Systems In MATLAB Research Articles

Feasibility of integrated solar photovoltaic pico‐pumped storage self‐sustained system for multi‐storey building in India

AbstractThis study explores the potential of utilizing a pico‐pumped storage system (PPSH) as an energy storage solution to enhance the integration of renewable energy sources in a multi‐story building. The study seeks to evaluate the system's ability to fulfil the energy requirements of a part of a multi‐storey building, considering factors such as cost‐effectiveness, longevity, and environmental impact. Basic relationships are used to model both floating solar PV systems and pumped storage systems in MATLAB. An algorithm based on linear programming is used to generate the optimal schedule, while a particle swarm optimization‐based algorithm is employed for the optimal design of the proposed system. In order to analyze the economic feasibility, the levelized cost of solar energy and the levelized cost of stored energy are estimated. An optimally sized floating solar PV integrated pico pumped storage system with an optimal operating strategy can perform technically. However, due to practical limitations, the system's dimensions cannot accommodate real‐world storage requirements. When levelized costs are considered, a pico‐pumped storage system becomes less appealing than battery storage systems, particularly if a new storage tank is to be constructed. Compared to battery storage systems, pumped storage systems have a lower energy density, which requires more space and height, especially in buildings. Pumped storage systems, on the other hand, have a longer lifespan and a lower environmental impact. Overall, the proposed system, along with an optimal scheduling algorithm, provides a long‐term solution for energy storage, aligning with the growing global emphasis on lowering carbon emissions and embracing renewable energy sources. Although there may be a high initial investment requirement and a restricted storage capacity, the sustained advantages of energy independence and a diminished carbon footprint render it an appealing option for environmentally conscious communities and green buildings.

Model-free control for autonomous prevention of adverse events in robotics.

Introduction: Preventive control is a critical feature in autonomous technology to ensure safe system operations. One application where safety is most important is robot-assisted needle interventions. During incisions into a tissue, adverse events such as mechanical buckling of the needle shaft and tissue displacements can occur on encounter with stiff membranes causing potential damage to the organ. Methods: To prevent these events before they occur, we propose a new control subroutine that autonomously chooses a) a reactive mechanism to stop the insertion procedure when a needle buckling or a severe tissue displacement event is predicted and b) an adaptive mechanism to continue the insertion procedure through needle steering control when a mild tissue displacement is detected. The subroutine is developed using a model-free control technique due to the nonlinearities of the unknown needle-tissue dynamics. First, an improved version of the model-free adaptive control (IMFAC) is developed by computing a fast time-varying partial pseudo derivative analytically from the dynamic linearization equation to enhance output convergence and robustness against external disturbances. Results and Discussion: Comparing IMFAC and MFAC algorithms on simulated nonlinear systems in MATLAB, IMFAC shows 20% faster output convergence against arbitrary disturbances. Next, IMFAC is integrated with event prediction algorithms from prior work to prevent adverse events during needle insertions in real time. Needle insertions in gelatin tissues with known environments show successful prevention of needle buckling and tissue displacement events. Needle insertions in biological tissues with unknown environments are performed using live fluoroscopic imaging as ground truth to verify timely prevention of adverse events. Finally, statistical ANOVA analysis on all insertion data shows the robustness of the prevention algorithm to various needles and tissue environments. Overall, the success rate of preventing adverse events in needle insertions through adaptive and reactive control was 95%, which is important toward achieving safety in robotic needle interventions.

Multiagent-Based Nonlinear Generalized Minimum Variance Control for Islanded AC Microgrids

Voltage regulation, frequency restoration, and reactive/active power sharing are the crucial tasks of the microgrid's secondary control, especially in the islanding operating mode. Because sensors and communication links in a microgrid are subject to noise, it is of paramount value to design a noise-resilient secondary voltage and frequency control. This paper proposes a minimum variance control approach for the secondary control of AC microgrids that can effectively perform noise attenuation, voltage/frequency restoration, and reactive/active power sharing. To this end, the nonlinear generalized minimum variance (NGMV) control approach is introduced to the islanded microgrid's secondary control system. The effectiveness of the proposed control approach is verified by simulating two microgrid test systems in MATLAB.

Comparative Analysis of Anti-Islanding Prevention Technique in Grid Connected PV System

Abstract: This paper presents a novel islanding prevention scheme of Grid-Connected PV Systems in Matlab/ Simulink based on monitoring the dc-link voltage of the PV inverter. A 100kW PV System equipped with islanding protection like frequency relays, a ROCOF relay, and respectively the proposed dc-link voltage relay are simulated under the conditions of islanding and the detection time for all these AI techniques are compared.

MORpH: Model reduction of linear port-Hamiltonian systems in MATLAB

Abstract We present a novel software toolbox MORpH for the efficient storage, analysis, interconnection and structure-preserving model order reduction (MOR) of linear port-Hamiltonian differential-algebraic equation systems (pH-DAEs). The model class of pH-DAEs enables energy-based modeling and a flexible coupling of models across different physical domains. This makes them particularly suited for the simulation and control of complex technical systems. To promote the use of recent theoretical findings in engineering practice, efficient software solutions are required. In this work, we illustrate how possibly large-scale pH-DAEs can be efficiently stored and interconnected in MATLAB in an object-oriented way. We discuss three structure-preserving MOR strategies that are supported by MORpH and demonstrate the application and performance of selected MOR algorithms by means of two benchmark examples.

Using Deep Transfer Learning Technique to Protect Electrical Distribution Systems Against High-Impedance Faults

The dependence of high-impedance faults (HIFs) detection methods on a large amount of training data has always been a fundamental problem in electrical distribution systems. This article proposes a novel protection system based on the transfer learning technique and GoogleNet architecture to reduce this dependence. The proposed protection system uses a small amount of data to extend the knowledge of pretrained GoogleNet architecture to the HIF detection problem. In this system, a small amount of third harmonic angle data of the current at the measurement point are obtained from the understudy electrical distribution system. Then, the preprocessing phase is performed, and the extracted data are converted to image data using the Wigner–Ville distribution. Afterward, these converted images are fed to the GoogleNet architecture as an input dataset to update the GoogleNet pretrained knowledge. Finally, the process of fault detection and classification is accomplished only by transferring the GoogleNet pretrained knowledge. The simulation results of the modified IEEE 13-bus and 34-bus distribution systems in EMTP-RV and MATLAB indicate the high accuracy of the proposed protection system despite the use of a small amount of input training data.

Observability Enhancement of Smart Grid Based on Optimal Placement of PMUs

This paper presents an efficient observation concerning the enhancement of smart grid (SG) based on the optimal placement of phasor measurement units (OPP) using nonlinear programming (NLP). The proposed algorithm tries to achieve two objectives: (i) to ascertain the minimum number of phasor measurement units (PMUs) and (ii) to increase the redundancy of the SG at all the buses. Synchronized current and voltage phasors are obtained to enhance the accuracy of the state estimation results—a minimum number of PMUs results in a lack of communication facilities at the substation. PMU losses will lead to unobservable buses at the SG. Therefore, PMU losses and communication constraints should be considered during the design process. Limited channel capacity, conventional measurement, and zero-injection bus measurements are also included in the proposed PMU formulation. The proposed algorithm is examined on IEEE~14-, 30-, 57-, 118-, and 300-bus test systems in MATLAB to verify its effectiveness. Furthermore, the results are compared with the simplex linear programming and mixed linear programming methods to prove the efficacy of the presented algorithm. The output thus obtained reveals that the NLP algorithm obtains approximately the same PMUs as other methods.

Тестирование радиолокаторов с синтезированной апертурой антенны при помощи DRFM

The aim of this work is the practical development of the technology for synthetic aperture radars (SAR) testing using Digital Radio-Frequency Memory (DRFM). In this work, the methods of numerical mathematical modeling of interacting radio frequency systems in MATLAB and the methods for prototyping these systems using modular equipment from Keysight Technologies were used. And also, real manufactured devices (DRFM module) were used. In this work, the technology of synthetic aperture radars (SAR) testing using DRFM are discussed. The SAR prototype, built on the basis of modular equipment from Keysight Technologies and running under the MATLAB control is described. The structural and functional diagrams of the SAR model are considered, its operating modes are listed. A DRFM device, made on the basis of a VPX module with an FPGA and creating several arbitrary located simulated point targets on the SAR image is described. The structure of this DRFM is given. As a result of the work, a test radar image, formed by the SAR model as a result of processing synthesized in DRFM a digital radio-hologram (DRH), was obtained.

Wide-Area Network State Monitoring System Based On LoRa Communication

To meet the requirements of long range, small amount of data transmission, better data correctnessand less delay,a wide-Area Network State Monitoring System approach based on LoRa communication is discussed in our Project. The objective is to study and test the performance of Two communication techniques used in wide area monitoring system, a single input single output (SISO) system and a multiple input multiple output system (MIMO) in terms ofBit Error Rate(BER) with varying the signal to noise Ratio(SNR).In addition, we study the Wide Area Monitoring system based on LoRa communication. The IEEE 14-bus power system with Phasor Measurement Units(PMUs) placed at selected buses is considered. The simulation results demonstrate that the MIMO system outperform the SISO system in terms of Bit Error Rate. Furthermore, the value of the reporting rate has been varied for both systems in MATLAB to see the effect on the data correctness and the results show that the Bit Error Rate value decreases with the increase of reporting rate.Finally, we dealt with a modified LoRa MATLAB code emulator to investigate the data error and delay. The results show that LoRa Technology has better performance in terms of delay and error.

Reactive Power Support in Radial Distribution Network Using Mine Blast Algorithm

The passive power distribution networks are prone to imperfect voltage profile and higher power losses, especially at the far end of long feeders. The capacitor placement is studied in this article using a novel Mine Blast Algorithm (MBA). The voltage profile improvement and reduction in the net annual cost are also considered along with minimizing the power loss. The optimization problem is formulated and solved in two steps. Firstly, the Voltage Stability Index (VSI) is used to rank the nodes for placement of the capacitors. Secondly, from the priority list of nodes in the previous step, the MBA is utilized to provide the optimal location and sizes of the capacitors ensuring loss minimization, voltage profile improvement, and reduced net annual cost. Finally, the results are tested on 33 and 69 radial node systems in MATLAB. The results for the considered variables are presented which show a significant improvement in active and reactive power loss reduction and voltage profile with lesser reactive power injection.

Synchronization of N-Non-Linear Slave Systems with Master System Using Non-Adaptive and Adaptive Coupled Observers

Synchronization of N-slave chaotic systems with a master system is a challenging task, particularly in recent times. In this paper, a novel methodology is proposed for synchronizing the N number of slave systems with a master system. The proposed methodology is based on coupled adaptive synchronous observers. The difference between the corresponding states of master and slave systems is converged to the origin by means of a novel feedback control scheme to achieve synchronization between the master and slave systems. The efficacy of the proposed methodology is verified through a simulation of FitzHugh–Nagumo non-linear systems in MATLAB. The simulation results validate and prove claims, and these systems are successfully synchronized by CCS and CCAS observer-based control.

Optimal Siting and Sizing of Distributed Generators by Strawberry Plant Propagation Algorithm

Increasing the unplanned penetration of Distributed Generators (DGs) has spurred active and reactive power losses in the distribution system. This article suggests using a novel Strawberry Plant Propagation Algorithm (SPPA) for planning the placement of the DGs with the aim of reducing the network (active) power losses and improving the overall voltage profile. The proposed method (SPPA) has been tested on 33 and 69 node radial systems in MATLAB. A cost analysis was also performed and compared with other contemporary methods. The results for the considered variables show the significance of the proposed method in comparison to various other counterparts, including the Mine Blast Algorithm and Particle Swarm Optimization.

Coding closed and open quantum systems in MATLAB: applications in quantum optics and condensed matter

We develop a package of numerical simulations implemented in MATLAB to solve complex many-body quantum systems. We focus on widely used examples that include the calculation of the magnetization dynamics for the closed and open Ising model, dynamical quantum phase transition in cavity QED arrays, Markovian dynamics for interacting two-level systems, and the non-Markovian dynamics of the pure-dephasing spin-boson model. These examples will be useful for undergraduate and graduate students with a medium or high-level background in MATLAB, and also for researchers interested in numerical studies applied to quantum optics and condensed matter systems.

Coordinated Control of OLTC and Energy Storage for Voltage Regulation in Distribution Network With High PV Penetration

Accommodating increased penetration of renewable energy resources like solar Photo-Voltaics (PV) imposes severe challenges on the voltage regulation of the traditionally designed distribution system. Battery Energy Storage Systems (BESS) can mitigate voltage regulation issues, as they can act quickly in response to the uncertainties introduced due to solar PV. However, if there is no coordination between existing devices such as On Load Tap Changing Transformers (OLTC) and BESS, then BESS takes all the burden and is generally over-utilized. The uncoordinated control schematic shall also lead to underutilization of OLTC. Hence, in this paper, a coordinated control strategy to control BESS along with OLTC is proposed to warrant acceptable voltage magnitudes across the distribution feeder. The formulated optimization problem aims to mitigate the voltage deviation from its required values while reducing the number of changes in tap positions and also enhancing the battery life. The improvement in voltage regulation and optimal utilization of resources by using the proposed coordinated scheme over the traditional uncoordinated scheme is demonstrated for the IEEE 13 bus and 33 bus distribution systems in MATLAB/ Simulink.

Discrete-continuous dynamic simulation of plantwide batch process systems in MATLAB

Batch chemical and biochemical plants play an important role in the process industries. They are characterised by hybrid (continuous & discrete) dynamics as well as complex sequences and decision logic in the case of shared resources. This is challenging from a modelling and simulation perspective, both in terms of numerical algorithms as well as implementability and scalability/maintainability within software environments. In this work it is shown that it is possible to model complex plantwide batch processes at reasonably high performance, accuracy, and practicability in MATLAB/Simulink using the StateFlow toolbox. To this end, useful implementation guidelines are presented, and a complex example batch process is modelled. As focus lies on the implementability of complex batch control logic, the model is limited to mass balances. The simulation results are evaluated and carefully visualised, indicating the MATLAB's capabilities for analysis of such systems.

Numerical investigation of combustion optimization in a tangential firing boiler considering steam tube overheating

A comprehensive numerical study of the combustion optimization of a 660-MW tangentially fired boiler under the constraint of steam tube overheating is presented. To obtain the chemical products and the heat flux at the heating surfaces, a three-dimensional (3D) combustion model was established using computational fluid dynamics (CFD) software. In addition, a 1D + 1D thermal hydraulic model was developed using MATLAB to describe the heating process inside the tubes. Detailed mapping methods were also provided to connect the mesh systems in CFD and MATLAB. As a result, the tube wall temperature can be calculated by considering the coupled heat transfer on the gas and steam sides. The simulation results reveal that under full load conditions, the upward tilting of the separated over-fire air (SOFA) burners can reduce the formation of CO and NOx, which helps achieve higher boiler efficiency. However, when the SOFA tilt angle increases from +20° to +30°, 0.16% of the outer surfaces of the final re-heater would exceed the allowable temperature of the TP347H material; additionally, the improvement in the boiler efficiency and decrease in NOx formation are much less. Thus, considering the unit’s safe operation, the optimal SOFA tilt angle for combustion optimization should be +20°.

A contemporary adaptive air suspension using LQR control for passenger vehicles

Long rides on irregular roads and infrastructure problems like uncomfortable seating have a very bad impact on human body. The passengers suffer not only physical pain but also stress related problems. Airsprings gain more popularity in passenger vehicles with an increase in demand for ride comfort. Ride comfort and vehicle handling, being the two critical factors of a suspension system often contradict each other. This led to an extensive research on active automobile suspension systems. The authors of this article propose an innovative design of adaptive air suspension system with LQR control strategy. The proposed LQR controller is tuned by Particle Swarm Optimization. A dynamic model of an air suspension system used in passenger vehicles was designed and simulated for both passive and adaptive systems in MATLAB. An experimental evaluation was done to check the performance of the adaptive air suspension system on a vibration shaker table. Air suspension is a non-linear system and thus the authors have derived a stiffness equation for the same with minimal assumptions. A comparative analysis between the most commonly used PID controller and proposed LQR controller was performed over bumps, potholes and ISO standard random roads in MATLAB. Simulation results showed that adaptive air suspension system improves the ride comfort by reducing the maximum displacement amplitude of the vehicle over random roads by 31% while ensuring the stability of the vehicle by reducing the settling time by 85%. The experimental results of an adaptive air suspension system subjected to random vibrations of frequencies between 5 Hz to 20 Hz, exhibited a reduction of sprung mass acceleration by about 30% demonstrating that the proposed controller is effective for random vibration inputs.

The Brain Dynamics Toolbox for Matlab

Abstract Nonlinear dynamical systems are increasingly informing both theoretical and empirical branches of neuroscience. The Brain Dynamics Toolbox provides an interactive simulation platform for exploring such systems in Matlab . It supports the major classes of differential equations that arise in computational neuroscience: Ordinary Differential Equations, Delay Differential Equations and Stochastic Differential Equations. The design of the graphical interface fosters intuitive exploration of the dynamics while still supporting scripted parameter explorations and large-scale simulations. Although the toolbox is intended for dynamical models in computational neuroscience, it can be applied to dynamical systems from any domain.

Optimal Location and Sizing of Distributed Generation Unit Using Human Opinion Dynamics Optimization Technique

The demand of electricity is soaring rapidly. Distributed genera-tion (DG) is one of the most suitable alternatives to fulfill this swellingdemand of energy. DG is a small scale generation which is directly in-stalled in the distribution network or at load centre. Optimal allocationof DG is a vital factor in improving the voltage profile of the system andin reduction of total power losses. In this article, a detailed study of threedifferent methods for DG allocation and sizing has been discussed. Thefirst method is based on Newton Raphson load flow based technique todeduce the optimal location of DG in two different IEEE bus systems inMATLAB software. The next methodology is based on particle swarmoptimization (PSO) technique where a multi-objective function is beingminimized. The objective function has been modified and PSO has beenimplemented to attain optimal size and location of DG unit. The thirdmethod considered is based on human opinion dynamics evolution-ary multi-objective optimization technique which is used to obtain thebest possible size and location of DG unit in IEEE 14 and IEEE 30 bussystems. The human opinion dynamics method shows superiority inminimizing the size and location muti-objective function, over the othermethods considered herein.

Sss & sssMOR: Analysis and reduction of large-scale dynamic systems in MATLAB

Abstract We present two MATLAB toolboxes, provided as open-source code, that expand the capabilities of the Control System Toolbox to large-scale models. sss allows the definition and analysis of sparse state-space (sss) objects with functions (such as bode, step, norm,…) revisited to exploit the sparsity of the system matrices. sssMOR entails model reduction algorithms that capture the relevant dynamics of high order systems in models of significantly lower dimensions. The sssMOR_App provides a graphical user interface for easy interaction with the tools. With sss and sssMOR it is possible to analyze dynamical systems with state-space dimensions higher than O(104), which is typically the limit for built-in ss objects. In this contribution, we give a first introduction to the toolboxes and the main functionality. Numerical examples show the advantages of using the tools.