitative and quantitative criteria that can affect the selection process. The adoption of the fuzzy AHP is aimed to model the linguistic unclear, ambiguous, and incomplete knowledge. Additionally, TOPSIS, which is a ranking multi-criteria decision making method, is employed to rank the alternative sites based upon overall efficiency. The contribution of this paper lies in the evolution of a new approach that is flexible and practical to the decision maker, in providing the guidelines for the solar power plant site choices under stakeholder needs: at the same time, the desirable functions are achieved, in avoiding flood, reducing cost, time and causing less environmental impact. The new approach is assessed in the empirical study during major flooding in Thailand during the fourth quarter of 2011 to 2012. The result analysis and sensitivity analysis are also presented.

A Short-Term PV Power Forecasting Method Using a Hybrid Kmeans-GRA-SVR Model under Ideal Weather Condition

With the continuous increase of solar penetration rate, it has brought challenges to the smooth operation of the power grid. Therefore, to make photovoltaic power generation not affect the smooth operation of the grid, accurate photovoltaic power prediction is required. And short-term forecasting is essential for the deployment of daily power generation plans. In this paper, A short-term photovoltaic power generation forecast method based on K-means++, grey relational analysis (GRA) and support vector regression (SVR) (Hybrid Kmeans-GRA-SVR, HKGSVR) was proposed. The historical power data was clustered through the multi-index K-means++ algorithm. And the similar days and the nearest neighbor similar day of the prediction day were selected by the GRA algorithm. Then, similar days and nearest neighbor similar days were used to train SVR to obtain an accurate photovoltaic power prediction model. Under ideal weather, the average values of MAE, RMSE, and R2 were 0.8101 kW, 0.9608 kW, and 99.66%, respectively. The average computation time was 1.7487 s, which was significantly better than the SVR model. Thus, the demonstrated numerical results verify the effectiveness of the proposed model for short-term PV power prediction.

A Temporary Frequency Response Strategy Using a Voltage Source-Based PermanentMagnet Synchronous Generator and Energy Storage Systems

Energy storage systems(ESS)and permanent magnet synchronous generators(PMSG)are speculated to be able to exhibit frequency regulation capabilities by adding differential and proportional control loops with different control objectives.The available PMSG kinetic energy and charging/discharging capacities of the ESS were restricted.To improve the inertia response and frequency control capability,we propose a short-term frequency support strategy for the ESS and PMSG.To this end,the weights were embedded in the control loops to adjust the participation of the differential and proportional controls based on the system frequency excursion.The effectiveness of the proposed control strategy was verified using PSCAD/EMTDC.The simulations revealed that the proposed strategy could improve the maximum rate of change of the frequency nadir and maximum frequency excursion.Therefore,it provides a promising solution of ancillary services for frequency regulation of PMSG and ESS.

Application of artificial intelligent systems for real power transfer allocation

The application of various artificial intelligent(AI) techniques,namely artificial neural network(ANN),adaptive neuro fuzzy interface system(ANFIS),genetic algorithm optimized least square support vector machine(GA-LSSVM) and multivariable regression(MVR) models was presented to identify the real power transfer between generators and loads.These AI techniques adopt supervised learning,which first uses modified nodal equation(MNE) method to determine real power contribution from each generator to loads.Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques.The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of various AI methods compared to that of the MNE method.

Improved AVOA based on LSSVM for wind power prediction

Improving the prediction accuracy of wind power is an effective means to reduce the impact of wind power on power grid.Therefore,we proposed an improved African vulture optimization algorithm(AVOA)to realize the prediction model of multi-objective optimization least squares support vector machine(LSSVM).Firstly,the original wind power time series was decomposed into a certain number of intrinsic modal components(IMFs)using variational modal decomposition(VMD).Secondly,random numbers in population initialization were replaced by Tent chaotic mapping,multi-objective LSSVM optimization was introduced by AVOA improved by elitist non-dominated sorting and crowding operator,and then each component was predicted.Finally,Tent multi-objective AVOA-LSSVM(TMOALSSVM)method was used to sum each component to obtain the final prediction result.The simulation results show that the improved AVOA based on Tent chaotic mapping,the improved non-dominated sorting algorithm with elite strategy,and the improved crowding operator are the optimal models for single-objective and multi-objective prediction.Among them,TMOALSSVM model has the smallest average error of stroke power values in four seasons,which are 0.0694,0.0545 and 0.0211,respectively.The average value of DS statistics in the four seasons is 0.9902,and the statistical value is the largest.The proposed model effectively predicts four seasons of wind power values on lateral and longitudinal precision,and faster and more accurately finds the optimal solution on the current solution space sets,which proves that the method has a certain scientific significance in the development of wind power prediction technology.

FLUID INDUCED HYDRAULIC SYSTEM VIBRATIONOF POWERED SUPPORT

Fluid and solid interaction analysis of hydraulic support under the coming pressure of roof rocks was presented. The mathematical model of the system was proposed and numerical studies by the character line method were carried out.

Automatic lifting system design and application of large load powered support test rig

This paper presented a design of an automatic lifting system. It is used for large load powered support and improves the old method wherein powered support lifting depends on manual control. This system applies a high accuracy gear shunt motor to match the flow for 4 lifting cylinders, and also allocates bypass throttles to realize automatic lifting. Through the dis- placement sensor feedback the height deviation among 4 lifting cylinders during the whole lifting process, when the deviation is up to the sitting value, the corresponding bypass throttle is operated immediately to reduce the deviation, so that the moving platform of the powered support would not be stuck. Through real application, it is shown that this system can realize automatic lifting of powered support; the lifting speed is controlled between 5 and 10 mm/s, and the final aligning accuracy is up to 1 mm.

Numerical Methods for Safeguarding the Performance of the Quenching Process

A new numerical technique for testing and evaluation of quenching media and quenching systems is outlined. The measured time-temperature samples as a result of cooling curve test are analyzed by the new software developed, in order to characterize quantitatively the quenchants. The method applied is based on Fourier analysis. Examples for evaluation and comparison of cooling performance of quenchants are presented the applicability of the computational technique.