scholarly journals Generator Assessment of Hydro Power Station Adequacy after Reconstruction from Classical to HIS SF6 Substation

2017 ◽  
Vol 7 (2) ◽  
pp. 729
Author(s):  
Srete Nikolovski ◽  
Goran Slipac ◽  
Emir Alibašić
Keyword(s):  
State Space Model ◽  
Annual Reports ◽  
Power Station ◽  
Hydro Power ◽  
Space Model ◽  
System Operator ◽  
Adequacy Assessment ◽  
High Level ◽  
Maintenance Process ◽  
Reliability And Availability

<p>Reliability analysis of substations and generator assessment of power plant stations are very important elements in a design and maintenance process. This paper presents a generator adequacy assessment of a classical “H” scheme for an open conventional substation, which is often used, and a new HIS - High Integrated Switchgear with SF6 gas isolation. Generator adequacy indices of both types of classical and HIS switchgear were compared and the results showed a high level of reliability and availability of the HIS presented substation. The input data were the annual reports of Croatian TSO-Transmission System Operator (HOPS) and statistics of operation events of Croatian National Electricity (HEP Inc.). For the HIS substation, the input reliability data were used from relevant international literature since only few of HIS substations are installed in Croatia. The generator is modelled with a three-state Markov state space model and Monte Carlo simulations were used for the generator assessment analysis. Adequacy indices LOLP and EDNS were obtained using DIgSILENT software.</p>

The profitability of herding: evidence from Taiwan

2018 ◽  
Vol 44 (7) ◽  
pp. 919-934 ◽  
Author(s):  
Chun-Da Chen ◽  
Riza Demirer
Keyword(s):  
Design Methodology ◽  
State Space Model ◽  
Investment Strategy ◽  
Investment Strategies ◽  
Past Performance ◽  
Absolute Deviation ◽  
Cross Sectional ◽  
Content Type ◽  
Space Model ◽  
High Level

Purpose The purpose of this paper is to show that the level of herding in an industry can be the basis for a profitable investment strategy. Design/methodology/approach The authors apply three different herding measures in the paper, including cross-sectional standard deviation, cross-sectional absolute deviation and non-linear model – state–space model. Findings The authors find that industries that experience a high level of herding yield higher subsequent returns regardless of their past performance. Consequently, the authors show that a herding-based investment strategy generates significant profits, even after adjusting for risk. The findings also show that the herding effect when combined with past performance as part of a conditional investment strategy yields significant profits regardless of the formation and holding periods. The findings suggest that the level of herding could serve as a systematic driver of returns and could be exploited for profitable investment strategies. Originality/value To the best of authors’ knowledge, this is the first study in the literature to show that herding by itself can serve as a determinant of returns regardless of past performance.

scholarly journals A State Space Model of a Visuomotor Rotation Experiment

2017 ◽  
Author(s):  
Mireille E. Broucke
Keyword(s):  
Motor Control ◽  
State Space ◽  
Linear Time ◽  
State Space Model ◽  
Visuomotor Rotation ◽  
Human Motor Control ◽  
Space Model ◽  
Linear Time Invariant ◽  
Human Motor ◽  
High Level

We present a new linear time-invariant (LTI) state space model to explain adaptation in human motor control. We focus on a visuomotor rotation experiment in which a human subject must rapidly move a cursor on a horizontal screen through a target disk. The hand itself is occluded from view, while the cursor is rotated relative to the hand angle by an amount of r degrees. Our model is based on the application of well-known techniques from control theory, in particular regulator theory. The model is simple, yet it reveals a plausible architecture for the high level computations underlying human motor control, including a representation of the internal model. It is a two state LTI model, where each state has a physical interpretation

Multivariable modeling and control of an activated sludge process

1998 ◽  
Vol 37 (12) ◽  
pp. 149-156 ◽  
Author(s):  
Carl-Fredrik Lindberg
Keyword(s):  
Activated Sludge ◽  
Nitrate Concentration ◽  
State Space Model ◽  
Activated Sludge Process ◽  
Invariant State ◽  
Linear Quadratic ◽  
Modeling And Control ◽  
Space Model ◽  
And Control ◽  
Time Invariant

This paper contains two contributions. First it is shown, in a simulation study using the IAWQ model, that a linear multivariable time-invariant state-space model can be used to predict the ammonium and nitrate concentration in the last aerated zone in a pre-denitrifying activated sludge process. Secondly, using the estimated linear model, a multivariable linear quadratic (LQ) controller is designed and used to control the ammonium and nitrate concentration.

Development of L1-norm sliding mode observer for sensor fault diagnosis of an industrial gas turbine

2021 ◽  
pp. 095965182199617
Author(s):  
Mahyar Akbari ◽  
Abdol Majid Khoshnood ◽  
Saied Irani
Keyword(s):  
Fault Detection ◽  
State Space ◽  
Gas Turbine ◽  
Sliding Mode ◽  
State Space Model ◽  
Sensor Fault ◽  
Space Model ◽  
Decision Logic ◽  
Sensor Fault Detection ◽  
Industrial Gas Turbine

In this article, a novel approach for model-based sensor fault detection and estimation of gas turbine is presented. The proposed method includes driving a state-space model of gas turbine, designing a novel L1-norm Lyapunov-based observer, and a decision logic which is based on bank of observers. The novel observer is designed using multiple Lyapunov functions based on L1-norm, reducing the estimation noise while increasing the accuracy. The L1-norm observer is similar to sliding mode observer in switching time. The proposed observer also acts as a low-pass filter, subsequently reducing estimation chattering. Since a bank of observers is required in model-based sensor fault detection, a bank of L1-norm observers is designed in this article. Corresponding to the use of the bank of observers, a two-step fault detection decision logic is developed. Furthermore, the proposed state-space model is a hybrid data-driven model which is divided into two models for steady-state and transient conditions, according to the nature of the gas turbine. The model is developed by applying a subspace algorithm to the real field data of SGT-600 (an industrial gas turbine). The proposed model was validated by applying to two other similar gas turbines with different ambient and operational conditions. The results of the proposed approach implementation demonstrate precise gas turbine sensor fault detection and estimation.

Modeling of CCLP in koryo extract production

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Ji Chol ◽  
Ri Jun Il
Keyword(s):  
Process Control ◽  
Medical Care ◽  
State Space ◽  
State Space Model ◽  
The State ◽  
Space Model ◽  
Effective Components ◽  
Counter Current

Abstract The modeling of counter-current leaching plant (CCLP) in Koryo Extract Production is presented in this paper. Koryo medicine is a natural physic to be used for a diet and the medical care. The counter-current leaching method is mainly used for producing Koryo medicine. The purpose of the modeling in the previous works is to indicate the concentration distributions, and not to describe the model for the process control. In literature, there are no nearly the papers for modeling CCLP and especially not the presence of papers that have described the issue for extracting the effective components from the Koryo medicinal materials. First, this paper presents that CCLP can be shown like the equivalent process consisting of two tanks, where there is a shaking apparatus, respectively. It allows leachate to flow between two tanks. Then, this paper presents the principle model for CCLP and the state space model on based it. The accuracy of the model has been verified from experiments made at CCLP in the Koryo Extract Production at the Gang Gyi Koryo Manufacture Factory.

scholarly journals An Adaptive Model Predictive Voltage Control for LC-Filtered Voltage Source Inverters

2021 ◽  
Vol 11 (2) ◽  
pp. 704
Author(s):  
Hosein Gholami-Khesht ◽  
Pooya Davari ◽  
Frede Blaabjerg
Keyword(s):  
Control System ◽  
System Performance ◽  
State Space Model ◽  
Adaptive Observer ◽  
Voltage Source ◽  
Adaptive Model ◽  
Space Model ◽  
System Uncertainties ◽  
Augmented State ◽  
Load Conditions

The three-phase inductor and capacitor filter (LC)-filtered voltage source inverter (VSI) is subjected to uncertain and time-variant parameters and disturbances, e.g., due to aging, thermal effects, and load changes. These uncertainties and disturbances have a considerable impact on the performance of a VSI’s control system. It can degrade system performance or even cause system instability. Therefore, considering the effects of all system uncertainties and disturbances in the control system design is necessary. In this respect and to tackle this issue, this paper proposes an adaptive model predictive control (MPC), which consists of three main parts: an MPC, an augmented state-space model, and an adaptive observer. The augmented state-space model considers all system uncertainties and disturbances and lumps them into two disturbance inputs. The proposed adaptive observer determines the lumped disturbance functions, enabling the control system to keep the nominal system performance under different load conditions and parameters uncertainty. Moreover, it provides load-current-sensorless operation of MPC, which reduces the size and cost, and simultaneously improves the system reliability. Finally, MPC selects the proper converter voltage vector that minimizes the tracking errors based on the augmented model and outputs of the adaptive observer. Simulations and experiments on a 5 kW VSI examine the performance of the proposed adaptive MPC under different load conditions and parameter uncertainties and compare them with the conventional MPC.

Sign in / Sign up

Export Citation Format

Share Document