Importance analysis of off-grid wind power generation systems

Lu, Hongwei; Pan, Haiyang; He, Li; Zhang, J.Q.

doi:10.1016/j.rser.2015.12.286

Cited by 12 publications

(10 citation statements)

References 23 publications

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“…The detailed calculation procedures of the two indicators are followed as reference [34]. When the two methods are developed, the running status of the wind power system should be considered.…”

Section: Importance Analysis For Weight Evaluationmentioning

confidence: 99%

“…It should be specially noted that the cut-out wind speed is 18 m/s (v co ). According to the weight calculation method in Table 2 and the above data, the weight parameters in different operating states can be obtained as Equations (30)- (34…”

Section: Weight Analysismentioning

confidence: 99%

“…As for the importance rankings of the system components, the results of the two evaluation models depict little difference from a qualitative perspective. Components C5, C8, and C9 are more important than others and have great impacts on the top event when the entire system failed (the definition of a top event is found in reference [34]). The impacts of components C5, C8, and C9 are particularly prominent, and they are marked as key characteristics (A).…”

Section: Balance Of Energy Supply -Demandmentioning

confidence: 99%

See 2 more Smart Citations

An Importance Analysis–Based Weight Evaluation Framework for Identifying Key Components of Multi-Configuration Off-Grid Wind Power Generation Systems under Stochastic Data Inputs

Bin

Pan

et al. 2019

Energies

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Wind power systems have great potential due to its inexhaustible nature and benign environmental impacts. Especially in remote areas, where wind is plentiful, but it is difficult to get grid-connected power, an off-grid wind power system is an effective alternative for power supply. Reliable and safe operation of the generating system are essential for electricity production and supply. Importance analysis to identify key components of the system is a critical part of reliability assessment. This paper proposes an importance analysis–based weight evaluation framework for identifying key components of multi-configuration off-grid wind power generation systems under stochastic inputs. In the framework, the joint importance analysis based on Birnbaum importance and Criticality importance are introduced to analyze the system reliability and failure rate. Wind speed with stochastic characteristics, load demand with multiple scenarios, and energy transfer with different paths are also merged into the evaluation framework. The results reveal that the rectifier, battery, discharge load, and valve controller dominate the reliability of the off-grid wind power generation system. High priority should be placed on these components during the design phase and maintenance stage. The proposed approach is a positive step forward in promoting component importance analysis and providing more theoretical supports in system design, reliability analysis, and monitoring scheme formulation.

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Section: Importance Analysis For Weight Evaluationmentioning

confidence: 99%

Section: Weight Analysismentioning

confidence: 99%

Section: Balance Of Energy Supply -Demandmentioning

confidence: 99%

See 1 more Smart Citation

An Importance Analysis–Based Weight Evaluation Framework for Identifying Key Components of Multi-Configuration Off-Grid Wind Power Generation Systems under Stochastic Data Inputs

Bin

Pan

et al. 2019

Energies

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show abstract

“…Yang et al (2016) used the computational fluid dynamics (CFD) approach to estimate the potential of wind power generation on the roof of different buildings in ten urban sites. Lu et al (2016) analyzed the performance of wind power generation systems using the Birnbaum Importance and CI (Criticality Importance) methods. Wei et al (2016) conducted a robust technical-economic analysis of wind power generation and carbon capture in wind power plants using the environmental-economic dispatch method.…”

Section: Introductionmentioning

confidence: 99%

Forecasting the wind power generation using Box–Jenkins and hybrid artificial intelligence

Jafarian‐Namin

Goli

Qolipour

et al. 2019

IJESM

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Purpose The purpose of this paper is to forecast wind power generation in an area through different methods, and then, recommend the most suitable one using some performance criteria. Design/methodology/approach The Box–Jenkins modeling and the Neural network modeling approaches are applied to perform forecasting for the last 12 months. Findings The results indicated that among the tested artificial neural network (ANN) model and its improved model, artificial neural network-genetic algorithm (ANN-GA) with RMSE of 0.4213 and R2 of 0.9212 gains the best performance in prediction of wind power generation values. Finally, a comparison between ANN-GA and ARIMA method confirmed a far superior power generation prediction performance for ARIMA with RMSE of 0.3443 and R2 of 0.9480. Originality/value Performance of the ARIMA method is evaluated in comparison to several types of ANN models including ANN, and its improved model using GA as ANN-GA and particle swarm optimization (PSO) as ANN-PSO.

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“…The present situation and shortcomings of off-grid wind power development are analyzed according to the present situation of wind resources in China, and it is considered that wind power is of great significance to solve the problem of power supply in remote areas (Wu and Zhang, 2009). Importance and reliability analysis is conducted for an off-grid wind power generation system, concluding that the renewable energy is the best choice for solving the electrification problem in remote areas (Lu et al , 2016). And then, they qualitatively analyzed the local benefits that the electrification can bring to remote areas.…”

Section: Introductionmentioning

confidence: 99%

Research on decision making of energy utilization project in China based on benefit evaluation

Niu

Zhao

Song

2019

IJESM

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Purpose There are thousands of areas excluded from using electrical energy in China. It is mainly because that these places, which are away from towns, have the characteristics of scattered living and low-power consumption and are difficult to construct the power grid. The utilization of energy in remote areas could improve the level of education and quality of life for people living in there, which has great social significance. However, how to choose the optimal power generation model quantitatively according to local energy advantages is a difficult problem. Design/methodology/approach To carry out a better assessment of the energy benefits of Chinese rural areas to assist the decision-making of energy utilization project, this paper takes Sunan Yugu Autonomous County in Gansu Province as an example. Four feasible energy utilization scenarios are proposed by analyzing its geographical conditions and re-source advantage, respectively, are photovoltaic power generation, biomass power generation, wind power generation and power grid extension. Based on the above scenarios, the evaluation index system of comprehensive utilization of energy in remote areas is constructed, and the comprehensive benefit of each model is evaluated by adopting entropy-based fuzzy comprehensive evaluation model. Findings Evaluation results show that the comprehensive benefits of photovoltaic power generation is the best, followed by power grid extension. Thus, preference should be given to the two models in the energy utilization in Sunan County. This evaluation model can provide a scientific reference for the selection decision-making of energy utilization project, which is helpful to provide the feasibility and efficiency of the construction of energy utilization project. Originality/value The authors construct the comprehensive benefit evaluation index system and evaluate the comprehensive benefits of different scenarios are by using entropy - fuzzy comprehensive evaluation model. Then the qualitative problem can be analyzed quantitatively. The purpose of this study is to support the decision-making of energy investment. Simultaneously, the paper also has some practical significance in improving the credibility of the government and the quality of local people’s life.

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Importance analysis of off-grid wind power generation systems

Cited by 12 publications

References 23 publications

An Importance Analysis–Based Weight Evaluation Framework for Identifying Key Components of Multi-Configuration Off-Grid Wind Power Generation Systems under Stochastic Data Inputs

An Importance Analysis–Based Weight Evaluation Framework for Identifying Key Components of Multi-Configuration Off-Grid Wind Power Generation Systems under Stochastic Data Inputs

Forecasting the wind power generation using Box–Jenkins and hybrid artificial intelligence

Research on decision making of energy utilization project in China based on benefit evaluation

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