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Since the power grid grows and the necessity for higher system efficiency is due to the increasing number of renewable energy penetrations, power system operators need a fast and efficient method of operating the power system. One of the main problems in a modern power system operation that needs to be resolved is optimal power flow (OPF). OPF is an efficient generator scheduling method to meet energy demands with the aim of minimizing the total production cost of power plants while maintaining system stability, security, and reliability. This paper proposes a new method to solve OPF by using incremental particle swarm optimization (IPSO). IPSO is a new algorithm of particle swarm optimization (PSO) that modifies the PSO structure by increasing the particle size, where each particle changes its position to determine its optimal position. The advantage of IPSO is that the population increases with each iteration so that the optimization process becomes faster. The results of the research on optimal power flow for energy generation costs, system voltage stability, and losses obtained by the IPSO method are superior to the conventional PSO method. [ABSTRACT FROM AUTHOR]

Distributed energy resource (DER) has become an effective attempt in promoting use of renewable energy resources for electricity generation. The core intention of this study is to expand an approach for optimally placing several DER units to attain the most stable performance of the system and the greatest power losses decrease. The recommended technique is established on two analytical methods for analyzing voltage stability: the new modified modal analysis (MMA) and the continuation power flow (CPF) or MMA–CPF methods. The MMA evaluates voltage stability by considering incremental connection relating voltage and active power, which includes the eigenvalue and the related eigenvectors computed from the reduced modified Jacobian matrix. Furthermore, an active participation factor (APF) is computed from the eigenvectors of the reduced modified Jacobian matrix. The CPF method uses a predictor–corrector stepping pattern to reach the solution track and compute the tangent vector sensitivity (TVS). Both APF and TVS indicate each load bus sensitivity in the network. In addition, an objective function regarding losses decrease and eigenvalue is expressed to calculate the best bus position for DER allocation. The proposed MMA–CPF technique has been assessed on a 34-bus RDN and the outcomes demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

The quest for an intelligence compliance system to solve power stability problems in real-time with high predictive accuracy, and efficiency has led to the discovery of deep learning (DL) techniques. This paper investigates the potency of several artificial neural network (ANN) techniques in assessing the steady-state stability of a power system. The new voltage stability pointer (NVSP) was employed to parameterize and reduce the input data to the neural network algorithms to predict the proximity of power systems to voltage instability. In this study, we consider five neural network algorithms viz. feedforward neural network (FFNN), cascade-forward neural network (CFNN), layer recurrent neural network (LRNN), linear layer neural network (LLNN), and Elman neural network (ENN). The evaluation is based on the predictability and accuracy of these techniques for dynamic stability in power systems. The neural network algorithms were trained to mimic the NVSP dataset using a Levenberg-Marquardt (LM) model. Similarly, the performance analyses of the neural network techniques were deduced from the regression learner algorithm (RLA) using a root-mean-squared error (rmse) and response plot graph. The effectiveness of these NN algorithms was demonstrated on the IEEE 30-bus system and the Nigerian power system. The simulation results show that the FFNN and the CFNN possess a relatively better performance in terms of accuracy and efficiency for the considered power networks. [ABSTRACT FROM AUTHOR]

Electricity market players prioritize available transfer capability (ATC) as an attractive solution. Market participants can gain a financial advantage through accurate and fast ATC solutions. In order to provide a suitable and valuable solution, we use differential load flow equations. A dynamic system's entire time-domain trajectory can be solved by this method, along with a fictional time-domain differential equation. This article uses Newton-Raphson- Seydel instead of Newton-Raphson, which can also be used to determine voltage stability. A variable frequency transformer (VFT) was used in this study to increase and control transmission power. A 50% time saving on small systems was achieved with the proposed method, which was applied to seven different systems. In addition, it performed better on large systems by more than 90%. This proposal for static ATC presents promising results and can be applied to online applications. [ABSTRACT FROM AUTHOR]

Copyright of Revista Técnica Energía is the property of Centro Nacional de Control de Energia CENACE 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.)

Copyright of Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji is the property of Gazi University 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.)

Voltage stability represents one of the main issues in electrical power system. Under voltage load shedding (UVLS) has long been regarded as one of the most successful techniques to prevent the voltage collapse. However, the ordinary load shedding schemes do not consider the different load models and decreasing in the economic cost that resulted from load disconnection, so the dual techniques of load shedding with reactive compensation are needed. Usually loads being modeled as constant power, while in fact of load flow the various load models are utilized. An investigation of optimal dual load shedding with reactive compensation for distribution system based on direct backward forward sweep method (DBFSM) load flow along with a comparison among the other load models are presented in this paper. The teaching learning-based optimization (TLBO) algorithm is executed in order to reduce power losses and enhance the voltage profile. This algorithm is tested and applied to IEEE-16 bus distribution test system to find the optimal superior capacitor size and placement while minimizing load shading for the network. Five different load shedding sequences are considered and the optimization performance of load models demonstrated the comparison through MATLAB program. [ABSTRACT FROM AUTHOR]

Voltage and reactive power become one of the most critical aspects to monitor and sustain at an appropriate level in vast alternative current networks to ensure good functionality, load satisfaction, network integrity, and service quality. The network's spending should be obtained by calculating the load flow or applying more controllable variables to it, defined as the optimization power flow. In this vein, this paper focuses on improving the network's voltage profile, reactive power generation, and losses. The study begins with load flow estimation in various situations using the Newton–Raphson process, followed by an optimization capacity calculation using the simplified Reduced Gradient power flow method. For each system, four cases are simulated, one with and one without the SVC (Static Var Compensator) device, which is positioned in an ideal position on the IEEE 57 bus network. The confirmation of the data is carried out using the MATLAB program. A distinction is made between the two approaches based on the SVC device's position and its reactive power generation into the network. The simulation results indicate that the generalized Reduced Gradient optimization approach (GRG-OPF) offers reasonable efficiency, quick iteration in the simulation results, the best power budget with minimal active/reactive losses and the best voltage profile specifically in the case where SVC reactive power is taken as a variant into the GRG-OPF method. [ABSTRACT FROM AUTHOR]

This paper studies the voltage stability of the Slovak Republic's power system (PS) based on an assessment of the PV curves. The PV curve is a tool for assessing voltage stability, and based on its shape, it is possible to determine weak and strong voltage nodes with the possibility of voltage stability reserve quantification. We present an analysis of the influence of transformers with an automatic voltage regulator (AVR) on the shape of the PV curves and on the magnitude of voltage in the PS. In general, the 400 kV/110 kV transformers equipped with AVRs are critical assets for the PS as they address voltage control in the DS. However, in the case of voltage problems in the TS, the AVR function may worsen the voltage situation across the entire PS. Therefore, we closely analyze the negative effects of the AVR on the PS operation. This impact is clearly proved, and recommendations are given for the transmission system operator (TSO) in order to maintain voltage stability. In addition, the PV curves of the pilot nodes are analyzed very accurately, thereby confirming their importance in the TS in terms of a sufficient reserve of reactive power. The study was conducted in cooperation with the TSO, Slovenská elektrizačná prenosová sústava, a.s. [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.)

Based on the analysis of the operation characteristics of photovoltaic cells, a novel virtual synchronous generator adaptive power regulation strategy for two-stage three-phase photovoltaic system with high permeability of clean energy is proposed. By improving the maximum power point tracking process of photovoltaic cells, the variable power point tracking control of photovoltaic cells is realized, and the control effect of DC/DC converter on the output power of photovoltaic cells is fully exerted. Without additional energy storage equipment, the energy supply required for inertia support and primary regulation of virtual synchronous generator is accurately realized. Combined with inverter VSG control strategy, the control of photovoltaic virtual synchronous generator is realized.

One of the major concerns about the growing penetration of renewable energy into the power network is the analysis of the impact of such penetration on system stability. The Local Thevenin Index (LTI) based on the Wide Area Monitoring System (WAMS) is a novel technique in scientific research to assess the voltage stability of power systems integrated with renewable energy. From the standpoint of grid voltage stability, this index aids in determining the best location for integrating the wind farm into the existing power system. The effect of a significant penetration of doubly-fed induction generator (DFIG) based wind farms on the voltage stability of a large power network is analyzed in this research. The novelty of this research is to find the effect of the rise in wind power penetration level and additional distributed loads on a wind farm integrated large power system for voltage stability analysis. The MATLAB-Simulink platform is used to validate the proposed work with the New England 16-machine 68-bus power system.

Global energy demand pushes transmission lines to their limits, which causes voltage instability on the power grids. Solar and wind farms are being integrated with increased size and capacity to meet increased load demands, and this increased volumes of renewables, combined with their lower inertia and more sensitive voltage profiles, are complicating system operators’ roles. The execution of phasor measurement unit (PMU) with novel detection and protection schemes has been a focal point for power engineers. The real-time wide-area monitoring system (WAMS) helps grid operators to improve real-time voltage stability, situational awareness, fault detection, and grid planning. WAMS shows the path for developing substation predictions, improving system accuracy, and identifying control strategies to avoid power blackouts. It conducts post-event analysis and reduces the processing time of the power restoration. The novelty of this article is to describe load modeling, voltage stability, and islanding protection in real-time, as well as the technical challenges, limitations, opportunities, and solutions related to the same. Further, the paper explores and presents vital software and hardware resources, including HIL systems, for future use and research with WAMS technology.

In order to relieve the energy pressure and promote the clean transformation of energy structure, the new energy represented by wind power and photovoltaic power generation is connected to the grid on a large scale. However, due to the small inertia of the new energy unit, the proportion of conventional power supply decreases, and the system has the problems of frequency stability and voltage stability. In this paper, the reactive power distribution, voltage and frequency stability characteristics of the long chain connection channel of weak connection power network are studied. Combined with the actual situation of simulation and calculation of power grid A, the influence of photovoltaic centralized access on the load frequency characteristics of weak connection power network is analyzed, and some suggestions are put forward.

• A new comprehensive voltage stability index that characterized by minimal assumptions is formulated and suggested. • Develop a proposed index based on the most accurate transmission line model that can consider the impact of line length on voltage stability evaluation. • The new index takes into account the impact of off-load and on-load tap changer transformers that verified its accuracy by implementing some cases. Recently, voltage stability has become increasingly important because of the expansion and growing demands on power transmission networks. Several factors may contribute to the blackouts occurrence in power system, including severe voltage instability and insufficient power transfer capabilities. To avert voltage collapse in power grids, identifying the critical operating conditions with high precision is crucial. By representing a new index in this paper, the assessment of voltage stability within transmission networks can be undertaken. In contrast to other indices, the proposed index has least assumptions and can assess the voltage stability in power systems with significant precision. Afterward, the suggested index is broadened to encompass the influence of on-load tap changers (OLTC). In order to attain this, the OLTC model has been developed using a precise implementation of mathematical equations, enabling an accurate evaluation of the impact of tap changer variations on voltage stability. To ascertain the efficacy of the proposed index, an evaluation has been conducted on a two-bus as well as 9-and 30-bus transmission test systems under various operational scenarios. The simulation outcomes suggest the superior effectiveness of the suggested index compared to other well-established indices. These results illustrate its ability to accurately assess the impacts of OLTC. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method rooted in differential geometry to approximate the voltage stability boundary of power systems under high variability of renewable generation. We extract intrinsic geometric information of the power flow solution manifold at a given operating point. Specifically, coefficients of the Levi-Civita connection are constructed to approximate the geodesics of the manifold starting at an operating point along any interested directions that represent possible fluctuations in generation and load. Then, based on the geodesic approximation, we further predict the voltage collapse point by solving a few univariate quadratic equations. Conventional methods mostly rely on either expensive numerical continuation at specified directions or numerical optimization. Instead, the proposed approach constructs the Christoffel symbols of the second kind from the Riemannian metric tensors to characterize the complete local geometry which is then extended to the proximity of the stability boundary with efficient computations. As a result, this approach is suitable to handle high-dimensional variability in operating points due to the large-scale integration of renewable resources. Using various case studies, we demonstrate the advantages of the proposed method and provide additional insights and discussions on voltage stability in renewable-rich power systems. • High renewable penetration leads to global parameter variation in power flow equations. • A novel method is proposed to estimate power flow solution space boundary. • Only local information is needed to construct manifold geometrics based on Levi-Civita connection. • Shape of the voltage stability boundary for global parameter variation is obtained. • Numerical studies demonstrate high speedup compared to continuation power flow. [ABSTRACT FROM AUTHOR]

In this paper, a systematic short- and long-term voltage stability analysis of grid-forming converters with current limitations is conducted. For this, sampling studies are performed in an aggregated version of the Nordic test system. Here, the grid-forming control approach, the simulation type (EMT/phasor), current prioritisation and load composition are varied. Also, a stability-enhancing control method is developed to stabilise the converter during current limitation. The proposed method does not require any parameter tuning and can be applied to almost all grid-forming approaches. Its performance is demonstrated by comparing it to similar methods. The results show that the proposed method can greatly improve short- and long-term voltage stability for all investigated grid-forming approaches. In addition, accurate load models are crucial, as small modelling differences can have a greater impact on stability than the choice of simulation type. Here, both simulation types show the same voltage dynamics but have small differences in the stability limits. • Voltage stability analysis of various grid-forming converters with current limitation. • Variations in control approach, model type (phasor/EMT) and current prioritisation. • Derivation of a computationally efficient power system model for sampling studies. • Short and long-term voltage instability can occur due to current limitation. • A proposed stability-enhancing control method can stabilise the converter. [ABSTRACT FROM AUTHOR]

We propose a neural network using an unsupervised learning strategy for direct computation of closest saddle–node bifurcations, eliminating the need for labeled training data. Our method not only estimates the worst-case load increase scenarios but also significantly reduces the computational complexity traditionally associated with this task during inference time. Simulation results validate the effectiveness and real-time applicability of our approach, demonstrating its potential as a robust tool for modern power system analysis. • Using neural networks to approximate proximity to the bifurcation surface. • Unsupervised learning strategy: No need for labeled data. • Augmented Lagrangian formulation for constraint handling. • Offline neural network training for rapid, accurate load scenario predictions online. [ABSTRACT FROM AUTHOR]

This paper proposes the new problem of calculating the worst-voltage-case (WVC) under power flows uncertainty, particularly at interfaces between transmission and distribution grid operators. The goal of the calculation is to verify if the realization of the worst uncertainty scenario leads to abnormal voltages, or assure where the voltage instability is not a risk, and inform the transmission system operator. The problem is formulated as a tailored non-convex, nonlinear optimal power flow (OPF) with complementarity or equilibrium constraints (ECs). The latter model the generator switch between under voltage control and under reactive power limit. The problem is converted into a mathematically equivalent nonlinear programming OPF problem in which ECs are handled as penalty terms in the objective function. The paper has conducted a series of experiments on the 60-bus Nordic system, which have pointed out the challenges associated to such computations to obtain meaningful results and unveiled new insights. The findings and scalability are confirmed using a real-world 1203-bus system. • This paper proposes the new problem of calculating the worst voltage under flows uncertainty at TSO-DSO interfaces. • The goal of the calculation is to verify if the worst uncertainty scenario creates voltage instability. • The problem is formulated as a tailored AC optimal power flow with complementarity constraints. • The problem is converted into a scalable equivalent OPF problem in which complementarity constraints are handled as penalty terms. • The paper pointed out the challenges to this computation to obtain meaningful results and unveiled new insights. [ABSTRACT FROM AUTHOR]

The deployment of medium-duty and heavy-duty (MDHD) electric vehicles (EVs), characterized by their substantial battery capacity and high charging power demand, poses a potential threat to voltage stability within distribution networks. One possible solution to voltage instability is reactive power compensation from charging MDHD EVs. However, this process must be carefully facilitated in order to be effective. This paper introduces an innovative distribution network voltage stability solution by first identifying the network’s weakest buses and then utilizing a metaheuristic algorithm to schedule reactive power compensation from MDHD EVs. In the paper, multiple metaheuristic algorithms, including genetic algorithms, particle swarm optimization, moth flame optimization, salp swarm algorithms, whale optimization, and grey wolf optimization, are subjected to rigorous evaluation concerning their efficacy in terms of voltage stability improvement, power loss reduction, and computational efficiency. The proposed methodology optimizes power flow with the salp swarm algorithm, which was determined to be the most effective tool, to mitigate voltage fluctuations and enhance overall stability. The simulation results, conducted on a modified IEEE 33 bus distribution system, convincingly demonstrate the algorithm’s efficacy in augmenting voltage stability and curtailing power losses, supporting the reliable and efficient integration of MDHD EVs into distribution networks.

Recently, the generalization of P2P (peer-to-peer) technology with enhanced security due to blockchain technology and the expansion of renewable energy-based distributed energy resources have led to blockchain technology being applied in power transactions, thus giving the potential to become a new platform for DC microgrid operation. Meanwhile, the voltage of a DC microgrid represents the balance of energy supply and demand and also serves as a stability index. The balance is represented as a steady state; the stability is represented during and after events. This paper examines the stability of the DC microgrid built on a university campus in Korea and, in particular, the blockchain technology-based power transactions performed in the DC microgrid. The test is based on the pre-planned transaction schedule applied in the DC microgrid. The transaction schedule has used day-ahead and real-time bidding data. Although many technologies are included in the project, this paper focuses on the voltage stability of the DC microgrid. In addition, the DC protection is applied and evaluated. To consider general DC protection, the DC breaker was simplified with several IGBTs, diodes, capacitors, and arrestors and was designed to interrupt the fault current within five milliseconds. The stability was evaluated using a PSCAD/EMTDCTM.

Advancements in power conversion efficiency and the growing prevalence of DC loads worldwide have underscored the importance of DC microgrids in modern energy systems. Addressing the challenges of power-sharing and voltage stability in these DC microgrids has been a prominent research focus. Sliding mode control (SMC) has demonstrated remarkable performance in various power electronic converter applications. This paper proposes the integration of universal droop control (UDC) with SMC to facilitate distributed energy resource interfacing and power-sharing control in DC microgrids. Compared to traditional Proportional-Integral (PI) control, the proposed control approach exhibits superior dynamic response characteristics. The UDC is strategically incorporated prior to the SMC and establishes limits on voltage variation and maximum power drawn from the DC–DC converters within the microgrid. A dynamic model of the DC–DC converter is developed as the initial stage, focusing on voltage regulation at the DC link through nonlinear control laws tailored for Distributed Generation (DG)-based converters. The UDC ensures voltage stability in the DC microgrid by imposing predetermined power constraints on the DGs. Comparative evaluations, involving different load scenarios, have been conducted to assess the performance of the proposed UDC-based SMC control in comparison to the PI control-based system. The results demonstrate the superior efficiency of the UDC-based SMC control in handling dynamic load changes. Furthermore, a practical test of the proposed controller has been conducted using a hardware prototype of a DC microgrid.

In the process of integrating renewable energy sources into DC microgrids, the isolated bidirectional bridge plays a crucial role. Under load disturbances, voltage fluctuations in the microgrid can affect system stability. This study focuses on using a Genetic Algorithm to optimize the parameters of three typical DAB controllers (PI controller based on pole placement, sliding mode controller, and model predictive controller) with the aim of improving voltage stability, especially during sudden load drops. The results demonstrate that controllers optimized using Genetic Algorithm outperform the methods of pole placement and traditional manual tuning significantly. For the PI controller, the maximum drop rate reduced from 8.00% to 4.00%. The phase margin increased from 123° to 126°. In the case of the sliding mode controller, the maximum drop rate decreased from 7.50% to 5.00%. The phase margin increased from 127° to 155°. As for the model predictive controller, the maximum drop rate reduced from 1.00% to 0.70%. The gain margin increased from 25.8 dB to 26.2 dB. These results highlight the potential of using the Genetic Algorithm in optimizing control parameters, offering the prospect of improving the performance and stability of DC–DC converters.

The ongoing development of renewable energy and microgrid technologies has gradually transformed the conventional energy infrastructure and upgraded it into a modernized system with more distributed generation and localized energy storage options. Compared with power grids utilizing synchronous generation, inverter-based networks cannot physically provide large amounts of inertia, which means that more advanced and extensive studies regarding stability considerations are required for such systems. Therefore, appropriate analytical methods are needed for the voltage stability analysis of renewable-dominated power systems, which incorporate a large number of inverters and distributed energy sources. This paper provides a comprehensive literature review of voltage stability analyses of power systems with high levels of renewable energy penetration. A series of generalized evaluation schemes and improvement methods relating to the voltage stability of power systems integrated with various distributed energy resources are discussed. The existing voltage stability analysis methods and corresponding simulation verification models for microgrids are also reviewed in a systematic manner. The traditional and improved voltage stability analysis methods are reviewed according to the microgrid operation mode, the types of distributed generators, and the microgrid configurations. Moreover, the voltage stability indices, which play a crucial role in voltage stability assessments, are critically evaluated in terms of the applicable conditions. The associated modeling and simulation techniques are also presented and discussed. This contribution presents guidelines for voltage stability analysis and instability mitigation methods for modern renewable-rich power systems.