Voltage Stability Improvement Research Articles

The Effect Pso/Abc, Abc/Bfo, Pso/Bfo and Cs/Bfo Hybrid Techniques on Power System Buses for Voltage Stability Margin Improvement

This paper presents and investigates new approaches inspired by nature to determine the optimal placement of UPFC for enhancing voltage stability margin of power system network. Voltage collapse phenomenon has remained an operational problem yet to be solved by power system engineers. To improve the voltage stability of the power system network, new optimisation techniques viz: PSO/ABC, ABC/BFO, PSO/BFO AND CS/BFO hybrids are investigated for their performance on power system buses for voltage stability improvement. The performance of the proposed hybrid methods are examined on the practical Nigerian 56 - bus network for voltage stability improvement. The simulation results has shown that ABC/BFO technique is better than BFO/PSO by 3.44 in improving voltage stability of margin of power system, gives additional improvement of 4.07, totalling 7.51% and lastly BFO/CS technique improved voltage stability margin of power system further by 5% totalling 12.51%. Also this research revealed that the smaller the gamma value the better the UPFC contribution to voltage stability enhancement. BFO/CS technique yielded the smallest gamma values of 0. 74532 and 0.830913 in both Nigerian practical network and IEEE – 14 bus network as shown in the analysis.

Evaluating Reliability and Economics of EV Charging Configurations and Deep Reinforcement Learning in Robotics and Autonomy

Growing EV popularity drives companies to focus on reliable charging station designs despite challenges in maintaining reliability. A proposed 36-ported design combines uniform and non-uniform port arrangements, tested with 50-350 kW systems. Failure rates are estimated using MILHDBK217F and MILHBK-338B standards, assessing port reliability and station success rates through binomial distribution and cost analysis. This design improves voltage stability and reduces maintenance costs through enhanced port reliability. In robotics and autonomous systems, Deep Reinforcement Learning (DRL) excels but faces challenges from unsafe policies leading to hazardous decisions. This study introduces a reliability assessment framework for DRL-controlled systems, using formal neural network analysis. A two-level verification approach evaluates safety locally using reachability tools and globally by aggregating local safety metrics across tasks. Experimental validation confirms the framework's effectiveness in enhancing RAS safety.

Effect of NASCION‐Type ceramic dispersion in PAN/PVA‐based blend polymer electrolyte: A structural, thermal, and electrical study

AbstractSolid flexible separators having adequate ion conductivity at ambient temperature along with good thermal and voltage stability are potential candidates for separators in all solid‐state ion batteries. In the present work, zirconium and niobium‐doped Li1.3Al0.3Ti1.7 (PO4)3 ceramic particles have been incorporated into a polyvinyl alcohol (PVA) and polyacrylonitrile (PAN)‐based blend that served as a flexible matrix to create a flexible polymer–ceramic framework and have been examined for conductivity, dielectric properties, voltage stability, thermal stability, and electrochemical performance. The flexible polymer–ceramic framework shows high thermal stability, improved conductivity, and a high‐voltage window. Optimized dc conductivity of 9.8 × 10−5 S cm−1 has been observed among all investigated samples, with an improved voltage stability of 4.94 V. Further, the Trukhan model has been used to understand the effect of filler loading on ion migration properties. The optimized solid polymer electrolyte (SPE) shows improved ion mobility (μ) of 5.13 × 10−2 cm2 V−1 s, number density (n) = 2.39 × 1015 cm3, and diffusion coefficient (D) of 2.09 × 10−3 cm2 s−1. It also shows a very high specific capacitance of ~10−4 Fg−1, excellent cycling stability, and 93.75% capacity retention after 100 cycles.

Large scale penetration impact of PMS-WTGS on voltage profile and power loss for 5-bus, 330kV system of the Nigerian grid

In recent times, adverse environmental changes and the gradual reduction in fossil fuel deposits is making integration of renewable energy secure global attention. This paper therefore investigates the effect of high penetration of wind power on power loss and voltage profile of 52-bus, 330kV Nigerian grid. Modeling and simulation of the study were successfully done using the Continuation Power Flow method and Power System Analysis Toolbox in the Matrix Laboratory environment. The Ant Colony Optimization (ACO) technique codes were used to determine the best sites and sizes of Permanent Magnet Synchronous-based Wind Turbine Generators (PMS-WTGs) on the grid as nonoptimal placement and size of PMS-WTGs will result into active power losses and poor voltage profile. The ACO and power flow analysis indicated two load buses, Aladja bus and Yola bus as best sites for PMS-WTGs with optimal sizes of 100MW and 197MW respectively. The result shows a decrease in the system's active (42.1%) and reactive (43.9%) power losses while heightening voltage magnitudes of critical buses to statutory values and enhancing the grid power quality. The overall results indicate that integrating 297MW PMS-WTGs improves voltage stability and power loss reduction by maximizing system loadability and reducing line losses.

Optimal Allocation of Distributed Generation Using Improved Cuckoo Search Algorithm

This work presents an improved cuckoo search algorithm based on Success Rate (CSA-SR) for optimal allocation of Distributed Generation (DG). This is necessary in order to improve the power quality of the distribution system by minimizing power loss and improving voltage stability. Voltage Stability Index (VSI) is applied to identify restricted unhealthy buses/areas in the distribution networks. The work is implemented on standard IEEE 33 Bus test systems. Newton Raphson Power Flow (NRPF) technique is used in MATLAB R2019b environment for the power flow analysis. The overall IEEE 33 Bus system real power loss obtained from the simulation result is found to be 202.7071MW at the base case. Following the application of 3 DGs using CSA-SR, the real power loss is found to be 113.9630 MW which shows a reduction of 88.441MW which is equivalent to 43.77% as related to the base case. The results minimized the system losses while significantly enhancing the voltage profile of the bus voltages as a result of optimal siting and sizing of the DG. These show that the CSA-SR technique outperformed PSO, which was used to ascertain the effectiveness of the developed scheme.

Evaluation of Reliability and Financial Feasibility of Various EV Charging Station Layouts

As the popularity of electric vehicles (EVs) continues to rise, companies are increasingly focusing on expanding charging infrastructure to meet growing consumer demand. Despite attempts to design charging stations that align with distribution system requirements, ensuring reliable performance for EV charging ports remains a complex challenge. To address this issue, a unique design featuring 56 ports, comprising both uniform and non-uniform arrangements, has been introduced. These configurations underwent testing across distribution systems ranging from 50 to 500 kW. Reliability assessments were carried out using established standards for failure rate estimation and Monte Carlo simulations to evaluate port probability functions in terms of failure rate and reliability. By scrutinizing the failure rates of individual ports, a systematic evaluation method was established to gauge the overall performance of the charging station. The failure rate of the proposed 56-ported charging station was further assessed using the binomial distribution method. Also, cost estimation procedures were developed, taking into account the maintenance costs associated with the failure and success rates of individual ports for the proposed design. The research findings suggest that by enhancing port arrangement reliability and improving voltage stability, it is possible to achieve lower failure rates and maintenance costs, thereby enhancing overall system performance

Voltage stability improvement of distribution networks using reactive power capability of electric vehicle charging stations

Modern power networks are affected by the increasing adoption of electric vehicles (EVs) driven by environmental concerns. Electric vehicle charging stations (EVCSs) pose serious challenges due to the fluctuating charging demand leading to voltage instabilities and affecting the secure operation of power networks. This research proposes a novel approach to address these instabilities by utilizing the capabilities of EVCSs in absorbing and injecting reactive power. An efficient management of the reactive power of EVCSs is achieved by embedding differential evolutionary algorithms in a specialized optimization framework. We employ the two-point estimation method (2PEM) to deal with the uncertainties in renewable energy, load fluctuations, and EV demand patterns. The effectiveness of 2PEM is validated through comparison with Monte Carlo simulation (MCS). Demonstrated on a 51-bus network model, the proposed framework represents its real-world applicability. The results show a significant improvement in voltage stability, along with a considerable reduction in power loss.

Voltage stability improvement and power losses reduction through multiple grid contingency supports

A stable power system is a desirable state for the optimal performance and delivery of electricity to the end-users. This study evaluates the effectiveness of grid contingency support devices in power system stability enhancement. The new voltage stability pointer (NVSP) was employed to optimally infer the flexible alternating current transmission systems devices through N − 1 contingency ranking. In this research, the static synchronous compensator (STATCOM) was considered as a grid support device. The effectiveness of this technique was validated in R2018a MATLAB with the IEEE 30-bus system using different combinable contingency cases to ascertain the critical lines and vulnerable buses to outages. Based on the results obtained through the NVSP, buses 30, 26, and 29 were cited as STATCOM candidate buses for overall optimal grid performance. The results obtained from the simulation revealed that the total real power loss was reduced by 90.21%. Similarly, the voltage magnitude of the buses was significantly improved to a minimum of 1.00 p.u. after placement of STATCOMs. Further investigation on single STATCOM placement in the IEEE 30-bus system revealed that the highest level of voltage improvement, minimum level of voltage deviation and maximum active power loss reduction was achieved when the STATCOM was placed at bus 30. The overall assessment of the proposed technique yielded better results compared with other methods on the same test system.

Application of SSSC for Voltage Stability Improvement in the Nigerian 330 kV Transmission System using Particle Swarm Optimization Technique

Load imbalance has always been a major cause of voltage instability of the power system network and increase in voltage instability affects the power system reliability. In this paper, static synchronous series capacitor (SSSC) FACTS device was implemented to improve the voltage stability in the Nigerian 330 kV transmission network using particle swarm optimization (PSO) technique. Modelled power system network in the power system analysis toolbox (PSAT) is simulated to determine the existing power flow analysis and the level of instability in the power system generation plants situated in the Northern region. The outcome of the power flow is thereafter, optimized with PSO by generating the relationship with a high prediction accuracy between voltage at each location and an inter-linked transmission line distance of the 330kV. The model was generated with least square method and the high prediction accuracy determination was carried out with R-square value of the polynomial order. The best model was optimized and the entire computations were carried out in MatLab resulting in the determination of the optimal location which was between Jebba transmission and Shiroro generation stations. SSSC FACTS controller was implemented on the optimized transmission line and the simulation results showed that the introduction of SSSC improved the voltage stability of the power system network.

Multi-Agent Graph-Attention Deep Reinforcement Learning for Post-Contingency Grid Emergency Voltage Control.

Grid emergency voltage control (GEVC) is paramount in electric power systems to improve voltage stability and prevent cascading outages and blackouts in case of contingencies. While most deep reinforcement learning (DRL)-based paradigms perform single agents in a static environment, real-world agents for GEVC are expected to cooperate in a dynamically shifting grid. Moreover, due to high uncertainties from combinatory natures of various contingencies and load consumption, along with the complexity of dynamic grid operation, the data efficiency and control performance of the existing DRL-based methods are challenged. To address these limitations, we propose a multi-agent graph-attention (GATT)-based DRL algorithm for GEVC in multi-area power systems. We develop graph convolutional network (GCN)-based agents for feature representation of the graph-structured voltages to improve the decision accuracy in a data-efficient manner. Furthermore, a cutting-edge attention mechanism concentrates on effective information sharing among multiple agents, synergizing different-sized subnetworks in the grid for cooperative learning. We address several key challenges in the existing DRL-based GEVC approaches, including low scalability and poor stability against high uncertainties. Test results in the IEEE benchmark system verify the advantages of the proposed method over several recent multi-agent DRL-based algorithms.

Improving voltage collapse point under transmission line outage by optimal placement and sizing of SVC using genetic algorithm

In many power systems, voltage instability can increase the risk of voltage collapse and, as a result, turn the power system toward a blackout. Therefore, increasing the voltage collapse point is required. A transmission line outage is an emergency condition in power systems that can lead to voltage instability and voltage collapse. Thus, it is expected to employ shunt-connected flexible AC transmission systems (FACTS) such as the static var compensator (SVC) to increase the voltage collapse point when lines outage. This paper presents the genetic algorithm (GA) application to optimal placement and sizing of an SVC for increasing voltage collapse points following lines outage. The continuation power flow (CPF) technique has been used to determine the maximum loading point (MLP) corresponding to the point of voltage collapse. Also, to reduce the number of scenarios when line outages occur, a list in ascending order is established based on the line outage priority (LOP). The IEEE 14-bus test system is chosen to carry out simulations, and an SVC will be installed in the system based on the GA results. Simulation results confirm the effectiveness of an SVC for improving voltage stability as well as increasing voltage profile.

Optimal allocation of Combined DG and DSTATCOM for Improving Voltage Stability and Economical Benefits of Distribution System

In the vertically integrated power sector, the distribution system serves as the link between customers and the transmission network. Different load models, including industrial, residential, and commercial, are taken into account within the distribution systems. The loading pattern of these load models varies with a large range according to the peak hours. During peak load conditions, the voltage magnitude of some nodes exceeds the permissible limit of voltage value. It affects the voltage stability of the distribution system, leading to decreased reliability, heightened power losses, diminished voltage stability, and other safety concerns. Optimal placement of capacitors, applying DGs, using FACTS devices, and Distribution Network reconfigurations are possible to reduce the power loss. This paper focuses on reducing power loss and enhancing the voltage profile and stability of the system. It addresses the technical, economic, and environmental benefits of the distribution system through appropriate placement and sizing of DG and DSTATCOM units in a coordinated manner. The issue is approached as a Multi-Objective Optimization Problem (MOP) and is tackled through the application of the Group Teaching Optimization (GTO) algorithm, an innovative metaheuristic method. A numerical illustration utilizing an IEEE 69-node system is examined, and the simulated outcomes are presented in tabular form. These results are then juxtaposed with findings from comparable methodologies outlined in existing literature.

Improving voltage stability in subtransmission through pv curves and critical voltage balance for photovoltaic compensation

Improving voltage stability in subtransmission through pv curves and critical voltage balance for photovoltaic compensation

Realization of Small Scale Models of FCATS Devices and its Optimization in Power Systems using Stability Indices and Particle Swarm Optimization

This article focuses on the physical realization of SVC, TCSC, combined SVC and TCSC scale down models, which have been realized in the laboratory, developed and tested and presented the experimental results. These practical test results have been proven the effectiveness of these devices with closed loop control systems developed with microcontrollers. The voltage stability can be assessed accurately using stability indices. These indices can either reveal the critical bus or line of a power system. The said indices plays vital role in identifying the most critical n-1 and n-2 contingencies. This article further focuses on optimization of these devices in IEEE 9 bus, 14 bus and 30 bus test systems using stability indices and Particle Swarm Optimization (PSO). The simulation results for all these systems have been presented and which proves the tremendous improvement in voltage stability of power systems.

A new control method of hybrid energy storage system for DC microgrid application

AbstractEnergy storage system play a crucial role in safeguarding the reliability and steady voltage supply within microgrids. While batteries are the prevalent choice for energy storage in such applications, their limitation in handling high‐frequency discharging and charging necessitates the incorporation of high‐energy density and high‐power density storage devices to enhance power quality, maintain power balance, and reduce fluctuations. In this study, we introduce a hybrid energy storage system (HESS) solution, combining a battery and a supercapacitor, to address intermittent power supply challenges. The effective management of this HESS is pivotal for constant DC voltage and sustaining microgrid stability. To achieve this, we propose an innovative control strategy called the Adaptive Filter‐Based Method (AFBM) for DC microgrid operation, which prioritizes stable and smooth performance while addressing safety and degradation concerns related to the storage devices. Our control strategy determines the distribution of charging and discharging currents for each storage device within the DC microgrid based on their state of charge. We conducted simulations in MATLAB/Simulink, comparing the proposed AFBM method with the conventional filter‐based approach using identical configurations, parameters, and operational modes. The results demonstrate the superior performance of our proposed system, showcasing improved voltage stability, more equitable load distribution, and efficient charging and discharging of storage devices compared to the traditional method. This research contributes to the advancement of microgrid energy storage solutions, enhancing their reliability and performance.

Adaptive Virtual Impedance Control with MPC’s Cost Function for DG Inverters in a Microgrid with Mismatched Feeder Impedances for Future Energy Communities

More and more distributed generations (DGs), such as wind, PV or battery bank sources, are connected to electric systems or customer loads. However, the locations of these DGs are based on the highest energy that can be potentially harvested for electric power generation. Therefore, these locations create different line impedances based on the distance from the DGs to the loads or the point of common coupling (PCC). This paper presents an adaptive virtual impedance (AVI) in the predictive control scheme in order to ensure power sharing accuracy and voltage stability at the PCC in a microgrid network. The reference voltage from mismatched feeder impedances was modified by utilizing the suggested AVI-based predictive control for creating equal power sharing between the DGs in order to avoid overburdening any individual DG with low-rated power. The AVI strategy used droop control as the input control for generating equal power sharing, while the AVI output was used as the reference voltage for the finite control set–model predictive control (FCS-MPC) for creating a minimum voltage error deviation for the cost function (CF) for the inverter’s vector switching pattern in order to improve voltage stability at the PCC. The proposed AVI-based controller was tested using two DG inverter circuits in a decentralized control mode with different values of line impedance and rated power. The performance of the suggested controller was compared via MATLAB/Simulink with that of a controller based on static virtual impedance (SVI) in terms of efficiency of power sharing and voltage stability at the PCC. From the results, it was found that (1) the voltage transient magnitude for the AVI-based controller was reduced within less than 0.02 s, and the voltage at the PCC was maintained with about 0.9% error which is the least as compared with those for the SVI-based controller and (2) equal power sharing between the DGs increased during the change in the load demand when using the AVI-based controller as compared with using the SVI-based controller. The proposed controller was capable of giving more accurate power sharing between the DGs, as well as maintaining the voltage at the PCC, which makes it suitable for the power generation of consumer loads based on DG locations for future energy communities.

Improvement of Voltage Stability in Power <span>System by Using SVC and STATCOM</span>

Improvement of Voltage Stability in Power <span>System by Using SVC and STATCOM</span>

Performance analysis of power system dynamics with facts controllers: Optimal placement and impact of SSSC and STATCOM

This paper explores the impact of integrating Flexible AC Transmission Systems (FACTS) controllers, specifically the Static Synchronous Series Compensator (SSSC) and the Static Synchronous Compensator (STATCOM), on power system performance. The objective of this study is to evaluate how these controllers can enhance various aspects of power system operation, including voltage regulation, power flow stability, and overall system efficiency. The methodology involves simulating power systems with and without the deployment of SSSC and STATCOM and analyzing their effects on voltage profiles, power flow characteristics, and system losses. The findings reveal that both SSSC and STATCOM significantly improve voltage stability and power flow control, leading to reduced system losses and enhanced operational efficiency. This study introduces a novel approach by comparing the performance enhancements provided by SSSC and STATCOM in different operational scenarios, offering valuable insights into their effectiveness. The results underscore the potential of FACTS technology in advancing power system stability and efficiency, making a substantial contribution to the field of power system optimization.

Online Nonlinear P-Q Droop Estimation of Distributed Generations Based on Kalman-Filter Algorithm to Improve Voltage Stability

Online Nonlinear P-Q Droop Estimation of Distributed Generations Based on Kalman-Filter Algorithm to Improve Voltage Stability

Optimal Grid-Support Strategy With Inverter-Interfaced Distributed Generators for Short-Term Voltage Stability Improvement

Optimal Grid-Support Strategy With Inverter-Interfaced Distributed Generators for Short-Term Voltage Stability Improvement