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This paper introduces the Walrus Optimization Algorithm (WaOA) to address load frequency control and automatic voltage regulation in a two-area interconnected power systems. The load frequency control and automatic voltage regulation are critical for maintaining power quality by ensuring stable frequency and voltage levels. The parameters of fractional order Proportional-Integral-Derivative (FO-PID) controller are optimized using WaOA, inspired by the social and foraging behaviors of walruses, which inhabit the arctic and sub-arctic regions. The proposed method demonstrates faster convergence in frequency and voltage regulation and improved tie-line power stabilization compared to recent optimization algorithms such as salp swarm, whale optimization, crayfish optimization, secretary bird optimization, hippopotamus optimization, brown bear optimization, teaching learning optimization, artificial gorilla troop optimization, and wild horse optimization. MATLAB simulations show that the WaOA-tuned FO-PID controller improves frequency regulation by approximately 25%, and exhibits a considerable faster settling time. Bode plot analyses confirm the stability with gain margins of 5.83 dB and 9.61 dB, and phase margins of 10.8 degrees and 28.6 degrees for the two areas respectively. The system modeling and validation in MATLAB showcases the superior performance and reliability of the WaOA-tuned FO-PID controller in enhancing power system stability and quality under step, random step load disturbance, with nonlinearities like GDC and GDB, and system parameter variations. [ABSTRACT FROM AUTHOR]

As the large-scale development of wind farms (WFs) progresses, the connection of WFs to the regional power grid is evolving from the conventional receiving power grid to the sending power grid with a high proportion of wind power (WP). Due to the randomness of WP output, higher requirements are put forward for the voltage stability of each node of the regional power grid, and various reactive power compensation devices (RPCDs) need to be rationally configured to meet the stable operation requirements of the system. This paper proposes an optimal configuration method for multi-type RPCDs in regional power grids with a high proportion of WP. The RPCDs are located according to the proposed static voltage stability index (VSI) and dynamic VSI based on dynamic voltage drop area, and the optimal configuration model of RPCDs is constructed with the lowest construction cost as the objective function to determine the installed capacity of various RPCDs. Finally, the corresponding regional power grid model for intensive access to WFs is constructed on the simulation platform to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The rising integration of photovoltaic (PV) systems into electrical grids has introduced significant challenges allied with voltage stability, power quality, and grid reliability, particularly beneath high PV penetration scenarios. This work presents a hybrid optimization approach combining particle swarm optimization (PSO) and grey wolf optimization (GWO) to mitigate these challenges effectively. The hybrid PSO–GWO method is not only applied to optimize the position and sizing of PV systems, but also the configuration of grid‐supportive devices like static synchronous compensators (STATCOMs), in Institute of Electrical and Electronics Institute (IEEE) 14‐test bus system. The proposed hybrid system led to a 42.2% power loss reduction, from 18.5 to 10.7 MW effectively enhancing efficiency of the grid, improves voltage profiles, all bus voltages maintained with in the acceptable range of 0.95–1.05 p.u. The study also identified optimal locations for PV units, with placements at bus 3, 6, and 9, where PV sizes were adjusted to 10, 12, and 8 MW, respectively. Additionally, the optimal placement of STATCOMs at bus 4, 7, and 10 provided reactive power support of up to 9 MVAR, further enhancing system stability. The findings suggest that the hybrid PSO–GWO optimization technique is a promising tool for managing the complexities of high PV penetration in modern electrical grids, ensuring proficient and reliable grid operation. [ABSTRACT FROM AUTHOR]

Proton exchange membrane fuel cell (PEMFC) with dead-ended anode (DEA) suffers from nitrogen diffusion and water accumulation, leading to unstable performance. The core of this paper is to enhance the stability of DEA operation. By coupling the flow field structure with the DEA mode, the factors affecting the stability are explored, the performance degradation mechanism after DEA operation is revealed, and the purging strategy is formulated by combining the energy management with the voltage stability as a prerequisite. The experimental results show that the serpentine flow field is advantageous for maintaining the most stable DEA operation with a minimum voltage recession of 17.01 mV and a voltage undershoot of 11.63 mV. The local current density distribution exhibited a pattern of highest values at anode inlet and lowest at anode outlet, which could be improved by increasing operating pressure and reducing load current density. In this experiment, PCB was innovatively combined to investigate the degradation of each region of PEMFC after 60h of DEA operation. It is found that the most severe performance degradation occurs in anode outlet with a degradation rate exceeding 50%, while the center area has a degradation rate of no more than 20%. • The flow field structures are evaluated for the most stable DEA operation. • Experimentally investigated the stability of DEA operation based on PCB segmented cell technology. • The optimized purging strategy is formulated to maintain the stability operation with high output energy. [ABSTRACT FROM AUTHOR]

This study explores the optimization of dynamic voltage restorers (DVRs) within hydro turbine systems using the Bee Optimization Algorithm (BOA), focusing on enhancing power system stability and quality through advanced control strategies. Emphasizing total harmonic distortion (THD) minimization, the research addresses power quality challenges prevalent in hydroelectric power generation. Detailed simulations demonstrate how BOA effectively reduces THD, optimizing DVR performance in response to grid disturbances typical in renewable energy integrations. Findings validate the BOA's efficacy in improving voltage stability and underscore the potential of bio-inspired algorithms for smart grid applications in hydro settings. This approach not only supports the reliability of hydroelectric power systems but also opens new avenues for employing multi-objective optimization techniques to advance DVR functionality, contributing to the sustainable management of energy infrastructures. [ABSTRACT FROM AUTHOR]

The research focuses on incorporating microgrids into engineering curricula for achieving voltage stability in today's power systems. This helps to meet the increasing demand for engineers to integrate distributed power generation and renewable energy sources. Some limitations of the current literature include the absence of models outlining approaches to microgrid education and limited insight into teaching strategies for electrical power systems. The research used a quantitative methodology to survey 100 engineering students enrolled in a microgrid modeling class to achieve the study's objectives. The data analysis involved machine learning models such as Random Forest, Gradient Boosting, K-Means, hierarchical clustering, and regression models. The major findings identified exam score as the most significant determiner of student performance (weight ≈ 0.40). Based on the clustering analysis, it was found that microgrid systems can be grouped into four operational states. It was also seen that linear regression models were highly accurate and better than other highly complex models, like Decision Tree, with a model accuracy of R2 ≈ 0.4. One of the study's major strengths is the potential impact of the proposed framework for integrating microgrids into engineering education on the professional training of engineers. This framework, based on theoretical knowledge and practical experience as well as on developing advanced analytical skills, can significantly enhance the professional training of engineers to deal with the complexities of contemporary power systems, including microgrids and sustainable energy progress. [ABSTRACT FROM AUTHOR]

Copyright of Integrated Intelligent Energy is the property of Editorial Department of Integrated Intelligent Energy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In power system, stability analysis becomes important to identify the level of stability and security of electrical power systems. This article proposes a flexible alternating current systems-unified power flow compensator (FACTS-UPQC) compensator installed in the high-voltage network to ensure stability of voltage and frequency in the power grid facing voltage dips, over-voltage and short-circuit faults. Thus, an artificial intelligence algorithm based on fuzzy logic method is implemented to have the appropriate values of FACTS-UPQC conditioner. The voltage stability improvement is demonstrated by the variation margin of amplitude and phase angle. Frequency stability aims to obtain a frequency within a minimal variation. A 14-bus test electrical system is modeled to implement the advanced control strategy. MATLAB/Simulink software is used to prove the functionality of the method in improving the stability of power system. The simulation results showed a reduction of harmonic distortion rate (HDR) and a minimization of the voltage variation range for the implemented fuzzy logic system compared with the literature. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The rapidly increasing proportion of renewable energy sources has led to a reduction in the relative share of synchronous units, which has resulted in a decline in the inertia of the power system and a decrease in its voltage support capacity. This has led to several issues related to the frequency and voltage stabilities of the power system. To ensure these frequency and voltage stabilities, it is necessary to maintain a number of synchronous units online in the day-ahead generation schedule. First, the dynamic frequency change process after a power system fault is discussed, and a linear expression is derived for the frequency stability constraints involving energy storage systems and wind turbines. Second, the short-circuit capacity of the bus is characterized to describe the strength of voltage support, and the minimum short-circuit capacity requirement of the bus is solved based on the transient voltage recovery problem after clearance of the short-circuit faults. The total short-circuit capacity provided by the unit to the bus is then calculated through the network reactance matrix to establish the voltage stability constraint. Subsequently, the security-constrained unit commitment model considering frequency and voltage stabilities (FVS-SCUC) is established. Finally, the effectiveness of the proposed model is demonstrated through a numerical simulation of the IEEE-39 system comprising storage and wind turbines. The model ensures the frequency and voltage securities of the system, and the renewable energy output is improved upon considering energy storage. Thus, the overall system cost was reduced by nearly 30% by considering the frequency regulation effects of the energy storage system and wind turbine as well as the voltage regulation effects of the energy storage system. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The rapid integration of renewable energy sources and the increasing complexity of modern power systems urge the development of advanced methods for ensuring power system stability. This paper presents a novel continuation power flow (CPF) method that combines two well-known parameterization techniques: natural parameterization and arc-length parameterization. The proposed hybrid approach significantly improves computational efficiency, reducing processing time by 32.76% compared to conventional methods while maintaining high accuracy. The method enables faster and more reliable stability assessments by efficiently managing the complexities and uncertainties, particularly in grids with high penetration of renewable energy. [ABSTRACT FROM AUTHOR]

This paper presents a model predictive control (MPC) technique for the control of reactive power flow from a static synchronous compensator (STATCOM) into a weak power system network. The MPC strategy enables the STATCOM to mitigate weak phase voltage magnitudes in a distribution grid. The weak voltage magnitudes usually emanate from large inductive loads connected to the grid’s point of common coupling (PCC). The MPC utilizes a finite control set of voltage vectors to minimize a cost function, which reduces the errors between set references and the corresponding predicted variables. The references in the cost function are set by two outer loop controllers. A time delay compensation strategy is introduced and proposed for selecting the gains of the outer loop controllers. An LC filter was also designed at the STATCOM’s output terminals to confine the harmonics in the injected compensation current to permissible limits. A robust all high pass filter dual second order generalized integrator (AHPF-DSOGI) based phase locked loop (PLL) is developed and proposed for synchronization of the STATCOM into the weak grid. The overall MPC strategy on the STATCOM enables shunt injection of compensation currents at the PCC while mitigating harmonics and consequently improving power quality. The STATCOM effectively regulated the bus voltage when required by switching between the capacitive and inductive modes. Results showing the efficacy of integration of the STATCOM to the grid and robust capabilities of the STATCOM in mitigating voltage swell and dip, as well as harmonics, are presented.

Abstract This paper provides six metaheuristic algorithms, namely Fast Cuckoo Search (FCS), Salp Swarm Algorithm (SSA), Dynamic control Cuckoo search (DCCS), Gradient-Based Optimizer (GBO), Northern Goshawk Optimization (NGO), Opposition Flow Direction Algorithm (OFDA) to efficiently solve the optimal power flow (OPF) issue. Under standard and conservative operating settings, the OPF problem is modeled utilizing a range of objectives, constraints, and formulations. Five case studies have been conducted using IEEE 30-bus and IEEE 118-bus standard test systems to evaluate the effectiveness and robustness of the proposed algorithms. A performance evaluation procedure is suggested to compare the optimization techniques' strength and resilience. A fresh comparison methodology is created to compare the proposed methodologies with other well-known methodologies. Compared to previously reported optimization algorithms in the literature, the obtained results show the potential of GBO to solve various OPF problems efficiently.

The stability of the operation of the power system is essential to ensure a continuous supply of electricity to meet the load of the system. In the operational process, voltage stability (VS) should be recognized and predicted as a basic requirement. In electrical systems, deep learning and machine learning algorithms have found widespread applications. These algorithms can learn from previous data to detect and predict future scenarios of potential instability. This study introduces long short-term memory (LSTM) technology to predict the stability of the nominal voltage of the power system. Based on the results, the recommended LSTM technology achieved the highest accuracy target of 99.5%. In addition, the LSTM model outperforms other machine learning (ML) and deep learning techniques, i.e., support vector machines (SVMs), Naive Bayes (NB), and convolutional neural networks (CNNs), when comparing the accuracy of the VS forecast. The results show that the LSTM method is useful to predict the voltage of an electrical system. The IEEE 33-bus system indicates that the recommended approach can rapidly and precisely verify the system stability category. Furthermore, the proposed method outperforms conventional assessment methods that rely on shallow learning. [ABSTRACT FROM AUTHOR]

The widespread integration of wind turbines poses voltage stability challenges to power systems. To enhance the ability of wind power systems to actively support grid voltage, grid-forming control techniques are increasingly being employed. However, current research primarily focuses on voltage stability challenges at the point of common coupling in wind power systems, lacking thorough investigation into system voltage response characterization. This paper establishes the voltage response model of a grid-forming wind power system. Based on this model, mathematical derivation and theoretical analysis are conducted, and the effect factors of the voltage at the point of common coupling are investigated. Furthermore, a voltage stabilization method is explored by adjusting the above effect factors. Finally, based on the MATLAB/Simulink platform, the simulation verification of each effect factor is carried out. The results indicate that voltage response characterization obtained by the theoretical analysis and simulation is similar and that the proposed method is valid. [ABSTRACT FROM AUTHOR]

Distributed photovoltaic (PV) output exhibits strong stochasticity and weak adjustability. After being integrated with the network, its interaction with stochastic loads increases the difficulty of assessing the distribution network's static voltage stability (SVS). In response to this issue, this article presents a probabilistic assessment method for SVS in a distribution network with distributed PV that considers the bilateral uncertainties and correlations on the source and load sides. The probabilistic models for the uncertain variables are established, with the correlation between stochastic variables described using the Copula function. The three-point estimate method (3PEM) based on the Nataf transformation is used to generate correlated samples. Continuous power flow (CPF) calculations are then performed on these samples to obtain the system's critical voltage stability state. The distribution curves of critical voltage and load margin index (LMI) are fitted using Cornish-Fisher series. Finally, the utility function is introduced to establish the degree of risk of voltage instability under different scenarios, and the SVS assessment of the distribution network is completed. The IEEE 33-node distribution system is utilized to test the method presented, and the results across various scenarios highlight the method's effectiveness. [ABSTRACT FROM AUTHOR]

The burgeoning energy demands induced by modern civilization necessitate the procurement of additional electrical energy reserves to effectively address this escalating challenge. However, the installation of new power generation units necessitates building/upgrade of accompanying transmission infrastructure, a task fraught with complexities. To augment the loading capacity of existing transmission lines, power engineers have devised efficient solutions, one of which involves the integration of novel devices. This paper delves into the management of reactive power within vulnerable transmission networks, focusing particularly on the pivotal role of Flexible AC Transmission System (FACTS) devices. Among the diverse array of FACTS technologies engineered to fortify grid resilience, the Static Synchronous Compensator (STATCOM) which emerges as a transformative asset. The paper explores the integration of STATCOM within the 132 kV transmission network of the Diyala city ring power system to enhance its stability and operational efficiency. Simulations of the Diyala power network and load flow analysis were conducted using MATLAB/Simulink environment. The results unveiled a notable enhancement in power quality upon the integration of STATCOM, as compared to the base scenario devoid of such augmentation. These findings bear significant implications, offering valuable insights for the Iraqi grid operator and other nations grappling with analogous challenges pertaining to frail power networks. Incorporating such advanced devices into national electrical systems could potentially mitigate operational inefficiencies, defer infrastructure investment and bolster overall grid resilience. [ABSTRACT FROM AUTHOR]

The optimization of a suitable controlling method is a priority in running any DC/DC boost converter effectively. However, a problem may arise as the occurring oscillations in the microgrid caused by the incremental negative resistance of the Constant Power Load (CPL) variation may lead to system instability. In order to tackle this intrinsic problem, three proposed Sliding Mode Control (SMC) methods were simulated and examined against multiple variations of CPL in MatLab/Simulink. Integral Sliding Mode Control (ISMC) and Two-variable Sliding Mode Control (TSMC) methods showed a better system performance than the Low Pass Filter SMC (LPFSMC) in terms of stability of output voltage in both steady state and transient conditions. The output voltages of ISMC and TSMC had a margin of error of approximately 1 V in the steady-state response and a minor overshoot of less than 1% in the transient response. The steady-state output voltage when using LPFSMC showed approximately 3 V of error and the transient state had a noticeable overshoot near 3%. However, all three controlling methods had a similar efficiency of around 98%. The outstanding robustness of ISMC exhibited the highest voltage stability with the lowest chattering in both steady state and transient responses through the compensation of adequate current to satisfy the CPL requirement. [ABSTRACT FROM AUTHOR]

Due to the microgrid (MG) operational flexibility and local blackstart capabilities, the MG-aided restoration service is essential for strengthening the resilience of the electrical system in the event of a disaster. An MG-aided load restoration service is described in this study, along with a game-theoretic remuneration scheme. The utility company (UC) and numerous MGs are modeled using a two-level game framework to depict this multi-agent load restoration service between the two parties. This is a Nash game designed to imitate the non-cooperative connection between MGs on the first level. The second stage is the Stackelberg game, which is headed by UC and is used to calculate the service compensation in order to maximize cost efficiency while minimizing service costs. This study is used to determine the impact of MG assistance on system voltage stability as well as the cost-effectiveness of the UC remuneration option using transmission line sensitivity. The MGs' decision-making on energy dispatching also becomes extremely interactive when these quantified stability incentive are added to the economic incentive. Case studies based on the IEEE 6-bus and 57-bus test systems demonstrate the effectiveness of the proposed decision-making strategy on increasing the cost efficiency of the MG-aided load restoration service. [ABSTRACT FROM AUTHOR]

In the distribution system, proper placement of distributed generation (DG) is still a very challenging issue for getting their maximum potential benefits. Power system stability should be determined through load modeling, hybrid energy storage system (HESS), and photovoltaics (PV) modeling. This paper proposed the optimal sizing and location of photovoltaic using the Modified Harris Hawk Optimization (MHHO) algorithm. The energy generated from the photovoltaic (PV) is stored in the HESS, where the energy's charging and discharging from the storage unit is framed with a reduced power loss (active and reactive power). The optimal sizing and placement of the PV system will provide better voltage stability. The Modified Harris Hawk Optimization Algorithm (MHHO) frames the system's voltage stability. The Newton-Raphson load flow method is used to analyze the loading in the power system. The IEEE 33 and 69 bus systems are used to analyze the load flow to the consumers, thus analyzing the power system's dynamic performance. The performance and voltage stability of the presented model are compared with the existing optimization techniques, which include the Firefly Algorithm (FA), Crow Search Optimization (CSO), Particle Swarm Optimization (PSO), Analytical PSO (APSO), Improved Cayote Optimization Algorithm (COA) and Whale optimization algorithm (WOA) through the MATLAB/Simulink platform. [ABSTRACT FROM AUTHOR]

In an integrated distribution system incorporating distributed generation (DG), various technical challenges must be addressed when the grid becomes disconnected and transforms into an islanded system. The main focus in such circumstances revolves around ensuring the stability of the islanded network. This study presents an advanced decision-making framework for supporting islanded networks by integrating metaheuristic Black Widow Optimization (BWO) and the rate of change of the voltage stability index (RoCVSI). The Rate of Change of the Voltage Stability Index (RoCVSI) detects instability in islanded networks by continuously monitoring rapid changes in the voltage stability margin. Upon identifying potential instability, an advanced decision-making strategy utilizing the Black Widow Optimization (BWO) algorithm is deployed. BWO generates multiple load-shedding scenarios and evaluates their impact on system stability, iteratively refining the solutions through processes similar to selection and cannibalism in black widow spiders. The optimal load-shedding strategy is then implemented to selectively shed specific loads, thereby reducing demand and enhancing island stability. The proposed scheme’s effectiveness for islanded network stability is assessed by extensively analyzing the IEEE 33-bus system. The efficiency of the proposed approach is confirmed through a comparative analysis, with results indicating the better efficiency of the proposed method in the islanded network. [ABSTRACT FROM AUTHOR]

Integrating renewable energy sources and distributed energy resources (DERs) in the Malaysian low voltage distribution network has introduced voltage stability challenges, particularly voltage rises, leading to detrimental impacts on network performance. This paper presents a novel reactive power control strategy for addressing these challenges. Unlike conventional methods with fixed reactive power references, the proposed technique dynamically adjusts the reactive power reference in real time, considering voltage and active power injection. It calculates the rate of change in reactive power reference (ΔQ) per second by analyzing Volt-VAR and Watt-VAR components and updates the reference accordingly. Simulations conducted on a low voltage distribution network in Taman Impian Putra, Malaysia, showcase the adverse effects of high photovoltaic (PV) penetration on voltage stability and highlight the success of the proposed strategy in mitigating voltage rise. The technique effectively reduces average voltage, maintains voltage regulation during high sun irradiance and low load demand periods, and surpasses the adaptability of existing methods dependent on PV active injection or network voltage alone. The proposed strategy ensures accurate control and efficiently addresses dynamic network changes by accounting for both PV active power injection and network voltage. This approach offers enhanced voltage regulation, adaptability to varying network conditions, and reduced losses, making it a promising solution for mitigating voltage rise in the Malaysian low voltage distribution network. The simulations, validated using MATLAB Simulation and OpenDSS, confirm the strategy’s efficacy and potential for real-world implementation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper provides six metaheuristic algorithms, namely Fast Cuckoo Search (FCS), Salp Swarm Algorithm (SSA), Dynamic control Cuckoo search (DCCS), Gradient-Based Optimizer (GBO), Northern Goshawk Optimization (NGO), Opposition Flow Direction Algorithm (OFDA) to efficiently solve the optimal power flow (OPF) issue. Under standard and conservative operating settings, the OPF problem is modeled utilizing a range of objectives, constraints, and formulations. Five case studies have been conducted using IEEE 30-bus and IEEE 118-bus standard test systems to evaluate the effectiveness and robustness of the proposed algorithms. A performance evaluation procedure is suggested to compare the optimization techniques' strength and resilience. A fresh comparison methodology is created to compare the proposed methodologies with other well-known methodologies. Compared to previously reported optimization algorithms in the literature, the obtained results show the potential of GBO to solve various OPF problems efficiently. [ABSTRACT FROM AUTHOR]

Voltage instability in power systems arises due to the shortage of reactive power and may cause abnormally low bus voltages leading to a partial or complete blackout. In order to maintain the system voltages within a safe limit, voltage control techniques such as shunt capacitor banks, Static VAR Compensators (SVCs), load shedding, and transformer tap-changer blocking, are employed. In this paper, a novel receding-horizon Model Predictive Control (MPC)-based voltage controller is proposed, which, by optimally controlling generator reactive power and SVC output, maintains the voltage stability of a power system. For this, a sensitivity-based analysis is performed to design a state-space model of the power system. The frequency and voltage dependency of load and generation are considered in the system equations. The voltage control is done step-wise, and the optimal control action in each step is calculated by minimizing a cost function subject to a set of relevant constraints. Different Voltage Stability Indices (VSIs) are used as a measure of voltage stability and also used in the constraints for the optimization problem. The performance of the proposed controller is evaluated on IEEE 9-, 39- and 118-bus systems, considering different types of loads and contingencies. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive performance analysis of power systems incorporating High Voltage Direct Current (HVDC) transmission lines, with a focus on the impact of integrating advanced Flexible AC Transmission Systems (FACTS) devices, namely Static Synchronous Series Compensator (SSSC) and Static Synchronous Compensator (STATCOM). This study evaluates key performance parameters, including Total Power Loss (TPL), Voltage deviation (Vdev), transmission efficiency, and corona loss, across three configurations, HVDC alone, HVDC with SSSC, and HVDC with STATCOM. Through simulations conducted using MATLAB or Simulink, the results demonstrate that the addition of SSSC and STATCOM significantly improves system performance by reducing power losses, enhancing voltage stability, and optimizing transmission efficiency. The analysis reveals that HVDC systems with SSSC outperform other configurations in terms of power loss reduction and voltage stability, while STATCOM improves voltage regulation and minimizes deviations. This study highlights the benefits of incorporating SSSC and STATCOM into HVDC systems for enhancing power system efficiency, stability, and operational reliability. [ABSTRACT FROM AUTHOR]

A continuous trend of growing load demand in the present-day power distribution networks (PDNs) often forces these networks to operate on the verge of their loadability limits. Under such a stressed condition, the network reconfiguration (a proven effective method) needs to be executed efficiently in the presence of distributed generators (DGs) so as to enhance the stability limit along with other objectives. The complexity grows even more when parameters like loadability and voltage stability need to be evaluated under critical loading conditions. For all the above reasons, the proper arrangement of the line data for different open switch combinations satisfying the system operational constraints is a significant challenge for the execution of load flow for effective planning. To address this issue, a new framework is proposed using a graph theory integrated sweep-based radial load flow (RLF) technique with an inbuilt mechanism of feasibility (radiality and connectivity) checking. Unlike other conventional RLF techniques, this approach does not require any sequential node and branch numbering and it has the ability to handle topological changes with constant annual load growth. The superiority of the suggested approach is validated by considering a 69-bus test distribution system for four different cases of DG and network reconfiguration (NR) under four different load conditions. The comparative analysis of various parameters including active power loss reduction, loadability maximization, voltage stability maximization, and minimum system voltage under distinct load conditions are presented which can be a part of futuristic distribution system planning and can successfully avoid system voltage collapse. [ABSTRACT FROM AUTHOR]

Recent advancements in renewable energy technologies, alongside changes in utility infrastructure and progressive government policies, have bolstered the integration of renewable-based distributed generation units within distribution systems. This paper introduces the Energy Valley Optimizer, a novel tool designed for the strategic placement of distributed generation units and capacitor banks. This placement is crucial not only for optimizing energy loss and enhancing bus voltage stability but also for promoting sustainable energy use and reducing environmental impact over the long term. By minimizing energy loss and voltage fluctuations, the optimizer contributes to a more sustainable and resilient energy system. It achieves this through the optimal allocation of resources across various load patterns within a 24 h period and is tested on the ALG-AB-Hassi-Sida 157-bus distribution network in South Algeria. Comparative analysis with existing algorithms—such as the Liver Cancer Algorithm, Walrus Optimization Algorithm, and Zebra Optimization Algorithm—demonstrates the superior performance of the Energy Valley Optimizer. It not only enhances technical and economic efficiencies but also significantly lowers the total cost of energy over 24 years, thus supporting sustainable development goals in energy management. [ABSTRACT FROM AUTHOR]

This paper emphasizes the significance of implementing an effective control system to enhance the performance of a three-stage DC–DC buck converter (TDDC). Herein, we present the development of an observer controller (OC) for TDDC, where average modeling of the DC–DC converter was employed alongside an observer algorithm for the OC. The primary focus is on the adoption of an observation topology aimed at enhancing system responsiveness under various conditions, including variable input voltages, reference voltage changes, load fluctuations, integration with photovoltaics, and battery charging. This approach ensures improved stability and performance, addressing the dynamic challenges inherent in such systems. A comparative analysis was conducted on two distinct control topologies for the proposed TDDC system, namely proportional–integral (PI) and advanced OC. Simulink software was used to model and simulate the proposed system. The results demonstrate lower rising and settling times of the TDDC for the OC and PI implementations, respectively. Additionally, the system with the OC eliminates 20% of the overshoot, while the system with OC minimizes the output voltage oscillations from 13% to 2% compared to the PI system. The OC was integrated into the TDDC to enhance system stability and improve the control loops, particularly the third loop. These improvements make the TDDC with OC suitable for application to renewable energy systems, microgrids, telecommunication networks, and electric vehicles, where precise control and stability are essential.

Voltage instability is a major problem facing power utility companies due to a lack of maintenance and financial support to maintain the existing power system networks (PSN). Lack of maintenance occurs when PS fails to replace the aging equipment and services and upgrades existing networks. Also, the lack of financial support occurs when there is insufficient financial capital to carry out the above maintenance activities, which has incurred greater power loss in the systems. There is a need to eliminate the loss incurred in the system to avoid voltage collapse. The best way to increase the lifespan of a PSN and improve voltage stability is the optimum allocation of distributed generation (DG). The most common DG are solar photovoltaic (PV) and wind turbines. This review discusses the economic, environmental, and technical benefits of non-traditional DG technologies over a traditional system. However, this work reviewed different DG technologies that can be incorporated into PSN for better loss reduction. Detailed descriptions of energy loss, power loss, and multi-objectives for optimal DG planning were also discussed, along with comprehensive methods used in the sizing and placement of DG for voltage profile improvement (VPI). The findings recommend that the hybrid meta-heuristic algorithm be used for DG placement has it significantly improves voltage profile and lowers power loss. The present study concluded that with proper DG placement, the advantage of DG can be maximally accomplished, the voltage profile is improved, and losses are minimized.

The continuous challenge of ensuring energy supply is a significant concern. Traditionally, utilities have addressed increasing load demands by building new central power plants or expanding existing ones. However, these methods are time-consuming and costly, providing only short-term solutions. Additionally, power plants are often far from load centers, resulting in higher power losses during long-distance transmission. The integration of distributed generation (DG), characterized by smaller scale and lower capital costs, with nearby consumers can effectively address these challenges. Due to the significant influence of DG penetration and their specific locations on the distribution system's performance, this study offers a novel Zebra Optimization Algorithm (ZOA). The suggested ZOA is used to optimize the capacity and position of various DG units connected to a radial distribution system to reduce power losses and study the stability of the system after DG allocation using the Voltage Stability Index (VSI). The evaluation is conducted using the IEEE 33-bus test system, considering various scenarios including single and multiple DGs of different types. The results demonstrate that in the best scenario, the ZOA can reduce losses by up to 94.25 % and improve the VSI from 0.69643 to 0.9605. These findings highlight the superior performance of the ZOA over other techniques in optimizing DG placement and sizing for power system performance.

The shift of conventional vehicles to electric vehicles (EVs) is on pace nowadays. Increment in EVs adoption eventually results as increment of load on the existing power distribution system. This increment can adversely affect the performance of the distribution system. Location of electric vehicles charging station (EVCS) in the distribution system requires more technical finding before moving on into it. Implementation needs attention for several aspects like electric profile, economics, and traffic management and so, this work considers all of them. The impact of charging stations (EVCS) on operating parameters of the distribution network such as voltage stability, reliability and power losses are investigated by the proposed formulation of a Voltage Stability-Reliability-Power Loss (VRP) indices in this work. This index has the capabilities of considering voltage stability, reliability, and power loss under a single frame. The capabilities of the system with random load changes are compared with the base system without increments in load. This presented work gives assurance about the EV based load increment capabilities in the existing system without compromising with distribution system constraints. The main contribution of the proposed work is to examine the impact of voltage sensitivity, system stability, power losses, reliability measures, and a complex VRP index on choosing locations for EV charging stations and its effects on the existing system. Also, to ensure accurate results, these factors are assessed across seven distinct load scenarios, contributing significantly to the ongoing research in this field.

The global electricity demand is growing rapidly and is expected to double by 2050. This growth requires significantly expanding the current high-voltage transmission lines, which is a long-term and costly solution. As an alternative, utilities use advanced technologies like Flexible Alternating Current Transmission System (FACTS) devices as a temporary measure, postponing the expansion. However, it is necessary to locate these devices in the network properly to avoid negative outcomes. Traditional methods for FACTS placement focus on voltage profile improvement and power loss reduction, neglecting rotor angle stability. This can lead to oscillatory instability, especially in weak power grids. To address this issue, the paper proposes a simple approach to optimize the placement of shunt FACTS devices in power systems. The method improves both voltage and rotor angle stability without compromising power loss. The proposed approach considers rotor angle stability constraints, which is essential for system stability during transient events. The study was demonstrated on Nigeria’s 50-bus 330 kV power system, with results indicating a 31% improvement in angle stability with an enhanced voltage profile. The method is straightforward, non-iterative, and provides a cost-effective solution for FACTS device placement in power systems.

Abstract A structured approach to managing reactive power is imperative within the context of power systems. Among the restructuring initiatives in the electrical sector, power systems have undergone delineation into three principal categories: generation, transmission, and distribution entities, each of which is overseen by an independent system operator. Notably, active power emerges as the predominant commodity transacted within the electrical market, with the autonomous grid operator assuming the responsibility of ensuring conducive conditions for the execution of energy contracts across the transmission infrastructure. Ancillary services, comprising essential frameworks for energy generation and delivery to end-users, encompass reactive power services pivotal in the regulation of bus voltage. Of particular significance among the array of ancillary services requisite in a competitive market milieu is the provision of adequate reactive power to uphold grid safety and voltage stability. A salient impediment to the realization of energy contracts lies in the inadequacy of reactive power within the grid, which poses potential risks to its operational safety and voltage equilibrium. The optimal allocation of the reactive power load is predicated upon presumptions of consistent outcomes within the active power market. Under this conceptual framework, generators are afforded continual compensation for the provision of reactive power indispensable for sustaining their active energy production endeavors.

Abstract Under grid voltage sags, over current protection and exploiting the maximum capacity of the inverter are the two main goals of grid-connected PV inverters. To facilitate low-voltage ride-through (LVRT), it is imperative to ensure that inverter currents are sinusoidal and remain within permissible limits throughout the inverter operation. An improved LVRT control strategy for a two-stage three-phase grid-connected PV system is presented here to address these challenges. To provide over current limitation as well as to ensure maximum exploitation of the inverter capacity, a control strategy is proposed, and performance the strategy is evaluated based on the three generation scenarios on a 2-kW grid connected PV system. An active power curtailment (APC) loop is activated only in high power generation scenario to limit the current’s amplitude below the inverter’s rated current. The superior performance of the proposed strategy is established by comparison with two recent LVRT control strategies. The proposed method not only injects necessary active and reactive power but also minimizes overcurrent with increased exploitation of the inverter’s capacity under unbalanced grid voltage sag.

A structured approach to managing reactive power is imperative within the context of power systems. Among the restructuring initiatives in the electrical sector, power systems have undergone delineation into three principal categories: generation, transmission, and distribution entities, each of which is overseen by an independent system operator. Notably, active power emerges as the predominant commodity transacted within the electrical market, with the autonomous grid operator assuming the responsibility of ensuring conducive conditions for the execution of energy contracts across the transmission infrastructure. Ancillary services, comprising essential frameworks for energy generation and delivery to end-users, encompass reactive power services pivotal in the regulation of bus voltage. Of particular significance among the array of ancillary services requisite in a competitive market milieu is the provision of adequate reactive power to uphold grid safety and voltage stability. A salient impediment to the realization of energy contracts lies in the inadequacy of reactive power within the grid, which poses potential risks to its operational safety and voltage equilibrium. The optimal allocation of the reactive power load is predicated upon presumptions of consistent outcomes within the active power market. Under this conceptual framework, generators are afforded continual compensation for the provision of reactive power indispensable for sustaining their active energy production endeavors. [ABSTRACT FROM AUTHOR]

In large-scale wind farms, the voltage fluctuations caused by the uncertainty of wind speed at the turbine terminals pose a pressing challenge. This article presents a localized voltage control strategy tailored toward rapid adjustments in turbine terminal voltage in wind turbine generators. Based on relative voltage observation, this strategy achieves voltage coordination between the high and low ends of the transformer in wind turbine generators. Firstly, the overall structure of the wind farm and the characteristics of terminal voltage are analyzed. Secondly, the principles and feasibility of the relative voltage control strategy are examined. Finally, the effectiveness of the proposed control strategy is validated through simulation results from a specific wind farm. The results demonstrate its capability to achieve a fast and stable voltage dynamic response within the wind farm based on local information, thus mitigating the risk of voltage out of limit. [ABSTRACT FROM AUTHOR]

The maintenance of an uninterrupted electricity supply to meet demand is of paramount importance for maintaining the stable operation of an electrical power system. Machine learning and deep learning play a crucial role in maintaining that stable operation. These algorithms have the ability to acquire knowledge from past data, enabling them to efficiently identify and forecast potential scenarios of instability in the future. This work presents a hybrid convolutional long short-term memory (ConvLSTM) technique for training and predicting nodal voltage stability in an IEEE 14-bus microgrid. Analysis of the findings shows that the suggested ConvLSTM model exhibits the highest level of precision, reaching a value of 97.65%. Furthermore, the ConvLSTM model has been shown to perform better compared to alternative machine learning and deep learning models such as convolutional neural networks, k-nearest neighbors, and support vector machine models, specifically in terms of accurately forecasting voltage stability. The IEEE 14-bus system tests indicate that the suggested method can quickly and accurately determine the stability status of the system. The comparative analysis obtained the results and further justified the efficiency and voltage stability of the proposed model. [ABSTRACT FROM AUTHOR]

Under grid voltage sags, over current protection and exploiting the maximum capacity of the inverter are the two main goals of grid-connected PV inverters. To facilitate low-voltage ride-through (LVRT), it is imperative to ensure that inverter currents are sinusoidal and remain within permissible limits throughout the inverter operation. An improved LVRT control strategy for a two-stage three-phase grid-connected PV system is presented here to address these challenges. To provide over current limitation as well as to ensure maximum exploitation of the inverter capacity, a control strategy is proposed, and performance the strategy is evaluated based on the three generation scenarios on a 2-kW grid connected PV system. An active power curtailment (APC) loop is activated only in high power generation scenario to limit the current’s amplitude below the inverter’s rated current. The superior performance of the proposed strategy is established by comparison with two recent LVRT control strategies. The proposed method not only injects necessary active and reactive power but also minimizes overcurrent with increased exploitation of the inverter’s capacity under unbalanced grid voltage sag. [ABSTRACT FROM AUTHOR]

Challenges in the operation of power systems arise from several factors such as the interconnection of large power systems, integration of new energy sources and the increase in electrical energy demand. These challenges have required the development of fast and reliable tools for evaluating the operation of power systems. The load margin (LM) is an important index in evaluating the stability of power systems, but traditional methods for determining the LM consist of solving a set of differential-algebraic equations whose information may not always be available. Data-Driven techniques such as Artificial Neural Networks were developed to calculate and monitor LM, but may present unsatisfactory performance due to difficulty in generalization. Therefore, this article proposes a design method for Physics-Informed Neural Networks whose parameters will be tuned by bio-inspired algorithms in an optimization model. Physical knowledge regarding the operation of power systems is incorporated into the PINN training process. Case studies were carried out and discussed in the IEEE 68-bus system considering the N-1 criterion for disconnection of transmission lines. The PINN load margin results obtained by the proposed method showed lower error values for the Root Mean Square Error (RMSE), Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE) indices than the traditional training Levenberg-Marquard method. [ABSTRACT FROM AUTHOR]