Search results for: Dongxiao Niu

Items from 1 to 20 out of 99 results

article

Travel costs, trade, and market segmentation: Evidence from China's high‐speed railway

Dongxiao Niu, Weizeng Sun, Siqi Zheng

Papers in Regional Science > 99 > 6 > 1799 - 1825

Using high‐speed railway construction as a natural experiment, this paper contributes to our understanding of how passenger‐oriented transportation infrastructure affects inter‐regional trade. The findings show that trade value increases and market segmentation decreases with high‐speed railway (HSR) expansion, indicating that movement of people fosters movement of freight. The heterogeneous analyses...

article

Prediction of end-use energy consumption in a region of Northwest China

Xing Yang, Hui Kang, Dongxiao Niu

Wuhan University Journal of Natural Sciences > 2018 > 23 > 1 > 25-30

End-use energy consumption can reflect the industrial development of a country and the living standards of its residents. The study of end-use energy consumption can provide a solid basis for industrial restructuring, energy saving, and emission reduction. In this paper, we analyzed the end-use energy consumption of a region in Northwestern China, and applied the Markov prediction method to forecast...

article

Analysis of wind turbine micrositing efficiency: An application of two-subprocess data envelopment analysis method

Dongxiao Niu, Zongyun Song, Xinli Xiao, Yuwei Wang

Journal of Cleaner Production > 2018 > 170 > C > 193-204

China has encountered a huge challenge in the process of wind development due to serious wind curtailment and lower generation efficiency. Inferior wind turbines micrositing is the main reason leading to such problems. In order to better assess the wind turbines micrositing of wind farms (WF) in China, two-subprocess data envelopment analysis (DEA) model is proposed. The improved DEA model divides...

article

Intelligent Forecasting Model for Regional Power Grid With Distributed Generation

Xiaomin Xu, Dongxiao Niu, Qiong Wang, Peng Wang, more

IEEE Systems Journal > 2017 > 11 > 3 > 1836 - 1845

With the rapid growth of energy demand, environmental and energy security issues have gain more and more attention recently. Distributed generation (DG), as one of the innovation energy power modes, has been rapidly developing in recent years. Thus, accurate prediction of distributed power load is significant for the balance of power supply and demand. This paper presents an intelligent model with...

article

Incorporating the influence of China's industrial capacity elimination policies in electricity demand forecasting

Zongyun Song, Dongxiao Niu, Shuyu Dai, Xinli Xiao, more

Utilities Policy > 2017 > 47 > C > 1-11

Elimination of high-emitting industrial capacity can be an effective way to control and relieve air pollution but it will also influence demand. Accurate forecasting of electricity demand requires consideration of the impact of capacity elimination policies. This paper applies a modified firefly algorithm improved by Gaussian disturbance to optimize the parameters of Support Vector Machine (SVM) in...

article

Integration of solar technology to modern greenhouse in China: Current status, challenges and prospect

Tianyue Wang, Gaoxiang Wu, Jiewei Chen, Peng Cui, more

Renewable and Sustainable Energy Reviews > 2017 > 70 > C > 1178-1188

Given the threat of environmental degradation and land deterioration to conventional agriculture, modern greenhouse cultivation has attracted increasing attention as an effective alternative. However, the high energy consumption of greenhouse systems is concerning given the need to limit the environmental impact of human activities. The solar integration to agricultural greenhouse in the form of modern...

article

Focus on the current competitiveness of coal industry in China: Has the depression time gone?

Zongyun Song, Dongxiao Niu, Xinli Xiao

Resources Policy > 2017 > 51 > C > 172-182

Since 2012 the coal industry in China has deeply fallen into depression. When entering into 2015, the tragedy continued. What the future of China's coal is has confused the scholars and managers. In order to evaluate the current competitiveness of coal industry in China, the diamond model is employed in present study to analyze the influence of six components on the competitiveness, namely factor...

article

Exploring the impact of determining factors behind CO2 emissions in China: A CGE appraisal

Bowen Xiao, Dongxiao Niu, Han Wu

Science of The Total Environment > 2017 > 581-582 > C > 559-572

Along with the arrival of the post-Kyoto Protocol era, the Chinese government faces ever greater pressure to reduce greenhouse gases (GHGs). Hence, this paper aims to discuss the drivers of carbon dioxide (CO₂) emissions and their impact on society as a whole. First, we analyzed the background and overall situations of CO₂ emissions in China. Then, we reviewed previous studies to explore the determinants...

article

Power Grid Development Level Evaluation Based on Adaptive Neural-fuzzy Inference System

Han Wu, Dongxiao Niu, Weidong Liu, Ke Sun

Procedia Engineering > 2017 > 174 > C > 850-857

In allusion to the assessment of development level of power grid, consistency analysis is still insufficient. It is significant to make more research on how to adopt adaptive self-learning algorithm to determine the development level of power grid according to its own characteristics. Therefore, an adaptive neural-fuzzy inference system (ANFIS) based on principal component analysis(PCA) was proposed...

article

Greenhouse gas emission factors of purchased electricity from interconnected grids

Ling Ji, Sai Liang, Shen Qu, Yanxia Zhang, more

Applied Energy > 2016 > 184 > C > 751-758

Electricity trade among power grids leads to difficulties in measuring greenhouse gas (GHG) emission factors of purchased electricity. Traditional methods assume either electricity purchased from a grid is entirely produced locally (Boundary I) or imported electricity is entirely produced by the exporting grid (Boundary II) (in fact a blend of electricity produced by many grids). Both methods ignore...

article

Can China achieve its 2020 carbon intensity target? A scenario analysis based on system dynamics approach

Bowen Xiao, Dongxiao Niu, Xiaodan Guo

Ecological Indicators > 2016 > 71 > C > 99-112

Since Chinese government put a target to decrease carbon intensity 40–45% in 2020 than that of 2005, a series of emission mitigation measures has been implemented. Against this backdrop, we established a system dynamics model to investigate the energy consumption, CO₂ emission and mitigation options in China. The results show that the carbon intensity will reduce by 22.68%, 26.84%, 43.77%, and 46...

article

Can natural gas-fired power generation break through the dilemma in China? A system dynamics analysis

Bowen Xiao, Dongxiao Niu, Xiaodan Guo

Journal of Cleaner Production > 2016 > 137 > C > 1191-1204

Recently, the share of natural gas in the generation of electricity has shown a dramatic increase in China. However, the domestic natural gas source, natural gas price and unclear policy environment are the barriers lying on the development way of natural gas power generation. This paper aims to evaluate development pattern and constraints in the development of China's natural gas power generation...

article

Have market-oriented reforms improved the electricity generation efficiency of China's thermal power industry? An empirical analysis

Ming Meng, Sarah Mander, Xiaoli Zhao, Dongxiao Niu

Energy > 2016 > 114 > C > 734-741

In 2003, China implemented market-oriented reforms to its electric power industry, aimed at improving the generation efficiency of its thermal power plants. In this paper, we use the polynomial functions, PLS (partial least squares) algorithm, and generation efficiency data from 1993 to 2012 to evaluate the effect of these reforms. Empirical analysis shows that the reforms caused a sudden down shift...

chapter

Risk Management Evaluation Based on Elman Neural Network for Power Plant Construction Project

Yongli Wang, Dongxiao Niu, Mian Xing

Studies in Computational Intelligence > Advances in Intelligent Information and Database Systems > Computational Intelligence > 315-324

Risk management is very important to the power construction. The power plant construction project risk management means the uncertain influence on construction project goals and production operation management throughout the life cycle which could cause the losses made by uncertain events. The purpose of this paper is to establish an evaluation model for risk management evaluation. Firstly, the method...

chapter

An AFSA-TSGM Based Wavelet Neural Network for Power Load Forecasting

Dongxiao Niu, Zhihong Gu, Yunyun Zhang

Lecture Notes in Computer Science > Advances in Neural Networks – ISNN 2009 > Applications I > 1034-1043

An intelligent methodology for power load forecasting was developed. In this forecasting system, wavelet neural network techniques were used in combination with a new evolutionary learning algorithm. The new evolutionary learning algorithm introduced the Tabu Search Algorithm and Genetic Mutation Operator into Artificial Fish Swarm Algorithm (AFSA) to construct a hybrid optimizing algorithm, and is...

chapter

A Short-Term Load Forecasting Model Based on LS-SVM Optimized by Dynamic Inertia Weight Particle Swarm Optimization Algorithm

Dongxiao Niu, Bingen Kou, Yunyun Zhang, Zhihong Gu

Lecture Notes in Computer Science > Advances in Neural Networks – ISNN 2009 > Support Vector Machines and Kernel Methods > 242-250

Short-term load forecasting is very important for power system, how to improve the accuracy of load forecasting is the keystone people pay attention to. A combined model of least squares support vector machines optimized by an improved particle swarm. Optimization algorithm is proposed in this paper to do the short-term load forecasting. Least squares support vector machines (LS-SVM) are new kinds...

chapter

SVM Model Based on Particle Swarm Optimization for Short-Term Load Forecasting

Yongli Wang, Dongxiao Niu, Weijun Wang

Lecture Notes in Computer Science > Advances in Neural Networks - ISNN 2008 > Applications of Neural Networks in Electronic Engineering > 642-649

A model integrating Particle Swarm Optimization (PSO) and support vector machines (SVM) is presented to forecast short-term load of electric power systems in this paper. PSO is a method for finding a solution of stochastic global optimizer based on swarm intelligence. Using the interaction of particles, PSO searches the solution space intelligently and finds out the best one. The PSO-SVM method proposed...

chapter

Optimization of Short-Term Load Forecasting Based on Fractal Theory

Yongli Wang, Dongxiao Niu, Ling Ji

Studies in Computational Intelligence > New Challenges for Intelligent Information and Database Systems > Data Mining and Computational Intelligence > 175-186

Power load forecasting is an important part in the planning of power transmission construction. Considering the importance of the peak load to the dispatching and management of the system, the error of peak load is proposed in this paper as criteria to evaluate the effect of the forecasting model. The accuracy of short term load forecasting is directly related to the operation of power generators...

chapter

Application of Short-Term Load Forecasting Based on Improved Gray-Markov Residuals Amending of BP Neural Network

Dongxiao Niu, Cong Xu, Jianqing Li, Yanan Wei

Lecture Notes in Computer Science > Advances in Swarm Intelligence > Intelligent Computing Methods and Applications > 564-569

For the characteristics of short-term load forecasting, we established load forecasting model based on BP neural network, combined the advantages of gray prediction and Markov forecasting, and make an amendment for the prediction residual, this has greatly improved the precision of prediction. Research has shown that neural network and gray - Markov residual error correction model has the value of...

chapter

Power Load Forecasting Using Data Mining and Knowledge Discovery Technology

Yongli Wang, Dongxiao Niu, Yakun Wang

Lecture Notes in Computer Science > Intelligent Information and Database Systems > Applications of Intelligent Systems > 319-328

Considering the importance of the peak load to the dispatching and management of the system, the error of peak load is proposed in this paper as criteria to evaluate the effect of the forecasting model. This paper proposes a systemic framework that attempts to used data mining and knowledge discovery (DMKD) pretreatment of the data. And a new model is proposed which combining artificial neural networks...

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INFONA - science communication portal

Search results for: Dongxiao Niu

Travel costs, trade, and market segmentation: Evidence from China's high‐speed railway

Prediction of end-use energy consumption in a region of Northwest China

Analysis of wind turbine micrositing efficiency: An application of two-subprocess data envelopment analysis method

Intelligent Forecasting Model for Regional Power Grid With Distributed Generation

Incorporating the influence of China's industrial capacity elimination policies in electricity demand forecasting

Integration of solar technology to modern greenhouse in China: Current status, challenges and prospect

Focus on the current competitiveness of coal industry in China: Has the depression time gone?

Exploring the impact of determining factors behind CO2 emissions in China: A CGE appraisal

Power Grid Development Level Evaluation Based on Adaptive Neural-fuzzy Inference System

Greenhouse gas emission factors of purchased electricity from interconnected grids

Can China achieve its 2020 carbon intensity target? A scenario analysis based on system dynamics approach

Can natural gas-fired power generation break through the dilemma in China? A system dynamics analysis

Have market-oriented reforms improved the electricity generation efficiency of China's thermal power industry? An empirical analysis

Risk Management Evaluation Based on Elman Neural Network for Power Plant Construction Project

An AFSA-TSGM Based Wavelet Neural Network for Power Load Forecasting

A Short-Term Load Forecasting Model Based on LS-SVM Optimized by Dynamic Inertia Weight Particle Swarm Optimization Algorithm

SVM Model Based on Particle Swarm Optimization for Short-Term Load Forecasting

Optimization of Short-Term Load Forecasting Based on Fractal Theory

Application of Short-Term Load Forecasting Based on Improved Gray-Markov Residuals Amending of BP Neural Network

Power Load Forecasting Using Data Mining and Knowledge Discovery Technology

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