Capacity planning of hydro-wind-solar hybrid power systems considering hydropower forbidden zones

In the capacity planning of hydro-wind-solar power systems(CPHPS),it is crucial to use flexible hydropower to complement the variable wind-solar power.Hydropower units must be operated such that they avoid specific restricted operation zones,that is,forbidden zones(FZs),to avoid the risks associated with hydropower unit vibration.FZs cause limitations in terms of both the hydropower generation and flexible regulation in the hydro-wind-solar power systems.Therefore,it is essential to consider FZs when determining the optimal wind-solar power capacity that can be compensated by the hydropower.This study presents a mathematical model that incorporates the FZ constraints into the CPHPS problem.Firstly,the FZs of the hydropower units are converted into those of the hydropower plants based on set theory.Secondly,a mathematical model was formulated for the CPHPS,which couples the FZ constraints of hydropower plants with other operational constraints(e.g.,power balance constraints,new energy consumption limits,and hydropower generation functions).Thirdly,dynamic programming with successive approximations is employed to solve the proposed model.Lastly,case studies were conducted on the hydro-wind-solar system of the Qingshui River to demonstrate the effectiveness of the proposed model.

Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

Research on Disaster Prevention and Mitigation Technologies in Power Systems

Power systems are critical to modern society,providing the backbone for all economic,industrial,and residential activities.However,these systems face significant threats from both natural and man-made disasters,such as earthquakes,floods,hurricanes,cyber-attacks,and equipment failures.The vulnerability of power systems to these disasters can result in prolonged outages,economic losses,safety risks,and social consequences.This paper explores various disaster prevention and mitigation technologies employed in power systems to enhance resilience and ensure reliable electricity supply during and after disasters.It discusses early warning systems for natural hazards,resilient infrastructure designs,and cybersecurity measures to defend against man-made threats.Additionally,it examines fault detection,power system restoration,and disaster-resilient control strategies that aid in quick recovery from disruptions.The integration of smart grids,renewable energy sources,and advanced control technologies is emphasized as crucial for improving disaster preparedness and minimizing recovery time.Through the application of these technologies,power systems can better withstand and recover from the growing risks posed by both natural and human-induced disasters.

Adaptive Protection Mechanisms in Power Systems

With the increasing complexity and dynamic nature of modern power grids,adaptive protection mechanisms have emerged as a promising solution to address the challenges faced by traditional protection systems.These systems dynamically adjust their settings based on real-time grid conditions,enabling faster fault detection,improved fault isolation,and enhanced system stability.The need for such adaptive protection systems has become more pronounced as power systems evolve with the integration of renewable energy sources,distributed generation,and microgrids.By leveraging advanced technologies such as machine learning,artificial intelligence,smart sensors,and wide-area measurement systems,adaptive protection mechanisms provide a more flexible and resilient approach to grid protection.This paper explores the definition,key features,enabling technologies,and applications of adaptive protection in power systems,with a focus on its role in distribution networks,transmission networks,and the integration of renewable energy sources.The integration of adaptive protection into modern power grids is essential for maintaining grid reliability,minimizing service interruptions,and optimizing the overall performance of power systems.

Fault Detection and Prevention Strategies in Power Systems

Power systems are critical to modern society,but their complexity has increased with the integration of renewable energy and advanced technologies.This paper explores fault detection and prevention strategies essential for ensuring system reliability.We examine traditional methods such as overcurrent and differential protection,as well as advanced techniques including machine learning(ML)and artificial intelligence(AI).Additionally,we discuss fault prevention strategies like predictive maintenance,redundancy,and self-healing grids.Despite advancements,challenges such as the complexity of modern grids,cybersecurity threats,and economic constraints remain.The paper concludes with future prospects,emphasizing emerging technologies and global research initiatives aimed at enhancing grid resilience and security.

Reliability and sensitivity analysis of loop-designed security and stability control system in interconnected power systems

Security and stability control system(SSCS)in power systems involves collecting information and sending the decision from/to control stations at different layers;the tree structure of the SSCS requires more levels.Failure of a station or channel can cause all the execution stations(EXs)to be out of control.The randomness of the controllable capacity of the EXs increases the difficulty of the reliability evaluation of the SSCS.In this study,the loop designed SSCS and reliability analysis are examined for the interconnected systems.The uncertainty analysis of the controllable capacity based on the evidence theory for the SSCS is proposed.The bidirectional and loop channels are introduced to reduce the layers and stations of the existing SSCS with tree configuration.The reliability evaluation and sensitivity analysis are proposed to quantify the controllability and vulnerable components for the SSCS in different configurations.By aiming at the randomness of the controllable capacity of the EXs,the uncertainty analysis of the controllable capacity of the SSCS based on the evidence theory is proposed to quantify the probability of the SSCS for balancing the active power deficiency of the grid.

A reusable planar triggered spark-gap switch batched-fabricated with PCB technology for medium- and low-voltage pulse power systems

Triggered spark-gap switch is a popular discharge switch for pulse power systems.Previous studies have focused on planarizing this switch using thin film techniques in order to meet the requirements of compact size in the systems.Such switches are one-shot due to electrodes being too thin to sufficiently resist spark-erosion.Additionally,these switches did not employ any structures in securing internal gas composition,resulting in inconsistent performance under harsh atmospheres.In this work,a novel planar triggered spark-gap switch(PTS)with a hermetically sealed cavity was batched-prepared with printed circuit board(PCB)technology,to achieve reusability with low cost.The proposed PTS was inspected by micro-computed tomography to ensure PCB techniques meet the requirements of machining precision.The results from electrical experiments demonstrated that PCB PTS were consistent and reusable with lifespan over 20 times.The calculated switch voltage and circuit current were consistent with those derived from real-world measurements.Finally,PCB PTS was used to introduce hexanitrostilbene(HNS)pellets in a pulse power system to verify its performance.

Decentralized Resilient H_∞Load Frequency Control for Cyber-Physical Power Systems Under DoS Attacks

This paper designs a decentralized resilient H_(∞)load frequency control(LFC)scheme for multi-area cyber-physical power systems(CPPSs).Under the network-based control framework,the sampled measurements are transmitted through the communication networks,which may be attacked by energylimited denial-of-service(DoS)attacks with a characterization of the maximum count of continuous data losses(resilience index).Each area is controlled in a decentralized mode,and the impacts on one area from other areas via their interconnections are regarded as the additional load disturbance of this area.Then,the closed-loop LFC system of each area under DoS attacks is modeled as an aperiodic sampled-data control system with external disturbances.Under this modeling,a decentralized resilient H_(∞)scheme is presented to design the state-feedback controllers with guaranteed H∞performance and resilience index based on a novel transmission interval-dependent loop functional method.When given the controllers,the proposed scheme can obtain a less conservative H_(∞)performance and resilience index that the LFC system can tolerate.The effectiveness of the proposed LFC scheme is evaluated on a one-area CPPS and two three-area CPPSs under DoS attacks.

Random-phase-induced chaos in power systems

This paper studies how random phase （namely, noise-perturbed phase） effects the dynamical behaviours of a simple model of power system which operates in a stable regime far away from chaotic behaviour in the absence of noise. It finds that when the phase perturbation is weak, chaos is absent in power systems. With the increase of disturbed intensity σ, power systems become unstable and fall into chaos as σ further increases. These phenomena imply that random phase can induce and enhance chaos in power systems. Furthermore, the possible mechanism behind the action of random phase is addressed.

Review of demand-side energy sharing and collective self-consumption schemes in future power systems

The widespread use of distributed energy sources provides exciting potential for demand-side energy sharing and collective self-consumption schemes.Demand-side energy sharing and collective self-consumption systems are committed to coordinating the operation of distributed generation,energy storage,and load demand.Recently,with the development of Internet technology,sharing economy is rapidly penetrating various fields.The application of sharing economy in the energy sector enables more and more end-users to participate in energy transactions.However,the deployment of energy sharing technologies poses many challenges.This paper comprehensively reviews recent developments in demand-side energy sharing and collective self-consumption schemes.The definition and classification of sharing economy are presented,with a focus on the applications in the energy sector:virtual power plants,peer-to-peer energy trading,shared energy storage,and microgrid energy sharing cloud.Challenges and future research directions are thoroughly discussed.

Optimal coordinated voltage control of power systems

An immune algorithm solution is proposed in this paper to deal with the problem of optimal coordination of local physically based controllers in order to preserve or retain mid and long term voltage stability. This problem is in fact a global coordination control problem which involves not only sequencing and timing different control devices but also tuning the parameters of controllers. A multi-stage coordinated control scheme is presented, aiming at retaining good voltage levels with minimal control efforts and costs after severe disturbances in power systems. A self-pattem-recognized vaccination procedure is developed to transfer effective heuristic information into the new generation of solution candidates to speed up the convergence of the search procedure to global optima. An example of four bus power system case study is investigated to show the effectiveness and efficiency of the proposed algorithm, compared with several existing approaches such as differential dynamic programming and tree-search.

Development of a methodology for assessing the adequacy of electric power systems

This study presents the results of a research into the developing a methodology for assessing the adequacy of advanced electric power systems characterized by the integration of various innovative technologies,which complicates their analysis.The methodology development is aimed at solving two main problems:(1)increase the adequacy of modeling the processes that occur in the electric power system and (2)enhance the computational efficiency of the adequacy assessment methodology.This study proposes a new mathematical model to minimize the power shortage and enhance the adequacy of modeling the processes.The model considers quadratic power transmission losses and network coefficients.The computational efficiency of the adequacy assessment methodology is enhanced using efficient random-number generators to form the calculated states of electric power systems and machine learning methods to assess power shortages and other reliability characteristics in the calculated states.

Adaptive Robust Control of Multi-Machine Power Systems with Control Time Delay

The adaptive H_∞ control problem of multi-machine power system in the case of disturbances and uncertain parameters is discussed,based on a Hamiltonian model.Considered the effect of time delay during control and transmission,a Hamilton model with control time delay is established.Lyapunov-Krasovskii function is selected,and a controller which makes the system asymptotically stable is got.The controller not only achieves the stability control for nonlinear systems with time delay,but also has the ability to suppress the external disturbances and adaptive ability to system parameter perturbation.The simulation results show the effect of the controller.

China Power Systems, Today and Tomorrow

Through rapid extension and incessant improvement of 500 kV (including 330 kV) and 220 kV transmission trunk networks, China power systems have entered a new era of large power networks, large power plants, large power units, extra-high voltage transmission and highly automatic control. It is symbolized by the installed

A review on simulation models of cascading failures in power systems

Among various power system disturbances,cascading failures are considered the most serious and extreme threats to grid operations,potentially leading to significant stability issues or even widespread power blackouts.Simulating power systems’behaviors during cascading failures is of great importance to comprehend how failures originate and propagate,as well as to develop effective preventive and mitigative control strategies.The intricate mechanism of cascading failures,characterized by multi-timescale dynamics,presents exceptional challenges for their simulations.This paper provides a comprehensive review of simulation models for cascading failures,providing a systematic categorization and a comparison of these models.The challenges and potential research directions for the future are also discussed.

Estimating Transient Stability Regions of Large-Scale Power Systems Part I:Koopman Operator and Reduced-Order Model

This paper presents an estimation of transient stability regions for large-scale power systems.In Part I,a Koopman operator based model reduction(KOMR)method is proposed to derive a low-order dynamical model with reasonable accuracy for transient stability analysis of large-scale power systems.Unlike traditional reduction methods based on linearized models,the proposed method does not require linearization,but captures dominant modes of the original nonlinear dynamics by employing a Koopman operator defined in an infinite-dimensional observable space.Combined with the Galerkin projection,the obtained dominant Koopman eigenvalues and modes produce a reduced-order nonlinear model.To approximate the Koopman operator with sufficient accuracy,we introduce a Polynomial-based Multi-trajectory Kernel Dynamic Mode Decomposition(PMK-DMD)algorithm,which outperforms traditional DMD in various scenarios.In the end,the proposed method is applied to the IEEE 10-machine-39-bus power system and IEEE 16-machine-68-bus power system,which demonstrates that our method is significantly superior to the modal analysis method in both qualitative and quantitative aspects.