娄素华, 杨印浩, 吴耀武, 马龙飞, 宋锐. 考虑大气污染物扩散时空特性的煤电机群发电调度及配煤协调优化[J]. 中国电机工程学报, 2020, 40(21): 6956-6964. DOI: 10.13334/j.0258-8013.pcsee.200006
引用本文: 娄素华, 杨印浩, 吴耀武, 马龙飞, 宋锐. 考虑大气污染物扩散时空特性的煤电机群发电调度及配煤协调优化[J]. 中国电机工程学报, 2020, 40(21): 6956-6964. DOI: 10.13334/j.0258-8013.pcsee.200006
LOU Su-hua, YANG Yin-hao, WU Yao-wu, MA Long-fei, SONG Rui. Coal-fired Power Generation Dispatch and Coal Blending Coordinated Optimization Considering the Spatiotemporal Characteristics of Atmospheric Pollutants Diffusion[J]. Proceedings of the CSEE, 2020, 40(21): 6956-6964. DOI: 10.13334/j.0258-8013.pcsee.200006
Citation: LOU Su-hua, YANG Yin-hao, WU Yao-wu, MA Long-fei, SONG Rui. Coal-fired Power Generation Dispatch and Coal Blending Coordinated Optimization Considering the Spatiotemporal Characteristics of Atmospheric Pollutants Diffusion[J]. Proceedings of the CSEE, 2020, 40(21): 6956-6964. DOI: 10.13334/j.0258-8013.pcsee.200006

考虑大气污染物扩散时空特性的煤电机群发电调度及配煤协调优化

Coal-fired Power Generation Dispatch and Coal Blending Coordinated Optimization Considering the Spatiotemporal Characteristics of Atmospheric Pollutants Diffusion

  • 摘要: 燃煤发电的污染物排放加重了近煤电区域空气质量的劣化,亟需在发电生产过程中针对煤电气载污染物浓度进行控制。深入分析煤电气载污染物扩散能力随不同气象条件的变化特征,基于源荷空间布局与时变的风速风向条件,采用高斯烟羽模型描述燃煤污染物扩散浓度的时空分布;提出考虑大气污染物扩散特性的煤电机群协调发电与配煤优化模型,将煤电发电调度和配煤优化问题协同建模,以较低的运行成本代价获得环境效益有效改善。IEEE 14节点系统的算例结果验证了所述模型与方法的有效性。

     

    Abstract: Pollutant emissions from coal-fired power generation aggravate the deterioration of air quality in areas near coal-fired power, and it is urgent to control the concentration of coal-borne pollutants during power generation. In this paper, the characteristics of the coal-borne pollutants diffusion capacity with different meteorological conditions were analyzed in depth. Based on the spatial distribution of source and load and the time-varying wind speed and wind direction conditions, Gaussian plume model was used to describe the spatiotemporal distribution of the concentration of coal-borne pollutants; The coal-fired power generations coordinated power generation and coal blending optimization model that takes into account the characteristics of atmospheric pollutants diffusion, co-models coal power generation scheduling and coal blending optimization issues, and obtains effective improvement in environmental benefits at a lower operating cost. The results of an IEEE 14-node system verified the effectiveness of the proposed model and method.

     

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