Complex Power Research Articles

A Novel Adaptive Model Predictive Control Strategy for DFIG Wind Turbine With Parameter Variations in Complex Power Systems

In this paper, a novel adaptive model predictive control (MPC) strategy is proposed for doubly fed induction generator (DFIG) wind turbine (WT), which is integrated into a complex power system, in order to improve the power output tracking precision and dynamic performance. Considering the existence of parameter variations in DFIG, an adaptive parameter estimation method is firstly designed. By analysis of stability, the convergence of the parameter estimation algorithm is rigorously proved. Furthermore, the parameter estimation algorithm is effectively integrated into MPC to realize real-time optimal control of DFIG with the adaptive model. To achieve the rotor side converter (RSC) design based on adaptive MPC, the DFIG model is linearized. In addition, a virtual output compensation (VOC) strategy is adopted to alleviate the impact of model linearization errors on the MPC, especially the variation of the model parameter. The newly proposed adaptive MPC-based RSC is capable of greatly improving the tracking performance, meanwhile taking into account the realistic constraints under various operation conditions. The simulation results demonstrate the effectiveness and superiority of the proposed control method.

Improving and warning the static stability limit of complex power grid tie-line based on WAMS

In order to solve the technical problems of traditional power system classic formulas that are difficult to explain the static stability limit changes of power grid interconnection lines, as well as the difficulties in improving and warning the static stability limit power of interconnection lines, this paper provides a method for improving and warning the static stability limit of power grid interconnection lines. Firstly, based on the electrical quantities measured by the wide-area measurement system (WAMS) of the power grid, the equivalent reactance of the power grid interconnection lines, and the equivalent impedance from the high voltage side and medium voltage side of the three coil transformers on both sides of the interconnection line are determined. Secondly, under pre-set operation mode and constraint conditions, the configuration quantity and capacity of the dynamic reactive power sources on the medium voltage side of the three coil transformers on both sides of the interconnection line are determined. Finally, based on the determined configuration and pre-set operation mode of the dynamic reactive power sources on the medium voltage side of the three coil transformers on both sides of the interconnection line, the historical electrical quantities measured by WAMS. The static stability limit and static stability margin of the interconnection line are calculated, and warnings are provided.

High-performance omnidirectional-sliding hybrid nanogenerator for self-powered wireless nodes

Energy-autonomous smart electronics have been the focus of the next generation of the Internet of Things. Recently, advanced power technology with sustainable energy supply and pollution-free characteristics has become a research hotspot. Herein, to realize a reliable and unattended power unit, we propose a high-performance omnidirectional-sliding triboelectric-electromagnetic hybrid nanogenerator (OS-TEHNG) to convert the mechanical energy into electricity. The free-standing triboelectric nanogenerator (TENG) achieves a charge transfer of 24.4 μC in one cycle and a short-circuit current of 0.36 mA after optimizing the electrode structure. The TENG with 130 kΩ impedance allows efficient charging of energy storage units without complex power management modules (PMMs). The electromagnetic part achieves an open-circuit voltage of 300 V after optimization. OS-TEHNG achieves a peak power density of 1568.4 W/m3 and an average power density of 352.3 W/m3 at 2 Hz. As a result, OS-TEHNG charges a 1 mF capacitor to 46 V within 8 s. The strong power supply capability allows OS-TEHNG to charge smartwatches and phones. Furthermore, a completely self-powered wireless keyboard with a PMM and an energy storage unit based on OS-TEHNG is developed. The wireless self-powered keyboard sends data 213 times after only sliding the OS-TEHNG once. Finally, OS-TEHNG is successfully demonstrated to drive a 40 mW wireless sensor node with a 1.3-inch OLED screen in continuous operation. This work represents a significant advance toward self-powered microsystems and practical power sources.

A Fuzzy Control Strategy to Synchronize Fractional-Order Nonlinear Systems Including Input Saturation

One of the most important engineering problems, with numerous uses in the applied sciences, is the synchronization of chaos dynamical systems. This paper introduces a dynamic-free T-S fuzzy sliding mode control (TSFSMC) method for synchronizing the different chaotic fractional-order (FO) systems, when there is input saturation. Using a new definition of fractional calculus and the fractional version of the Lyapunov stability theorem and linear matrix inequality concept, a Takagi–Sugeno fuzzy sliding mode controller is driven to suppress and synchronize the undesired behavior of the FO chaotic systems without any unpleasant chattering phenomenon. Finally, an example of synchronization of complex power grid systems is provided to illustrate the theoretical result of the paper in real-world applications.

“Something has to change”

“Something has to change”

Identifying critical nodes in power grids containing renewable energy based on electrical spreading probability

The identification of critical nodes is important for safe operation and accident prevention in power grids. With the accelerated development of renewable energies, the uncertainty of renewable energy has brought greater challenges to the node importance assessment of the power system. The electrical spreading probability method is proposed in this paper to identify the critical nodes in the power grid containing renewable energy. First, the uncertainty factors of renewable energy are established through probability density functions, and Monte Carlo simulation and stochastic DC optimum power flow are adopted to effectively deal with the impact of uncertain power output from solar and wind energies. Then, considering the system topology and load loss after cascading failures calculated by Monte Carlo simulation, a method is proposed to calculate the probability of nodes being infected. Finally, according to the Susceptible–Infected model, a method depending on the propagation ability of nodes is proposed to identify the critical nodes in the complex power system. The effectiveness of the proposed ESP method is verified through simulation examples of the modified IEEE39 power system and the modified IEEE118 power system.

Stability Analysis: Two-Area Power System with Wind Power Integration

This paper focuses on a comprehensive stability study of a two-area power system with wind power integration and synthetic inertia control in each area, considering the effects of varying the interconnection link. Normally, synthetic inertia proposals are analyzed in one-area systems, in which stability is tested without considering transmission system phenomena, such as coherency. As modern power systems are progressively becoming interconnected, the possibility of forming two or more non-coherent areas is likely, which poses a challenge to synthetic inertia control techniques that use system frequency as a main feedback signal. In this context, this work addresses a crucial gap in the existing literature and provides a valuable starting point for studying more complex interconnected power systems with wind power integration. Simulations were performed in Matlab-Simulink considering a data-driven frequency dynamics model of the Chilean Electric System, and a wind power model with synthetic inertia control H2 norm minimization in each area. The results showed that it is possible to find local optimal feedback gains, preserving the stability of the global system under significant variations in the interconnection link. RoCoF and Nadir indicators are provided, highlighting the benefits of synthetic inertia control, particularly in low-inertia situations.

Customized poly (aniline-co-o-aminobenzoic acid) by functionalizing with n/p dopants and its application in symmetrical redox supercapacitor

The chemically synthesized poly (aniline-co-o-aminobenzoic acid) copolymer was functionalized electrochemically by cationic and anionic doping and tailored its property for suitable redox behavior. The mechanism during this process has been proposed using cyclic voltammetry studies, and the doping was confirmed in FTIR and UV studies. In the electrochemical impedance spectroscopy, undoped and doped behavior revealed the possibility of fine-tuning of conditions that are required for redox supercapacitor. A symmetrical supercapacitor was fabricated with an optimized doped co-polymer-based electrode and the specific capacitance values were 107 Fg−1 for n-doped polymer and 140 Fg−1 for p-doped polymer. The electrochemical characterization of n/p 1 cm2 cells in terms of specific power, specific energy, specific capacitance, columbic efficiency, IR drop, and ESR was calculated from charge/discharge studies. Data were analyzed in terms of complex power versus complex capacitance, and hence, active region of n/p supercapacitor was obtained. This concept paves way for future tailoring of dopants during the synthesis of conducting polymer and its copolymers.Graphical abstract

Deep Neural Network Regression‐Assisted Pressure Sensor for Decoupling Thermal Variations at Different Operating Temperatures

Decoupling environment‐dependent response in sensing techniques is essential for the diverse practical applications. This work presents a novel thermal effect decoupling method for sponge pressure sensors based on a deep neural network (DNN) regression model, which is difficult to achieve owing to the material‐ and structure‐related complex effects of the sponge‐based pressure sensor. A poly(3,4‐ethylenedioxythiophene):poly(styrenesulfonate)‐based multifunctional device is fabricated with a both pressure and thermally responsive part and an only thermally responsive part; and a DNN model with two input features is adapted to implement the substantial pressure prediction system without thermal interference. Proposed model shows the robust decoupled pressure‐sensing capability with high accuracy of ≈96.23% using two input features. It also enables accurate pressure prediction under both the thermally steady and transition regions, which indicates significant potential for a precise measurement system. These results demonstrate the possibility of reliable pressure monitoring under varying thermal conditions, which is important for accurately measuring pressure in complex power plants, human–machine interfaces, and compact wearable platforms.

Scale analysis using FSA methodology for single-phase natural circulation in a simplified RCCS

Improving the safety and reliability of innovative Generation IV nuclear reactors can be achieved by adopting passive safety systems for accident prevention. These systems rely only on physical phenomena such as natural circulation and eliminate the need for an external response in the event of an accident. While passive natural circulation systems are widely used in modern nuclear reactors, their complexity and high thermal power output make them difficult to simulate at full scale. One solution is to study reduced-scale systems that are more feasible for experimental investigation. The correct scale procedure is essential to ensure that the results of these systems represent those expected in a real facility. This article describes a small-scale, single-phase water natural circulation circuit representing a simplified reactor cavity cooling system. The standard scale method is combined with an innovative fractional scaling analysis to determine the conditions and similarity parameters for a test facility. This analysis outlines the necessary simplifications required to achieve a certain similarity between natural circulation systems in the transient regime. The methodology is applied to two studies from the literature, demonstrating the feasibility of comparing different passive heat removal systems.

Power-Compensated Triple-Vector Model Predictive Direct Power Control Strategy for Nonredundant Fault-Tolerant Rectifiers

A power compensated triple-vector model predictive direct power control (PCTV-MPDPC) strategy is proposed in this paper for non-redundant fault-tolerant three-phase rectifiers. The system fault tolerance ability and post-fault control performance are enhanced with low hardware complexity. By defining the negative conjugate of complex power as the control variable, a straight-forward pattern of power-voltage relationship analysis is obtained. Besides, a novel voltage vector selection method is put forward based on the location of the error vector between the reference and real control variables. The sector identification process can be omitted to derive a unified expression for duty ratio calculation. On top of that, an intuitive power compensation architecture is proposed to eliminate the dc-bus voltage deviation so that its utilization rate can be maximized. With the proposed PCTV-MPDPC strategy, the power ripples and input current harmonics can be significantly reduced. Superior steady-state and dynamic performance can be achieved compared with the conventional finite-control-set MPDPC (FCS-MPDPC) scheme and a recently proposed multiple-vector model predictive power control (MV-MPPC) method, along with excellent dc-bus voltage deviation suppression effect. Furthermore, simulation validation in Matlab/Simulink and experimental verification on a four-switch three-phase rectifier are carried out to demonstrate the effectiveness of the proposed PCTV-MPDPC strategy.

Approaches for smart linear regression in a difficult quasi economic dispatch problem

<span lang="EN-US">Traditional methods indispensably necessitate monotonically increasing characteristic for fuel cost of generators in a thermal power plant. However, in medium and large thermal power plants, this condition is a dream to accomplish. So, to meet out these exigencies heuristic methods like swarm optimization technique, genetic algorithm technique and bee colony based hybrid solar thermal technology (BHSTT) are used to realize the practical nonlinearities associated with valve point loading emanated out of multi-valving effect, associated with power station. However, the heuristic methods too face challenges arising out of bulky thermal power plants adopting cubic cost functions and possessing stringent non-convex economic dispatch problem following multi-valving and erratic behavior of nonlinear loads at the load center. So, at its favor function evaluation method dealing with cubic cost function is attempted in this dissertation to yield a satisfactory optimal solution for economic dispatch problem. This method deals with the real power generation of producing units as well as the complex power of units, as well as dealing with severe nonlinear stringent fuel cost characteristics that are prevalent in today’s bulky thermal power plants. In comparison to previous approaches, the findings achieved are highly encouraging.</span>

Banning indirect boycotts: Contentious interactions and the role of the state in marketplace activism

AbstractIn 2019, the prime ministers of the United Kingdom and Australia both declared their intent to ban indirect, or secondary, boycotts. In the United Kingdom, the ban was directed against public bodies engaging in the “boycott, divest, and sanction” (BDS) campaign against Israel. In Australia, the proposed ban was directed against environmental action groups. Research on market-based activism to date has focused primarily on conceptualizing the use of the market by nonstate actors to achieve social change, with less attention paid to the role of the state in these dynamics. State efforts to curtail social movements’ repertoires of contention require careful scrutiny to understand the state's role in legitimizing or delegitimizing political activism and to reveal the complex power dynamics between corporations, social movements, and the state. This article analyzes two key instances of the state declaring an intent to prevent activists from protesting through the market. By investigating how indirect boycotts were problematized by state actors, we aim to reveal the rationale behind the state's intervention in marketplace politics. Our findings indicate that opposition to the political cause behind the boycott, rather than a problematization of the strategy itself, drives state intervention.

Academic language and learning in higher education: a call to Derridean hospitality

ABSTRACT Academic Language and Learning (ALL) is a relatively recent practice field in Australian Higher Education (HE). Throughout its history, the institutional positioning of ALL has varied significantly in line with an incessantly changing HE environment. Most recently, neoliberal policies and discourses are reconfiguring the professional identities of ALL practitioners and complicating their relationship with students, increasingly depriving both of a hospitable home in universities. Implicit in these discourses is also the depoliticisation of the ALL teacher–student relation and assumptions of mastery of these educators over their object of knowledge, the students. Rather than aligning ALL practitioners with neoliberal subject positionings, this conceptual paper explores the framing of ALL practitioners, particularly their relations with students, in terms of Derridean hospitality. The article details Derrida’s deconstruction of the concept of hospitality in order to (1) examine the complex power dynamics that structure the relationship between ALL practitioners and the student guest/foreigner and (2) insist on an ethical responsiveness to student difference based on responsibility for the other and a radical opening to the new. Derrida’s ideas of hospitality, the paper argues, offers an alternative language for thinking, speaking, and enacting ALL practitioner–student relations and opens new ethico-political horizons.

Perspectives on and the road towards 100 Gb/s TDM PON with intensity-modulation and direct-detection

We assess the status of current generation 25G and 50G time division multiplexed passive optical network (TDM PON) technologies based on leveraging the cost efficiencies of the Ethernet intra-datacenter ecosystem. As a first step towards 100G TDM PON, we predict the real-world impact of a flexible modulation enhancement to 50G PON, whereby four-level pulse amplitude modulation (PAM4) symbols can be transmitted at the same symbol rate as 50 Gb/s PAM2, but only where excess margins permit. We find that sufficient margins are likely to exist to allow for a majority of future 50G PON optical network units to operate at 100 Gb/s PAM4. Next, we look at the options for a 100G PON capable of supporting the full loss budget and reach requirements. There is no technical risk if coherent technology is adopted, but intensity-modulation and direct-detection (IM-DD) will provide lower complexity, lower cost, and lower power dissipation. We evaluate this option and conclude that by following IM-DD Ethernet optics to 100 GBd, single wavelength IM-DD will continue to be feasible for 100G PON and will be a strong contender for the next generation of PON after 50 Gb/s.

Cost Optimization and Reliability Parameter Extraction of a Complex Engineering System

Nowadays, the transformation of the various energy system is the core objective of the dedicated sustainable development goal related to energy sustainable world within the new United Nations development agenda. Different nuclear regulatory authorities around the globe, sets Technical Specifications (TSs) for ensuring the human and environmental safety of various highly volatile and complex Nuclear Power Generation Plants (NPGPs). TSs define numerous measures and limitations related to safety and sustainability that must be followed by all NPGPs around the world. Reliability, availability and cost components associated with a NPGPs form important bases for the setting of TSs. In this work, a framework based on few recent metaheuristics like Cuckoo Search Algorithm (CSA), Grey Wolf Optimizer (GWO), Hybrid PSO GWO algorithm (HPSOGWO) has been presented for cost optimization and reliability parameter extraction of a complex engineering system named Heat Removal System (HRS) of a nuclear power generation plant safety system (NPGPSS). A multi-criteria decision-making (MCDM) method named Weighted-Sum Method (WSM) has also been employed for prioritizing the available metaheuristics based on available beneficial and non-beneficial criteria’s.

Hierarchical Automatic Multilayer Power Plane Generation With Genetic Optimization and Multilayer Perceptron

Abstract We present an automatic multilayer power plane generation method to accelerate the design of printed circuit boards (PCB). In PCB design, while automatic solvers have been developed to predict important indicators such as the IR-drop, power integrity, and signal integrity, the generation of the power plane itself still largely relies on laborious manual methods. Our automatic power plane generation approach is based on genetic optimization combined with a multilayer perceptron (MLP) and is able to automatically generate power planes across a diverse set of problems with varying levels of difficulty. Our method GOMLP consists of an outer loop genetic optimizer (GO) and an inner loop MLP that generate power planes automatically. The critical elements of our approach include contour detection, feature expansion, and a distance measure to enable island-minimizing complex power plane generation. We compare our approach to a baseline solution based on A*. The A* method consisting of a sequential island generation and merging process which can produce less than ideal solutions. Our experimental results show that on single layer power plane problems, our method outperforms A* in 71% of the problems with varying levels of board layout difficulty. We further describe H-GOMLP, which extends GOMLP to multilayer power plane problems using hierarchical clustering and net similarities based on the Hausdorff distance.

Adaptive multistep model predictive control for tubular grid-connected solid oxide fuel cells

In the research of renewable energy power generation, tubular grid-connected solid oxide fuel cells with the apparent advantage in voltage regulation have been widely applied in power systems. Recently, a model predictive control has been applied to consider the nonlinear constraints of tubular grid-connected solid oxide fuel cells, which cannot be considered by a proportional-integral-derivative controller. Both model predictive control and proportional-integral-derivative controller achieve only 80% fuel efficiency. An adaptive multistep model predictive control (AMMPC) is proposed to improve the fuel efficiency of tubular grid-connected solid oxide fuel cells and simultaneously consider systemic thermodynamics and electrochemistry constraints. The AMMPC contains the advantages of adaptive control and multistep model predictive control. Both adaptive two-step model predictive control and three-step model predictive control are designed for tubular grid-connected solid oxide fuel cells. With the more accurate prediction ability, the AMMPC improves the fuel efficiency of tubular grid-connected solid oxide fuel cells with higher fuel efficiency (86.5%) than model predictive control (80%) and proportional-integral-derivative (80%). Both feasibility and effectiveness of the AMMPC are verified with high fuel efficiency under simple and complex power demands cases.

Analysis and general calculation of DC fault currents in MMC-MTDC grids

The short-circuit fault of MMC-MTDC has great influence on the safe and stable operation of the MMC-HVDC transmission system. To analyze the changing trend of short-circuit current after fault, this paper studies the short-circuit fault mechanism based on the analytical formula of MMC short-circuit current, and analyzes the influence of capacitance, inductance and resistance on short-circuit current. Subsequently, the discharge characteristics of each converter station in multi-terminal complex power grid under different fault conditions are investigated. Based on the above research, a general calculation method for short-circuit current of multi-terminal complex direct power grid is proposed. Then, a four-terminal power grid and a six-terminal power grid are built based on the PSCAD/ EMTDC electromagnetic transient simulation platform to verify the fault characteristics of MMC and discharge characteristics of multi-terminal network converter stations respectively. Finally, a digital-physical hybrid simulation experiment platform is erected to verify the effectiveness of the analytical calculation method for short-circuit current. The results demonstrate that the theoretical solution method can accurately characterize the fault current variation trend, which has an extremely important guiding significance for the engineering design and control protection of MMCHVDC transmission network.

Structure of Psychopathology in Romanian Preschool-Aged Children in an Epidemiological and a High-Risk Sample

Research on bifactor models of psychopathology in early childhood is limited to community samples with little longitudinal follow-up. We examined general and specific forms of psychopathology within 2 independent samples of preschool-aged Romanian children. Within a sample with children exposed to psychosocial deprivation, we also examined antecedents and longitudinal outcomes of the general factor. One sample consisted of 350 Romanian children (mean age = 39.7 months, SD = 10.9) from an epidemiological study; the second sample consisted of 170 Romanian children (mean age = 55.6 months, SD = 1.9) exposed to severe early-life deprivation, as well as community comparison children, with longitudinal follow-up at 8 and 12 years. Psychopathology symptoms were assessed through caregiver-reported structured clinical interviews. An SI-1 bifactor model of psychopathology was supported in both samples and included specific factors for externalizing, internalizing, and disturbed relatedness symptoms. In the second sample, longer duration of psychosocial deprivation and lower-quality caregiving were associated with higher scores on the general and all specific factors. Higher scores on the general factor were associated with later cognitive function, competence, and psychopathology symptoms. Considering all factors together, only the general factor explained variance in later childhood outcomes and was slightly stronger compared to a total symptom count for some, but not all, outcomes. General psychopathology in early childhood explains meaningful variance in child outcomes across multiple domains of functioning in later childhood. However, important questions remain regarding its clinical utility and usefulness, given complex measurement and limited explanatory power beyond the more accessible approach of a total symptom count. The Bucharest Early Intervention Project; https://clinicaltrials.gov/; NCT00747396.