Voltage Stability of Large Power Networks with a Large Amount of Wind Power

2005 ◽  
Vol 29 (5) ◽  
pp. 421-430 ◽  
Author(s):  
Vladislav Akhmatov
Keyword(s):  
Wind Turbines ◽  
Voltage Stability ◽  
Wind Farm ◽  
Electricity Consumption ◽  
Main Concern ◽  
Voltage Collapse ◽  
Power Network ◽  
Local Wind ◽  
Large Power ◽  
Grid Operation

The article presents results of voltage stability investigations carried out on a large power network model. Presumably, around 50 per cent of electricity consumption is covered by wind turbines and by local combined heat and power (CHP) units. In investigations, a distinction is made between local wind turbines and those in a large wind farm subject to the Grid Specifications of the transmission system operator (Eltra, 2000). The main concerns of maintaining power system operation are (i) a risk of significant power loss due to tripping of local units and (ii) a risk of overvoltage at the periphery of the power network. This is contrary to previous investigations predicting that the main concern should be a risk of voltage collapse (Bruntt et al., 1999). As demonstrated, voltage collapse does not occur, because local wind turbines will trip when abnormal grid operation is indicated. This “eliminates” the problem of voltage-collapse. On the other hand, this introduces new problems with regard to (i) establishing power reserves and (ii) protecting the power network against overvoltage.

Voltage Stability Analysis of a Distributed Network Incorporating Wind Power Resource

2011 ◽  
Vol 1 (1) ◽  
pp. 1-11
Author(s):  
Denis Juma ◽  
Bessie Monchusi ◽  
Josiah Munda ◽  
Adisa Jimoh
Keyword(s):  
South Africa ◽  
Stability Analysis ◽  
Voltage Stability ◽  
Wind Farm ◽  
Load Flow ◽  
Distributed Network ◽  
Power Network ◽  
Induction Generators ◽  
Doubly Fed Induction Generators ◽  
Doubly Fed

This paper investigates the impacts of a wind farm connected at Harterbeespoort substation in South Africa on voltage stability of the power network. The site wind speed was determined and analyzed for viability. A comparison is made between the use of Doubly-Fed Induction Generators and Self-excited Induction Generators driven by the wind turbines. The resulting P-V and Q-V curves from load flow studies are presented and analyzed. The models for this study were implemented in DigSILENT PowerFactory.

Dynamic Simulation of a Wind Farm With Variable Speed Wind Turbines

2003 ◽  
Author(s):  
E. Muljadi ◽  
C. P. Butterfield
Keyword(s):  
Wind Turbine ◽  
Wind Power ◽  
Wind Turbines ◽  
Wind Farm ◽  
Reactive Power ◽  
Power Network ◽  
Variable Speed ◽  
Power Capacity ◽  
Advantages And Disadvantages ◽  
The Impact

Wind power generation has increased very rapidly in the past few years. The total U.S. wind power capacity by the end of 2001 was 4,260 megawatts. As wind power capacity increases, it becomes increasingly important to study the impact of wind farm output on the surrounding power networks. In this paper, we attempt to simulate a wind farm by including the properties of the wind turbine, the wind speed time series, the characteristics of surrounding power network, and reactive power compensation. Mechanical stress and fatigue load of the wind turbine components are beyond the scope this paper. The paper emphasizes the impact of the wind farms on the electrical side of the power network. A typical wind farm with variable speed wind turbines connected to an existing power grid is investigated. Different control strategies for feeding wind energy into the power network are investigated, and the advantages and disadvantages are presented.

scholarly journals Stability Analysis of Wind Farm Connected Multi Machine System using Fuzzy Controller Based STATCOM and SVC

2019 ◽  
Vol 8 (4) ◽  
pp. 12346-12354
Keyword(s):  
Comparative Analysis ◽  
Wind Farm ◽  
Fuzzy Controller ◽  
Wind Farms ◽  
Main Concern ◽  
Large Power ◽  
Ground Fault ◽  
Facts Devices ◽  
Dynamic Time ◽  
Fault Clearance

Large capacity wind farm are used to fulfil the demand of power now days. Stability of these wind farms is the main concern when integrating with the large power system. FACTS devices are employed with the system to advance the dynamic time responses of the system. In this paper a comparative analysis of STATCOM and SVC has been done. At the place of conventional controllers like P, PI, PID fuzzy logic control (FLC) has been used in the FACTS devices used. These FACTS devices are used to improve the power quality of the overall system. To inspect the system performance and analyze the behavior of the system a three phase to ground fault has been taken into account at two different locations, the software used for modelling and simulation is MATLAB/Simulink. Results demonstrate damping and oscillations of Fuzzy controlled STATCOM and SVC based system.The comparative analysis shows that the system with FLC based STATCOM has better performance than the FLC based SVC and fast fault clearance.

scholarly journals A statistical jacobian application for power system optimization of voltage stability

2019 ◽  
Vol 13 (1) ◽  
pp. 331 ◽  
Author(s):  
Raja Masood Larik ◽  
Mohd. Wazir Mustafa ◽  
Manoj Kumar Panjwani
Keyword(s):  
Power Systems ◽  
Power System ◽  
Optimal Power Flow ◽  
Voltage Stability ◽  
Stability Margin ◽  
Singular Values ◽  
System Optimization ◽  
Load Flow ◽  
Voltage Collapse ◽  
Large Power

<p>Despite a tremendous development in optimal power flow (OPF), owing to the obvious complexity, non-linearity and unwieldy size of the large interconnected power systems, several problems remain unanswered in the existing methods of OPF. Seizing specific topics for maximizing voltage stability margin and its implementation, a detailed literature survey discussing the existing methods of solution and their drawbacks is presented in this research. The phenomenon of voltage collapse in power systems, methods to investigate voltage collapse, and methods related to voltage stability are briefly surveyed. Finally, the study presents a statistical method for analyzing a power system through eigenvalue analysis in relation to the singular values of the load flow Jacobian. Future study may focus on changes in theories in conjunction with large power systems.</p>

Dynamic Simulation of a Wind Farm With Variable-Speed Wind Turbines

2003 ◽  
Vol 125 (4) ◽  
pp. 410-417
Author(s):  
E. Muljadi ◽  
C. P. Butterfield
Keyword(s):  
Wind Turbine ◽  
Wind Power ◽  
Wind Turbines ◽  
Wind Farm ◽  
Reactive Power ◽  
Power Network ◽  
Variable Speed ◽  
Power Capacity ◽  
Advantages And Disadvantages ◽  
The Impact

Wind power generation has increased very rapidly in the past few years. The total U.S. wind power capacity by the end of 2002 was 4,685 megawatts. As wind power capacity increases, it becomes increasingly important to study the impact of wind farm output on the surrounding power networks. In this paper, we attempt to simulate a wind farm by including the properties of the wind turbine, the wind speed time series, the characteristics of surrounding power network, and reactive power compensation. Mechanical stress and fatigue load of the wind turbine components are beyond the scope this paper. The paper emphasizes the impact of the wind farms on the electrical side of the power network. We investigate a typical wind farm with variable-speed wind turbines connected to an existing power grid. We also examine different control strategies for feeding wind energy into the power network and present the advantages and disadvantages.

scholarly journals Temperature and Wind Distribution Effects on Wind Energy Production in Adrar Region (Southern Algeria)

2021 ◽  
Vol 16 (8) ◽  
pp. 1473-1477
Author(s):  
Miloud Benmedjahed ◽  
Abdeldjalil Dahbi ◽  
Abdelkader Hadidi ◽  
Samir Mouhadjer
Keyword(s):  
Wind Energy ◽  
Wind Turbines ◽  
Energy Production ◽  
Wind Farm ◽  
Electricity Consumption ◽  
Electricity Production ◽  
Effect Of Temperature ◽  
Short Period ◽  
Monthly Period ◽  
Wind Distribution

The hottest transitions occur in the summer, as we notice during this period the peak of electricity consumption in Adrar, where the electricity network must use all kinds of energy, especially the wind energy produced by Cabertein wind farm. We evaluated the effect of temperature and wind distribution on the energy produced by one of Gamesa G52 wind turbines, and this was done by studying the wind distribution and determining the number of hours per year according to five cases. Finally, to estimate the monthly produced energy, we used a logical temperature equation, and then we determined the seasonal and annual energy. Low winds are the only reason why wind turbines are unable to produce electricity for a monthly period ranging from 152 An hour (May) to 274 hours (September), meaning that the seasonal production stop, for this reason, ranges between 590 hours (spring) and 779 hours (summer), with an average of 2736 hours per year, while temperatures did not constitute an obstacle to electricity production except. In three months for a short period of 2 hours (June and July) and 22 hours (August), affecting production in the summer season, with an estimated time of 26 hours.

scholarly journals Feedforward Artificial Neural Network for Predicting Voltage Stability Indices in Power Systems

2019 ◽  
Vol 8 (3S) ◽  
pp. 47-54
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Voltage Stability ◽  
Test System ◽  
Stability Control ◽  
Main Concern ◽  
Voltage Collapse ◽  
Artificial Neural ◽  
Voltage Stability Control ◽  
Stability Indices

Several electricity failures associated with the voltage stability incident have appeared in a few countries. Nowadays, main concern towards voltage stability control and prediction is no longer crucial, however significant awareness is arising to sustain power system’s stability to conceal recurrence of major blackouts. Numerous types of line voltage stability indices (LVSI) being appointed to validate the weakest lines in IEEE 30-Bus test system. Besides that, LVSI is being forecasted by Feedforward Back Propagation Artificial Neural Network (FFBPNN) in order to recognize the voltage stability in IEEE 30-Bus test system. The calculated indices by using LVSI and forecasted indices by using FFBPNN are realistically applicable to discover the voltage collapse event in the system. The actual output for the VCPI(Power) in line 2-5 is 1.0459, while the predicted VCPI(Power) by using FFBPNN is 1.0459 with 3 seconds training time with 0% error percentage. Generally, the voltage collapse event has been successfully proven based on the capability of VCPI(Power). Therefore, necessary measures are capable to be performed by the power system operators to evade voltage collapse events occurred.

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