Institutional Repository of GuangZhou Institute of Energy Conversion, CAS
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Interval prediction of short-term photovoltaic power based on an improved GRU model
No full textThe accurate prediction of photovoltaic (PV) power is crucial for planning, constructing, and scheduling high-penetration distributed PV power systems. Traditional point prediction methods suffer from instability and lack reliability, which can be effectively addressed through interval prediction. This study proposes a short-term PV power interval prediction method based on the framework of sparrow search algorithm (SSA)-variational mode decomposition (VMD)-convolutional neural network (CNN)-gate recurrent unit (GRU). First, PV data undergo similar day clustering based on permutation entropy and VMD is applied to solar radiation signals with high correlation. Then, the hyperparameters of GRU are optimized by SSA according to the comprehensive evaluation indicator of interval prediction proposed in this study. Subsequently, quantile prediction results are obtained based on CNN-GRU using the optimal parameters from SSA optimization. Finally, the prediction interval is composed of multiple quantile prediction results. A MATLAB R2022b program is developed to compare different prediction methods. The results demonstrate that compared to single neural network methods, the proposed method effectively improves the coverage width-based criterion. In the interval prediction of sunny and rainy similar days, the comprehensive evaluation indicators of the proposed method are only 54.3% and 37.4% of the single GRU, respectively, indicating significantly improved interval prediction accuracy.
Gate recurrent unit (GRU) network structure. imag
Special Project for Guiding the Transformation of Scientific and Technological Achievements of Shanxi Province[202204021301061]
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Promoting Decarbonization in China: Revealing the Impact of Various Energy Policies on the Power Sector Based on a Coupled Model
No full textThe carbon emissions of the power industry account for over 50% of China's total carbon emissions, so achieving carbon peak and carbon neutrality in the power sector is crucial. This study aims to simulate the impacts of three energy policies-carbon constraints, the development of a high proportion of renewable energy, and carbon trading-on China's energy transition, economic development, and the power sector's energy mix. Through the construction of a dynamic computable general equilibrium (CGE) model for China and its integration with the SWITCH-China electricity model, the impact of diverse energy policies on China's energy transition, economic progress, and the power mix within the electricity industry has been simulated. The integration of the SWITCH-China model can address the limitations of the CGE model in providing a detailed understanding of the specific intricacies of the electricity sector. The results indicate that increasing the stringency of carbon restrictions compels a reduction in fossil energy use, controlling the output of coal-fired power units, and thereby reducing carbon emissions. The development of a high proportion of renewable energy enhances the cleanliness of the power sector's generation structure, further promoting the national energy transition. Implementing a carbon trading policy, where the entire industry shares the burden of carbon reduction costs, can effectively mitigate the economic losses of the power sector. Finally, the policies to further enhance the implementation of carbon trading policies, strengthen effective governmental regulation, and escalate the deployment of renewable energy sources are recommended
The dominant-substrate driven the enhanced performance in co-digestion of Pennisetum hybrid and livestock waste
No full textCo-digestion has been considered a promising method to improve methane yield. The effect of the proportion of dominant substrate on the performance and microbial community of anaerobic digestion of Pennisetum hybrid (PH) and livestock waste (LW) was investigated. An obvious synergistic effect was obtained with an increase of 15.20%-17.45% in specific methane yield compared to the predicted value. Meanwhile, the dominant substrate influenced the relational model between methane yield enhancement rate and mixture ratio. For the LWdominant systems, a parabolic model between enhancement rate and mixture ratio was observed with a highest value of 392.16 mL/g VS achieved at a PH:LW ratio of 2:8. While a linear pattern appeared for PH-dominant systems with the highest methane yield of 307.59 mL/g VS. Co-digestion selectively enriched the relative abundance of Clostridium_sensu_stricto_1, Terrisporobacter, Syntrophomonas, Methanosarcina and Methanobacterium, which boosted the performance of hydrolysis, acidogenesis, acetogenesis and methanogenesis processes
Pilot-scale experimental study on natural gas hydrate decomposition with innovation depressurization modes
No full textNatural gas hydrate (NGH), a novel energy source characterized by large reserves, and wide distribution, has attracted worldwide attention in recent years. How to develop NGH economically and efficiently has always been a research hotspot. Although the depressurization method is currently considered the most promising production method, the production efficiency still cannot meet commercialization needs. Therefore, innovation depressurization modes need to be developed to achieve the goal of commercial production of NGH. This study applied a pilot-scale hydrate simulator (PHS) with an effective volume of 117.8 L to conduct three NGH decomposition experiments under different depressurization modes, including the Regular Depressurization (RD), the Cyclic Depressurization (CD), and the Cyclic Depressurization below the Quadruple point (CD-Q). The behavior of the NGH decomposition and the decomposition efficiency were research focus in this study. The experimental results indicate that the lower the final reservoir pressure leads to the higher the total gas production. In comparison to the RD mode, both the CD and CD-Q modes exhibit significant advantages regarding the total gas production volume and the effective average gas production rate. In the initial stage of production, the flow of NGH decomposition products in the wellbore resembles "Slug Flow ", while in the later stage of production, it resembles "Flow with Liquid Entrainment ". The decomposition rates of NGH reached 100% under both CD and CDQ modes. Particularly, under the CD-Q mode, the decomposition rate of NGH approached nearly 90% at the end of the depressurization stage. The CD mode can be combined with a multi-well network to perform asynchronous cyclic depressurization to achieve high-efficiency continuous gas production. This method provides an innovation strategy for both NGH commercial development and carbon storage
Studies on the quantitative analysis of an electrochemical solution via the Schlieren method
No full textA quantitative schlieren technique has been applied to measure the change of copper sulfate concentration in an electrochemical cell during the copper electroplating process. We constructed a mathematical model that correlates the grayscale values of schlieren images with the concentration of copper sulfate and analyzed the impact of refraction, reflection, and absorption of light during its passage through the solution on the precision of a schlieren quantitative analysis. Ultimately, by examining the temporal and spatial changes in the distribution of the copper sulfate concentration, we ascertained the impacts of convection, diffusion, and electromigration on the concentration distribution. The impact of the current studies would be greatly expanded in important electrochemical practices such as renewable energy conversions and rechargeable batteries. (c) 2024 Optica Publishing Grou
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