Nur Ashida Salim

Cascading Collapse Assessment Considering Hidden Failure

Hidden failure relay protection is the major cause of cascading failure in power system. Therefore, in this study, a hidden failure model has been developed to study the impact of certain parameter that could cause cascading collapse. The parameters that could lead to major blackout include system loading level, spinning reserve, hidden failure probability and other factors. As the overall load is the key factor that could affect the risk of cascading outages, this study will reveal the impact of it to the system. A test system of IEEE 24 bus RTS is used as a case study. The hidden failure model adopts here is the steady state analysis, which is caused by line tripping. The significant loads at which blackout risk sharply increases are identifiable for cascading collapse. This study can provide guidance for the utility on when and how to mitigate the cascading collapse from spreading to the entire power system. This study also can determine the critical loading in the risk of cascading failure.

Risk based Uncertainty (RibUt) Assessment of a Power System Using Bootstrap Technique

There are various approach used to prevent from the occurrence of power system blackout in order to ensure the sustainability and efficiency of energy supply. Generally, power system blackout can be mitigated by referring to the risk assessment of a power system. This paper presents the risk assessment of a power system performed by using the proposed bootstrap technique and the fuzzy set technique. The risk of the system is measured by using the expected energy not supplied (EENS) index as well as the probability of load curtailment (PLC) index. The application of bootstrap technique is important to assess the risk indices at every level of system uncertainty. The 24-bus IEEE Reliability Test System (RTS) and 2737-bus Polish system are used as a case study in the analysis of risk based EENS and PLC. Comparative studies have been made on the risk assessment determined by using the proposed bootstrap technique and the fuzzy set technique.

Case study of Short Term Load Forecasting for weekends

This paper presents the Short Term Load Forecasting (STLF) to predict the demand in the future. STLF is a method used to predict a day ahead, 24 hours load demand. Two factors were considered in this forecasting: time and also the temperature of the day. The main objective of this project is to analyze the profile or pattern of the forecasted load and also to predict the load demand during weekends. Artificial Neural Network (ANN) in MATLAB software was used in solving the forecasting problem. The percentage of average error was determined by using the Mean Absolute Percentage Error (MAPE).

Critical System Cascading Collapse Assessment for Determining the Sensitive Transmission Lines and Severity of Total Loading Conditions

This paper presents a computationally accurate technique used to determine the estimated average probability of a system cascading collapse considering the effect of hidden failure on a protection system. This includes an accurate calculation of the probability of hidden failure as it will give significant effect on the results of the estimated average probability of system cascading collapse. The estimated average probability of a system cascading collapse is then used to determine the severe loading condition contributing to a higher risk of a system cascading collapse. This information is important because it will assist the utility to determine the maximum level of increase in the system loading condition before the occurrence of critical power system cascading collapse. Furthermore, the initial tripping of sensitive transmission line contributing to a critical system cascading collapse can also be determined by using the proposed method. Based on the results obtained from this study, it was found that selecting the accurate probability of hidden failure is very important as it will affect the estimated average probability of a system cascading collapse. Comparative study has been done with other techniques to verify the effectiveness of the proposed method used in the determination of sensitive transmission lines.

Risk assessment of dynamic system cascading collapse for determining the sensitive transmission lines and severity of total loading conditions

This paper presents a computationally accurate technique used to determine the estimated average probability of a dynamic system cascading collapse considering the effect of hidden failure on a protection system. This requires an accurate calculation of the probability of hidden failure as it will give significant effect on the results of the estimated average probability of dynamic system cascading collapse. The estimated average probability of a dynamic system cascading collapse is then used to determine the severe loading condition contributing to a higher risk of a system cascading collapse. This information of risk assessment is important to the utility that will assist them to determine the maximum level of increase in the system loading condition before a critical dynamic system cascading collapse is incurred. Furthermore, initial tripping of sensitive transmission line contributing to a dynamic critical system cascading collapse can also be determined by using the proposed risk assessment. Based on the results obtained from this study, it was found that selecting the accurate probability of hidden failure is very important as it will affect the estimated average probability of a dynamic system cascading collapse used for determining the results of sensitive transmission lines and severity of total loading conditions.

An effective approach to determine the sensitive transmission lines due to the effect of hidden failure in a protection system

Protection system hidden failure was identified as one of the main causes of cascading failure. However, in the current practice of power system analysis, protection system is assumed to be perfect and the impact of hidden failures of a protection system is neglected. This paper proposes a systematically accurate technique to evaluate the impact of protection system hidden failures to the probability of system cascading outage. Further analysis is performed by analyzing the results of the probability of a system cascading outage which will then be used to identify the initial tripping of sensitive transmission lines that could contribute to calamitous cascading outage in the system. In accordance with the results that have been obtained, it is important to decide on the accurate value of the hidden failure probability as it will have an effect on the probability of a system cascading outage. This analysis is beneficial not only for the power system operation and planning, but also to the system operator in order to determine the exact locations to improve the protection system.

Improvisation on Standard Limit of the Critical Clearing Time Specified for the Protection Relays Using one Machine Infinite Bus Equivalent

This paper presents a computationally accurate technique used to determine the critical clearing time using the one machine infinite bus equivalent system based on the equal area criterion. The critical clearing time is the maximum time interval by which the fault must be cleared in order to preserve the system stability. The computation of critical clearing time involves an intrinsic mathematical formulation derived from the pre-fault, during fault and post-fault conditions. The value of critical clearing time becomes significantly less when transient instability is induced by a three phase fault occurred at the bus bar closest to the substation connected with a sensitive generator. By setting the protection relay with the obtained value of critical clearing time, it is adequate to sustain the transient stability even though fault happened at the other locations. During the occurrence of fault, a circuit breaker which is operating earlier than the smallest critical clearing time will not agitate to a transient instability. The IEEE Reliability Test System 1979 (RTS-79) is used to verify the robustness of the methodology in a determining the critical clearing time.

Placement of SVC and Transformer Tap Setting for Minimum Loss Using Evolutionary Programming

This research paper presents an application of Fast Voltage Stability Index (FVSI) power flow based technique and Evolutionary Programming (EP) technique to determine the placement and sizing of Static VAR Compensator (SVC) for installation at transmission system. SVC which is one of the Flexible AC Transmission System (FACTS) available in the market is used in this research for reducing the power losses in the system as well as monitoring the minimum voltage. The system will be stressed out by increasing the loadability of certain buses until it is near to its maximum loadability. The determination of the placement of Static VAR Compensator (SVC) was determined by using power flow based approach of Fast Voltage Stability Index (FVSI) to detect the weakest line which consequently will lead to the weakest bus. The Evolutionary Programming (EP) technique is used to look for the best sizing of Static VAR Compensator (SVC). The Evolutionary Programming (EP) technique and Fast Voltage Stability Index (FVSI) is tested with IEEE 14 bus test system to prove the effectiveness of the proposed technique. Further, the comparison between installation of SVC and transformer tap setting in order to identify which one is more effective in minimizing the power losses.

Optimal Charging Schedule Coordination of Electric Vehicles in Smart Grid

Received Dec 04, 2017 Revised Jan 11, 2018 Accepted Apr 15, 2018 Wireless Body Area Networks (WBANs) are fundamental technology in health care that permits the information of a patient’s essential body parameters to be gathered by the sensors. However, the safety and concealment defense of the gathered information is a key uncertain problem. A Hybrid Key Management (HKM) scheme [13] is worked based on Public Key Cryptography (PKC)-authentication scheme. This scheme uses a oneway hash function to construct a Merkle Tree. The PKC method increase the computational complexity and lacking scalability. Additionally, it increases expensive computation, communication costs and delay. To overcome this problem, Robust Security for Protected Health Information by ECC with signature Hash Function in WBAN (RSP) is proposed. The system employs hash-chain based key signature technique to achieve efficient, secure transmission from sensor to user in WBAN. Moreover, Elliptical Curve Cryptography algorithm is used to verifies the authenticate sensor. In addition, it describes the experimental results of the proposed system demonstrate the efficient data communication in a network.A Weblogs contains the history of User Navigation Pattern while user accessing the websites. The user navigation pattern can be analyzed based on the previous user navigation that is stored in weblog. The weblog comprises of various entries like IP address, status code and number of bytes transferred, categories and time stamp. The user interest can be classified based on categories and attributes and it is helpful in identifying user behavior. The aim of the research is to identifying the interested user behavior and not interested user behavior based on classification. The process of identifying user interest, it consists of Modified Span Algorithm and Personalization Algorithm based on the classification algorithm user prediction can be analyzed. The research work explores to analyze user prediction behavior based on user personalization that is captured from weblogs.Wireless Body Area Networks (WBANs) are fundamental technology in health care that permits the information of a patient’s essential body parameters to be gathered by the sensors. However, the safety and concealment defense of the gathered information is a key uncertain problem. A Hybrid Key Management (HKM) scheme [13] is worked based on Public Key Cryptography (PKC)-authentication scheme. This scheme uses a oneway hash function to construct a Merkle Tree. The PKC method increase the computational complexity and lacking scalability. Additionally, it increases expensive computation, communication costs and delay. To overcome this problem, Robust Security for Protected Health Information by ECC with signature Hash Function in WBAN (RSP) is proposed. The system employs hash-chain based key signature technique to achieve efficient, secure transmission from sensor to user in WBAN. Moreover, Elliptical Curve Cryptography algorithm is used to verifies the authenticate sensor. In addition, it describes the experimental results of the proposed system demonstrate the efficient data communication in a network.

Performance of Environmental and Energy Audit for Manufacturing Industrial Buildings.

Applied Computing Technology (ACT), Universiti Tun Hussein Onn Malaysia (UTHM), Parit Raja, Batu Pahat, 86400 Johor, Malaysia. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia (UTHM), Parit Raja, Batu Pahat, 86400 Johor, Malaysia. Department of Management Information Systems, College of Commerce and Business Administrations, Dhofar University, Salalah, Oman.