Voltage Stability Research Articles

Reduction‐Induced Oxygen Loss: the Hidden Surface Reconstruction Mechanism of Layered Oxide Cathodes in Lithium‐Ion Batteries

AbstractThe surface reconstruction from the layered to rocksalt‐type phase represents a primary deterioration pathway of layered‐oxide cathodes in lithium‐ion batteries, involving irreversible oxygen loss and transition metal migration. This degradation mechanism has primarily been attributed to the oxidative instability of highly delithiated cathodes at high voltages (>4.3 V vs Li/Li+). However, the battery degradation also occurs under seemingly stable voltage ranges, the origin of which remains unclear. Herein, a hidden mechanism to induce surface reconstruction and oxygen loss is proposed, termed the “quasi‐conversion reaction”, which is revealed to occur during electrochemical reduction (discharge) processes just below 3.0 V (vs Li/Li+). Combined experiments and first‐principles calculations unveil that the oxygens at the surface can be extracted from the cathode lattice by forming lithium oxides and oxygen vacancies, at significantly higher potentials than conventional conversion reaction, due to the instability of surface oxygens coordinated with fewer cations than in the bulk. The chemical incompatibility between lithium oxides and commercial carbonate‐based electrolytes results in electrolyte decomposition, forming an organic‐rich blocking layer and gaseous byproducts, which further increases the cell impedance. This study emphasizes the necessity of a thorough understanding of surface instability upon reduction to develop long‐lasting batteries.

A Robust Linear Active Disturbance Rejection Control for Renewable Energy Grid-Connected System Based on APF

With the energy transition and changes in electrical load structures, harmonic distortion in power systems is increasingly threatening grid stability, especially during the integration of renewable energy sources. Active power filters (APFs) are commonly used to improve power quality, but current fluctuations and voltage instability caused by DC-side capacitor charging and discharging hinder effective harmonic compensation. To address this, this paper presents a method combining a variable-step-size adaptive linear predictor with linear active disturbance rejection control (VALP-LADRC). By integrating an adaptive linear predictor (ALP) with LADRC, the proposed method effectively reduces the impact of disturbances on control, improving voltage regulation and harmonic compensation, and enhancing renewable energy grid integration. To address delays during the adjustment of initial parameters in the adaptive predictor, we combine it with a variable-step-size algorithm, significantly improving disturbance rejection and tracking accuracy, while solving voltage drop issues. The simulation results in a photovoltaic grid-connected system show that VALP-LADRC effectively mitigates disturbances, ensures voltage stability, and enhances power quality. This approach offers a promising solution for supporting sustainable development through better renewable energy integration and improved power quality.

Improving Power Quality and Fault Ride-Through (FRT) in Grid-Connected Hybrid Energy Systems: Design and Optimization of Dynamic Voltage Restorers

The integration of renewable energy sources (RESs) into grid-connected systems has become pivotal in addressing climate change and building a sustainable, carbon-neutral society. However, challenges like power quality issues, grid stability, and fault ride-through (FRT) requirements remain significant. This study explores strategies to enhance FRT capabilities and improve power quality in hybrid energy systems. It emphasizes the role of advanced devices such as Dynamic Voltage Restorers (DVRs), EV charging stations, and energy storage solutions. The effectiveness of these technologies is analyzed under various fault scenarios, highlighting improvements in transient response, voltage stability, and harmonic reduction. Additionally, hybrid energy systems, combining multiple RESs and backup sources, are proposed as viable solutions to address intermittency and system reliability. MATLAB/SIMULINK simulations validate the proposed approaches, showcasing their effectiveness in mitigating grid disturbances and maintaining operational efficiency. The findings underline the importance of innovative control strategies and hybrid configurations in ensuring a resilient and sustainable energy infrastructure.

Coordinated Volt/VAR Control in Distribution Networks Considering Demand Response via Safe Deep Reinforcement Learning

Volt–VAR control (VVC) is essential in maintaining voltage stability and operational efficiency in distribution networks, particularly with the increasing integration of distributed energy resources. Traditional methods often struggle to manage real-time fluctuations in demand and generation. First, various resources such as static VAR compensators, photovoltaic systems, and demand response strategies are incorporated into the VVC scheme to enhance voltage regulation. Then, the VVC scheme is formulated as a constrained Markov decision process. Next, a safe deep reinforcement learning (SDRL) algorithm is proposed, incorporating a novel Lagrange multiplier update mechanism to ensure that the control policies adhere to safety constraints during the learning process. Finally, extensive simulations with the IEEE-33 test feeder demonstrate that the proposed SDRL-based VVC approach effectively improves voltage regulation and reduces power losses.

Methodology for Determining the Optimal Location and Capacity of STATCOM Based on Grid Clustering for Grid Voltage Stability

Methodology for Determining the Optimal Location and Capacity of STATCOM Based on Grid Clustering for Grid Voltage Stability

ENHANCING VOLTAGE STABILITY AND ENERGY OUTPUT OF PLTM SALIDO IN THE PLN DISTRIBUTION NETWORK

Distributed generation (DG) integration in PLN’s extended distribution network often encounters voltage instability issues due to high voltage drops. These challenges restrict power delivery and can lead to disconnection, particularly during peak load conditions. This study investigates methods to enhance voltage stability and optimize the energy output of PLTM Salido. Using ETAP Power Station software, various operational schemes were simulated to address the problem of low terminal voltage. The study focused on the impact of reactive power injection and governor settings optimization to maintain generator performance under high demand. Results indicate that reactive power injection significantly improves terminal voltage, ensuring continuous power delivery. Adding a third generator unit further increased energy supply capacity, leveraging the full potential of available hydropower. The optimized operation of PLTM Salido with two generators increased daily energy output by 32.2%, while introducing a third generator boosted energy delivery by 107%. This research highlights the critical role of reactive power management and system configuration in enhancing the performance of small-scale hydropower plants in rural distribution networks.

Polysaccharides: The Sustainable Foreground in Energy Storage Systems

Polysaccharides offer a perfect option as raw materials for the development of a new generation of sustainable batteries and supercapacitors. This is due to their abundance and inherent structural characteristics. Polysaccharides can be chemically functionalized and engineered, offering a wide range of possibilities as electrode materials (as precursors of porous nanocarbons), binders and separators. Their hierarchical morphology also enables their exploitation as aerogel and hydrogel structures for quasi-solid and solid polymer electrolytes with high conductivity and wide voltage stability windows. In this review, we discuss how different polysaccharides, such as lignocellulosic biomass, starch, chitosan, natural gums, sugars and marine polysaccharides, can be applied in different components of energy storage systems (ESSs). An overview of the recent research work adhering to each functionality of different polysaccharides in various storage systems is provided.

Improving the Thermal Stability of Indium Oxide n-Type Field-Effect Transistors by Enhancing Crystallinity through Ultrahigh-Temperature Rapid Thermal Annealing.

Ultrathin indium oxide films show great potential as channel materials of complementary metal oxide semiconductor back-end-of-line transistors due to their high carrier mobility, smooth surface, and low leakage current. However, it has severe thermal stability problems (unstable and negative threshold voltage shifts at high temperatures). In this paper, we clarified how the improved crystallinity of indium oxide by using ultrahigh-temperature rapid thermal O2 annealing could reduce donor-like defects and suppress thermal-induced defects, drastically enhancing thermal stability. Not only does more crystalline indium oxide depict the high stability of threshold voltage in stringent high-temperature test environments and under positive bias, but it also shows much less degradation under forming gas annealing than as-deposited transistors. Furthermore, we also successfully solved the channel length-dependent threshold voltage problem, which is often observed in oxide transistors, by suppressing defects induced by the metal deposition process and metal doping.

Improved threshold voltage stability for GaN p-channel field effect transistors by hydrogen plasma treatment

Improved threshold voltage stability for GaN p-channel field effect transistors by hydrogen plasma treatment

Two-stage multi-objective framework for optimal operation of modern distribution network considering demand response program.

To improve the inadequate reliability of the grid that has led to a worsening energy crisis and environmental issues, comprehensive research on new clean renewable energy and efficient, cost-effective, and eco-friendly energy management technologies is essential. This requires the creation of advanced energy management systems to enhance system reliability and optimize efficiency. Demand-side energy management systems are a superior solution for multiple reasons. Firstly, they empower consumers to actively oversee and regulate their energy consumption, resulting in substantial cost savings by minimizing usage during peak hours and enhancing overall efficiency. The Demand Response Program (DRP) and optimal power sharing have gained significant attention to provide technical and economic benefits, while they require an efficient operation framework. Therefore, a two-stage framework is proposed for multi-objective operation of a distribution network with several generation resources. The first stage applies DRP to maximize the distribution network operator's (DNO) profit by optimizing common incentive rate for all consumers participate in DRP and an individual curtailed power for each consumer. In addition to an individual incentive rate for each consumer participates in DRP which is a new solution in the field of demand side management. The second stage achieves optimal power sharing among generation resources, while considering multiple objectives and incorporating the modified load of the first stage. The multi-objective problem is formulated to reduce energy losses, voltage deviation, total operational cost, gas emissions, and maximize the voltage stability index. The problem is optimized using a combination of the technique for order of preference by similarity to ideal solution (TOPSIS) and the elephant herding optimization (EHO) technique. The framework is validated using a modified IEEE 33-bus that incorporates photovoltaic system, diesel generators, and wind generation system. The proposed framework based on an individual incentive rate DRP provides superior response compared to common incentive rate DRP which reduces the total energy losses by 38.13%, reduces the total generation cost by 9.468%, and reduces the emission by 5.9%.

Optimal Siting, Sizing, and Energy Management of Distributed Renewable Generation and Storage Under Atmospheric Conditions

Integrating new generation and storage resources within power systems is challenging because of the stochastic nature of renewable generation, voltage regulation, and the use of microgrids. Classical optimization methods struggle with these nonlinear, multifaceted issues. This paper presents a novel optimization framework for integrating, sizing, and siting distributed renewable generation and energy storage systems in power distribution networks. To accurately reflect load variability, the framework considers four distinct load models—constant impedance, current, power, and ZIP (constant impedance, constant current, constant power). Our approach utilized three metaheuristic approaches to enhance the efficiency of power system management. The validation results on the IEEE 33 Bus System conclude that the Elephant Herding Optimization (EHO) emerged as the best performer regarding voltage stability and real power loss reduction with a voltage stability index of 0.0031346. Modified Ant Lion Optimization (ALO) achieved a best voltage stability index of 0.0024115 and power losses of 7.5092 MVA. The Red Colobus Monkey Optimization (RMO) algorithm realized a voltage stability index of 0.0052053 and real power losses of 20.7564 MVA. Overall, the results conclude that ALO is the most effective approach for optimizing distributed renewable energy systems under different climatic conditions. According to the analysis, the algorithm works best in ideal circumstances when the percentages of wind and irradiance are 60% or greater.

Optimal voltage and frequency control strategy for renewable-dominated deregulated power network

Maintaining stable voltage and frequency regulation is critical for modern power systems, particularly with the integration of renewable energy sources. This study proposes a coordinated control strategy for voltage and frequency in a deregulated power system comprising six Generation Companies (GENCOs) and six Distribution Companies (DISCOs). The system integrates thermal, diesel, wind, solar photovoltaic (PV), and hydroelectric sources. Two stochastic modeling techniques are used to characterize wind and solar generation, accounting for their variability within the control loops. A novel Leader Harris Hawks Optimization-based Model Predictive Controller (MPC-LHHO) is implemented, achieving a reduction in frequency deviation undershoot by 67.45% and voltage settling time by 91.11% compared to conventional controllers under poolco and bilateral transactions. Auxiliary devices, including the Unified Power Flow Controller (UPFC) and grid-connected electric vehicles (EVs), further enhance performance, reducing frequency deviations by 52.18% under stochastic scenarios. Rigorous evaluation under contract violations, random load variations, and renewable intermittency demonstrates the strategy’s robustness and efficacy.

Voltage support strength analysis and stability control strategy for grid‐forming wind power transmission system

AbstractIncreasing the short‐circuit ratio (SCR) of the power transmission system is crucial to ensuring voltage stability when the system has a high‐penetration of wind energy resources. This paper first analyses the weak nodes in the power system and quantifies the SCR requirements of these nodes under voltage safety constraints. Based on this analysis, a third‐order dynamic model of a virtual synchronous generator is established, and a design method for virtual transient reactance is proposed to meet the system's SCR requirements. Finally, a power system simulation with high‐penetration of wind energy is constructed, validating that under the proposed voltage stability support control strategy, grid‐forming wind turbines can meet the system's SCR requirements by optimizing the design of transient reactance, thereby improving the voltage stability of the system.

Impacts of grid-connected wind power generation on the voltage stability

Impacts of grid-connected wind power generation on the voltage stability

Voltage stability and frequency stability analysis of Zhejiang power grid

Voltage stability and frequency stability analysis of Zhejiang power grid

Simultaneous Effect of Thermal Aging and Phase Separation on Insulation Properties of 500 kV DC XLPE Blends with Voltage Stabilizers

Simultaneous Effect of Thermal Aging and Phase Separation on Insulation Properties of 500 kV DC XLPE Blends with Voltage Stabilizers

Optimal active and reactive power dispatch in the presence of wind farms using voltage indicators and metaheuristic methods

Wind power plants penetration into power grids has grown considerably due to the fact of being cheap and clean. As a result, many countries require that the wind turbines must be capable of offering ancillary services such as reactive power control and voltage regulation. Furthermore, some voltage stability indices rely on both reactive and active power; consequently, it is useful to take also into account the active power during the planning stage so as to fulfil the load requirement and to enhance the voltage stability. The present study intends to present an optimization algorithm permitting to diminish the electrical losses and enhance the voltage profile by getting the fittest allocation of active power production of traditional generators and wind power plants. Besides, wind farms reactive power injection is determined. To verify the proposed algorithm, a 40 MW wind farm (WF) made up of doubly fed induction generator (DFIG) and the 14 IEEE bus system are used. In the case study, three different metaheuristic methods are used to resolve the objective function. Finally, the simulation results are reported.

Picometre-level surface control of a closed-loop, adaptive X-ray mirror with integrated real-time interferometric feedback.

We provide a technical description and experimental results of the practical development and offline testing of an innovative, closed-loop, adaptive mirror system capable of making rapid, precise and ultra-stable changes in the size and shape of reflected X-ray beams generated at synchrotron light and free-electron laser facilities. The optical surface of a piezoelectric bimorph deformable mirror is continuously monitored at 20 kHz by an array of interferometric sensors. This matrix of height data is autonomously converted into voltage commands that are sent at 1 Hz to the piezo actuators to modify the shape of the mirror optical surface. Hence, users can rapidly switch in closed-loop between pre-calibrated X-ray wavefronts by selecting the corresponding freeform optical profile. This closed-loop monitoring is shown to repeatably bend and stabilize the low- and mid-spatial frequency components of the mirror surface to any given profile with an error <200 pm peak-to-valley, regardless of the recent history of bending and hysteresis. Without closed-loop stabilization after bending, the mirror height profile is shown to drift by hundreds of nanometres, which will slowly distort the X-ray wavefront. The metrology frame that holds the interferometric sensors is designed to be largely insensitive to temperature changes, providing an ultra-stable reference datum to enhance repeatability. We demonstrate an unprecedented level of fast and precise optical control in the X-ray domain: the profile of a macroscopic X-ray mirror of over 0.5 m in length was freely adjusted and stabilized to atomic level height resolution. Aside from demonstrating the extreme sensitivity of the interferometer sensors, this study also highlights the voltage repeatability and stability of the programmable high-voltage power supply, the accuracy of the correction-calculation algorithms and the almost instantaneous response of the bimorph mirror to command voltage pulses. Finally, we demonstrate the robustness of the system by showing that the bimorph mirror's optical surface was not damaged by more than 1 million voltage cycles, including no occurrence of the `junction effect' or weakening of piezoelectric actuator strength. Hence, this hardware combination provides a real time, hyper-precise, temperature-insensitive, closed-loop system which could benefit many optical communities, including EUV lithography, who require sub-nanometre bending control of the mirror form.

Analysis of key influencing factors of transient voltage stability based on generalized polynomial Chaos

Analysis of key influencing factors of transient voltage stability based on generalized polynomial Chaos

Improving Online Voltage Stability Monitoring in Smart Grids: A Physics-Informed Guided Deep Learning Model

Improving Online Voltage Stability Monitoring in Smart Grids: A Physics-Informed Guided Deep Learning Model