RETRACTED: Survey of the most influential parameters on the wind farm net present value (NPV) by adaptive neuro-fuzzy approach

Petković, Dalibor; Shamshirband, Shahaboddin; Kamsin, Amirrudin; Lee, Malrey; Aničić, Obrad; Nikolić, Vlastimir

doi:10.1016/j.rser.2015.12.175

Cited by 30 publications

(14 citation statements)

References 49 publications

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“…By 2020, the total installed capacity will see an increase of 16% over the total installed capacity in 2012. Of this new capacity, gas and coal will continue to feature strongly in Malaysia's several studies [9][10][11]. The strong limitation of NPV as presented by [12] is the need for estimation of discounting rates.…”

Section: Introductionmentioning

confidence: 99%

The Optimal Generation Cost-Based Tariff Rates for Onshore Wind Energy in Malaysia

et al. 2017

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Abstract:The government of Malaysia has recently decided to explore the feasibility of wind energy to generate electricity in the country. Their ambition is to achieve a measureable target in the percentage contribution of electricity generated by renewable energy technology in the national electricity generation mix. As part of this initiative, a study of wind energy policy has been conducted by identifying the optimal feed-in tariff (FiT) rates to support the development of wind energy in the country. The aim of this paper is to calculate the optimal level of tariff that is suitable with local wind conditions. A closed-form equation for optimal feed-in tariff rate of wind energy with consideration of the availability of capital allowance has been developed. The focus is on small-and utility-scale wind turbine installations. As a result, by considering the availability of capital allowance, the optimal FiT rates for small-scale wind turbines in Malaysia are between 0.9245-1.1313 RM/kWh, while utility-scale rates are between 0.7396 and 0.9050 RM/kWh. The level of FiT is changed with the changing value of economic parameters. Kudat, in northern Borneo, has been identified as a prime site for wind energy development in the country; however, more work needs to be conducted, including the development of a regional wind map and measurement of wind data at more new potential sites.

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Section: Introductionmentioning

confidence: 99%

The Optimal Generation Cost-Based Tariff Rates for Onshore Wind Energy in Malaysia

et al. 2017

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“…al. states that at the decision about implementing of investment project, the terms net present value (NPV) and net future value (NFV) are used [13]. According to the authors, net present value is defined by the sum of discounted values of individual concepts in the flow, where each term is discounted to a common reference date.…”

Section: Methodsmentioning

confidence: 99%

Life Cycle Cost Calculation at the Transport Company in the Supply of Production of Wooden Houses – Case Study

2017

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Abstract.A correct information manager's decision-maker database is a very important element that substantially affects its success. This article presents the potential of using the methodology of life cycle cost calculation in the conditions of a transport company that focuses on the logistic supply of wood-housing producers. The problem is presented through a case study and addresses the decision-making aspect of the decision about acquisition of the transport vehicle. This decision uses time value indicators, inflation rates, average rate of profitability of industry and life cycle costs. Due to the short life cycle of the analyzed period, it was not necessary to consider the ergonomic requirements resulting from the trend of anthropometric dimensions growth.

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“…The results of this paper showed that the ANFIS results are more accurate than the results of the artificial neural network (ANN) and genetic programming (GP) techniques. Petković et al [36] constructed the ANFIS model to evaluate the investment risk of a wind power project. 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 ).…”

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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RETRACTED: Survey of the most influential parameters on the wind farm net present value (NPV) by adaptive neuro-fuzzy approach

Cited by 30 publications

References 49 publications

The Optimal Generation Cost-Based Tariff Rates for Onshore Wind Energy in Malaysia

The Optimal Generation Cost-Based Tariff Rates for Onshore Wind Energy in Malaysia

Life Cycle Cost Calculation at the Transport Company in the Supply of Production of Wooden Houses – Case Study

Measuring Country Sustainability Performance Using Ensembles of Neuro-Fuzzy Technique

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