Gas Turbine Generation System Research Articles

Mitigation effect of flywheel energy storage on the performance of marine gas turbine DC microgrid under high-power load mutation

Due to the slow response of output power of the traditional marine micro gas turbine, the directly connecting of high-power load to a shipboard micro gas turbine power generation system usually causes large power imbalance and instability instantly. To address this issue, a flywheel energy storage system (FESS) is applied to compensate the transient power changes, mitigate load fluctuations and maintain the voltage of the shipboard direct current (DC) bus. Based on a practical 100 kW micro gas turbine generator set, a detailed model of DC microgrid for the micro gas turbine generation system including micro gas turbine, FESS, synchronous generator, excitation system and load is established. The coordinated control strategy of micro gas turbine, FESS and load system is designed. The mitigation effects of FESS on marine gas turbine DC microgrid under high-power load mutation are explored by performing simulation with sudden load changes of 25%, 50% and 75% rated power and comparing the performance with and without FESS. The effectiveness of the control strategy has been verified by simulation analysis. The simulation results show that by reasonably designing the coordinated control strategy, the fluctuation of the power system can be effectively mitigated when sudden load, especially high-power sudden load is considered. The stability of the marine gas turbine microgrid has been greatly improved.

Optimal Scheduling of Integrated Energy Systems Considering Carbon Trading

Under the background where the electricity market and the carbon market are booming, the operation and dispatch of the integrated energy system requires the introduction of a carbon trading mechanism that can help guide customers and system operators to optimize electricity consumption and dispatch plans. A mathematical model of the community-integrated energy system, including energy storage, gas turbine generation system, and flexible load, is constructed based on energy hubs. In the consideration of costs in operation and carbon trading of the system, a low carbon economic dispatch model is established for IES to achieve the optimization objective of minimizing the total cost. The simulation results show that the coupled electric and thermal dispatch and the participation and interaction of flexible electric and thermal loads can lower the load peak-to-valley difference and significantly reduce the system operation cost, and the flexible load participation and dispatch under the carbon trading system can effectively bring the system more environmental and economic benefits.

Gas Turbine Model Parameter Classification During Abnormal Operation Using Support Vector Machine For Maintenance

When there is a contingency in a major transmission system, it is crucial to locate and detect abnormal parameters using an accurately modeled gas turbine (GT) generator. In this paper, a new method was proposed to model, a GT generator system. Firstly, MATLAB/Simulink was used to rebuild GT-based model which was validated using a model in PSS/E. Secondly, an artificial intelligence (AI) based approach, namely Support Vector Machine (SVM) was used for problem recognition in GT power plant. The results showed that, under steady-state, the electrical power of the rebuilt GT model was the same as the model in PSS/E. The advantage of having the MATLAB / Simulink GT model was the ability to visually observe the output from each block which was not possible in PSS/E. In addition, the average training accuracy was over 90% for the detection of GT governor parameter during abnormal behavior. As an implication, the developed model should be considered to apply in real-world grids for operation engineers to detect abnormal governor parameters in GT in the next stage. In turn, it assists in the restoration of GT to its operating condition and minimizes troubleshooting time.

Experimental and numerical study on self-sustaining performance of a 30-kW micro gas turbine generator system during startup process

The safe startup of micro gas turbine (MGT) generator system is the premise of normal operation. The whole start-up process contains motor startup, ignition, speed acceleration, motor switching to generator and power acceleration. Motor switching to generator happens at the self-sustaining state, which is significant to safe start-up process. However, characteristics of MGT generator system at self-sustaining state are hardly to investigate due to the lack of performance maps and complete experiments. Therefore, this work analyzed start-up schedule and presented a theoretical and experimental study on the self-sustaining performance of MGT generator system, based on the self-designed 30 kW MGT generator system built in Jiangjin Turbocharger Plant, China. The self-sustaining speed boundary and fuel consumption area is determined from the aspects of safe startup. A novel principle for determining the self-sustaining point (SSP) is proposed. Results show that the self-sustaining state can be achieved only when speed is over 26,750 rpm, and the SSP is determined at the speed of 30,750 rpm based on the proposed principle. Finally, the self-sustaining TIT and natural gas flow are compared with the experimental data, with two relative errors both almost within 4%. This method is instructive to the MGT generator system startup process.

Influence of magnets magnetization direction on the performance of high-speed permanent magnet synchronous starter-generator for micro-gas turbine

Abstract High-speed surface-mounted permanent magnet synchronous machine is often used in micro gas turbine generation system due to its high rotor strength and high efficiency. The electrical machine in this kind of generation system needs to integrate two functions of starter and generator. Therefore, its comprehensive performance, including starting performance and generating performance, has become a comprehensive standard to measure machine performance. In this paper, a 40 kW, 20,000 r/min high-speed machine is taken as an example, the influence of magnets magnetization direction on the machine comprehensive performance is studied. The machine models with different magnets magnetization directions are established by using finite element method and the correctness of the models is verified by comparing the experimental data with the finite element calculation data. On this basis, the influence of different magnetization directions on the performance of the machine, such as generation loss, torque ripple, output voltage, start-up time and maximum starting ability, is analyzed. Furthermore, based on the Fourier decomposition of air gap flux density and the decoupling analysis of starting torque, the influence mechanism of magnetization direction on the performance of the machine is revealed. The presented results provide a reference for the selection of a suitable magnetization direction for high-speed surface-mounted permanent magnet machines.

Optimization of a Hybrid Solar PV and Gas Turbine Generator System Using the Loss of Load Probability Index

In this paper, an optimization approach for designing a hybrid renewable energy system with zero load rejection is presented for a specific location in Malaysia. The proposed renewble energy system includes photovoltaic system, gas turbine generator and battery bank. The aim of the optimization process is to design the system with a loss of load probability that is less than 1%. An improved numerical algorithm is proposed in this paper. Moreover, a comparison between electrification options, including the existing gas-turbine-based generator (existing system), electricity grid and the proposed system, is presented in terms of the annualized total life-cycle cost. The results show that the proposed system can reduce the annual running cost by USD 2.1 million, while the electricity grid connection option can reduce the annual cost by USD 1.16 million as compared to the existing gas-turbine-based generator. In addition to this, the proposed optimization algorithm provides a reliable power system with zero load rejection based on simulation results.

Frequency Control System Design of Turbine Gas using Electro-Hydraulic Converter

In controlling the electric power system, it requires Load Control Frequency (LFC) to control load in MW and frequency (Hz) in the nominal range of 50Hz. The nominal parameter for the controller is the opening of the fuel valve, which is driven by the Electro-Hydraulic Converter (EHC). The control variable contained in the gas turbine system itself is the deviation between the setpoint and the feedback does not exceed 5% if the value exceeds the set value, it will produce a deviation, that means playing the error control. If the backup control system is active at startup, this system will result in not being able to synchronize because variable input from the network can only be controlled by frequency and active power control. It can also result in travel due to synchronous failure. If an error occurs during the operation of the backup controller load will be on, it will cause more speed or a maximum of 147 MW and of course, it will be dangerous for the gas turbine generator system. This paper will analyze the protection system from main control errors due to deviations between feedback and the setpoint set at 5% to 10% and see the system's response when there is a system change in the turbine gas. The control system design produces the largest error value at 7.2% valve opening with the control parameter Kp 12, Ti 1.9, Td 2. With simulations and data were taken through POS Simponi S+ and logic data analysis on PDDS (Programming Diagnostic Display System). The speed droop response value affects how much speed regulation is set, the smaller speed droop response value the faster the response to frequency changes and the greater speed droop response value the slower the response received by the system. In this study, the rise time value was 0.26 s and the settling time was 17.9 s.

Control Strategy for MGT Generation System Optimized by Improved WOA to Enhance Demand Response Capability

The grid-connected micro gas turbine (MGT) generation system is playing an important role in power systems because of its demand response capability and application in combined heat and power (CHP) systems. When applied to promote demand response, the generation system is expected to respond to follow instructions quickly, but a rapid response harms the safety and is not conducive to the benefits of customers, which leads to a contradiction. In this paper, a closed-loop power control is introduced for the MGT to improve demand response capability. The rate of fuel valve opening is limited so as to protect the equipment from thermal fatigue threats. An optimization method is developed for identifying the control parameters, balancing the response time and unrealized energy in the regulation process. An improved whale optimization algorithm (IWOA) is proposed to implement the optimization. Results of the algorithm performance verify that WOA is competitive with other heuristic algorithms, and IWOA is more suitable for parameter optimization problems than WOA because of better efficiency and exploitation capability. Results of power response further indicate that the proposed control strategy can achieve expected aims and is suitable for the MGT generation system.

Cooperative controls of micro gas turbine and super capacitor hybrid power generation system for pulsed power load

Due to slow response of conventional micro gas turbine(MGT) generator system, pulse power load(PPL) will cause large voltage sags and overshoot of direct current(DC) bus voltage, and even lead to instability. In this paper, super capacitor(SC) energy storage system(ESS) is applied to MGT to form a hybrid power generation system. Then the two cooperative control methods of hybrid generation system are proposed. One is the PI-based control algorithm, and the other is the fast power coordinated control method through MGT output power forecast. The fast power dynamic response of SC ESS can compensate for low dynamic response of MGT, which makes the hybrid generation system in equilibrium state of transient power in real time. Voltage of DC bus is smooth, and adaptability of MGT to PPL is enhanced. The second control algorithm is proposed according to power output characteristics of MGT, and has the advantages of fast and balanced power distribution. The algorithm of fast charging and exiting of SC ESS is proposed based on load conditions, and the charging process will not cause any impact. Finally, simulation model is established to verify the effectiveness of the two control algorithms, and the results are compared.

Use of hot supercritical CO2 produced from a geothermal reservoir to generate electric power in a gas turbine power generation system

CO2 capture and sequestration in deep saline aquifers is widely considered to be a leading option for controlling greenhouse gas emissions. One such possibility involves injection of supercritical carbon dioxide into a high-permeability geothermal reservoir. In addition to the benefit of sequestering the CO2 in the reservoir, the CO2 can be used to mine geothermal heat for utilization above ground. This paper describes one of the options for generating power from hot supercritical CO2 obtained from CO2 production wells connected to a geothermal reservoir, where the original source of the CO2 is CO2 captured from fossil-fired power plants or industrial processes. The cost of power generated using CO2 produced from a geothermal reservoir with a gas turbine generation system is compared to the cost of generating power from a conventional geothermal steam power plant.

Power balance control of micro gas turbine generation system based on supercapacitor energy storage

In view of the impact load problems in the traditional micro gas turbine (MT) power generation system, this paper analyzes its working mechanism and finds the reason lies in the slow response of the micro turbine output power adjustment. In order to make up for the shortage of the instantaneous output power of micro turbine, the method of instantaneous power fast control is proposed. Control algorithm of instantaneous compensation power is raised by power response prediction of MT. The high power dynamic response of super-capacitor energy storage can compensate low dynamic response problem of MT output power, so the instantaneous power of the system is real balance to ensure that the DC bus voltage is smooth and adaptability of MT power generation system is enhanced for impact load. Finally, the correctness and feasibility of the proposed control strategy are verified by simulation results.

An Effective Fault Feature Extraction Method for Gas Turbine Generator System Diagnosis

Fault diagnosis is very important to maintain the operation of a gas turbine generator system (GTGS) in power plants, where any abnormal situations will interrupt the electricity supply. The fault diagnosis of the GTGS faces the main challenge that the acquired data, vibration or sound signals, contain a great deal of redundant information which extends the fault identification time and degrades the diagnostic accuracy. To improve the diagnostic performance in the GTGS, an effective fault feature extraction framework is proposed to solve the problem of the signal disorder and redundant information in the acquired signal. The proposed framework combines feature extraction with a general machine learning method, support vector machine (SVM), to implement an intelligent fault diagnosis. The feature extraction method adopts wavelet packet transform and time-domain statistical features to extract the features of faults from the vibration signal. To further reduce the redundant information in extracted features, kernel principal component analysis is applied in this study. Experimental results indicate that the proposed feature extracted technique is an effective method to extract the useful features of faults, resulting in improvement of the performance of fault diagnosis for the GTGS.

A Study of Optimal Capacity Configuration with Multi-Objective for Islanded Micro-Grid

This paper investigates a method to configure capacity of different kinds of generation in an islanded micro-grid, including PVGS (PV generation system), WTGS (wind turbine generator system), ESS (Energy Storage System) and MTGS (Micro gas turbine generator system), with a diesel generator set as reserve. Based on the structure, we build a mathematical model with restraints in operation and two objectives, of which one is the annual cost of the devices and the other is the percentage of utilization of PV and wind resources. A strategy of operation based on the SOC (State of Charge) of the ESS is put forward and power the ESS get charged and discharged and generated by the MTGS is determined according to this strategy. NSGA-II is applied to solve the model. Finally, a case is addressed. This paper would provide support to construction of islanded micro-grid.

Real-time fault diagnosis for gas turbine generator systems using extreme learning machine

Real-time fault diagnostic system is very important to maintain the operation of the gas turbine generator system (GTGS) in power plants, where any abnormal situation will interrupt the electricity supply. The GTGS is complicated and has many types of component faults. To prevent from interruption of electricity supply, a reliable and quick response framework for real-time fault diagnosis of the GTGS is necessary. As the architecture and the learning algorithm of extreme learning machine (ELM) are simple and effective respectively, ELM can identify faults quickly and precisely as compared with traditional identification techniques such as support vector machines (SVM). This paper therefore proposes a new application of ELM for building a real-time fault diagnostic system in which data pre-processing techniques are integrated. In terms of data pre-processing, wavelet packet transform and time-domain statistical features are proposed for extraction of vibration signal features. Kernel principal component analysis is then applied to further reduce the redundant features in order to shorten the fault identification time and improve accuracy. To evaluate the system performance, a comparison between ELM and the prevailing SVM on the fault detection was conducted. Experimental results show that the proposed diagnostic framework can detect component faults much faster than SVM, while ELM is competitive with SVM in accuracy. This paper is also the first in the literature that explores the superiority of the fault identification time of ELM.

Simultaneous-Fault Diagnosis of Gas Turbine Generator Systems Using a Pairwise-Coupled Probabilistic Classifier

A reliable fault diagnostic system for gas turbine generator system (GTGS), which is complicated and inherent with many types of component faults, is essential to avoid the interruption of electricity supply. However, the GTGS diagnosis faces challenges in terms of the existence of simultaneous-fault diagnosis and high cost in acquiring the exponentially increased simultaneous-fault vibration signals for constructing the diagnostic system. This research proposes a new diagnostic framework combining feature extraction, pairwise-coupled probabilistic classifier, and decision threshold optimization. The feature extraction module adopts wavelet packet transform and time-domain statistical features to extract vibration signal features. Kernel principal component analysis is then applied to further reduce the redundant features. The features of single faults in a simultaneous-fault pattern are extracted and then detected using a probabilistic classifier, namely, pairwise-coupled relevance vector machine, which is trained with single-fault patterns only. Therefore, the training dataset of simultaneous-fault patterns is unnecessary. To optimize the decision threshold, this research proposes to use grid search method which can ensure a global solution as compared with traditional computational intelligence techniques. Experimental results show that the proposed framework performs well for both single-fault and simultaneous-fault diagnosis and is superior to the frameworks without feature extraction and pairwise coupling.

The Application of Flywheel Energy Storage Device in Marine Gas Turbine Generator Set

Marine gas turbine generator set; Flywheel energy; Stability Abstract. Based on modular modeling idea, the modular model of marine generation system was set by the technology of systematic simulation. One set of simulation models of marine gas turbine generation system was generated. Results show that flywheel energy storage device can enhance the stability of power grid and play a better role in making marine gas turbine generation system stable under heavy load fluctuations.

A Study on the Stability of Marine Gas Turbine Generation Module Power System

Based on modular modeling idea, the modular model of marine generation system was set by the technology of systematic simulation. One set of simulation models of marine gas turbine generation system was generated. Results show that flywheel energy storage device can enhance the stability of power grid and play a better role in making marine gas turbine generation system stable under heavy load fluctuations.

A Megawatt-Scale Power Hardware-in-the-Loop Simulation Setup for Motor Drives

We report on the application of a 5-MW variable voltage source (VVS) amplifier converter for utilization in power hardware-in-the-loop (PHIL) experiments with megawatt-scale motor drives. In particular, a commercial 2.5-MW variable speed motor drive (VSD) with active front end was connected to a virtual power system using the VVS for integrating the drive with a simulated power system. An illustrative example is given, whereby a 4-MW gas turbine generator system, including various loads, is simulated and interfaced with the VSD hardware in the lab through the VVS using current feedback to the simulation. Mechanical loading is applied to the motor via an identical 2.5-MW dynamometer connected to the same shaft. This paper first describes the PHIL facility, illustrates the challenges of powering a motor drive from a controlled voltage source converter at the multimegawatt scale, and provides experimental results from dynamic simulations. While certain challenges remain with the accuracy of the interface, it is concluded that PHIL simulations at the megawatt power level are possible and may prove useful for validating models of drive systems in the future.

Two healthcare buildings get the power, the noise, and the vibration from a gas turbine generator system.

A package gas turbine generator was installed at a small, 4.3-MW cogeneration power plant of a mixed use development with office, retail, hospital, residential, and other occupancies. Shortly after commissioning, noise complaints were received from nearby medical offices about undesirable tonal noise intrusions. At another nearby hospital building, a neurosurgery suite addition would include a new intra-operative magnetic resonance imaging (iMRI) unit. Ambient vibration measurements at that site indicated prominent discrete frequencies of disturbance that could affect iMRI image quality. Investigations found loud broadband noise and dominant ground borne vibration in the vicinity of the turbine, with strong tonal peaks relating to turbine and generator rotational rates. The intrusive noise in nearby medical offices and the structure borne vibration at the hospital included matching strong tonal peaks. Various noise- and vibration-mitigating measures were proposed and some were implemented with successful results for the medical offices and new iMRI suite. Mitigating measures are discussed, along with measurement results and photographs.

G0801-1-3 動特性モデルに基づく2軸マイクロガスタービン発電システムの回転数制御(動力エネルギー部門一般(1))

In this study, to establish the methodology for controlling the rotational speed of two shaft axial micro gas turbine generator system, modeling strategy of static and dynamic characteristics of the system based on nonlinear model is proposed. This model is constructed based on the combination of measured data and correction factors and does not rely on compressor and turbine map, which yields better prediction results with higher accuracy. To investigate the stability and robustness of the system, H infinity algorithm is employed as a system controller. The difference on controller performance designed based on the dynamical modeling of the target system and the measured data is discussed.