Multi-machine System Research Articles

Dyeing scheduling optimization in a multi-machine system with resource constraints

Abstract Water consumption is one of the most important concerns for a textile dyeing company in the era of global energy revolution. Different from the traditional production scheduling which focuses on the production efficiency improvement, the dyeing scheduling emphasizes the constraints of resource consumption. Besides, different from the traditional production scheduling where the task relevance is seldomly considered, the colour depth heavily impacts the water consumption and the dyeing scheduling results, which aggravates the uncertainty and complexity when modelling the dyeing scheduling optimization. Therefore, how to select proper dyeing orders among a large number of orders and schedule them for the purpose of generating more profit is challenging. To address the above issue, an optimization model with objective of maximizing profit and consideration of water consumption, delivery due time, and machine capacity, is built, and genetic algorithm is adopted to solve the problem. A numeric experiment is conducted to validate the effectiveness of the proposed method.

VOLTAGE FLICKER MITIGATION USING GTOBASED STATCOM TO IMPROVE POWER QUALITY OF A MULTI MACHINE SYSTEM

Transmission networks of modern power systems are becoming increasingly stressed because of growing demand and restrictions on building new lines. One of the consequences of such a stressed system is the threat of losing stability following a disturbance. Flexible ac transmission system (FACTS) devices are found to be very effective in a transmission network for better utilization of its existing facilities without sacrificing the desired stability margin. FACTS such as Static Synchronous Compensator (STATCOM), employ the latest technology of power electronic switching devices in electric power transmission systems to control voltage and power flow. The STATCOM adjusts voltage at its terminal by managing the amount of reactive power injected into or absorbed from the power supply. When the system voltage is low, STATCOM creates reactive power; when the system voltage is high, STATCOM absorbs reactive power. In this paper STATCOM controllers are designed for improving transient stability of multi machine systems. Proposed controllers are implemented under MATLAB/SIMULNK environment. Results of PI based controllers installed with multi machine system is found to be better on comparison with conventional system.

Nonlinear modelling and design of synergetic controllers for single penstock multi-machine hydropower system

The existence of a shared pipeline in a multi-machine system can lead to hydraulic coupling effects between units. It increases the difficulty of controlling hydroelectric units and affects the stability of the power system. This paper refines the model of the hydroelectric generator unit and builds a nonlinear model of a hydro-generator unit with the single penstock multi-machine system. The synergetic control theory was introduced, and the governor and excitation system controllers were designed separately. A joint synergistic controller is obtained by analyzing the two systems' synergistic factors and controlled characteristics. This controller realizes the joint control of the excitation and governor system. The simulation selected a proportion-integral-derivative (PID) controller with optimized parameters, synergistic governor controller (SEC), and synergistic excitation controller (SGC) for comparison to verify the effectiveness of the proposed method. The results indicate that the proposed control method exhibits competent control effects in the single penstock multi-machine system. It can reduce the impact of hydraulic coupling, shorten the adjusting time, and ensure the fast and stable operation of the system. In addition, the values of system time parameters and synergetic control parameters are analyzed separately to provide a reference for achieving optimal control.

Design of optimal controller for static compensator via Hamiltonian formalism for the multimachine system

Design of optimal controller for static compensator via Hamiltonian formalism for the multimachine system

Intelligent method for Power flow using Artificial Neural Network with UPFC

It is slightly difficult to transmit such a large amount of electricity in very flexible and efficient way as the size of conventionally used relay and protective devices will increase while transmitting such a large amount of electricity which will increase the operating cost. So for transmission of such a large amount of electricity, Flexible Alternating Current Transmission Systems (FACTS) will have been found to be promising aspect in terms of the analysis of the power system. In this paper the comparative analysis of unified power flow controller(upfc) is presented in presence of LG fault. ANN controllers are applied in UPFC in MATLAB/SIMULINK environment. There is significant reductions in oscillations in rotor angle deviation of multimachine systems using ANN controller compare to conventional PI controller. Hardware prototype model of UPFC also shows improvement in voltage stably in multimachine. There is improvement in rotor angle stability of power system using ANN controller compared to conventional PI controller. Oscillations are reduced.

STABILISATEUR DE SYSTÈME D'ALIMENTATION ROBUSTE BASÉ SUR UN CONTRÔLE H∞ STRUCTURÉ POUR LA STABILITÉ D'UN SYSTÈME MULTI-MACHINE

A robust design of power system stabilizers (PSSs) using H∞ output feedback control has been introduced in this work. To facilitate the implementation of the designed PSSs, the proposed technique employs the H∞ to tune the fixed-structure conventional lead-lag PSS parameters of the multi-machine system. These PSSs are used to improve the damping of the local and inter-area low-frequency oscillations in power systems under different operating conditions. The proposed control is tested on a multi-machine system, which is a three-machine nine-bus system. A comparative simulation study shows a significant enhancement and good performance of the proposed design compared to an IEEE conventional power system stabilizer.

Estimation of the Region of Attraction of Polynomial Swing Equation Using Sum of Squares Theory

Estimation of the region of attraction of the power system using sum of squares (SOS) programming theory is investigated in this paper. Firstly, the Taylor expansion formula is applied to explore the inherent polynomial structure of the swing equation. The single machine projection equation for a multi-machine system is proposed based on the amplitude characteristic of the rotor angle response in decoupled space. Secondly, the theory of SOS programming originating from the polynomial system is derived, and the theory about estimation of the region of attraction for the differential algebraic system is summarized. Thirdly, the method for estimating the region of attraction for the polynomial swing equation based on a V-S two-stage iterative procedure is proposed. Finally, a single machine infinite bus power system, an IEEE 3-machine power system, and an IEEE 4-machine power system are employed to validate the effectiveness and accuracy of the proposed method and analysis.

Modal Analysis of Strong Resonance in Multi-Machine System with Power System Stabilizer

Modal Analysis of Strong Resonance in Multi-Machine System with Power System Stabilizer

Localization method of subsynchronous oscillation source based on high-resolution time-frequency distribution image and CNN

The penetration of new energy sources such as wind power is increasing, which consequently increases the occurrence rate of subsynchronous oscillation events. However, existing subsynchronous oscillation source-identification methods primarily analyze fixed-mode oscillations and rarely consider time-varying features, such as frequency drift, caused by the random volatility of wind farms when oscillations occur. This paper proposes a subsynchronous oscillation source-localization method that involves an enhanced short-time Fourier transform and a convolutional neural network (CNN). First, an enhanced STFT is performed to secure high-resolution time-frequency distribution (TFD) images from the measured data of the generation unit ports. Next, these TFD images are amalgamated to form a subsynchronous oscillation feature map that serves as input to the CNN to train the localization model. Ultimately, the trained CNN model realizes the online localization of subsynchronous oscillation sources. The effectiveness and accuracy of the proposed method are validated via multimachine system models simulating forced and natural oscillation events using the Power Systems Computer Aided Design platform. Test results show that the proposed method can localize subsynchronous oscillation sources online while considering unpredictable fluctuations in wind farms, thus providing a foundation for oscillation suppression in practical engineering scenarios.

A Predictive Out-of-Step Identification Method Based on Wide-Area Velocity-Acceleration Trajectory

Online identification of the transient instability is essential in power system analysis, as it facilitates the grid operator to decide and coordinate system failure correction control actions. The rapid technological development of phasor measurement units (PMUs) provides an opportunity for online transient out-of-step identification in real-time. This paper analyzes the characteristics of angular velocity-acceleration trajectories in detail, and then proposes a predictive transient out-of-step identification method among coherent groups of generators based on the velocity-acceleration trajectory sampled by PMUs. To prove that the method can distinguish the transient out-of-step event following disturbance reliably, a mathematical proof of the criterion extended to multi-machine system is made, and the influences of the exciter and emergency control are taken into consideration to a certain extent. Finally, the effectiveness and predictability of the proposed method are demonstrated on a 39-bus New England test system and two large-scale power system simulation models of China by numerical studies.

Nonlinear Backstepping Control of Grid-Forming Converters in Presence of Grid-Following Converters and Synchronous Generators

Grids in near future are going to host synchronous generators (SGs), legacy grid-following converters (GFLCs), and relatively new grid-forming converters (GFCs), where the latter two technologies support converter-interfaced generations. This change is going to introduce new challenges – one of them is the dc-link voltage collapse issue in GFCs following the outage of a generator. As a solution, this paper proposes a nonlinear backstepping control strategy that guarantees Lyapunov stability of a reduced-order model of such systems. To this end, first a reduced model of a 6-bus system with one GFC, one GFLC, and one SG is considered to develop fundamental understanding of such systems and derive a stabilizing control strategy. Then, based on certain observations, the simplified model is extended to a multimachine system, which in turn helps developing the nonlinear control strategy in presence of bounded uncertainties. Further, a dc-link voltage tracking control is introduced to ensure controllable frequency support from GFCs. The proposed controller is decentralized in nature and requires limited communication only if neighboring buses have GFCs and/or GFLCs. Detailed phasor models of the 6-bus system and the modified 68-bus New England-New York system with 2 GFCs and 2 GFLCs are used to demonstrate the effectiveness of the proposed control strategies.

On the Destabilizing Mechanism of Nonuniform Damping in Grid-Forming Converters Penetrated Multi-Machine System

On the Destabilizing Mechanism of Nonuniform Damping in Grid-Forming Converters Penetrated Multi-Machine System

Allocating Robots/Cobots to Production Systems for Productivity and Ergonomics Optimization

Collaboration between humans and robots has great promise in manufacturing systems. The utilization of cobots in a manufacturing system can improve both productivity and ergonomics. In this paper, we study the problem of how to allocate limited cobot/robots to manufacturing systems with multiple workstations so that an integrated performance measure, considering both productivity and ergonomics is optimized. Previous work on cobot/robot allocation in manufacturing systems focus on the decomposition of tasks for a single workstation into multiple work elements, and then split them between human and robots, rather than studying multi-machine systems. To bridge this gap, we consider the allocation of cobots/robots to a multi-stage manufacturing system. Specifically, we establish an integrated performance measure and formulate cobot/robot allocation into a constraint integer programming problem. With this formulation, we obtain the optimal allocation of one available cobot/robot in simulated production systems, based on the integrated performance measure of productivity and ergonomics. Furthermore, the allocation problems of production systems with multiple cobots/robots is considered and solved with a scalable algorithm. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Collaborative robots and independent robots are increasingly applied to manufacturing production systems. However, how to optimally allocate both types of robots considering both productivity and ergonomics influence has not been well studied. In this article, we established a practical optimization method to allocate cobots/robots to different workstations and split the work between cobot and human in one workstation when there are multiple workstations and a limited number of available cobots/robots in the manufacturing systems. Based on various real-world scenarios, we inferred useful insights for the robot/cobot allocation problem. To deal with the computational load when the number of workstations is large, a scalable optimization algorithm is also adopted. The case study results demonstrated the effectiveness of the proposed approach.

Decoupled Control of a Multi-Machines System Fed by a Single Multilevel Inverter Six-Phase

The use of multiphase motors offers an additional possibility of independent control of a set of series-connected motors that are supplied from a single inverter.This paper presents independent vector control of six-phase two-motor drive machine series-connected fed by a seven-level six-phase inverter. Via appropriate phase transposition during the series connection of the stator windings, the fully decoupled control of the two machines is possible. The control system multi-machines classic based on vector control with conventional inverters comprise various problems are related to low power quality, pressure on motor bearing, etc. However, decoupling control of a series six-phase two-motor drive machine by a seven-level six-phase inverter is developed. A simulations result clearly shows the possibility of independent vector control of the two machines, although a single seven-level six-phase inverter is used as the supply.

Multi-Parameter Practical Stability Region Analysis of Wind Power System Based on Limit Cycle Amplitude Tracing

The existing division of system stability region does not fully consider the influence of nonlinear characteristics of the system. To address the challenge that it is difficult to inscribe the stability region of wind power grid-connected systems accurately and quantitatively, this paper proposes a nonlinear system multi-parameter practical stability region analysis method based on limit cycle amplitude tracking. Firstly, the nonlinear dynamic model of multi-machine system with doubly fed induction generator (DFIG) is established, and the bifurcation diagram of the system is obtained by nonlinear analysis of the model. Then, the limit cycle-parameter diagram is obtained by tracking the limit cycle of the Hopf bifurcation point of the system, and the problem of how the system oscillation evolves with the change of operating parameters is analyzed. Afterwards, the single parameter practical stability region of the nonlinear system is obtained by combining the system equilibrium manifold. Finally, the multi-parameter practical stability region of the nonlinear system is obtained by the three-dimensional bifurcation map with the system time delay, DFIG output active power and reactive load as the bifurcation parameters. The division of the stability region has important guiding significance for the parameter adjustment in the actual operation of the system.

Generalized Turbine Model Based Analysis and Simulation of Ultra-Low Frequency Oscillation of Hydropower Units

The occurrence of ultra-low frequency oscillation (ULFO) events in the power grid has a significant number of hydropower units in recent years. Considering this aspect, relevant studies have shown that the turbine model has an important impact on the ULFO behavior of hydropower units. Based on the study of the generalized turbine model, the flow factor closely related to the inherent parameters of the turbine and the variation of the generating flow is defined in this paper. The ULFO model of the hydropower unit with full consideration of the flow factor is established. Based on the frequency characteristics of the system and the Routh stability criterion, the mechanism of the influence of the flow factor on the ULFO behavior of the hydropower unit is analyzed. The simulation results of single-machine and multi-machine systems show that, compared with the ideal turbine model, the generalized turbine model considering the flow factor can increase the stability margin of the system. It can provide greater damping torque and restrain the ULFO behavior of hydropower units. The flow factor is larger, and the suppression effect of the ULFO is more obvious.

Knowledge-enhanced reinforcement learning for multi-machine integrated production and maintenance scheduling

Machines deteriorate as they perform production operations, leading to increased production cost rates. When the deterioration reaches a certain level, the machine may break down, which disrupts production and requires costly Corrective Maintenance (CM) to restore operation. Preventive Maintenance (PM) can improve machine health but requires production downtime and expenses. Thus, to balance the increased production cost from degradation against the maintenance cost, it is important to jointly optimize production and maintenance scheduling. This paper aims to address the joint optimization problem for a multi-machine system to achieve the optimal overall business reward under incomplete information and system production demand constraints. We propose a novel method called Knowledge Enhanced Reinforcement Learning (KERL), which adopts a centralized multi-agent actor-critic architecture. KERL enhances the performance of Reinforcement Learning (RL) for multi-machine production and maintenance scheduling by leveraging the prior knowledge of the constraint to determine the production decisions and handle the cooperation among machines in the system. The performance of KERL is evaluated in both deterministic and stochastic case studies and is compared to three baseline methods. Results show that KERL achieves a higher overall business reward than baseline methods and learns to avoid failures in the stochastic environment.

A Novel Simplified Modeling Approach for VSC-HVDC Links in Performance Analysis of Multi-Machine Systems

A Novel Simplified Modeling Approach for VSC-HVDC Links in Performance Analysis of Multi-Machine Systems

Participation Factors Weak Robustness Analysis and Mitigation of Direct-Drive Wind Farms Connected to the Parallel-Compensated Grid

Reactive power compensation requirement and large parasitic shunt-capacitor in offshore wind power generation systems form the parallel-compensated grid. However, the direct-drive wind farms connected to the parallel-compensated grid faces the risk of oscillations. This paper presents a unique phenomenon that the participation factors (PFs) of close oscillation modes in direct-drive wind farms connected to the parallel-compensated grid are sensitive to parameter perturbations. The phenomenon is defined as PFs weak robustness (PFWR) and its necessary conditions are revealed. To deepen the understanding of PFWR, the PFs transfer characteristics of close oscillation modes are analyzed under parameter perturbations. Then, the hazards of PFWR are discussed, and mitigation methods are proposed. PSCAD/EMTDC simulations of a multi-machine system are performed to verify the theoretical analysis.

Recurrent neural network based design of fractional order power system stabilizer for effective damping of power oscillations in multimachine system

The complexity of modern power systems has risen due to the growing demand for electricity. To mitigate this problem, the role of the electric utility in supplying safe and reliable electricity has become increasingly crucial. Low-frequency oscillations (LFOs) in a power system are an inevitable aspect. Therefore, the reliability of the system requires appropriate damping to overcome these LFOs. This paper proposes a novel design methodology for a fractional-order power system stabilizer (FO-PSS) to enhance the stability of the power system network. FO-PSS is designed to effectively dampen LFOs in both single-machine infinite bus systems (SMIB) and multi-machine power systems (MMPS). Recurrent neural network (RNN) is used to predict the parameters of proposed PSSs. To evaluate the efficacy of the proposed PSS, various test cases are considered. The results are compared to those obtained from traditional PSSs and optimization based PSSs. The effectiveness of the proposed RNN-based FO-PSS is demonstrated under diverse loading conditions.