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weibull probability distribution function-Based Matched Filter Approach for Retinal Blood Vessels Segmentation 1st

1st International Conference on Computational Intelligence (ICCI)

作者： Singh, Nagendra Pratap Srivastava, Rajeev Indian Inst Technol BHU Dept CSE Varanasi 221005 Uttar Pradesh India

ISBN: (纸本)9789811025259;9789811025242

Retinal blood vessels contain an important information that is useful for computer-aided diagnosis of various retinal pathologies such as hypertension, diabetes, glaucoma, etc. Therefore, a retinal blood vessel segmentation is a prominent task. In this paper, a novel weibull probability distribution function-based matched filter approach is introduced to improve the performance of retinal blood vessel segmentation with respect to prominent matched filter approaches and other matched filter-based approaches existing in literature. Moreover, to enhance the quality of input retinal images in pre-processing step, the concept of principal component analysis (PCA)-based gray scale conversion and contrast-limited adaptive histogram equalization (CLAHE) are used. To design a proposed matched filter, the appropriate value of parameters are selected on the basis of an exhaustive experimental analysis. The proposed approach has been tested on 20 retinal images of test set taken from the DRIVE database and confirms that the proposed approach achieved better performance with respect to other prominent matched filter-based approaches.

关键词： weibull probability distribution function Matched filter Retinal blood vessels segmentation Entropy-based optimal thresholding

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Probabilistic Optimal Power Flow with weibull probability distribution function of System Loading Using Percentiles Estimation

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2013年第3期41卷 252-270页

作者： Chayakulkheeree, Keerati Sripatum Univ Sch Engn Dept Elect Engn Bangkok 10900 Thailand

This article proposes a probabilistic optimal power flow for hour-ahead scheduling in a power system considering the statistical distribution function of system loading using the weibull probability distribution function. In the proposed probabilistic optimal power flow, the deterministic optimal power flow problem is solved as the sub-problem in probabilistic optimal power flow and decomposed into a total operating cost minimization sub-objective, which is solved by successive quadratic programming and the real power loss minimization sub-objective, which is solved by successive linear programming. In the proposed method, the weibull probability distribution function parameters of the optimal power flow variables are estimated from percentile values and evaluated by Akaike information criteria. The proposed probabilistic optimal power flow algorithm is tested on the IEEE 30-bus and IEEE 300-bus systems and compared to Monte Carlo simulation. The investigations show that the proposed probabilistic optimal power flow can successfully estimate the probability distribution function parameters of optimal power flow output variables considering the weibull probability distribution function of system load with simple and minimal computational procedure. With the proposed estimation of the weibull parameters method, the number of optimal power flow runs can be reduced substantially in the probabilistic optimal power flow process.

关键词： probabilistic optimal power flow percentile Monte Carlo simulation weibull probability distribution function

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Fracture Failure Evaluation of Foam WMA Mixes Containing RAP by Applying weibull probability distribution function

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INTERNATIONAL JOURNAL OF PAVEMENT RESEARCH AND TECHNOLOGY 2022年第6期15卷 1277-1296页

作者： Kavussi, Amir Motevalizadeh, Seyed Mohsen Tarbiat Modares Univ Fac Civil & Environm Engn Tehran Iran

Will reclaimed asphalt pavement (RAP) be used more in pavements in the future? This is why researchers tended toward investigating high-RAP mixes. Hence, evaluating the fracture resistance of warm mix asphalt (WMA) mixes containing various RAP contents was chosen as the aim of this research. The first step was to determine the optimum binder contents and the required mixing temperatures. The optimized mixes were compacted and were tested under fracture in semi-circular bending (SCB) test. The SCB specimens were tested in fracture opening mode at temperatures varying from 25 to - 20 & DEG;C and after exposure to freeze-thaw cycles. The role of RAP materials in WMA mixes was investigated, assessing crack evolution criteria at different condition regimes. Analytical indices and the R-curve method were employed in investigating the experimental results. Moreover, the possibility of cracking failure was determined through the weibull probability distribution function. The desirability value that was defined to represent the degree of agreement between the criteria of the optimized mixes and predefined goals, showed that mixes with 30% RAP were the most desirable. As the RAP content increased lower desirability values were recorded. R-curves showed that the foam WMA mixes containing 30% of RAP were the most resistant mixes against fracture failure. At the same time, weibull analysis showed that greater RAP contents resulted in increased cracking in WMA mixes, while the inclusion of 30% RAP resulted in the most desirable mixes.

关键词： Semi-circular bending test Water-based foamed bitumen Reclaimed asphalt pavement Response surface method weibull probability distribution function

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Techno-economic integrated multi-criteria analysis of wind to hydrogen systems: A comprehensive parametric study

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2024年 88卷 477-487页

作者： Dehshiri, Seyyed Shahabaddin Hosseini Dehshiri, Seyyed Jalaladdin Hosseini Mostafaeipour, Ali Le, Ttu Sharif Univ Technol Dept Mech Engn Tehran Iran Allameh Tabatabai Univ Fac Management & Accounting Dept Ind Management Tehran Iran Duy Tan Univ Inst Res & Dev Da Nang Vietnam Duy Tan Univ Sch Engn & Technol Da Nang Vietnam

While Iran has notable renewable energy potentials, the renewable energy sector of this country has remained underdeveloped, mostly because of easy access to cheap fossil fuels. This paper discusses and analyzed the possibility for hydrogen generation from wind resource in urban city which is suffered from air pollution and is located in northwestern Iran. Wind energy and power density estimations were performed using the 2-parameter weibull probability distribution function. These estimates were used to predict the power output, hydrogen output, economic viability, and environmental benefit of building a wind power-hydrogen production unit in one of several candidate sites in the studied area. Ultimately, the most suitable site for such a project was determined using the SWARA/WASPAS method. After investigating 16 different conventional wind turbines, the best one in terms of achievable power and hydrogen output and economic feasibility was determined. The results showed that Gamesa G80 with a capacity of 2 GW was the best wind turbine for the urban area. Gardaneh-Almas with a wind power density of 1252W/m(2) was identified as the best site for power generation in the region. Potential wind-powered hydrogen output at this site was estimated to 97 ton/yr. LCOE and LCOH for this site were estimated to 0.047 $/kWh and 4.6 $/kg-H-2, respectively.

关键词： Renewable energy Wind energy weibull probability distribution function Hydrogen production Multi-criteria decision-making

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Optimal power flow solution of power system incorporating stochastic wind power using Gbest guided artificial bee colony algorithm

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2015年 64卷 562-578页

作者： Roy, Ranjit Jadhav, H. T. SV Natl Inst Technol Dept Elect Engn Surat India

This paper focuses primarily on implementation of optimal power flow (OPF) problem considering wind power. The stochastic nature of wind speed is modeled using two parameter weibull probability density function. The economic aspect is examined in view of the system wide social cost, which includes additional costs like expected penalty cost and expected reserves cost to account for wind power generation imbalance. The optimization problem is solved using Gbest guided artificial bee colony optimization algorithm (GABC) and tested on IEEE 30 bus system. The simulation results obtained using proposed method are compared with other methods available in the literature for a case of conventional OPF as well as OPF incorporating stochastic wind. Subsequently an extensive simulation study is conducted to investigate the effect of wind power and different cost components on optimal dispatch and emission. Numerical simulations indicate that the operation cost of system and emission depends upon the transmission system bottlenecks and the intermittency of wind power generation. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Gbest guided artificial bee colony Optimal power flow weibull probability distribution function Wind power

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Comparative Analysis of Economic Viability with Distributed Energy Resources on Unit Commitment

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2016年第14期44卷 1588-1607页

作者： Govardhan, Manisha Roy, Ranjit Sardar Vallabhbhai Natl Inst Technol Dept Elect Engn Surat 395007 Gujarat India

Classic unit commitment is the important and challenging task of allocating generating units subject to basic constraints over a scheduled time horizon to obtain the least generation cost. Penetration of distributed energy resources in modern power systems makes generation planning more complex. This article presents the individual and combined effect of three distributed energy resources, namely wind power generator as a renewable energy source, plug-in electric vehicles, and emergency demand response program on unit commitment. The inconsistent nature of wind speed and wind power is characterized by the weibull probability distribution function considering overestimation and underestimation costs of stochastic wind power. The comprehensive comparative analysis of the economic viability on unit commitment is carried out to minimize the total cost of the entire system. To obtain the optimum solution, a modified teaching-learning-based optimization algorithm is used. The IEEE standard ten-unit test system is used for this study. To validate the efficacy of the modified teaching-learning-based optimization algorithm, a 26-unit reliability test system is also considered. It is found that the collective effect of wind power generator, plug-in electric vehicles, and emergency demand response program on unit commitment provides significant reduction in the total cost.

关键词： distributed energy resources emergency demand response program modified teaching-learning-based optimization algorithm plug-in electric vehicles teaching-learning based optimization algorithm unit commitment problem weibull probability distribution function

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Gbest guided artificial bee colony algorithm for environmental/economic dispatch considering wind power

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EXPERT SYSTEMS WITH APPLICATIONS 2013年第16期40卷 6385-6399页

作者： Jadhav, H. T. Roy, Ranjit SV Natl Inst Technol Dept Elect Engn Surat India

The current energy consumption in most of the countries is weighing heavily on fossil fuels, which account for about 70-90% of total energy used. The ecological concerns about air pollution and global warming are encouraging wider use of clean renewable technologies such as wind and solar energy. In this paper, Gbest guided artificial bee colony algorithm (GABC) is applied to optimize the emission and overall cost of operation of wind-thermal power system. The random nature of wind power is modeled using weibull probability distribution function (PDF). Moreover, the uncertainty in wind power is considered in the cost model by including the power imbalance terms such as overestimation and underestimation costs of available wind power. To validate the effectiveness of proposed method, it is first applied to three standard test systems considering different technical constraints such as valve loading effect, prohibited zones, ramp rate limits, etc. In second part, the effect of wind power generation on dispatch cost and emission is analyzed for IEEE-30 bus test system. A comparative analysis with other similar optimization techniques reveals that the proposed technique has better solution accuracy and convergence results. (c) 2013 Elsevier Ltd. All rights reserved.

关键词： Carbon tax Gbest guided artificial bee colony Multi-objective emission economic load dispatch weibull probability distribution function Wind power

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Economic emission dispatch for wind-fossil-fuel-based power system using chemical reaction optimisation

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2015年第12期25卷 3248-3274页

作者： Roy, Provas Kumar Hazra, Sunanda Dr BC Roy Engn Coll Dept Elect Engn Durgapur W Bengal India

This paper presents a chemical reaction optimisation algorithm based on the chemical molecular reaction to optimise total cost in wind-fossil-fuel-based power systems, while all operating constraints are satisfied. With the continuing search for alternatives to conventional energy sources and global warming, it is necessary to include wind energy conversion system generators in the economic load dispatch problem. The random nature of wind power is modelled using weibull probability distribution function. Because of uncertainty in wind power, wind cost is generalised by including overestimation and underestimation cost of available wind power. The proposed approach is examined and tested on the standard Institute of Electrical and Electronics Engineers 30-bus test system having three conventional thermal generators, two gas generators, one oil generator and two wind turbines and a 40-unit test system having three wind turbines and 37 thermal generating units. The simulation results show that the proposed algorithm gives comparatively better operational cost compared with other optimisation techniques. Copyright (C) 2014 John Wiley & Sons, Ltd.

关键词： dispatch fuel cost emission cost weibull probability distribution function wind turbine fossil fuel chemical reaction optimisation

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Security Constrained Economic Dispatch Considering Wind Energy Conversion Systems

Security Constrained Economic Dispatch Considering Wind Ener...

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General Meeting of the IEEE-Power-and-Energy-Society (PES)

作者： Mishra, S. Mishra, Y. Vignesh, S. Indian Inst Technol Delhi Dept Elect Engn New Delhi 110016 India

ISBN: (纸本)9781457710018

The available wind power is stochastic and requires appropriate tools in the OPF model for economic and reliable power system operation. This paper exhibit the OPF formulation with factors involved in the intermittency of wind power. weibull distribution is adopted to find the stochastic wind speed and power distribution. The reserve requirement is evaluated based on the wind distribution and risk of under/over estimation of the wind power. In addition, the Wind Energy Conversion System (WECS) is represented by Doubly Fed Induction Generator (DFIG) based wind farms. The reactive power capability for DFIG based wind farm is also analyzed. The study is performed on IEEE-30 bus system with wind farm located at different buses and with different wind profiles. Also the reactive power capacity to be installed in the wind farm to maintain a satisfactory voltage profile under the various wind flow scenario is demonstrated.

关键词： Bacterial Foraging Algorithm (BFA) Doubly Fed Induction Generator (DFIG) Optimal Power Flow (OPF) weibull probability distribution function Wind energy

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Forward Clearing of Energy Market for Wind Incorporated Power System 8

Forward Clearing of Energy Market for Wind Incorporated Powe...

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8th IEEE International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)

作者： Sharma, Akanksha Jain, Sanjay K. Thapar Inst Engn & Technol Patiala Punjab India

ISBN: (纸本)9781728108377

In this paper the forward market clearing of wind integrated power system considering the randomness in wind power generation is presented. The intermittent nature of wind power is characterized by weibull probability density function (PDF). The aim is to minimize the cost of energy supplied by thermal and wind generators. The cost of energy also incorporates overestimation and underestimation cost of available wind power. Gravitational search algorithm (GSA) based scheduling is utilized for the market clearing purpose. The results have been obtained on IEEE 30-bus and IEEE 57-bus test systems to investigate the effectiveness of the presented algorithm for optimal scheduling.

关键词： gravitational search algorithm market clearing weibull probability distribution function wind energy

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