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.

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.

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

Reviewing 40 years of artificial intelligence applied to power systems-A taxonomic perspective

Artificial intelligence(AI)as a multi-purpose technology is gaining increased attention and is now widely used across all sectors of the economy.The growing complexity of planning and operating power systems makes AI extremely valuable for the power industry.Until now,there has been a lack of clarity regarding the specific points along the power system supply chain where AI applications demonstrate significant value,as well as which AI domains are best suited for such applications.This study employs an AI taxonomy and automated web search to qualitatively and quantitatively unveil the biggest potentials of AI in the power industry.Our analysis,based on a review of 258’919 publications between 1982 and 2022,reveals where AI applications are particularly promising.We consider six AI domains(reasoning,planning,learning,communication,perception,integration&interaction)and 19 use cases from the power supply chain(i.e.,generation,transmission networks,distribution networks,isolated grids/microgrids,market operations and retail).Our findings indicate that,as of now,the focus is predominantly on AI applications in power retail(55%),transmission(14%)and generation(13%).Most analyzed works describe applications built on algorithms of the AI domains“learning”(45%)and“planning”(14%).Results also suggest that the current definition of AI domains is ambiguous,and they highlight missing information on the actual use and successful implementation of AI in power system use cases.

Coordinated Frequency Control for Isolated Power Systems with High Penetration of DFIG-Based Wind Power

This paper proposes a coordinated frequency control scheme for emergency frequency regulation of isolated power systems with a high penetration of wind power.The proposed frequency control strategy is based on the novel nonlinear regulator theory,which takes advantage of nonlinearity of doubly fed induction generators(DFIGs)and generators to regulate the frequency of the power system.Frequency deviations and power imbalances are used to design nonlinear feedback controllers that achieve the reserve power distribution between generators and DFIGs,in various wind speed scenarios.The effectiveness and dynamic performance of the proposed nonlinear coordinated frequency control method are validated through simulations in an actual isolated power grid.

Generic Modeling and Control Framework for Power Systems Dominated by Power Converters Connected Through a Passive Transmission and Distribution Grid

In this paper,a compact mathematical model having an elegant structure,together with a generic control framework,are proposed for generic power systems dominated by power converters that are interconnected through a passive transmission and distribution(T&D)grid,by adopting the port-Hamiltonian(pH)systems theory and the fundamental circuit theory.The models of generic T&D lines are developed and then the model of a generic T&D grid is established.With the proposed control framework,the controlled converters are proven to be passive and Input-to-State Stable(ISS).The compact mathematical model is scalable and can be applied to power systems with multiple power electronic converters with generic passive controllers,passive local loads,and different types of passive T&D lines connected in a meshed configuration without self-loops,so it is very generic.Moreover,the resulting power system is proven to be ISS as well.The analysis is carried out without assumptions on constant frequency/voltage,constant loads,and/or lossless networks,except the need of passivity for all parts involved,and without using the Clarke/Park transformations or the graph theory.To simplify the presentation,three-phase balanced systems are adopted but the results can be easily adapted for single-phase or unbalanced three-phase systems.

A Review on Cybersecurity Analysis,Attack Detection,and Attack Defense Methods in Cyber-physical Power Systems

Potential malicious cyber-attacks to power systems which are connected to a wide range of stakeholders from the top to tail will impose significant societal risks and challenges.The timely detection and defense are of crucial importance for safe and reliable operation of cyber-physical power systems(CPPSs).This paper presents a comprehensive review of some of the latest attack detection and defense strategies.Firstly,the vulnerabilities brought by some new information and communication technologies(ICTs)are analyzed,and their impacts on the security of CPPSs are discussed.Various malicious cyber-attacks on cyber and physical layers are then analyzed within CPPSs framework,and their features and negative impacts are discussed.Secondly,two current mainstream attack detection methods including state estimation based and machine learning based methods are analyzed,and their benefits and drawbacks are discussed.Moreover,two current mainstream attack defense methods including active defense and passive defense methods are comprehensively discussed.Finally,the trends and challenges in attack detection and defense strategies in CPPSs are provided.

Technical cross-fertilization between terrestrial microgrids and ship power systems

Aspects of terrestrial microgrids and ship power systems are examined.The work exposes a variety of technical synergies from these two power systems to effectively advance their technologies.Understanding their overlap allows congruent efforts to target both systems;understanding their differences hinders conflict and redundancy in early-stage design.The paper concludes by highlighting how an understanding of both systems can reduce the investment in research resources.

Physics Insight of the Inertia of Power Systems and Methods to Provide Inertial Response

The growth of renewable energy reduces the moment of inertia for the synchronous AC grid,so the authors put forward two basic questions:1)What is the physics insight that a synchronous AC grid needs for mechanical inertia?2)How to provide inertial response for the power grid dominated with renewable energy?Based on Einstein’s special relativity and the Lorentz transformation,these papers illustrates that the nature of the inertia of the AC grid comes from the relativity of the electromagnetic field and motion,and from the strong coupling between them.According to their nature,the inertial response of the synchronous generator is self-proven.By contrast,the converter for the grid-connection of renewable energies used various algorithms in order to provide virtual inertia.But because algorithms do not rebuild the coupling between electromagnetic fields and motion,it is doubtful whether they can provide inertia and inertial responses.Therefore,the authors propose that there is a need to build extra electromagnetic fields and motion coupling for grids with high penetration rates of renewable energy.Therefore,a new grid-connection technology via Motor-Generator Pair(MGP)is discussed.The electromagnetic-motion coupling of the MGP is analyzed,and the results of simulation and experimental studies are also reported.

On expansion of estimated stability region:Theory,methodology,and application to power systems

The expansion of the estimated stability region plays an important role in the stability analysis of nonlinear systems.However,current literatures have not provided a complete mathematical description for this problem.This paper reveals that essentially the enlargement or the compression of the estimated stability region results directly from the diffeomorphism map,which is induced by the flow contained in the stability region.By proving that any integration algorithm with an order higher than one can approximately trace the flow of the system,a generalized methodology is proposed to construct various algorithms to realize the enlargement or the compression of the estimated stability region.With this methodology,two new algorithms based on symbolic calculation are suggested to reduce the computational burden.Furthermore,this methodology is applied to construct a scalable numerical algorithm to calculate the critical clearing time(CCT) of the power system for given faults.Tests on the IEEE 10-machine 39-bus system show that the computational results coincide well with the step-by-step simulation with high accuracy.