Swarm Intelligence Based Multi-phase OPF For Peak Power Loss Reduction In A Smart Grid

Recently there has been increasing interest in improving smart grids efficiency using computational intelligence. A key challenge in future smart grid is designing Optimal Power Flow tool to solve important planning problems including optimal DG capacities. Although, a number of OPF tools exists for balanced networks there is a lack of research for unbalanced multi-phase distribution networks. In this paper, a new OPF technique has been proposed for the DG capacity planning of a smart grid. During the formulation of the proposed algorithm, multi-phase power distribution system is considered which has unbalanced loadings, voltage control and reactive power compensation devices. The proposed algorithm is built upon a co-simulation framework that optimizes the objective by adapting a constriction factor Particle Swarm optimization. The proposed multi-phase OPF technique is validated using IEEE 8500-node benchmark distribution system.Comment: IEEE PES GM 2014, Washington DC, US

Enhanced Estimation of Autoregressive Wind Power Prediction Model Using Constriction Factor Particle Swarm Optimization

Accurate forecasting is important for cost-effective and efficient monitoring and control of the renewable energy based power generation. Wind based power is one of the most difficult energy to predict accurately, due to the widely varying and unpredictable nature of wind energy. Although Autoregressive (AR) techniques have been widely used to create wind power models, they have shown limited accuracy in forecasting, as well as difficulty in determining the correct parameters for an optimized AR model. In this paper, Constriction Factor Particle Swarm Optimization (CF-PSO) is employed to optimally determine the parameters of an Autoregressive (AR) model for accurate prediction of the wind power output behaviour. Appropriate lag order of the proposed model is selected based on Akaike information criterion. The performance of the proposed PSO based AR model is compared with four well-established approaches; Forward-backward approach, Geometric lattice approach, Least-squares approach and Yule-Walker approach, that are widely used for error minimization of the AR model. To validate the proposed approach, real-life wind power data of \textit{Capital Wind Farm} was obtained from Australian Energy Market Operator. Experimental evaluation based on a number of different datasets demonstrate that the performance of the AR model is significantly improved compared with benchmark methods.Comment: The 9th IEEE Conference on Industrial Electronics and Applications (ICIEA) 201

Modeling and performance evaluation of stealthy false data injection attacks on smart grid in the presence of corrupted measurements

The false data injection (FDI) attack cannot be detected by the traditional anomaly detection techniques used in the energy system state estimators. In this paper, we demonstrate how FDI attacks can be constructed blindly, i.e., without system knowledge, including topological connectivity and line reactance information. Our analysis reveals that existing FDI attacks become detectable (consequently unsuccessful) by the state estimator if the data contains grossly corrupted measurements such as device malfunction and communication errors. The proposed sparse optimization based stealthy attacks construction strategy overcomes this limitation by separating the gross errors from the measurement matrix. Extensive theoretical modeling and experimental evaluation show that the proposed technique performs more stealthily (has less relative error) and efficiently (fast enough to maintain time requirement) compared to other methods on IEEE benchmark test systems.Comment: Keywords: Smart grid, False data injection, Blind attack, Principal component analysis (PCA), Journal of Computer and System Sciences, Elsevier, 201

A Collaborative Project Management and Tracking System for UUM Based on Multi Agent Interface

This project aims to build, implements, and evaluate a collaborative project management and tracking system for UUM. A multi agent interface will be used in term of facilitating and improving the data representation of student's projects that assigned for a certain lecturers. Providing a collaborative application for managing and classifying data contents are mostly an important and in particular the UUM Applied Science Division requires managing and tracking student project in more flexible and interactive way. This project will apply a modified Object-Oriented approach for software development to model and implement the propose system. The system will be tested and evaluated in term of usefulness

Academic Engagement and its Relationship with Academic Self-Handicapping In light of Some Variables

هدفت هذه الدراسة إلى التعرف على العلاقة بين الاندماج الأكاديمي والإعاقة الذاتية الأكاديمية في ضوء بعض المتغيرات. ولتحقيق أهداف الدراسة تم اختيار عينة مكونة من (410) طلاب وطالبات من الكلية القاسمي في باقة الغربية باستخدام طريقة العينة المتاحة، وتم تطبيق مقياس الإعاقة الذاتية الأكاديمية ومقياس الاندماج الأكاديمي لهم.  وأظهرت النتائج أن مستوى الاندماج الأكاديمي كان متوسطاً.  كما أشارت النتائج إلى عدم وجود فروق ذات دلالة إحصائية في الاندماج الأكاديمي حسب الجنس والتخصص، بينما أظهرت النتائج وجود علاقة ارتباطية سلبية ذات دلالة إحصائية بين الإعاقة الذاتية الأكاديمية الاندماج الأكاديمي.The aim of this study was to explore the relationship between academic engagement and academic self- handicapping in light of some variables. To achieve the objectives of the study, a sample of (410) male and female students from Al-Qasemi College in Baqa Al-Gharbiya was selected using the available sampling method, and the Academic Self-Handicapping Scale and the Academic Engagement Scale were applied to them. The results showed that the level of academic engagement was middle. Furthermore, the results indicated that there were no statistically significant differences in academic engagement based on gender and specialization. The results also showed a statistically significant negative correlation between academic self- handicapping and academic engagement

Kinerja Dinas Pengendalian Penduduk Dan Keluarga Berencana Di Kabupaten Bone

The aim of this study was to determine the Performance of the Population and Family Planning Control Office in Bone Regency. This study used qualitative with descriptive research type. The number of informants in this study was 5 people. Data collection techniques used document review, observation and interviews. Then data  interview results were analyzed descriptively and qualitatively. The results of this study  showed that the Performance of the Population and Family Planning Control Office in Bone Regency had not  run optimally in carrying out its programs in the community due to the P2KB's could not  reach certain areas by informer , such as lonely village and the presence of programs did not run well like the PUP (Marriage Age Maturity) program. The inhibiting factor were some areas that could not be reached aside from that,  workers did not yet maximally carry out their duties and the community itself . Also many families did not understand and knew the programs implemented by the P2KB

Peran Badan Pertanahan Nasional Dalam Mengoptimalisasi Penyelesaian Konflik Lahan Desa Maroangin Kecamatan Maiwa Kabupaten Enrekang

This study purposed to find out how the position and the National Land Agency of Enrekang Regency work together with the local government of Enrekang Regency in optimizing conflict resolution. This study used qualitative methods carried out by collecting data through library research, field research in the form of observations, in-depth interviews and document research. The results of this study showed  that the role of the Enrekang Regency National Land Agency had been proceeding, it could be seen from the regulator's point of view actually arranging to find out the clarity of the conflict that occurred between PT. PN XIV and the community of Maroangin Village, Maiwa sub-district, aspects of the dynamics of the government both sub-districts and village mobilized participation to maintain the dynamics of regional conflict if the meeting did not get a meeting point. This was a step taken by the government, the facilitator aspect facilitated the government from the sub-district to get and discuss the problems together that were the basis of the conflict. and as an actor so that this problem had not been resolved until now but this land conflict was lingering until now.                                                                                 

Data-Driven Stealthy Injection Attacks on Smart Grid

Smart grid cyber-security has come to the forefront of national security priorities due to emergence of new cyber threats such as the False Data Injection (FDI) attack. Using FDI, an attacker can intelligently modify smart grid measurement data to produce wrong system states which can directly affect the safe operation of the physical grid. The goal of this thesis is to investigate key research problems leading to the discovery of significant vulnerabilities and their impact on smart grid operation. The first problem investigates how a stealthy FDI attack can be constructed without the knowledge of system parameters, e.g., line reactance, bus and line connectivity. We show how an attacker can successfully carry out an FDI attack by analysing subspace information of the measurement data without requiring the system topological knowledge. In addition, we make a critical observation that existing subspace based attacks would fail in the presence of gross errors and missing values in the observed data. Next, we show how an attacker can circumvent this problem by using a sparse matrix separation technique. Extensive evaluation on several benchmark systems demonstrates the effectiveness of this approach. The second problem addresses the scenario when an attacker may eavesdrop but only has access to a limited number of measurement devices to inject false data. We show how an attack can be constructed by first estimating the hidden system topology from measurement data only and then use it to identify a set of critical sensors for data injection. Extensive experiments using graph-theoretic and eigenvalue analyses demonstrate that the estimated power grid structure is very close to the original grid topology, and a stealthy FDI attack can be carried out using only a small fraction of all available sensors. The third problem investigates a new type of stealthy Load Redistribution (LR) attack using FDI which can deliberately cause changes in the Locational Marginal Price (LMP) of smart grid nodes. To construct the LR-FDI attack, the Shift factor is estimated from measurement and LMP data. Finally, the impact of the attacks on the state estimation and the nodal energy prices is thoroughly investigated