基于太阳能和燃气的多能互补系统热电负荷分配技术研究
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摘要
随着新能源大规模并网,多能互补是电网发展的必然趋势,对于拥有多台并列运行机组的热电联产电厂面临着基于厂级的负荷分配问题。本文通过研究光伏电站和燃气-蒸汽联合循环机组的运行特性,确定机组的调度限制范围,并选定典型日负荷曲线对多能互补系统进行调度计算,获得实时负荷分配结果;同时,通过对同一负荷下不同机组运行组合方式的研究,获得该负荷下最优的运行组合方式。仿真计算表明:对于本文的研究对象,两抽凝式组合气耗量最小,一背一抽式次之,3台机组同时运行气耗量较大,因此,在机组运行限度范围内,应优先选用两抽凝式运行组合方式;每日在11:00—22:00时间段采用3台机组同时运行,其余时间段内采用2台抽凝式机组运行,可以有效降低机组启停次数。该结论在实现节能降耗的同时,为热电负荷调度提供数据和理论支持。
With the large-scale integration of new energy sources, multi-energy complementary is an inevitable trend of power grid development. For cogeneration plants with multiple parallel operating units, they are faced with plant-level load distribution issues. By studying the operating characteristics of photovoltaic power plants and gas-steam combined cycle units, the scheduling limits are determined in this paper. The typical daily load curve is selected to complete the scheduling calculation for multi-energy complementary system, and the real-time load distribution results are obtained. Meanwhile, the optimal combination mode can be obtained through the research on different operation combination modes under the same load. The simulation calculations show that, the gas consumption of double-condensing unit operation mode is the least, followed by a back and a condensing unit operation mode. The gas consumption of three-unit operating mode is the most. Therefore, within the operating limits, the double-condensing unit operation mode should be preferred. The three-unit operating mode should be operated simultaneously during the period of 11:00—22:00 to effectively reduce the number of starts and stops. It provides data and theoretical support for heat-electric load distribution while achieving energy saving and consumption reduction.
With the large-scale integration of new energy sources, multi-energy complementary is an inevitable trend of power grid development. For cogeneration plants with multiple parallel operating units, they are faced with plant-level load distribution issues. By studying the operating characteristics of photovoltaic power plants and gas-steam combined cycle units, the scheduling limits are determined in this paper. The typical daily load curve is selected to complete the scheduling calculation for multi-energy complementary system, and the real-time load distribution results are obtained. Meanwhile, the optimal combination mode can be obtained through the research on different operation combination modes under the same load. The simulation calculations show that, the gas consumption of double-condensing unit operation mode is the least, followed by a back and a condensing unit operation mode. The gas consumption of three-unit operating mode is the most. Therefore, within the operating limits, the double-condensing unit operation mode should be preferred. The three-unit operating mode should be operated simultaneously during the period of 11:00—22:00 to effectively reduce the number of starts and stops. It provides data and theoretical support for heat-electric load distribution while achieving energy saving and consumption reduction.
引文
[1]卢胤龙,韩明新,任洪波,等.多能互补分布式能源系统优化设计研究进展[J].上海电力学院学报, 2018,34(3):229-235.LU Yinlong, HAN Mingxin, REN Hongbo, et al.Progress on the design optimization of hybrid distributed energy systems[J]. Journal of Shanghai University of Electric Power, 2018, 34(3):229-235.
[2]谭忠富,谭清坤,赵蕊.多能互补系统关键技术综述[J].分布式能源, 2017(5):4-13.TAN Zhongfu, TAN Qingkun, ZHAO Rui. Review of key technologies for multi energy complementary systems[J]. Distributed Energy, 2017(5):4-13.
[3] KOIRALA B P, KOLIOU E, FRIEGE J, et al. Energetic communities for community energy:a review of key issues and trends shaping integrated community energy systems[J]. Renewable and Sustainable Energy Reviews,2016, 56:722-744.
[4]上官小英,常海青,梅华强.太阳能发电技术及其发展趋势和展望[J].能源与节能, 2019(3):60-63.SHANGGUAN Xiaoying, CHANG Haiqing, MEI Huaqiang. Solar power generation technologies and their development trends and prospects[J]. Energy and Energy Conservation, 2019(3):60-63.
[5]辛培裕.太阳能发电技术的综合评价及应用前景研究[D].北京:华北电力大学, 2015:1-4.XIN Peiyu. Research on solar power technology economic evaluation and application prospect[D].Beijing:North China Electric Power University, 2015:1-4.
[6]刘威,刘春雷.太阳能集热在清洁能源供热的应用[J].应用能源技术, 2018(2):38-41.LIU Wei, LIU Chunlei. Solar energy collector is used in clean energy heating[J]. Applied Energy Technology,2018(2):38-41.
[7]战栋栋,张红,庄骏.槽式太阳能直接产蒸汽系统接收器的研究进展[J].热力发电, 2009, 38(3):10-13.ZHAN Dongdong, ZHANG Hong, ZHUANG Jun.Advancement in study on solar energy receiver for direct steam generation[J]. Thermal Power Generation, 2009,38(3):10-13.
[8]裴杰,赵苗苗,刘明义,等.太阳能与燃气-蒸汽联合循环发电系统优化[J].热力发电, 2016, 45(1):122-125.PEI Jie, ZHAO Miaomiao, LIU Mingyi, et al.Optimization of Fresnel solar and gas-steam combined cycle hybrid power generation system[J]. Thermal Power Generation, 2016, 45(1):122-125.
[9]林汝谋,韩巍,金红光,等.太阳能互补的联合循环(ISCC)发电系统[J].燃气轮机技术, 2013, 26(2):1-15.LIN Rumou, HAN Wei, JIN Hongguang, et al. The integrated solar combined cycle power generation system[J]. Gas Turbine Technology, 2013, 26(2):1-15.
[10]黄廷辉,柴胜凯,庞顺,等.热电联产机组热、电负荷优化分配[J].热力发电, 2010, 39(12):1-4.HUANG Tinghui, CHAI Shengkai, PANG Shun, et al.Optimization of thermal and electrical load distribution for the cogeneration unit[J]. Thermal Power Generation,2010, 39(12):1-4.
[11]吴龙,袁奇,刘昕.供热机组热电负荷最佳分配方法分析[J].中国电机工程学报, 2012, 32(35):6-12.WU Long, YUAN Qi, LIU Xin. Research on the scheme of optimal load distribution for cogeneration units[J].Proceedings of the CSEE, 2012, 32(35):6-12.
[12]谢毅霏,卫鹏杰,张建伟.动态寻优法在供热机组热电负荷优化分配中的应用[J].山西电力, 2014(1):42-44.XIE Yifei, WEI Pengjie, ZHANG Jianwei. Application of dynamic optimization method in the optimization of heat and power load distribution of heating unit[J]. Shanxi Electric Power, 2014(1):42-44.
[13]杨允,张士杰,肖云汉.环境温度对燃气轮机分布式供能系统优化配置的影响[J].热能动力工程, 2013,28(4):345-351.YANG Yun, ZHANG Shijie, XIAO Yunhan. Influence of the ambient temperature on the optimized configuration of a gas-turbine-based distributed energy supply system[J].Journal of Engineering for Thermal Energy and Power,2013, 28(4):345-351.
[14]梁俊宇,赵明,李鹏飞,等.基于数据挖掘的火电机组主要参数基准值获取方法[J].热力发电, 2015, 44(1):73-76.LIANG Junyu, ZHAO Ming, LI Pengfei, et al. Data mining based determination method of main parameter benchmark values for power plants[J]. Thermal Power Generation, 2015, 44(1):73-76.
[15]宋鸣程,贾立,叶灵芝.基于Spark的火电大数据挖掘方法的研究[J].控制工程, 2018, 25(12):2158-2165.SONG Mingcheng, JIA Li, YE Lingzhi. The research of big data mining of thermal power method based on spark[J]. Control Engineering of China, 2018, 25(12):2158-2165.
[2]谭忠富,谭清坤,赵蕊.多能互补系统关键技术综述[J].分布式能源, 2017(5):4-13.TAN Zhongfu, TAN Qingkun, ZHAO Rui. Review of key technologies for multi energy complementary systems[J]. Distributed Energy, 2017(5):4-13.
[3] KOIRALA B P, KOLIOU E, FRIEGE J, et al. Energetic communities for community energy:a review of key issues and trends shaping integrated community energy systems[J]. Renewable and Sustainable Energy Reviews,2016, 56:722-744.
[4]上官小英,常海青,梅华强.太阳能发电技术及其发展趋势和展望[J].能源与节能, 2019(3):60-63.SHANGGUAN Xiaoying, CHANG Haiqing, MEI Huaqiang. Solar power generation technologies and their development trends and prospects[J]. Energy and Energy Conservation, 2019(3):60-63.
[5]辛培裕.太阳能发电技术的综合评价及应用前景研究[D].北京:华北电力大学, 2015:1-4.XIN Peiyu. Research on solar power technology economic evaluation and application prospect[D].Beijing:North China Electric Power University, 2015:1-4.
[6]刘威,刘春雷.太阳能集热在清洁能源供热的应用[J].应用能源技术, 2018(2):38-41.LIU Wei, LIU Chunlei. Solar energy collector is used in clean energy heating[J]. Applied Energy Technology,2018(2):38-41.
[7]战栋栋,张红,庄骏.槽式太阳能直接产蒸汽系统接收器的研究进展[J].热力发电, 2009, 38(3):10-13.ZHAN Dongdong, ZHANG Hong, ZHUANG Jun.Advancement in study on solar energy receiver for direct steam generation[J]. Thermal Power Generation, 2009,38(3):10-13.
[8]裴杰,赵苗苗,刘明义,等.太阳能与燃气-蒸汽联合循环发电系统优化[J].热力发电, 2016, 45(1):122-125.PEI Jie, ZHAO Miaomiao, LIU Mingyi, et al.Optimization of Fresnel solar and gas-steam combined cycle hybrid power generation system[J]. Thermal Power Generation, 2016, 45(1):122-125.
[9]林汝谋,韩巍,金红光,等.太阳能互补的联合循环(ISCC)发电系统[J].燃气轮机技术, 2013, 26(2):1-15.LIN Rumou, HAN Wei, JIN Hongguang, et al. The integrated solar combined cycle power generation system[J]. Gas Turbine Technology, 2013, 26(2):1-15.
[10]黄廷辉,柴胜凯,庞顺,等.热电联产机组热、电负荷优化分配[J].热力发电, 2010, 39(12):1-4.HUANG Tinghui, CHAI Shengkai, PANG Shun, et al.Optimization of thermal and electrical load distribution for the cogeneration unit[J]. Thermal Power Generation,2010, 39(12):1-4.
[11]吴龙,袁奇,刘昕.供热机组热电负荷最佳分配方法分析[J].中国电机工程学报, 2012, 32(35):6-12.WU Long, YUAN Qi, LIU Xin. Research on the scheme of optimal load distribution for cogeneration units[J].Proceedings of the CSEE, 2012, 32(35):6-12.
[12]谢毅霏,卫鹏杰,张建伟.动态寻优法在供热机组热电负荷优化分配中的应用[J].山西电力, 2014(1):42-44.XIE Yifei, WEI Pengjie, ZHANG Jianwei. Application of dynamic optimization method in the optimization of heat and power load distribution of heating unit[J]. Shanxi Electric Power, 2014(1):42-44.
[13]杨允,张士杰,肖云汉.环境温度对燃气轮机分布式供能系统优化配置的影响[J].热能动力工程, 2013,28(4):345-351.YANG Yun, ZHANG Shijie, XIAO Yunhan. Influence of the ambient temperature on the optimized configuration of a gas-turbine-based distributed energy supply system[J].Journal of Engineering for Thermal Energy and Power,2013, 28(4):345-351.
[14]梁俊宇,赵明,李鹏飞,等.基于数据挖掘的火电机组主要参数基准值获取方法[J].热力发电, 2015, 44(1):73-76.LIANG Junyu, ZHAO Ming, LI Pengfei, et al. Data mining based determination method of main parameter benchmark values for power plants[J]. Thermal Power Generation, 2015, 44(1):73-76.
[15]宋鸣程,贾立,叶灵芝.基于Spark的火电大数据挖掘方法的研究[J].控制工程, 2018, 25(12):2158-2165.SONG Mingcheng, JIA Li, YE Lingzhi. The research of big data mining of thermal power method based on spark[J]. Control Engineering of China, 2018, 25(12):2158-2165.