Marayati Marsadek

Risk based static security assessment in a practical interconnected power system

In security assessment of power systems, presently, the deterministic approach is the most widely used method. However, in the current competitive environment, the drawbacks become salient; hence security assessment based on the concept of risk is required. Risk assessment is an approach that quantitatively captures the factors that determine security level, namely likelihood and the severity of events. Risk index is used to quantify the degree of risk of the given operating condition. This paper presents risk based static security assessment on a practical interconnected power system at various loading condition using a risk index. The result captures the uncertainty in the occurrence of contingency and the variation of risk index as the load changes.

Bifurcation analysis based performance evaluation of power system incorporating FACTS controller

The major power system breakdowns are caused by problems relating to the system dynamic responses. The limiting factor in power system operation is the damping of oscillations. The damping torque provided by the FACTS device is proportional to the gain of the controller. A power system is highly nonlinear dynamical system, having always some influence on the controller performance. An inappropriate controller setting may cause interplay between controllers dispersed system wide, leading to evolution of nonlinear dynamic phenomena such as bifurcation. It is induced by variation in control gains and system parameters. For satisfactory system operation, appropriateness of each setting of the controller needs to be evaluated for a specific operating configuration. The in-depth evaluation of a controller setting leading to fine tuning of the controller gain is feasible through bifurcation analysis.

Formation of MoOx barrier layer under atmospheric based condition to control MoSe2 formation in CIGS thin film solar cell

ABSTRACT As part of the device fabrication process, selenization step is required to crystallise the CIGS absorber layer. However, during high temperature selenization process, excessive formation of MoSe2 can lead to delamination of the film and adverse effect on electrical properties of the solar cells. In this paper, a new method is proposed to form a Molybdenum Oxide (MoOx) barrier layer in between of the Mo back contact using plasma jet under atmospheric based conditions. The effect of MoOx compound (MoO2 and MoO3) towards the efficiency of the device is investigated. It has been proven that a thin layer of MoOx barrier layer is able to control the formation of MoSe2 effectively and provide a significant improvement in electrical properties of the devices. A power conversion efficiency of 5.24% with least efficiency variation across the champion device was achieved which demonstrates the importance of this methodology on small area devices.

Adaptive Controllers for Enhancement of Stand-Alone Hybrid System Performance

This paper describes the method to control a hybrid robot whose main task is to climb a pole to place an object on the top of the pole. The hybrid pole-climbing robot considered in this paper uses 2 Planetary PG36 DC-motors as actuators and an external rotary encoder sensor to provide a feedback on the change in robot orientation during the climbing movement. The orientation control of the pole-climbing robot using self-tuning method has been realized by identifying the transfer function of the actuator system under consideration, being followed with the calculation of control parameters using the self-tuning pole-placement method, and furthermore being implemented on the external rotary encoder sensor. Self-tuning pole-placement method has been explored to control the parameters q 0 , q 1 , q 2 , and p 1 of the controller. The experiments were done on a movement path in a form of a cylindrical pole. The first experiment was done based one the change in rotation angle of the rotary sensor with the angle values greater than 50˚ in the positive direction, whereas the second experiment was done with the angle values greater than -50˚ in the negative direction. The experiment results show that the control of the robot under consideration could maintain its original position at the time of angle change disturbance and that the robot could climb in a straight direction within the specified tolerance of orientation angle change.

Review on Substrate and Molybdenum Back Contact in CIGS Thin Film Solar Cell

Copper Indium Gallium Selenide- (CIGS-) based solar cells have become one of the most promising candidates among the thin film technologies for solar power generation. The current record efficiency of CIGS has reached 22.6% which is comparable to the crystalline silicon- (c-Si-) based solar cells. However, material properties and efficiency on small area devices are crucial aspects to be considered before manufacturing into large scale. The process for each layer of the CIGS solar cells, including the type of substrate used and deposition condition for the molybdenum back contact, will give a direct impact to the efficiency of the fabricated device. In this paper, brief introduction on the production, efficiency, etc. of a-Si, CdTe, and CIGS thin film solar cells and c-Si solar cells are first reviewed, followed by the recent progress of substrates. Different deposition techniques’ influence on the properties of molybdenum back contact for CIGS are discussed. Then, the formation and thickness influence factors of the interfacial MoSe2 layer are reviewed; its role in forming ohmic contact, possible detrimental effects, and characterization of the barrier layers are specified. Scale-up challenges/issues of CIGS module production are also presented to give an insight into commercializing CIGS solar cells.

Risk of Transient Stability Using Rotor Trajectory Index as Severity Function

This paper presents a new approach to determine the risk of transient stability. It describes the implementation of rotor trajectory index (RTI) to assess the severity of power systems when it is subjected to a three-phase fault. The (RTI) is proposed as an index used to represent severity of transient instability. Risk of transient stability for three-phase fault is calculated using a well-known risk formula. Risk of transient stability provides a quantitative measure to evaluate the potential loss of synchronism of a generator that takes into account the probability and consequences. RTI index is calculated based on the machines rotor angles obtained at each step of a time domain simulation. RTI is proposed as an index to show the severity of the three-phase fault towards transient stability since it allows a fast and accurate measurement of the degree of stability of the system facing a fault. The proposed technique is implemented on the IEEE 39-bus system.

Classification of risk of voltage collapse using risk matrix

Probabilistic method or risk assessment has been introduced to enhance deterministic approach in monitoring power system security. In general, risk assessment monitors power system security quantitatively by measuring the product of probability of disturbance to occur and the impact of such disturbance towards security violation. This research is performed to classify the risk of voltage collapse that would occur due to transmission line outage using risk matrix technique. The underlying principle of risk matrix method is to reflect the changes in risk components in the overall system classification assessment. To evaluate the effectiveness of this method, comparative study between risk matrix and conservative method is conducted. Based on the findings, it is revealed that risk matrix offered more comprehensive and reflective results as compared to conservative approach.

Voltage collapse risk index prediction for real time system's security monitoring

Risk based security assessment (RBSA) for power system security deals with the impact and probability of uncertainty to occur in the power system. In this study, the risk of voltage collapse is measured by considering the L-index as the impact of voltage collapse while Poisson probability density function is used to model the probability of transmission line outage. The prediction of voltage collapse risk index in real time requires precise, reliable and short processing time. To facilitate this analysis, Artificial Intelligent using Generalize Regression Neural Network (GRNN) technique is proposed where the spread value is determined using Cuckoo Search (CS) optimization method. To validate the effectiveness of the proposed method, the performance of GRNN with optimized spread value obtained using CS is compared with heuristic approach.

Feasibility study for grid-connected biomass and biogas

Renewable energy resources have gain popularity due to the attractive and competitive feed-in tariff. However, it is important to analyze the impact of grid connected renewable energy resources prior to the integration to the actual grid as they may lead to negative impact. Power system study is performed in order to assess the impact of grid connected renewable energy resources so that any issues can be properly managed. This paper described the power system study for actual power system with proposed grid connected biomass and biogas. Issue related to critical fault clearing time is managed by increasing the inertia of biomass and biogas.

Risk of Voltage Collapse Using Multi-Layer Feed-Forward Neural Network and Generalized Regression Neural Network

The computation of security risk index in identifying the system’s condition is one of the major concerns in power system analysis. Traditional method of this assessment is highly time consuming and infeasible for direct on-line implementation. Thus, this paper presents the application of Multi-Layer Feed Forward Network (MLFFN) to perform the prediction of voltage collapse risk index due to the line outage occurrence. The proposed ANN model consider load at the load buses as well as weather condition at the transmission lines as the input. In realizing the effectiveness of the proposed method, the results are compared with Generalized Regression Neural Network (GRNN) method. The results revealed that the MLFFN method shows a significant improvement over GRNN performance in terms of least error produced.