检索结果-内蒙古大学图书馆

Research on intelligent optimization separation technology of coal and gangue base on LS-FSVM by using a binary artificial sheep algorithm

引用

FUEL 2022年 319卷

作者： Zhou, Junpeng Guo, Yongcun Wang, Shuang Cheng, Gang Anhui Univ Sci & Technol State Key Lab Min Response & Disaster Prevent & C Huainan 232001 Peoples R China Anhui Univ Sci & Technol Sch Mech Engn Huainan 232001 Peoples R China

The separation of coal gangue is affected by various complicated factors. Noise, complex texture characteristics and sample isolation seriously affect the extraction of gangue. In order to improve the accuracy and stability of coal gangue separation, a coal gangue separation method based on artificial binary sheep algorithm optimized hyperplane membership fuzzy least squares support vector machine comprehensive feature classifier (BASA-LSFSVM) was proposed. The parameters of gray mean, gray frequency and entropy, energy, contrast and correlation were extracted from the gray matrix, and the parameters of fuzzy support vector machine classifier were optimized by artificial sheep binary algorithm. The improved BASA-LS-FSVM classification model was trained under the same sample. In order to verify the superiority of the model and algorithm, three comparison models are constructed: single feature classifier model, fusion feature classifier model and comprehensive feature classifier model. The synthetic feature classifier uses gray scale, texture and fusion features as the feature classifier model of normal plane least squares vector machine optimized by BASA, and trains the model under the same training samples. The training results show that the training correlation under the monomer characteristics has a better effect on the classification of characteristic quantity, and the sorting accuracy of coal gangue is 90% and 91%, respectively. The combined characteristic parameters of training frequency and ash have better separation effect, and the separation accuracy of gangue is higher. Under the comprehensive characteristics, the separation accuracy of coal gangue can reach 98% and 99%. The results show that the sorting effect is the best under the comprehensive characteristics. Compared with other models, the fitness function value of BASAA-NPFSVM model reached the optimal value in the 48th generation, and the separation accuracy of coal gangue reached 98% and 99%, respec

关键词： Coal and gangue Grayscale characteristic Texture characteristic binary artificial sheep algorithm Nonlinear low-pass filtering Fuzzy support vector machine

来源：评论

学校读者我要写书评

暂无评论

Network-constrained unit commitment with RE uncertainty and PHES by using a binary artificial sheep algorithm

引用

ENERGY 2019年 189卷

作者： Li, Chaoshun Wang, Wenxiao Wang, Jinwen Chen, Deshu Huazhong Univ Sci & Technol Sch Hydropower & Informat Engn Wuhan 430074 Peoples R China

With increasing share of renewable energy (RE) in power system, the unit commitment of hybrid power system have become more complicated due to network security demand and integration of pumped hydro energy storage (PHES). In this paper, a network-constrained unit commitment (NCUC) problem considering RE uncertainty and modulation of PHES has been raised. The NCUC model, with AC network security constraints and environmental constraints as well as traditional terms of constraints, is complicated to be solved. A novel binary artificial sheep algorithm (BASA) is used to solve the NCUC model. In the frame of BASA, the NCUC problem is decomposed as a master UC problem to determine start/stop status and economic load dispatch and a sub problem to check the AC network constraints. Based on the NCUC model and the solving method, the joint impacts of RE uncertainty and PHES have been studied. Test systems with different size have been adopted to verify the feasibility and effectiveness of the BASA. It is seen that the BASA has achieve an overall competitive performance on terms of operation cost and convergence speed by comparing it with existing methods. A modified IEEE 30-bus system with wind and photovoltaic power stations has been designed to reveal the impacts of RE and PHES. The results demonstrate that uncertainty of RE affects operation cost and security of the hybrid power system, and the adverse impact would aggravate as the RE forecasting error increase. The results also confirm the significant effect of PHES in restraining the negative influence of RE uncertainty. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Network-constrained unit commitment Renewable energy binary artificial sheep algorithm Scenario analysis Pumped hydro energy system

来源：评论

学校读者我要写书评

暂无评论

Study on unit commitment problem considering pumped storage and renewable energy via a novel binary artificial sheep algorithm

引用

APPLIED ENERGY 2017年 187卷 612-626页

作者： Wang, Wenxiao Li, Chaoshun Liao, Xiang Qin, Hui Huazhong Univ Sci & Technol Sch Hydropower & Informat Engn Wuhan 430074 Peoples R China

Wind power and photovoltaic power, two types of renewable energy (RE), have made large inroads into the power system. In this paper, we study a unit commitment (UC) problem that considers the uncertainty in RE and pumped hydro-energy storage (PHES). To improve the optimisation performance for this problem, we propose a novel heuristic algorithm called the binary artificial sheep algorithm (BASA) that is based on the social behaviour of sheep flock. To evaluate the effect of the uncertainty of RE, a scenario evaluation method is defined to assess quantitatively the stability and economy of the UC results with respect to different levels of RE forecasting errors. In addition, we investigate and analyse the effect of PHES on the UC problem. Three UC test systems with different RE and PHES combinations are used to verify the feasibility and effectiveness of the proposed BASA as well as its performance. The proposed BASA performed better than traditional fundamental metaheuristics in solving UC problems. Our results also demonstrated that the equivalent load fluctuation and operating costs of the thermal units will increase significantly with an increase in RE power forecast error, but the PHES can effectively counterbalance this adverse effect. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Unit commitment Wind power Photovoltaic power binary artificial sheep algorithm Scenario analysis Pumped hydro-energy system

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：