Journal of Computational Methods in Sciences and Engineering - Volume 24, issue 1 - Journals (2024)

Section A: Mathematics and Engineering Section B: Computer Science

Article Type: Other

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 1-1, 2024

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Calculation method of carbon flow distribution in load-intensive regional energy centers

Authors: Wang, Songcen | Chen, Hongyin | Li, Dezhi | Li, Jianfeng | Liu, Kaicheng | Zhong, Ming | Jia, Xiaoqiang | Jin, Lu

Article Type: Research Article

Abstract: With the development of the economy, people’s demand for green energy has increased significantly. However, the traditional single fossil energy supply system cannot meet the needs of low-carbon. Therefore, this study employs energy hub to establish a multi-energy flow network that enables the integration of carbon flow within the network. Additionally, by utilizing the multi-energy flow trend, a carbon flow tracking method is adopted to achieve real-time carbon flow calculation. Results show that this network calculates the electricity cost of 20043 yuan, gas cost of 67253 yuan, and carbon emission cost of 3152 yuan. Compared with the traditional energy flow …system, gas cost is reduced by 4.3% and 1.7%, electricity cost by 21.3% and 15.0%, and carbon emission cost by 8.7% and 6.6%. The two-way sharing carbon flow calculation model calculates that the user side and power supply side of the node each bear half of the network loss, proving two-way sharing effectiveness. Test results on IEEE5 machine 14-node system show that the calculation method can accurately find high-emission and low-emission areas, making the carbon emission allocation between power generation and user more fair and reasonable. This research can effectively reduce emissions cost, accurately calculate emissions flow in real time, and facilitate reasonable emission reduction planning. Show more

Keywords: Energy supply, energy hub, carbon flow, tidal current, green and environmentally friendly energy, multi energy flow power flow network

DOI: 10.3233/JCM-247175

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 3-18, 2024

Price: EUR 27.50

Integrated energy system evaluation and optimization based on integrated evaluation model and time-series optimization

Authors: Li, Lixin | Lv, Yan | Sun, Bo | Wang, Miao | Chen, Bin | Li, Zeke | Fan, Haiwei

Article Type: Research Article

Abstract: Against the backdrop of global attention to climate change and environmental sustainability, the development timing and comprehensive cost of regional renewable energy power generation projects have become a focus of attention. By constructing effective models to evaluate them, it can help promote the healthy development of renewable energy projects. The research aims to quantitatively evaluate the development status of local renewable energy projects by constructing a comprehensive evaluation model, minimize information loss, and improve the accuracy of evaluation results. This study adopted a comprehensive evaluation model that combines Analytic Hierarchy Process (AHP) based on accelerated genetic algorithm, entropy weight method, …and ideal point method. Firstly, the subjective weights of the development evaluation indicators for regional renewable energy power generation projects are calculated. Secondly, the entropy weight method is used to analyze the trend of each indicator and obtain objective weights. Finally, combined with the objective weights and the evaluation results calculated using the TOPSIS method, a comprehensive evaluation of renewable energy power generation projects in various regions is conducted. Through analysis, the core indicators of the development level of renewable energy power generation projects in various regions show specific performance, such as Hebei’s evaluation value of 0.4945 in the proportion of comprehensive energy development, and Inner Mongolia’s evaluation value of 0.4045 in the proportion of comprehensive energy installed capacity. Meanwhile, genetic optimization methods exhibit significant advantages in the calculation of optimization schemes compared to dynamic programming methods, possessing strong global search capabilities and high-precision solutions. This study provides a new research method and approach for the evaluation of regional renewable energy power generation projects, demonstrating the practical value and certain advantages of the research method. Show more

Keywords: Integrated evaluation model, timing optimization, energy system, renewable energy, power generation projects, sustainable, AGA-AHP

DOI: 10.3233/JCM-247173

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 19-36, 2024

Price: EUR 27.50

A day-ahead coordinated scheduling strategy for source storage and load considering demand response and lines loss

Authors: Meng, Junxia | Deng, Hanjun | Yu, Minqi | Yang, Shuai | Tan, Huang | Chen, Hongyin

Article Type: Research Article

Abstract: Day-ahead scheduling strategy is an effective way to improve the renewable energy accommodation. To increase the renewable energy accommodation in the regional power grids, reduce the total costs of the power system, and improve the supply reliability of the power system, this research suggests a multi-time-scale “source-storage-load” coordinated dispatching strategy that considers the distribution and characteristics of pumped energy storage and loss of the network. Taking the wind curtailment penalty costs, the system operating costs, and the load loss penalty costs as the objective functions, a day-ahead coordinated scheduling strategy for source storage and load considering demand response and lines …loss is established. Finally, the commercial software package CPLEX is called through the MATLAB platform to complete the optimization of mixed integer programming. Simulation results shows that the proposed scheduling strategy could build the power generation plant, effectively adjust the output power of pumped storage, and regulate the assumption of translationable load and transferable load. Show more

Keywords: Day-ahead coordinated scheduling strategy, line loss, source-storage-load, CPLEX, renewable energy

DOI: 10.3233/JCM-247171

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 37-49, 2024

Price: EUR 27.50

Internal revenue sharing methodology for virtual power plant clusters considering carbon incentive and penalty mechanisms

Authors: Gong, Taorong | Chen, Songsong | Shi, Kun | Chai, Zhichao | Wang, Yu

Article Type: Research Article

Abstract: With the rapid development of renewable energy and the urgent need for global carbon emission reduction, virtual power plants have become a high-profile energy management model that can integrate multiple energy resources. How to effectively integrate renewable energy to reduce carbon emissions, how to optimize the use of different energy resources, and how to fairly distribute economic benefits within virtual power plant clusters while encouraging the reduction of carbon emissions are issues that need to be addressed in research. The study first established a virtual power plant model and conducted in-depth optimization for its economic and environmental indicators. Subsequently, the …study constructed a game model within the virtual power plant cluster, aiming to solve the problem of income distribution in this diversified energy system. The research results found that commercial users have the highest carbon emissions, followed by industrial users, while residential users have the lowest carbon emissions. In terms of optimized user electricity consumption behavior, the peak-to-valley difference rate of industrial users has been reduced by 17%, and the daily load rate has increased by 6%; the peak-to-valley difference rate of commercial users has been reduced by 12%, and the daily load rate has increased by 6%; The peak-to-trough difference rate for residential users decreased by 8%, and the daily load rate increased by 4%. In addition, the research also proposes a method of internal revenue distribution of virtual power plant clusters based on a carbon reward and punishment mechanism, which provides a new way for the synergy effects and economic benefit distribution of virtual power plants. Research is of positive significance in solving pressing issues in the field of energy management and provides strong support for the development of future sustainable energy systems. Show more

Keywords: Virtual power plant, carbon reward and punishment mechanism, internal revenue sharing, shapley value model, IBDR

DOI: 10.3233/JCM-247169

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 51-68, 2024

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A multi-timescale optimization method for integrated energy systems with carbon capture and accounting

Authors: Wang, Yu | Tang, Bihong

Article Type: Research Article

Abstract: As the goal of “double carbon”, integrated energy systems aiming at the development of low-carbon economy are developing rapidly, and carbon capture and other emission reduction technologies are gradually gaining more extensive development space. For controlling carbon emissions and enhance the consumption of renewable energy. This work proposes to introduce carbon capture technology in the framework of integrated energy system and optimize the energy dispatching of integrated energy system in multiple time scales, and design a multi-time scale optimization model of integrated energy system with carbon capture. Based on the basic architecture of a low-carbon integrated energy system, this study …analyzes the power characteristics of each unit of the integrated energy system, which consists of thermal power units, gas turbines, electric boilers, batteries, gas storage, heat storage, etc. By studying the energy conversion and storage processes of each unit, a power model of each unit of the integrated energy system is established. On this basis, the relationship between carbon emissions and unit output of thermal power units and gas turbines was studied, and a carbon emission model for the energy supply unit in the comprehensive energy system was established. At the same time, in order to solve the problem of carbon emission reduction under the day ahead scheduling plan of the integrated energy system, considering the emission reduction goals and system operation security factors, the study analyzed the economic model and carbon emission model of the integrated energy system, established the day ahead low-carbon scheduling model of the integrated energy system, and reasonably planned the output of each unit that can achieve the carbon emission reduction goals on the premise of meeting the balance of supply and demand. The innovation of the research method of this paper is that this paper establishes a multi time scale rolling optimization model under the emission reduction goal of the integrated energy system. Based on the day ahead scheduling scheme obtained in the day ahead low-carbon scheduling phase, the day ahead plan is first revised through 4 h rolling scheduling in the day; Then, with the goal of minimizing the adjustment amount, fine tune the unit output within 15 minutes to provide a daily output plan for subsequent low-carbon emission reduction targets. The outcomes indicate that in the practical application, the carbon emission of the optimized model in the peak hour 11:00 to 12:00 phase is 118 tons, which is 7 tons less than the 125 tons of the traditional model. In summary, it demonstrates that the studied multi-timescale optimization model of integrated energy system with carbon capture has good application. We have studied and analyzed the low-carbon implementation mechanism of coordinated cooperation in multiple time scales, and constructed a multi time scale rolling optimization model, laying a theoretical foundation for subsequent low-carbon scheduling research. This enables the system to formulate more accurate and reasonable scheduling plans, while improving the low-carbon performance and economic benefits of the system, providing reference for the low-carbon development of the power system. Show more

Keywords: Carbon capture, multiple time scales, integrated energy systems, optimal dispatch, low carbon economy, energy conversion

DOI: 10.3233/JCM-247166

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 69-86, 2024

Price: EUR 27.50

A study on the innovative model of foreign language teaching in universities using big data corpus

Authors: Zhao, Ying | Liang, Genshun

Article Type: Research Article

Abstract: This paper aims to explore unsupervised cross-lingual word representation learning methods with the specific task of acquiring a bilingual translation lexicon on a monolingual corpus. Specifically, an unsupervised cross-lingual word representation co-training scheme based on different word embedding models is first designed and outperforms the baseline model. In this paper, we adeptly tackles the obstacles encountered in higher education foreign language teaching and underscores the necessity for inventive teaching methods, and design and implement a linear self-encoder-based principal component acquisition scheme for the interpoint mutual information matrix obtained from a monolingual corpus. And on top of this, a collaborative training …scheme based on linear self-encoder for cross-language word representation is designed to improve the learning effect of cross-language word embedding. The results of the study show that the most obvious rise in the pre and post tests of the experimental class in the practical application of the foreign language teaching model based on the method of this paper is the word sense guessing, which rose by 23.12%. Sentence meaning comprehension increased by 23.39%, main idea by 16.61%, factual details by 15.47%, and inferential judgment by 10.28%. Thus, the feasibility of the unsupervised cross-linguistic word representation learning collaborative training method is further verified. Show more

Keywords: Collaborative training, unsupervised learning, monolingual corpus, cross-lingual word representation, foreign language teaching

DOI: 10.3233/JCM-237113

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 87-103, 2024

Price: EUR 27.50

Validation study of Yunnan ethnic culture industry stock model under epidemic situation based on chaotic particle swarm optimization neural networks

Authors: Jiang, Jiaying | Wang, Zhixiu | Tao, Sha | Tan, Xinyi | He, Ying | Pan, Wenchao

Article Type: Research Article

Abstract: The new crown pneumonia epidemic is raging, in the context of global integration, the scope of the impact of this sudden event spread around the world, the stock market has not been spared, the financial risk has increased dramatically compared with the past, the emergence of the epidemic has led to the spread of investor panic, March 2020, the U.S. S&P 500 index appeared in the four plunge, and led to the market trading meltdown, the world’s financial markets have had an extremely serious impact. The study of the impact of Xin Guan Pneumonia on the company’s stock returns is …not only conducive to enriching the theoretical study of public health emergencies, but also conducive to improving the coping strategy, stabilizing the general economic market, and enhancing the public’s awareness of risk response. This paper compares the effect of the four intelligent algorithms of chaotic particle swarm algorithm, chaotic bee colony algorithm, chaotic fruit fly algorithm and chaotic ant colony algorithm combined with neural network on the prediction of the stock price trend of Yunnan national culture, and the study shows that the speed of convergence of the chaotic particle swarm optimization neural network and the speed of descent is better than that of the two models of chaotic fruit fly and chaotic bee colony, and the coefficients of decision of the chaotic particle swarm optimization neural network are higher than that of the other three models, and the errors are lower than the other three models. Indexes are lower than the other three models and have high accuracy in stock prediction of Yunnan ethnic culture, this finding emphasizes the potential of PSO-BP model to provide robust stock market prediction, which is important for both investors and policy makers in dealing with volatile market conditions. Show more

Keywords: Chaotic particle swarm optimization algorithm, BP neural network, ethnic culture of yunnan, stock prediction

DOI: 10.3233/JCM-237119

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 105-120, 2024

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Enhancing urban emergency management: A two-stage network DEA analysis of Chinese cities

Authors: Zhou, Fangjian | Guo, Hua | Lei, Yinchun | Tang, Chengling | Mo, Xiaoyin

Article Type: Research Article

Abstract: In order to scientifically evaluate the emergency management capabilities of major cities in China, this article conducts a comprehensive study on the input and output indicators of emergency response in each city. A two-stage network DEA model was used to construct an evaluation model that reflects the emergency management capacity of cities. A dataset containing emergency management data from 36 well-known cities in China was selected to effectively evaluate its performance, and the city that demonstrated the most effective input-output ratio in the field of emergency management was ultimately determined. The research results show that using a two-stage network DEA …model as the foundation to construct an evaluation model that reflects urban emergency management capabilities can promote a wise combination of subjective and objective evaluations, and achieve scientific investment in urban emergency assets. Show more

Keywords: Emergency management, novel network DEA, data envelopment analysis, radial distance

DOI: 10.3233/JCM-237115

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 121-133, 2024

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Application of BPNN’s intelligent ETQ model in network English teaching

Authors: Wu, Qianqian

Article Type: Research Article

Abstract: Teaching evaluation is a key initiative to improve the quality of education and teaching. The research significance of this study is rooted in addressing the limitations of the traditional evaluation of teaching quality (ETQ) model, which often relies on a single evaluation index, exhibits a one-sided perspective, and suffers from pronounced subjectivity. In this context, this paper delves into the application of the backpropagation neural network (BPNN) to enhance and refine the ETQ model. The intelligent ETQ model was constructed and utilized in network English teaching to enhance the effect and quality of network English teaching. By analyzing the characteristics …and needs of network English teaching, the advantages of BPNN in the ETQ were explored. The intelligent evaluation model was constructed, and its application effect in network English teaching was studied and evaluated. The total number of students satisfied with the BPNN based network English ETQ model was 151, with a total satisfaction rate of 75.5%. The ETQ model on the basis of BPNN was applied to network English teaching, which helped the average final score of Class 2 improve by 5.44 points compared to the division exam. The ETQ model based on BPNN was applied to network English teaching, which can improve the rationality of teaching evaluation and help improve students’ school English proficiency. Show more

Keywords: Network english teaching, evaluation of teaching quality, back propagation neural network, evaluating indicator, analytic hierarchy process, radial basis function

DOI: 10.3233/JCM-237117

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 1, pp. 135-151, 2024

Price: EUR 27.50