Intelligent optimized wind resource assessment and wind turbines selection in Huitengxile of Inner Mongolia, China

Dong, Yao; Wang, Jianzhou; He, Jia; Shi, Xiaomeng

doi:10.1016/j.apenergy.2013.04.028

Cited by 69 publications

(33 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although the paper claims that twenty-five potential turbines were assessed, results and analysis of only a few turbines were given in the article. Dong et al [61] proposed three criteria, namely matching index, turbine cost index and the integrated matching index for turbine selection. Three optimization algorithms were used which were particle swarm optimization, differential evolution, and genetic algorithm.…”

Section: Approaches For Turbine Selection Problemmentioning

confidence: 99%

“…(6) Conflict and incommensurability of criteria. While a number of studies [45,46,51,[55][56][57][59][60][61][62]64] have assumed multiple criteria for selection of the best turbine type, all of them have missed the two fundamental aspects of MCDM. These aspects are known as conflict between criteria and incommensurability.…”

Section: Novelty and Contribution Of The Proposed Approachmentioning

confidence: 99%

“…Despite this, such approaches have been frequently used in the turbine selection problems [46,[48][49][50][51][52][53][54][55][56][57][59][60][61]64]. (5) Failure to account for impact of changing hub height on cost and production.…”

Section: Novelty and Contribution Of The Proposed Approachmentioning

confidence: 99%

“…(2) Decision parameters that cannot be known by the developer. Most research papers assumed decision parameters for which information is not easily accessible (i.e., blade shape, product reliability, production volume, availability factors, organization of maintenance, system reliability indices, environmental issues, visual impact, political stability, among many others) [45][46][47][48][49][53][54][55][56][57][58][59][60][61][62][63]. Such parameters result in the selection approach being very complex and impractical.…”

Section: Novelty and Contribution Of The Proposed Approachmentioning

confidence: 99%

See 3 more Smart Citations

Fuzzy Logic Based Multi-Criteria Wind Turbine Selection Strategy—A Case Study of Qassim, Saudi Arabia

Rehman

Khan

2016

Energies

View full text Add to dashboard Cite

Abstract:The emergence of wind energy as a potential alternative to traditional sources of fuel has prompted notable research in recent years. One primary factor contributing to efficient utilization of wind energy from a wind farm is the type of turbines used. However, selection of a specific wind turbine type is a difficult task due to several criteria involved in the selection process. Important criteria include turbine's power rating, height of tower, energy output, rotor diameter, cut-in wind speed, and rated wind speed. The complexity of this selection process is further amplified by the presence of conflicts between the decision criteria. Therefore, a decision is desired that provides the best balance between all selection criteria. Considering the complexities involved in the decision-making process, this paper proposes a two-level decision turbine selection strategy based on fuzzy logic and multi-criteria decision-making (MCDM) approach. More specifically, the fuzzy arithmetic mean operator is used in the decision process. The proposed approach is applied to wind data collected from the site of Qassim, Saudi Arabia. Results indicate that the proposed approach was effective in finding the optimal turbine from a set of 20 turbines of various capacities.

show abstract

Section: Approaches For Turbine Selection Problemmentioning

confidence: 99%

Section: Novelty and Contribution Of The Proposed Approachmentioning

confidence: 99%

Section: Novelty and Contribution Of The Proposed Approachmentioning

confidence: 99%

Section: Novelty and Contribution Of The Proposed Approachmentioning

confidence: 99%

See 2 more Smart Citations

Fuzzy Logic Based Multi-Criteria Wind Turbine Selection Strategy—A Case Study of Qassim, Saudi Arabia

Rehman

Khan

2016

Energies

View full text Add to dashboard Cite

show abstract

“…Currently, genetic algorithms are used to optimize neural nets to solve some complicated problems [27]. The basic manipulations of GA contain six parts as described below [28].…”

Section: Genetic Algorithm (Ga)mentioning

confidence: 99%

A Novel Combined Model Based on an Artificial Intelligence Algorithm—A Case Study on Wind Speed Forecasting in Penglai, China

2016

View full text Add to dashboard Cite

Abstract:Wind speed forecasting plays a key role in wind-related engineering studies and is important in the management of wind farms. Current forecasting models based on different optimization algorithms can be adapted to various wind speed time series data. However, these methodologies cannot aggregate different hybrid forecasting methods and take advantage of the component models. To avoid these limitations, we propose a novel combined forecasting model called SSA-PSO-DWCM, i.e., particle swarm optimization (PSO) determined weight coefficients model. This model consisted of three main steps: one is the decomposition of the original wind speed signals to discard the noise, the second is the parameter optimization of the forecasting method, and the last is the combination of different models in a nonlinear way. The proposed combined model is examined by forecasting the wind speed (10-min intervals) of wind turbine 5 located in the Penglai region of China. The simulations reveal that the proposed combined model demonstrates a more reliable forecast than the component forecasting engines and the traditional combined method, which is based on a linear method.

show abstract

Wind Turbine Assessment

Balo,

Sua

2024

Wind Energy Storage and Conversion

View full text Add to dashboard Cite

Intelligent optimized wind resource assessment and wind turbines selection in Huitengxile of Inner Mongolia, China

Cited by 69 publications

References 15 publications

Fuzzy Logic Based Multi-Criteria Wind Turbine Selection Strategy—A Case Study of Qassim, Saudi Arabia

Fuzzy Logic Based Multi-Criteria Wind Turbine Selection Strategy—A Case Study of Qassim, Saudi Arabia

A Novel Combined Model Based on an Artificial Intelligence Algorithm—A Case Study on Wind Speed Forecasting in Penglai, China

Wind Turbine Assessment

Contact Info

Product

Resources

About