Assessing the proficiency of adaptive neuro-fuzzy system to estimate wind power density: Case study of Aligoodarz, Iran

The vast percentage of people of the world; particularly in the developing countries; are living mostly in the decentralized, rural and remote areas those are geographically secluded from the grid connection. Power distribution and continuous fuel transportation to produce the electrical energy for these areas pretenses a great challenge. Using renewable energy resources in off grid hybrid energy system might be a solution of this problem. Moreover, high cost of renewable energy systems has led to its slow adoption in many countries. Hence, it is vital to select an appropriate size of the system in order to reduce the cost and excess energy produced as well as to maximize the available resources. A hybrid energy system has been designed as well as simulated to support a small community considering an average load demand of 80 kWh/d with a peak load of 8.1 kW. The simulation and optimization of operations of the system have been done by HOMER software using the real time field data of solar radiation and average wind speed data of that area. The simulation ensures that the system is suitably feasible with respect to net present cost and CO2 emission reduction purpose. The result shows that NPC and CO2 emission can be reduced about 29.65% and 16 tons per year respectively compared with the conventional power plants. The NPC of the optimized system has been found about USD 160,626.00 having the per unit Cost of Energy about USD 0.431/kWh. The analyzed hybrid energy system might be applicable for other region of the world where the climate conditions are similar. © 2017 American Institute of Chemical Engineers Environ Prog, 37: 1424–1432, 2018

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“…Most cases the value of

α

is assumed tobe 0.143 and in this analysis the value of

α

was calculated by the method proposed by Justus . The probability distribution function (PDF) determines the probability of wind at a given velocity

V

and PDF is expressed by following expression . Cumulative distribution function (CDF) of wind speed

V

indicates the probability that the wind velocity is equal to or lower than

V

or within a given wind speed range and the CDF is expressed by following expression .…”

Section: Energymentioning

confidence: 99%

Performance investigation of an advanced hybrid renewable energy system in indonesia

Shezan

Al-Mamoon

Ping

2017

Env Prog and Sustain Energy

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“…The findings of this paper demonstrated that the ANFIS model can provide better performance compared to the regression of the net present value based on the coefficient of determination (R 2 ). Shamshirband et al [37] applied the ANFIS model to calculate and predict the monthly wind power density. The outcomes of this study showed that all of the values of wind power prediction were between the acceptable range of −10% to 10%.…”

Section: Sustainability and Fuzzy Neural Networkmentioning

confidence: 99%

Measuring Country Sustainability Performance Using Ensembles of Neuro-Fuzzy Technique

et al. 2018

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Global warming is one of the most important challenges nowadays. Sustainability practices and technologies have been proven to significantly reduce the amount of energy consumed and incur economic savings. Sustainability assessment tools and methods have been developed to support decision makers in evaluating the developments in sustainable technology. Several sustainability assessment tools and methods have been developed by fuzzy logic and neural network machine learning techniques. However, a combination of neural network and fuzzy logic, neuro-fuzzy, and the ensemble learning of this technique has been rarely explored when developing sustainability assessment methods. In addition, most of the methods developed in the literature solely rely on fuzzy logic. The main shortcoming of solely using the fuzzy logic rule-based technique is that it cannot automatically learn from the data. This problem of fuzzy logic has been solved by the use of neural networks in many real-world problems. The combination of these two techniques will take the advantages of both to precisely predict the output of a system. In addition, combining the outputs of several predictors can result in an improved accuracy in complex systems. This study accordingly aims to propose an accurate method for measuring countries' sustainability performance using a set of real-world data of the sustainability indicators. The adaptive neuro-fuzzy inference system (ANFIS) technique was used for discovering the fuzzy rules from data from 128 countries, and ensemble learning was used for measuring the countries' sustainability performance. The proposed method aims to provide the country rankings in term of sustainability. The results of this research show that the method has potential to be effectively implemented as a decision-making tool for measuring countries' sustainability performance.

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“…Two-parameter Weibull distribution is one of the widely used statistical methods in the modeling of wind speed data. The Weibull distribution function is given by the following [30][31][32][33][34][35][36]:…”

Section: Two-parameter Weibull Distributionmentioning

confidence: 99%

Finsler Geometry for Two‐Parameter Weibull Distribution Function

Dokur

Ceyhan

Kurban

2017

Mathematical Problems in Engineering

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To construct the geometry in nonflat spaces in order to understand nature has great importance in terms of applied science. Finsler geometry allows accurate modeling and describing ability for asymmetric structures in this application area. In this paper, two-dimensional Finsler space metric function is obtained for Weibull distribution which is used in many applications in this area such as wind speed modeling. The metric definition for two-parameter Weibull probability density function which has shape (k) and scale (c) parameters in two-dimensional Finsler space is realized using a different approach by Finsler geometry. In addition, new probability and cumulative probability density functions based on Finsler geometry are proposed which can be used in many real world applications. For future studies, it is aimed at proposing more accurate models by using this novel approach than the models which have two-parameter Weibull probability density function, especially used for determination of wind energy potential of a region.

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Assessing the proficiency of adaptive neuro-fuzzy system to estimate wind power density: Case study of Aligoodarz, Iran

Cited by 15 publications

References 43 publications

Performance investigation of an advanced hybrid renewable energy system in indonesia

Performance investigation of an advanced hybrid renewable energy system in indonesia

Measuring Country Sustainability Performance Using Ensembles of Neuro-Fuzzy Technique

Finsler Geometry for Two‐Parameter Weibull Distribution Function

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