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

Data Health Assurance in Social and Behavioral Sciences Research

This illustrative study reincarnates the philosophical assumption of Methodology for science among other assumptions like Epistemology and Ontology in the context of social and behavioral sciences. Based on literature review the study divided the overlapping and perplexing Gaussian Linear Regression Model (GLRM) assumptions into two comprehensive groups. The study modeled straightforward diagnostics for GLRM assumptions violations by using the data collected from 150 postgraduate university students. Finally, the study provides the remedial directions to address possible problems created by GLRM assumptions violations

Environmental & Financial Benefits of 360 kW Photo Voltaic Solar System (On-Grid) in University of Wah

In the 21st century, the utilization and application of renewable energy resources are the need of the hour. Currently, in Pakistan, the cost of electricity per unit is very high and it has a huge effect on financial matters. In this study, we have analyzed the 360 kW Photovoltaic (PV) Solar system (On-Grid) installed at the University of Wah, its effects on the financial aspects, and environment change before and after its installation and operation. There are many types of renewable energy resources but not all of them are environmentally friendly. The University of Wah opted for the PV Solar system because it is environmentally friendly with no carbon emissions and requires very less maintenance. In this paper, we have also discussed, how this system benefits the local community and benefits the environment. All the facts and statistics about the 360 kW PV Solar System (On-Grid) are shared in detail.Keyword: Photovoltaic solar panels, Electricity Demand, Renewable energy, Environmentally friendly, Climate chang

Caracterización metódica de aceite de salvado de arroz (Oryza sativa) de Pakistán

The hexane-extracted oil content of four varieties of rice (Oryza sativa) viz. Super Kernel, 386, 385 and Basmati, bran was ranged 14.70-19.10 %. Other physical and chemical parameters of the extracted oils were as follow: Iodine value 112.40, 109.80, 105.1 and 103.70; refractive index ( 40 °C ) 1.4650, 1.4680, 1.4657 and 1.4660; density ( 40 °C ) 0.919, 0.913, 0.909 and 0.911; saponification value 183, 177, 186 and 190; unsaponifiable matter 6.15, 5.60, 4.98 and 5.40 % respectively. Tocopherols ( α, γ and δ) in the oils were: 284.00, 175.12, 180.42, 300.06; 83.40, 98.70, 120.70, 90.60; 75.16, 57.20, 39.32, 83.00 mg/kg respectively. The contents of tocotrienols ( α, γ and δ) in the oils were: 120.30, 106.00, 95.20, 135.74; 196.00, 125.00, 210.0, 276.41; 72.50, 20.00, 39.30, 64.00 mg/kg respectively. The amount of γ - Oryzanol in the investigated oils was ranged 415.12-802.05 The induction periods (Rancimat, 20 L/h, 120 °C ) of the crude oils were 6.81, 5.99, 6.39 and 7.40 h respectively. The major sterol fractions of the oils consisted of campesterol ranged (10.10-19.20%), stigmasterol (14.00-19.28 %), b -sitosterol (49.30-58.20 %), and D5 ,avenasterol (8.14-13.05 %). The investigated varieties ( Super Kernel, 386, 385 and Basmati) of rice bran oil were found to contain high levels of oleic acid 42.67, 38.59, 40.68 and 36.78 % followed by linoleic and palmitic acids 31.58, 33.80, 28.70, 30.51 and 17.00, 14.88, 19.63, 20.00 % respectively. The contents of myristic, stearic and arachidic acids was 1.50, 2.02, 4.28, 1.00; 2.64, 2.87, 4.02, 7.48; and 1.28, 3.00, 1.00, 1.00 % respectively. A number of parameters of the investigated rice bran oils indigenous to Pakistan were comparable to those of typical rice bran and some other vegetable oils, reported in the literature. The results of the present analysis as compared with those of different vegetable oils demonstrated rice bran to be a potential oil source and thus could be useful for the establishment of a globalized database of this valuable crop.El contenido de aceite, extraído con hexano, del salvado de cuatro variedades de arroz (Oryza sativa) viz. Super Kernel, 386, 385 y Basmati, varió entre el 14.70 y el 19.10 %. Otros parámetros físicos y químicos de los aceites extraídos fueron respectivamente: Indice de yodo: 112.40, 109.80, 105.1 y 103.70; índice de refracción ( 40 °C ): 1.4650, 1.4680, 1.4657 y 1.4660; densidad ( 40 °C ) 0.919, 0.913, 0.909 y 0.911; índice de saponificación: 183, 177, 186 y 190; insaponificable: 6.15, 5.60, 4.98 y el 5.40 %. Los tocoferoles ( α, γ, δ) en los aceites fueron, respectivamente: 284.00, 175.12, 180.42, 300.06; 83.40, 98.70, 120.70, 90.60; 75.16, 57.20, 39.32 y 83.00 mg/kg. El contenido de tocotrienoles ( α, γ, δ) en los aceites fue: 120.30, 106.00, 95.20, 135.74; 196.00, 125.00, 210.0, 276.41; 72.50, 20.00, 39.30 y 64.00 mg/kg, respectivamente. En los aceites estudiados se encontró una concentración de γ -oryzanol que varió entre 415.12 y 802.05 µg/g . Los periodos de inducción (Rancimat, 20 L/h, 120 °C ) de los aceites crudos fueron 6.81, 5.99, 6.39 y 7.40 h, respectivamente. Las fracciones principales de esteroles en los aceites se componían de: campesterol (10.10-19.20 %), stigmasterol (14.00-19.28 %), b -sitosterol (49.30-58.20 %) y Δ5 ,avenasterol (8.14-13.05 %). Las variedades investigadas ( Super Kernel, 386, 385 and Basmati) de aceite de salvado de arroz contenían elevados niveles de acido oleico 42.67, 38.59, 40.68 y 36.78 % seguido por los ácidos linoleico y palmítico 31.58, 33.80, 28.70, 30.51; 17.00, 14.88, 19.63 y 20.00 %, respectivamente. Los contenidos en ácidos mirístico, esteárico y araquídico fueron 1.50, 2.02, 4.28, 1.00; 2.64, 2.87, 4.02, 7.48; 1.28, 3.00, 1.00 y 1.00 % respectivamente. Los valores encontrados en los parámetros de los salvados de arroz investigados de procedencia Paquistaní son parecidos a los encontrados en la literatura de otros salvados de arroz y de aceites extraídos de verduras. Los resultados del presente análisis, al igual que los similares obtenidos de aceites de diferentes verduras, han demostrado que el salvado de arroz podría ser una fuente potencial de aceite y también podrían ser útiles para el establecimiento de una base de datos globalizada de esta valiosa cosecha