Fully Distributed Risk-based Robust Reserve Scheduling for Bulk Hybrid AC-DC Systems

To enhance the cost-effectiveness of bulk hybrid AC-DC power systems and promote wind consumption,this paper proposes a two-stage risk-based robust reserve scheduling(RRRS)model.Different from traditional robust optimization,the proposed model applies an adjustable uncertainty set rather than a fixed one.Thereby,the operational risk is optimized together with the dispatch schedules,with a reasonable admissible region of wind power obtained correspondingly.In addition,both the operational base point and adjustment capacity of tielines are optimized in the RRRS model,which enables reserve sharing among the connected areas to handle the significant wind uncertainties.Based on the alternating direction method of multipliers(ADMM),a fully distributed framework is presented to solve the RRRS model in a distributed way.A dynamic penalty factor adjustment strategy(DPA)is also developed and applied to enhance its convergence properties.Since only limited information needs to be exchanged during the solution process,the communication burden is reduced and regional information is protected.Case studies on the 2-area 12-bus system and 3-area 354-bus system illustrate the effectiveness of the proposed model and approach.

Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy

The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.

Optimal Multi-Timescale Scheduling of Integrated Energy Systems with Hybrid Energy Storage System Based on Lyapunov Optimization

The economic operation of integrated energy system(IES)faces new challenges such as multi-timescale characteristics of heterogeneous energy sources,and cooperative operation of hybrid energy storage system(HESS).To this end,this paper investigates the multi-timescale rolling opti-mization problem for IES integrated with HESS.Firstly,the architecture of IES with HESS is established,a comparative analysis is conducted to evaluate the advantages of the HESS over a single energy storage system(SESS)in stabilizing power fluctuations.Secondly,the dayahead and real-time scheduling cost functions of IES are established,the day-ahead scheduling mainly depends on operation costs of the components in IES,the real-time optimal scheduling adopts the Lya-punov optimization method to schedule the battery and hydrogen energy storage in each time slot,so as to minimize the real-time average scheduling operation cost,and the problem of day-ahead and real-time scheduling error,which caused by the uncertainty of the energy storage is solved by online optimization.Finally,the proposed model is verified to reduce the scheduling operation cost and the dispatching error by performing an arithmetic example analysis of the IES in Shanghai,which provides a reference for the safe and stable operation of the IES.

A Double Sensitive Fault Detection Filter for Positive Markovian Jump Systems With A Hybrid Event-Triggered Mechanism

This paper is concerned with the double sensitive fault detection filter for positive Markovian jump systems. A new hybrid adaptive event-triggered mechanism is proposed by introducing a non-monotonic adaptive law. A linear adaptive event-triggered threshold is established by virtue of 1-norm inequality.Under such a triggering strategy, the original system can be transformed into an interval uncertain system. By using a stochastic copositive Lyapunov function, an asynchronous fault detection filter is designed for positive Markovian jump systems(PMJSs) in terms of linear programming. The presented filter satisfies both L_-gain(?_-gain) fault sensitivity and L_1(?_1)internal differential privacy sensitivity. The proposed approach is also extended to the discrete-time case. Finally, two examples are provided to illustrate the effectiveness of the proposed design.

Assessing the techno-economic feasibility of hybrid solar-hydrogen systems: A review of recent studies

Transition toward a sustainable,low-carbon energy future requires innovative,integrated solutions.Hybrid solar-hydrogen systems(HSHSs),which combine solar energy harvesting and hydrogen production,have excellent prosepects to address challenges related to renewable energy generation,storage,and usage.This article presents an overview of the research on the technical and economic feasibility of HSHSs,aimed at comprehensively articulating their current state,notable advancements,and future research directions.It begins by elucidating solar energy principles and conversion methods and emphasizing the potential of solar energy for hydrogen production.This study then explores the definitions,components,and synergistic integration of HSHSs.Optimized energy conversion and storage methods for efficient hydrogen production and storage are also highlighted.This study reviews the techniques employed for techno-economic evaluations over the last six years,addressing challenges such as the intermittency of solar energy and the efficiency of hydrogen production technologies.This review of the ongoing research provides helpful insights into the technological and economic feasibility of HSHSs.This underscores the necessity of continuous research and development efforts to overcome existing challenges and unlock their full potential.These systems can play a vital role in achieving a cleaner and more resilient energy future by optimizing the system performance,reducing costs,and fostering supportive policy frameworks.

Modeling and Control of Hybrid Machine Systems—a Five-bar Mechanism Case

A hybrid machine （HM） as a typical mechatronic device, is a useful tool to generate smooth motion, and combines the motions of a large constant speed motor with a small servo motor by means of a mechnical linkage mechanism, in order to provide a powerful programmable drive system. To achieve design objectives, a control system is required. To design a better control system and analyze the performance of an HM, a dynamic model is necessary. This paper first develops a dynamic model of an HM with a five-bar mechanism using a Lagrangian formulation. Then, several important properties which are very useful in system analysis, and control system design, are presented. Based on the developed dynamic model, two control approaches, computed torque, and combined computed torque and slide mode control, are adopted to control the HM system. Simulation results demonstrate the control performance and limitations of each control approach.

Semiconductor,molecular and hybrid systems for photoelectrochemical solar fuel production

The paper shortly reviews the basic direct approaches applied in searching for viable solutions to solar fuel production. These are generally distinguished in molecular and semiconductor(non-molecular)systems, however, hybrid strategies, proposed recently, have also been included. The most promising efforts are considered, highlighting key aspects and emerging critical issues. Special attention is paid to aspects such as electrode architecture, device design, and main differences in the scientific vision and challenges to directly produce solar fuels. This overview could be useful to orientate the readers in the wide panorama of research activities concerning water splitting, natural and artificial photosynthesis, and solar fuel production through the identification of common aspects, specialties and potentialities of the many initiatives and approaches that are developing worldwide in this field with the final aim to meet world energy demand.

Abiotic-Biological Hybrid Systems for CO2 Conversion to Value-Added Chemicals and Fuels

Abiotic-biological hybrid systems that combine the advantages of abiotic catalysis and biotransformation for the conversion of carbon dioxide(CO2)to value-added chemicals and fuels have emerged as an appealing way to address the global energy and environmental crisis caused by increased CO2 emission.We illustrate the recent progress in this field.Here,we first review the natural CO2 fixation pathways for an in-depth understanding of the biological CO2 transformation strategy and why a sustainable feed of reducing power is important.Second,we review the recent progress in the construction of abiotic-biological hybrid systems for CO2 transformation from two aspects:(i)microbial electrosynthesis systems that utilize electricity to support whole-cell biological CO2 conversion to products of interest and(ii)photosynthetic semiconductor biohybrid systems that integrate semiconductor nanomaterials with CO2-fixing microorganisms to harness solar energy for biological CO2 transformation.Lastly,we discuss potential approaches for further improvement of abiotic-biological hybrid systems.

A Numerical Convex Lens for the State-Discretized Modeling and Simulation of Megawatt Power Electronics Systems as Generalized Hybrid Systems

Modeling and simulation have emerged as an indispensable approach to create numerical experiment platforms and study engineering systems.However,the increasingly complicated systems that engineers face today dramatically challenge state-of-the-art modeling and simulation approaches.Such complicated systems,which are composed of not only continuous states but also discrete events,and which contain complex dynamics across multiple timescales,are defined as generalized hybrid systems(GHSs)in this paper.As a representative GHS,megawatt power electronics(MPE)systems have been largely integrated into the modern power grid,but MPE simulation remains a bottleneck due to its unacceptable time cost and poor convergence.To address this challenge,this paper proposes the numerical convex lens approach to achieve state-discretized modeling and simulation of GHSs.This approach transforms conventional time-discretized passive simulations designed for pure-continuous systems into state-discretized selective simulations designed for GHSs.When this approach was applied to a largescale MPE-based renewable energy system,a 1000-fold increase in simulation speed was achieved,in comparison with existing software.Furthermore,the proposed approach uniquely enables the switching transient simulation of a largescale megawatt system with high accuracy,compared with experimental results,and with no convergence concerns.The numerical convex lens approach leads to the highly efficient simulation of intricate GHSs across multiple timescales,and thus significantly extends engineers’capability to study systems with numerical experiments.

Simple hybrid dithiafulvenes-triphenylamine systems as dopant-free hole-transporting materials for efficient perovskite solar cells

Two extended hybrid conjugated systems based on a triphenylamine(TPA) core with two and three peripheral 1,4-dithiafulvenes(DTF) units coded WH-2 and WH-3 as hole-transporting materials(HTMs) applied in perovskite solar cells(PSCs) are synthesized by facile one-step reaction in good yield over 75%. DTF unit as electron donor can enhance the electron donating ability and the fusion of benzenic ring of TPA with DTF unit may lead to reinforced intermolecular interactions in the solid state. In addition,WH-2 and WH-3 exhibit a pyramid shape containing partial planarity and quasi three-dimensionality features, which is also conducive to enhancing the π-π stacking of molecules in the solid state. The above-mentioned structural characteristics make the two HTMs have good hole mobilities. As a result,WH-2 and WH-3 obtained the high intrinsic hole mobilities of 4.69 × 10^(-4)and 2.18 × 10^(-3)cm^(2)V^(-1)s^(-1)respectively. Finally, the power conversion efficiencies(PCEs) of PSCs with WH-2 and WH-3 as cost-effective dopant-free HTMs are 15.39% and 19.22% respectively and the PCE of PSC with WH-3 is on a par with that of PSC with Li-TFSI/t-BP doped Spiro-OMe TAD(19.67%).

Non-intrusive hybrid interval method for uncertain nonlinear systems using derivative information

This paper proposes a new non-intrusive hybrid interval method using derivative information for the dynamic response analysis of nonlinear systems with uncertain-but- bounded parameters and/or initial conditions. This method provides tighter solution ranges compared to the existing polynomial approximation interval methods. Interval arith- metic using the Chebyshev basis and interval arithmetic using the general form modified affine basis for polynomials are developed to obtain tighter bounds for interval computation. To further reduce the overestimation caused by the ＂wrap- ping effect＂ of interval arithmetic, the derivative information of dynamic responses is used to achieve exact solutions when the dynamic responses are monotonic with respect to all the uncertain variables. Finally, two typical numerical examples with nonlinearity are applied to demonstrate the effective- ness of the proposed hybrid interval method, in particular, its ability to effectively control the overestimation for specific timepoints.

Use of Dynamical Systems Modeling to Hybrid Cloud Database

In the article, an experiment is aimed at clarifying the transfer efficiency of the database in the cloud infrastructure. The system was added to the control unit, which has guided the database search in the local part or in the cloud. It is shown that the time data acquisition remains unchanged as a result of modification. Suggestions have been made about the use of the theory of dynamic systems to hybrid cloud database. The present work is aimed at attracting the attention of specialists in the field of cloud database to the apparatus control theory. The experiment presented in this article allows the use of the description of the known methods for solving important practical problems.

Hybrid Power Systems Energy Controller Based on Neural Network and Fuzzy Logic

This paper presents a novel adaptive scheme for energy management in stand-alone hybrid power systems. The proposed management system is designed to manage the power flow between the hybrid power system and energy storage elements in order to satisfy the load requirements based on artificial neural network (ANN) and fuzzy logic controllers. The neural network controller is employed to achieve the maximum power point (MPP) for different types of photovoltaic (PV) panels. The advance fuzzy logic controller is developed to distribute the power among the hybrid system and to manage the charge and discharge current flow for performance optimization. The developed management system performance was assessed using a hybrid system comprised PV panels, wind turbine (WT), battery storage, and proton exchange membrane fuel cell (PEMFC). To improve the generating performance of the PEMFC and prolong its life, stack temperature is controlled by a fuzzy logic controller. The dynamic behavior of the proposed model is examined under different operating conditions. Real-time measured parameters are used as inputs for the developed system. The proposed model and its control strategy offer a proper tool for optimizing hybrid power system performance, such as that used in smart-house applications.

Practical Stability Analysis of Linear Impulsive Hybrid Systems Involving Fractional Derivatives

Practical stabilities for linear fractional impulsive hybrid systems are investigated in detail.The transformation from a linear fractional differential system to a fractional impulsive hybrid system is interpreted.With the help of the Mittag-Leffler functions for matrix-type,several practical stability criteria for fractional impulsive hybrid systems are derived.Finally,a numerical example is provided to illustrate the effectiveness of the results.

An exact nonlinear hybrid-coordinate formulation for flexible multibody systems

The previous low-order approximate nonlinear formulations succeeded in capturing the stiffening terms, but failed in simulation of mechanical systems with large deformation due to the neglect of the high-order deformation terms. In this paper, a new hybrid-coordinate formulation is proposed, which is suitable for flexible multibody systems with large deformation. On the basis of exact strain- displacement relation, equations of motion for flexible multi-body system are derived by using virtual work principle. A matrix separation method is put forward to improve the efficiency of the calculation. Agreement of the present results with those obtained by absolute nodal coordinate formulation （ANCF） verifies the correctness of the proposed formulation. Furthermore, the present results are compared with those obtained by use of the linear model and the low-order approximate nonlinear model to show the suitability of the proposed models.

Model-Based Fault Tolerant Control for Hybrid Dynamic Systems with Sensor Faults

A model-based fault tolerant control approach for hybrid linear dynamic systems is proposed in this paper. The proposed method, taking advantage of reliable control, can maintain the performance of the faulty system during the time delay of fault detection and diagnosis (FDD) and fault accommodation (FA), which can be regarded as the first line of defence against sensor faults. Simulation results of a three-tank system with sensor fault are given to show the efficiency of the method.

ASYMPTOTIC SOLUTION OF SINGULARLY PERTURBED HYBRID DYNAMICAL SYSTEMS

In this paper, we consider a class of optimal control problem for the singularly perturbed hybrid dynamical systems. By means of variational method, we obtain the necessary conditions of the hybrid dynamical systems. Meanwhile, the existence of solution for the hybrid dynamical system is proved by the sewing method and the uniformly valid asymptotic expansion of the optimal trajectory is constructed by the boundary function method. Finally,an example is presented to illustrate the result.

Controlled unknown quantum operations on hybrid systems

Any unknown unitary operations conditioned on a control system can be deterministically performed if ancillary subspaces are available for the target systems [Zhou X Q, et al. 2011 Nat. Commun. 2 413]. In this paper, we show that previous optical schemes may be extended to general hybrid systems if unknown operations are provided by optical instruments. Moreover, a probabilistic scheme is proposed when the unknown operation may be performed on the subspaces of ancillary high-dimensional systems. Furthermore, the unknown operations conditioned on the multi-control system may be reduced to the case with a control system using additional linear circuit complexity. The new schemes may be more flexible for different systems or hybrid systems.

Max-plus-linear model-based predictive control for constrained hybrid systems: linear programming solution

In this paper, a linear programming method is proposed to solve model predictive control for a class of hybrid systems. Firstly, using the （max, ＋） algebra, a typical subclass of hybrid systems called max-plus-linear （MPL） systems is obtained. And then, model predictive control （MPC） framework is extended to MPL systems. In general, the nonlinear optimization approach or extended linear complementarity problem （ELCP） were applied to solve the MPL-MPC optimization problem. A new optimization method based on canonical forms for max-min-plus-scaling （MMPS） functions （using the operations maximization, minimization, addition and scalar multiplication） with linear constraints on the inputs is presented. The proposed approach consists in solving several linear programming problems and is more efficient than nonlinear optimization. The validity of the algorithm is illustrated by an example.

System security of hybrid AC-HVDC-systems challenges and new approaches for combined security assessment,preventive optimization and curative actions

The intense application of Voltage Source Converter based HVDC interconnections and grids will result in a hybrid AC-HVDC-system. The operation of such a system becomes complex regarding system security and system operation. This paper describes major challenges and proposes potential solutions, including a combined security assessment, preventive optimization and curative actions. A coordination of both systems enables an efficient application of existing transport capacity.