KNN_SVM Based Information Transmission Method for Renewable Energy Power Generation

Author(s):  
Kai Liang ◽  
Huan He ◽  
Guannan Liu ◽  
Daqian Wang ◽  
Xiaoyu Zhang ◽  
...  
Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2171
Author(s):  
Hyeonsu Han ◽  
Junghyuk Ko

Along with the increase in renewable energy, research on energy harvesting combined with piezoelectric energy is being conducted. However, it is difficult to predict the power generation of combined harvesting because there is no data on the power generation by a single piezoelectric material. Before predicting the corresponding power generation and efficiency, it is necessary to quantify the power generation by a single piezoelectric material alone. In this study, the generated power is measured based on three parameters (size of the piezoelectric ceramic, depth of compression, and speed of compression) that contribute to the deformation of a single PZT (Lead zirconate titanate)-based piezoelectric element. The generated power was analyzed by comparing with the corresponding parameters. The analysis results are as follows: (i) considering the difference between the size of the piezoelectric ceramic and the generated power, 20 mm was the most efficient piezoelectric ceramic size, (ii) considering the case of piezoelectric ceramics sized 14 mm, the generated power continued to increase with the increase in the compression depth of the piezoelectric ceramic, and (iii) For piezoelectric ceramics of all diameters, the longer the depth of deformation, the shorter the frequency, and depending on the depth of deformation, there is a specific frequency at which the charging power is maximum. Based on the findings of this study, PZT-based elements can be applied to cases that receive indirect force, including vibration energy and wave energy. In addition, the power generation of a PZT-based element can be predicted, and efficient conditions can be set for maximum power generation.


2021 ◽  
Vol 13 (12) ◽  
pp. 6681
Author(s):  
Simian Pang ◽  
Zixuan Zheng ◽  
Fan Luo ◽  
Xianyong Xiao ◽  
Lanlan Xu

Forecasting of large-scale renewable energy clusters composed of wind power generation, photovoltaic and concentrating solar power (CSP) generation encounters complex uncertainties due to spatial scale dispersion and time scale random fluctuation. In response to this, a short-term forecasting method is proposed to improve the hybrid forecasting accuracy of multiple generation types in the same region. It is formed through training the long short-term memory (LSTM) network using spatial panel data. Historical power data and meteorological data for CSP plant, wind farm and photovoltaic (PV) plant are included in the dataset. Based on the data set, the correlation between these three types of power generation is proved by Pearson coefficient, and the feasibility of improving the forecasting ability through the hybrid renewable energy clusters is analyzed. Moreover, cases study indicates that the uncertainty of renewable energy cluster power tends to weaken due to partial controllability of CSP generation. Compared with the traditional prediction method, the hybrid prediction method has better prediction accuracy in the real case of renewable energy cluster in Northwest China.


2021 ◽  
Vol 11 (13) ◽  
pp. 5907
Author(s):  
Valerii Havrysh ◽  
Antonina Kalinichenko ◽  
Anna Brzozowska ◽  
Jan Stebila

The European Union has set targets for renewable energy utilization. Poland is a member of the EU, and its authorities support an increase in renewable energy use. The background of this study is based on the role of renewable energy sources in improving energy security and mitigation of climate change. Agricultural waste is of a significant role in bioenergy. However, there is a lack of integrated methodology for the measurement of its potential. The possibility of developing an integrated evaluation methodology for renewable energy potential and its spatial distribution was assumed as the hypothesis. The novelty of this study is the integration of two renewable energy sources: crop residues and animal husbandry waste (for biogas). To determine agricultural waste energy potential, we took into account straw requirements for stock-raising and soil conservation. The total energy potential of agricultural waste was estimated at 279.94 PJ. It can cover up to 15% of national power generation. The spatial distribution of the agricultural residue energy potential was examined. This information can be used to predict appropriate locations for biomass-based power generation facilities. The potential reduction in carbon dioxide emissions ranges from 25.7 to 33.5 Mt per year.


2021 ◽  
Vol 753 (1) ◽  
pp. 012011
Author(s):  
Ika Wahyu Setya Andani ◽  
Agus Sugiyono ◽  
Khusnul Khotimah ◽  
Boanerges Desryanto Siregar

2021 ◽  
Vol 7 (3) ◽  
Author(s):  
Shakib Hassan Eon ◽  
Shakib Hassan Eon ◽  
Shakib Hassan Eon

Renewable energy generation is no more an alternative rather it becomes a choice for the power generation to meet the upcoming energy demand. Considering the non- renewable energy unavailability, as well as, the environmental impact, renewable energy should be the first choice. Most of the power generation in Bangladesh comes from nonrenewable energy and a noticeable amount of energy is imported from abroad. As a developing country, it is not cost-efficient and never ensures energy security. To ensure long-term energy security, it is time to shift power generation from nonrenewable to renewable energy generation. This paper presents an approximate calculation for the renewable power generating plant cost and returning year. The cost calculation is done in the context of Bangladesh.


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