New integration mechanism of solar energy into 300 MW coal-fired power plant: Performance and techno-economic analysis

Shagdar, Enkhbayar; Shuai, Yong; Lougou, Bachirou Guene; Mustafa, Azeem; Choidorj, Dashpuntsag; Tan, He‐Ping

doi:10.1016/j.energy.2021.122005

Cited by 30 publications

(8 citation statements)

References 52 publications

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“…In other words, DNI is the highest value during 12:00-13:00, and the solar incidence angle is significantly high during this period, which reduces the thermal efficiency of the solar field due to the larger optical loss. Similar observations were found in the numerical studies of Shagdar et al [54] and Chen et al [55]. The solar field exhibited a very good capability to collect solar thermal power during summer days, whereas during winter days, the operating performance of the solar field was significantly reduced due to a decrease in DNI and ambient temperature and an increase in solar incidence angle.…”

Section: Operating Performance Of the 50 Mw Csp Plant Under Four Refe...supporting

confidence: 84%

Performance Analysis of the 50 MW Concentrating Solar Power Plant under Various Operation Conditions

et al. 2022

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Power generation using concentrating solar energy is a potential solution to provide clean, green, and sustainable power generation in the long term. The objective of this paper is to analyze the performance of a parabolic trough collector-based concentrating solar power (CSP) plant by selecting four different reference days (i.e., 22 March, 22 June, 22 September, and 22 December), representing four seasons in Mongolian climate conditions. Numerical simulation of the 50 MW CSP plant was performed, both at nominal and part-load conditions using the heat balance method considering variations of power load owing to the direct normal irradiation (DNI). The results revealed that the 50 MW CSP plant could operate well throughout the year, and it showed the highest value of operating performance for the 22 June due to the higher DNI and small solar incidence angle. The operating performance for the 22 March and 22 September is nearly similar. The lowest value of operating performance occurred on the 22 December. Moreover, the operating performance of the CSP plant in the part-load conditions was significantly reduced compared to the nominal load owing to the DNI fluctuation. This study also revealed that the CSP plant could significantly contribute to environmental protection and climate change mitigation.

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Section: Operating Performance Of the 50 Mw Csp Plant Under Four Refe...supporting

confidence: 84%

Performance Analysis of the 50 MW Concentrating Solar Power Plant under Various Operation Conditions

et al. 2022

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“…e visual representation of the internal structure of RNN is shown in Figure 2(a), where the input and output are represented by x t and 􏽢 y t at time t, similarly, the output of the single hidden layer at time t is represented by a t , where w represents the weight metrics. Figure 2(a) can be mathematically represented as in equation (1).…”

Section: Temporal Feature Extractionmentioning

confidence: 99%

“…Photovoltaic (PV) power generation is one of the easiest-toaccess, low-cost, and most promising sources of renewable energy. When the energy demands rise in the developing country, the PV power generation annually increases; therefore, it mitigates the global energy and climatic change crisis [1]. According to the Global Future Report, by 2050, the PV generation capacity will reach 8000 GW [2].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Deep Learning‐Based Network for Photovoltaic Power Forecasting

et al. 2022

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For efficient energy distribution, microgrids (MG) provide significant assistance to main grids and act as a bridge between the power generation and consumption. Renewable energy generation resources, particularly photovoltaics (PVs), are considered as a clean source of energy but are highly complex, volatile, and intermittent in nature making their forecasting challenging. Thus, a reliable, optimized, and a robust forecasting method deployed at MG objectifies these challenges by providing accurate renewable energy production forecasting and establishing a precise power generation and consumption matching at MG. Furthermore, it ensures effective planning, operation, and acquisition from the main grid in the case of superior or inferior amounts of energy, respectively. Therefore, in this work, we develop an end-to-end hybrid network for automatic PV power forecasting, comprising three basic steps. Firstly, data preprocessing is performed to normalize, remove the outliers, and deal with the missing values prominently. Next, the temporal features are extracted using deep sequential modelling schemes, followed by the extraction of spatial features via convolutional neural networks. These features are then fed to fully connected layers for optimal PV power forecasting. In the third step, the proposed model is evaluated on publicly available PV power generation datasets, where its performance reveals lower error rates when compared to state-of-the-art methods.

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“…With the development of social productivity, while human's ability to use and transform nature to obtain material means of life has increased signifcantly, the pollution and damage to the ecological environment are also increasing, and the coordination between environment and economy is decreasing [1]. Economic growth and environmental protection are consistent in objectives and interact with each other.…”

Section: Introductionmentioning

confidence: 99%

A New Model of Environmental-Economic Coordination Prediction Using Credible Neural Network Integration and Big Data Analysis

Yang

et al. 2022

Security and Communication Networks

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Currently, a significant portion of sustained economic growth still depends on a high input of resources. We must fully understand the significance, difficulty, and long-term nature of resource conservation and environmental protection. We must also intensify our efforts to protect the ecological environment. We must gradually form a production mode, lifestyle, and consumption mode conducive to environmental protection. We must also establish a benign interactive relationship with the environment. This study offers a big data analysis and neural network integration optimization design strategy for a new kind of environmental and economic coordination prediction model. The data of the new type of environmental and economic impact with numerous parameters are preprocessed using big data analysis and principal component analysis. A neural network integration system is used to create the prediction model, and prediction research and error analysis are conducted to enhance the new kind of environmental and economic model. The simulation test analysis is completed lastly. According to the simulation findings, the proposed arithmetic has an accuracy that is 8.56% higher than that of the conventional arithmetic. A sustainable improvement management system with environmental objectives, environmental management planning plans, and environmental monitoring systems can be established with help from the new environmental and economic coordination prediction model, which can also assist in predicting the potential environmental impact caused by economic development activities. This will ensure sustainable development as a result of the mechanism.

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New integration mechanism of solar energy into 300 MW coal-fired power plant: Performance and techno-economic analysis

Cited by 30 publications

References 52 publications

Performance Analysis of the 50 MW Concentrating Solar Power Plant under Various Operation Conditions

Performance Analysis of the 50 MW Concentrating Solar Power Plant under Various Operation Conditions

A Hybrid Deep Learning‐Based Network for Photovoltaic Power Forecasting

A New Model of Environmental-Economic Coordination Prediction Using Credible Neural Network Integration and Big Data Analysis

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