scholarly journals Analysis of Voltage Rise Phenomena in Electrical Power Network With High Concentration of Renewable Distributed Generations

2022 ◽  
Author(s):  
AYODEJI AKINYEMI ◽  
Kabeya Musasa ◽  
Innocent Davidson
Keyword(s):  
Power System ◽  
Control Strategy ◽  
Power Flow ◽  
Electrical Power ◽  
Test System ◽  
Distribution Grid ◽  
High Concentration ◽  
Case Scenario ◽  
Worst Case ◽  
Voltage Rise

Abstract The increasing penetration levels of Renewable Distributed Generation (RDG) into power system have proven to bring both positive and negative impacts. The occurrence of under voltage at the far end of a conventional Distribution Network (DN) may not raise concern anymore with RDGs integration into the power system. However, a high penetration of RDG into power system may cause problems such as voltage rise or over-voltage and reverse power flows at the Point of Common Coupling (PCC) between RDG and DN. This research paper presents the voltage rise and reverse power flow effects in power system with high concentration of RDG. The analysis is conducted on a sample DN, i.e., IEEE 13-bus test system, with RDG by considering the most critical scenario such as low power demand and peak power injection to DN from RDG. The Simulations are carried out using MATLAB/Simulink software, a mathematical model of a distribution grid, integrating RDG is developed for studying the effects of voltage rise and bidirectional flow of power. Furthermore, a control strategy is proposed to be installed at PCC of the DN to control/or mitigate the voltage rise effects and to limit the reverse power flow when operating in a worst critical scenario of minimum load and maximum generation from RDG. The proposed control strategy also mitigates the voltage-current harmonic signals, improve the power factor, and voltage stability at PCC. Finally, recommendations are provided for the utility and independent power producer to counteract the effects of voltage rise at PCC. The study demonstrated that, PCC voltage can be sustained with a high concentration of RDG during a worst-case scenario without a reverse power flow and voltage rise beyond grid code limits.

The Study of Switching Overvoltages under Power System Restoration Scenario Using Extended Delta-Bar-Delta Algorithm

2013 ◽  
Vol 14 (3) ◽  
pp. 219-230 ◽  
Author(s):  
Iman Sadeghkhani ◽  
Abbas Ketabi ◽  
Rene Feuillet
Keyword(s):  
Power System ◽  
New England ◽  
Random Search ◽  
Test System ◽  
Power Equipment ◽  
Case Scenario ◽  
Worst Case ◽  
Power System Restoration ◽  
System Restoration ◽  
Artificial Neural Network Ann

Abstract This paper presents an intelligent approach to evaluate switching overvoltages during power equipment energization. Switching action is one of the most important issues in power system restoration schemes. This action may lead to overvoltages that can damage some equipment and delay ‎power system restoration. In this work, transient overvoltages caused by power equipment energization are analyzed and estimated using artificial neural network (ANN)-based approach. Three learning algorithms, delta-bar-delta (DBD), extended delta-bar-delta (EDBD), and directed random search (DRS), were used to train the ANNs. In the cases of transformer and shunt reactor energization, ANNs are trained with the worst case scenario of switching angle and remanent flux which reduce the number of required simulations for training ANN. Also, for achieving good generalization capability for developed ANN, equivalent parameters of the network are used as ANN inputs. The simulated results for a partial of 39-bus New England test system, ‎show that the proposed technique can estimate the peak values and ‎duration of switching overvoltages with good accuracy and EDBD algorithm presents best performance.

Investigation of Combined SVC and TCSC versus IPFC in Enhancing Power System Static Security

2018 ◽  
Vol 40 ◽  
pp. 119-135 ◽  
Author(s):  
Elutunji Buraimoh ◽  
Funso Kehinde Ariyo ◽  
Micheal Omoigui ◽  
Innocent Ewaen Davidson
Keyword(s):  
Power Systems ◽  
Power System ◽  
Transmission Line ◽  
Power Flow ◽  
Electrical Power ◽  
Severity Index ◽  
Test System ◽  
Security Assessment ◽  
Facts Devices ◽  
Static Security

Electrical power systems are often required to operate at full loading capacity due to ever increasing demand and transmission line contingencies with limited grid expansion. This results in line overload and operating near system limit, thereby threatening system security. Utilization of existing system can be achieved using Flexible Alternating Current Transmission System (FACTS) devices without violating system limits. This research investigation involves static security assessment of a modelled IEEE 30-bus test system in MATLAB/SIMULINK/PSAT environment. The security status with the incorporation of combined Static Var Compensator (SVC), Thyristor Controlled Series Compensator (TCSC) and Interline Power Flow Controller (IPFC) were determined. Prior to this, Contingency Severity Index (CSI) based on Performance Index (PI) of Voltage and Active Power was employed to determine the optimal location of the FACTS devices. Sequential Quadratic Programming (SQP) was applied to determine the optimal sizing/percentage compensation of FACTS. Subsequently, power system with and without the incorporation of FACTS devices were modelled. The ability of the compensated system to withstand credible transmission line contingencies without violating the normal operating limits (bus voltage and line thermal) was examined and presented. The paper presents how combined SVC/TCSC and an IPFC aided the power system to boost its steady state security in the face of possible line contingencies.

scholarly journals Radial Basis Function Neural Network Application to Power System Restoration Studies

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Iman Sadeghkhani ◽  
Abbas Ketabi ◽  
Rene Feuillet
Keyword(s):  
Neural Network ◽  
Power System ◽  
Radial Basis Function ◽  
Basis Function ◽  
Test System ◽  
Case Scenario ◽  
Worst Case ◽  
Power System Restoration ◽  
Radial Basis ◽  
System Restoration

One of the most important issues in power system restoration is overvoltages caused by transformer switching. These overvoltages might damage some equipment and delay power system restoration. This paper presents a radial basis function neural network (RBFNN) to study transformer switching overvoltages. To achieve good generalization capability for developed RBFNN, equivalent parameters of the network are added to RBFNN inputs. The developed RBFNN is trained with the worst-case scenario of switching angle and remanent flux and tested for typical cases. The simulated results for a partial of 39-bus New England test system show that the proposed technique can estimate the peak values and duration of switching overvoltages with good accuracy.

scholarly journals A Parallel Implementation of Unscheduled Flow Control in Interconnected Power Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-19
Author(s):  
G. Ozdemir Dag ◽  
Mustafa Bagriyanik
Keyword(s):  
Power Systems ◽  
Power System ◽  
Parallel Computation ◽  
High Performance ◽  
Power Flow ◽  
Parallel Implementation ◽  
Computation Time ◽  
Test System ◽  
Fuzzy Decision Making ◽  
Optimization Approach

The unscheduled power flow problem needs to be minimized or controlled as soon as possible in a deregulated power system since the transmission systems are mostly operated at their power-carrying limits or very close to it. The time spent for simulations to determine the current states of all the system and control variables of the interconnected power system is important. Taking necessary action in case of any failure of equipment or any other occurrence of an undesired situation could be critical. Using supercomputing facilities and parallel computing techniques together decreases the computation time greatly. In this study, a parallel implementation of a multiobjective optimization approach based on both genetic algorithms and fuzzy decision making to manage unscheduled flows is presented. Parallel computation techniques are applied using supercomputers (high-performance computers). The proposed method is applied to the IEEE 300 bus test system. Two different cases for some parameters of GA are considered to see the power of parallel computation technique. Then the simulation results are presented.

Based on Improvement Immunity Algorithm Electrical Power System Optimal Power Flow Computation

2013 ◽  
Vol 278-280 ◽  
pp. 1314-1317
Author(s):  
Li Xiao
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Electrical Power ◽  
Point System ◽  
Electrical Power System ◽  
Optimal Power ◽  
System Optimal ◽  
Comprehensive Search ◽  
Introduction Vector

Proposed one kind of improvement artificial immunization algorithm calculates the electrical power system most superior tidal current, this algorithm maintained the basic immunity algorithm comprehensive search ability, also the concept which is apart from through the introduction vector causes the immunity algorithm theoretically to guarantee the understanding the multiplicity. Through the IEEE-30pitch point system computed result indicated this algorithm is feasible. And so on compares with the heredity algorithm, this algorithm overall situation search ability strong, the convergence rate is quick.

WAMS - based control of series FACTS devices installed in tie-lines of interconnected power system

2010 ◽  
Vol 59 (3-4) ◽  
pp. 121-140 ◽  
Author(s):  
Łukasz Nogal ◽  
Jan Machowski
Keyword(s):  
Power System ◽  
Power Flow ◽  
Transient State ◽  
Test System ◽  
Direct Lyapunov Method ◽  
Control Laws ◽  
Interconnected Power System ◽  
State Variable ◽  
Facts Devices ◽  
Tie Lines

WAMS - based control of series FACTS devices installed in tie-lines of interconnected power systemThis paper addresses the state-variable stabilising control of the power system using such series FACTS devices as TCPAR installed in the tie-line connecting control areas in an interconnected power system. This stabilising control is activated in the transient state and is supplementary with respect to the main steady-state control designed for power flow regulation. Stabilising control laws, proposed in this paper, have been derived for a linear multi-machine system model using direct Lyapunov method with the aim to maximise the rate of energy dissipation during power swings and therefore maximisation their damping. The proposed control strategy is executed by a multi-loop controller with frequency deviations in all control areas used as the input signals. Validity of the proposed state-variable control has been confirmed by modal analysis and by computer simulation for a multi-machine test system.

scholarly journals Performance Analysis of Plug-in Electric Vehicle Supported DVR for Power-Quality Improvement and Energy Back-Up Strategy

2020 ◽  
Vol 8 (6) ◽  
pp. 945-952
Keyword(s):  
Electric Vehicle ◽  
Power Quality ◽  
Distribution System ◽  
Power Flow ◽  
Fossil Fuels ◽  
Electrical Power ◽  
Peak Load ◽  
Electrical Energy ◽  
Distribution Grid ◽  
Dynamic Voltage Restorer

Electric vehicle technology becomes increasingly important as it takes care of the environmental issues related to ICE vehicle and reduces the dependency on fossil fuels. Electric vehicle being greatly dependent on the limited electrical energy provided by a battery, the power flow efficiency is very important in this context. Electric vehicle integration to the distribution grid is increased at a faster rate because it can act as power backup to the grid/local loads reducing the peak load and filling the valley point. Most of software engineers own an Electric Vehicle based on eco-friendly principles. The Batteries in the car are connected to the charging point (or) grid monitoring of State of Charging (SOC) facilities in the parking area of company. When the Renewable power (solar energy) is available, the batteries will be charged to hundred percentage of SOC. Then excess power from PV will connect to load as well as grid. When the electrical power supply cutoff the car batteries will act as a battery bank of UPS and support to the critical load with condition based Allowable SOC. The total capacity of the batteries depends upon the no of cars available at a particular shift in a day. This work proposes the power backup of EV is utilized as an UPS to Software Company as well as used to support the Dynamic Voltage Restorer (DVR) to mitigate the fault occurring in the distribution system. Additionally, the EV supported DVR compensates voltage harmonics, voltage sag-swell, voltage interruptions coming from distribution to enhance power-quality of entire EV system without any additional compensation devices. The entire system is modeled using MATLAB/SIMULINK and the results confer the feasibility of the proposed objective.

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