Environmental efficiency analysis of China's coal-fired power plants considering heterogeneity in power generation company groups

2021 ◽  
pp. 105511
Author(s):  
Tomoaki Nakaishi ◽  
Hirotaka Takayabu ◽  
Shogo Eguchi
2014 ◽  
Vol 540 ◽  
pp. 525-527
Author(s):  
Hui Li ◽  
Jing Long Liang

coal-fired power plants in the process of power generation will produce large amounts of water vapor, here for the use of the water vapor heat tracing for economic analysis.


2018 ◽  
Vol 46 ◽  
pp. 126-135 ◽  
Author(s):  
Bai-Chen Xie ◽  
Jie Gao ◽  
Shuang Zhang ◽  
Rui-Zhi Pang ◽  
ZhongXiang Zhang

2021 ◽  
Vol 11 (15) ◽  
pp. 6887
Author(s):  
Chung-Hong Lee ◽  
Hsin-Chang Yang ◽  
Guan-Bo Ye

In recent years, many countries have provided promotion policies related to renewable energy in order to take advantage of the environmental factors of sufficient sunlight. However, the application of solar energy in the power grid also has disadvantages. The most obvious is the variability of power output, which will put pressure on the system. As more grid reserves are needed to compensate for fluctuations in power output, the variable nature of solar power may hinder further deployment. Besides, one of the main issues surrounding solar energy is the variability and unpredictability of sunlight. If it is cloudy or covered by clouds during the day, the photovoltaic cell cannot produce satisfactory electricity. How to collect relevant factors (variables) and data to make predictions so that the solar system can increase the power generation of solar power plants is an important topic that every solar supplier is constantly thinking about. The view is taken, therefore, in this work, we utilized the historical monitoring data collected by the ground-connected solar power plants to predict the power generation, using daily characteristics (24 h) to replace the usual seasonal characteristics (365 days) as the experimental basis. Further, we implemented daily numerical prediction of the whole-point power generation. The preliminary experimental evaluations demonstrate that our developed method is sensible, allowing for exploring the performance of solar power prediction.


2021 ◽  
Vol 11 (2) ◽  
pp. 727 ◽  
Author(s):  
Myeong-Hwan Hwang ◽  
Young-Gon Kim ◽  
Hae-Sol Lee ◽  
Young-Dae Kim ◽  
Hyun-Rok Cha

In recent years, photovoltaic (PV) power generation has attracted considerable attention as a new eco-friendly and renewable energy generation technology. With the recent development of semiconductor manufacturing technologies, PV power generation is gradually increasing. In this paper, we analyze the types of defects that form in PV power generation panels and propose a method for enhancing the productivity and efficiency of PV power stations by determining the defects of aging PV modules based on their temperature, power output, and panel images. The method proposed in the paper allows the replacement of individual panels that are experiencing a malfunction, thereby reducing the output loss of solar power generation plants. The aim is to develop a method that enables users to immediately check the type of failures among the six failure types that frequently occur in aging PV panels—namely, hotspot, panel breakage, connector breakage, busbar breakage, panel cell overheating, and diode failure—based on thermal images by using the failure detection system. By comparing the data acquired in the study with the thermal images of a PV power station, efficiency is increased by detecting solar module faults in deteriorated photovoltaic power plants.


Author(s):  
Yong Tian ◽  
Wen-Jing Liu ◽  
Qi-jie Jiang ◽  
Xin-Ying Xu

With the development of biomass power generation technology, biomass waste has a more excellent recycling value. The article establishes a biomass waste inventory model based on the material flow analysis method and predicts raw material waste’s energy utilization potential. The results show that the amount of biomass waste generated from 2016 to 2020 is on the rise. In 2020, biomass waste’s energy utilization can reach 107,802,300 tons, equivalent to 1,955.28PJ of energy. Through biomass energy analysis and emission analysis, the results show that the biomass waste can generate 182.02 billion kW⋅h in 2020, which can replace 35.9% of the region’s total power consumption, which is compared with the traditional power generation method under the same power generation capacity. Power generation can reduce SO2 emissions by 250,400 tons, NOx emissions by 399,300 tons, and PM10 emissions by 49,700 tons. Reduce direct economic losses by 712 million yuan. Therefore, Chinese promotion of the recycling of biomass waste and the acceleration of the biomass energy industry’s development is of great significance for reducing pollutant emissions and alleviating energy pressure.


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