Driving force model to evaluate China's photovoltaic industry: Historical and future trends

Luo, Zimeng; He, Jiaqian; Hu, Shanying

doi:10.1016/j.jclepro.2021.127637

Cited by 31 publications

(11 citation statements)

References 28 publications

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“…Solar energy is widely valued and utilized among diverse renewable energy sources because of its resourcefulness, cleanliness, and safety. Photovoltaic power generation is a way to use solar energy effectively, and its development has accelerated the construction of highpercentage renewable energy power generation systems [4]. According to the different prediction duration scales, PV power prediction can be divided into medium-and longterm prediction (usually months or years), short-term prediction (within a week), and ultra-short-term prediction (rolling prediction for 0.5-6 h).…”

Section: Introductionmentioning

confidence: 99%

PV Power Forecasting Based on Relevance Vector Machine with Sparrow Search Algorithm Considering Seasonal Distribution and Weather Type

Qiu

Sun

et al. 2022

Energies

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Accurate photovoltaic (PV) power forecasting is indispensable to enhancing the stability of the power grid and expanding the absorptive photoelectric capacity of the power grid. As an excellent nonlinear regression model, the relevance vector machine (RVM) can be employed to forecast PV power. However, the optimization of the free parameters is still a key problem for improving the performance of the RVM. Taking advantage of the strong global search capability, good stability, and fast convergence rate of the sparrow search algorithm (SSA), this paper optimizes the parameters of the RVM by using the SSA to develop an excellent RVM (called SSA-RVM). Consequently, a novel hybrid PV power forecasting model via the SSA-RVM is proposed to perform ultra-short-term (4 h ahead) prediction. In addition, the effects of seasonal distribution and weather type on PV power are fully considered, and different seasonal prediction models are established separately to improve the prediction capability. The benchmark is used to verify the accuracy of the SSA-RVM-based forecasting model under various conditions, and the experiment results demonstrate that the proposed SSA-RMV method outperforms the traditional RVM and support vector machine models, and it even shows a better prediction effect than the RVM models with other optimization approaches.

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Section: Introductionmentioning

confidence: 99%

PV Power Forecasting Based on Relevance Vector Machine with Sparrow Search Algorithm Considering Seasonal Distribution and Weather Type

Qiu

Sun

et al. 2022

Energies

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“…Polysilicon is the primary raw material of the photovoltaic industry. The current producing methods 7 of polysilicon primarily include improved Siemens, silane, 8 fluidized bed, 9 metallurgy, 10 and zinc reduction methods. 11 Because of its high stability and good quality, the Siemens method 12 has become the main manufacturing method (80% market share).…”

Section: Introductionmentioning

confidence: 99%

Theoretical study on the reaction mechanism of Si₂Cl₆ and HCl catalyzed by amine catalysts

et al. 2022

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“…For example, Tsai et al [3] assessed the competitiveness of Taiwan's solar photovoltaic industry based on six dimensions of the diamond model (i.e., firm strategy; government, structure, and rivalry; demand condition; chance; factor condition; and related and support industries). Luo et al [4] assessed the photovoltaic industry and its influencing factors using the diamond model. Zhao et al [5] constructed a system dynamics model to analyze the impact of research and development investment on China's photovoltaic power generation industry.…”

Section: Introductionmentioning

confidence: 99%

“…7 Very strong or demonstrated importanceAn activity is favored very strongly over another, indicating its dominance. 9Extreme importance The evidence favoring one activity over another is of the highest possible order 2,4,6,8. For compromise between the above values Sometimes, one needs to interpolate a compromise judgment numerically.…”

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confidence: 99%

The Relative Importance of Determinants of the Solar Photovoltaic Industry in China: Analyses by the Diamond Model and the Analytic Hierarchy Process

2021

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Within China’s renewable energy industry, the importance of the solar photovoltaic industry has been increasingly recognized. Many Chinese provinces have adopted various measures to develop the solar photovoltaic industry. This study used the diamond model and the analytic hierarchy process to clarify the relative importance of the determinants of the development of the solar photovoltaic industry. A total of 22 determinants in six categories (i.e., factor condition; demand condition; firm strategy, structure, and rivalry; related and support industries; government; and chance) were analyzed. The results show that besides factor condition, demand condition and firm strategy, structure, and rivalry have also had a strong influence on the development of China’s photovoltaic industry. The findings also indicate that some traditional factors, such as labor costs and acquiring land, are very important to the development of the solar photovoltaic industry. The relative importance of the determinants clarified through this study provides a standard for the actions of policymakers and decision makers.

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Driving force model to evaluate China's photovoltaic industry: Historical and future trends

Cited by 31 publications

References 28 publications

PV Power Forecasting Based on Relevance Vector Machine with Sparrow Search Algorithm Considering Seasonal Distribution and Weather Type

PV Power Forecasting Based on Relevance Vector Machine with Sparrow Search Algorithm Considering Seasonal Distribution and Weather Type

Theoretical study on the reaction mechanism of Si₂Cl₆ and HCl catalyzed by amine catalysts

The Relative Importance of Determinants of the Solar Photovoltaic Industry in China: Analyses by the Diamond Model and the Analytic Hierarchy Process

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Driving force model to evaluate China's photovoltaic industry: Historical and future trends

Cited by 31 publications

References 28 publications

PV Power Forecasting Based on Relevance Vector Machine with Sparrow Search Algorithm Considering Seasonal Distribution and Weather Type

PV Power Forecasting Based on Relevance Vector Machine with Sparrow Search Algorithm Considering Seasonal Distribution and Weather Type

Theoretical study on the reaction mechanism of Si2Cl6 and HCl catalyzed by amine catalysts

The Relative Importance of Determinants of the Solar Photovoltaic Industry in China: Analyses by the Diamond Model and the Analytic Hierarchy Process

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Theoretical study on the reaction mechanism of Si₂Cl₆ and HCl catalyzed by amine catalysts