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      全球能源互联网

      第5卷 第4期 2022年07月;页码:383-397
      EN

      电-热综合能源系统优化调度综述

      Review of Optimal Scheduling of Integrated Electricity and Heat Systems

      朱浩昊 ,朱继忠* ,李盛林 ,董瀚江 ,何晨可 ,蓝静
      , , , , ,
      • 华南理工大学电力学院,广东省 广州市 510641
      • ZHU Haohao, ZHU Jizhong*, LI Shenglin, DONG Hanjiang, HE Chenke, LAN Jing (School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, Guangdong Province, China

      摘 要

      Abstract

      随着热电联产机组、热泵、电锅炉、空调等能量转换设备的普及,电力系统和热力系统之间的能量转换和信息交互日益密切,逐步形成了电-热综合能源系统。热电联合调度可以促进可再生能源消纳,提高电力系统灵活性。首先,分析电-热综合能源系统组成,包括电网、热网和耦合设备等。在此基础上,从能量枢纽、网络拓扑和统一能路等角度回顾电-热综合能源系统建模的发展历程。然后,基于解析法和人工智能法等评述现有电-热综合能源系统优化调度研究的异同,包括考虑不确定性的电-热综合能源系统随机优化运行和热电联合鲁棒优化调度。最后,总结热电联合调度关键科学问题并对未来研究方向予以展望。

      With the popularization of energy conversion equipment such as combined heat and power units, heat pumps,electric boilers, and air conditioners, energy conversion and information interaction between electric power systems (EPS)and district heating systems (DHS) have become increasingly close, gradually forming integrated electricity and heat systems(IEHS). Combined heat and power dispatch (CHPD) can promote renewable energy accommodation and improve the flexibility of EPS. First, the composition of IEHS is introduced,including electric power networks, district heating networks and coupling equipment. On this basis, the development history of IEHS modeling is reviewed from the perspectives of energy hub,network topology and energy circuit theory. Subsequently, based on analytical methods and artificial intelligence algorithms, the similarities and differences of existing research on combined heat and power dispatch are reviewed. Among them, stochastic optimal operation of IEHS considering uncertainty and robust optimal scheduling of IEHS are included. Finally, the key scientific issues of CHPD are summarized and the future research prospect are proposed.

      参考文献

      1. [1]

        Renewables 2021. Renewable energy policy network for the 21st century [R/OL]. (2021) [2022-05-05]. http://www.chinacaj.net/ueditor/php/upload/file/20210903/1630633637477894.pdf. [百度学术]

      2. [2]

        国家能源局. 国家能源局举行新闻发布会发布2021年可再生能源并网运行情况等并答问[EB/OL]. (2022-01-29) [2022-05-05]. http://www.gov.cn/xinwen/2022-01/29/content_5671076.htm. [百度学术]

      3. [3]

        LI J X, WANG D, JIA H J, et al. Prospects of key technologies of integrated energy systems for rural electrification in China[J]. Global Energy Interconnection, 2021, 4(1): 3-17. [百度学术]

      4. [4]

        国家能源局. 国家能源局2021年一季度网上新闻发布会文字实录[EB/OL]. (2022-01-30) [2022-05-05]. http://www.nea.gov.cn/2021-01/30/c_139708580.htm. [百度学术]

      5. [5]

        吴建中. 欧洲综合能源系统发展的驱动与现状[J]. 电力系统自动化,2016,40(5):1-7.WU Jianzhong. Drivers and state-of-the-art of integrated energy systems in Europe[J]. Automation of Electric Power Systems, 2016, 40(5): 1-7(in Chinese). [百度学术]

      6. [6]

        WIRTZ M, KIVILIP L, REMMEN P, et al. 5th generation district heating: a novel design approach based on mathematical optimization[J]. Applied Energy, 2020, 260: 114158. [百度学术]

      7. [7]

        刘学智,严正,解大,等. 电热综合能源网的强耦合路径研究与展望[J/OL]. 电力系统自动化,2022:1-16.LIU Xuezhi, YAN Zheng, XIE Da, et al.Research and prospects of a pathway to tight coupling between electricity and heat networks[J/OL]. Automation of Electric Power Systems, 2022:1-16(in Chinese). [百度学术]

      8. [8]

        朱继忠,董瀚江,李盛林,等. 数据驱动的综合能源系统负荷预测综述[J]. 中国电机工程学报,2021,41(23):7905-7924.ZHU Jizhong, DONG Hanjiang, LI Shenglin, et al. Review of data-driven load forecasting for integrated energy system[J].Proceedings of the CSEE, 2021, 41(23): 7905-7924(in Chinese). [百度学术]

      9. [9]

        朱继忠. 电网安全经济运行理论与技术[M]. 北京:中国电力出版社,2018. [百度学术]

      10. [10]

        李志刚. 消纳大规模风电的互联电网多维协同优化调度方法研究[D]. 北京:清华大学,2016. [百度学术]

      11. [11]

        KANG C Q, CHEN X Y, XU Q Y, et al. Balance of power:toward a more environmentally friendly, efficient, and effective integration of energy systems in China[J]. IEEE Power and Energy Magazine, 2013, 11(5): 56-64. [百度学术]

      12. [12]

        贺平. 供热工程[M]. 北京:中国建筑工业出版社,2009. [百度学术]

      13. [13]

        MANSON J R, WALLIS S G. An accurate numerical algorithm for advective transport[J]. Communications in Numerical Methods in Engineering, 1995, 11(12): 1039-1045. [百度学术]

      14. [14]

        GUELPA E, TORO C, SCIACOVELLI A, et al. Optimal operation of large district heating networks through fast fluiddynamic simulation[J]. Energy, 2016, 102: 586-595. [百度学术]

      15. [15]

        BENONYSSON A, BØHM B, RAVN H F. Operational optimization in a district heating system[J]. Energy Conversion and Management, 1995, 36(5): 297-314. [百度学术]

      16. [16]

        YANG J W, ZHANG N, BOTTERUD A, et al. On an equivalent representation of the dynamics in district heating networks for combined electricity-heat operation[J]. IEEE Transactions on Power Systems, 2020, 35(1): 560-570. [百度学术]

      17. [17]

        GEIDL M, KOEPPEL G, FAVRE-PERROD P, et al. Energy hubs for the future[J]. IEEE Power and Energy Magazine,2007, 5(1): 24-30. [百度学术]

      18. [18]

        王伟亮,王丹,贾宏杰,等. 能源互联网背景下的典型区域综合能源系统稳态分析研究综述[J]. 中国电机工程学报,2016,36(12):3292-3306.WANG Weiliang, WANG Dan, JIA Hongjie, et al. Review of steady-state analysis of typical regional integrated energy system under the background of energy Internet[J]. Proceedings of the CSEE, 2016, 36(12): 3292-3306(in Chinese). [百度学术]

      19. [19]

        SALEHIMALEH M, AKBARIMAJD A, VALIPOUR K, et al.Generalized modeling and optimal management of energy hub based electricity, heat and cooling demands[J]. Energy, 2018,159: 669-685. [百度学术]

      20. [20]

        ELADL A A, EL-AFIFI M I, SAEED M A, et al. Optimal operation of energy hubs integrated with renewable energy sources and storage devices considering CO2 emissions[J].International Journal of Electrical Power & Energy Systems,2020, 117: 105719. [百度学术]

      21. [21]

        AYELE G T, HAURANT P, LAUMERT B, et al. An extended energy hub approach for load flow analysis of highly coupled district energy networks: illustration with electricity and heating[J]. Applied Energy, 2018, 212: 850-867. [百度学术]

      22. [22]

        LIU N, TAN L, SUN H N, et al. Bilevel heat-electricity energy sharing for integrated energy systems with energy hubs and prosumers[J]. IEEE Transactions on Industrial Informatics,2022, 18(6): 3754-3765. [百度学术]

      23. [23]

        黄武靖,张宁,董瑞彪,等. 多能源网络与能量枢纽联合规划方法[J]. 中国电机工程学报,2018,38(18):5425-5437.HUANG Wujing, ZHANG Ning, DONG Ruibiao, et al.Coordinated planning of multiple energy networks and energy hubs[J]. Proceedings of the CSEE, 2018, 38(18): 5425-5437(in Chinese). [百度学术]

      24. [24]

        LIU X Z, WU J Z, JENKINS N, et al. Combined analysis of electricity and heat networks[J]. Applied Energy, 2016, 162:1238-1250. [百度学术]

      25. [25]

        徐宪东,贾宏杰,靳小龙,等. 区域综合能源系统电/气/热混合潮流算法研究[J]. 中国电机工程学报,2015,35(14):3634-3642.XU Xiandong, JIA Hongjie, JIN Xiaolong, et al. Study on hybrid heat-gas-power flow algorithm for integrated community energy system[J]. Proceedings of the CSEE, 2015,35(14): 3634-3642(in Chinese). [百度学术]

      26. [26]

        王文学,胡伟,孙国强,等. 电-热互联综合能源系统区间潮流计算方法[J]. 电网技术,2019,43(1):83-95.WANG Wenxue, HU Wei, SUN Guoqiang, et al. Interval energy flow calculation method of integrated electro-thermal system[J]. Power System Technology, 2019, 43(1): 83-95(in Chinese). [百度学术]

      27. [27]

        靳小龙,穆云飞,贾宏杰,等. 考虑配电网重构的区域综合能源系统最优混合潮流计算[J]. 电力系统自动化,2017,41(1):18-24.JIN Xiaolong, MU Yunfei, JIA Hongjie, et al. Calculation of optimal hybrid power flow for integrated community energy system considering electric distribution network reconfiguration[J]. Automation of Electric Power Systems,2017, 41(1): 18-24(in Chinese). [百度学术]

      28. [28]

        FU X Q, SUN H B, GUO Q L, et al. Probabilistic power flow analysis considering the dependence between power and heat[J]. Applied Energy, 2017, 191: 582-592. [百度学术]

      29. [29]

        AYELE G T, MABROUK M T, HAURANT P, et al. Optimal heat and electric power flows in the presence of intermittent renewable source, heat storage and variable grid electricity tariff[J]. Energy Conversion and Management, 2021, 243: 114430. [百度学术]

      30. [30]

        CHEN D W, HU X, LI Y, et al. Nodal-pressure-based heating flow model for analyzing heating networks in integrated energy systems[J]. Energy Conversion and Management, 2020, 206:112491. [百度学术]

      31. [31]

        ZHANG S H, GU W, YAO S, et al. Partitional decoupling method for fast calculation of energy flow in a large-scale heat and electricity integrated energy system[J]. IEEE Transactions on Sustainable Energy, 2021, 12(1): 501-513. [百度学术]

      32. [32]

        陈皓勇,文俊中,王增煜,等. 能量网络的传递规律与网络方程[J]. 西安交通大学学报,2014,48(10):66-76.CHEN Haoyong, WEN Junzhong, WANG Zengyu, et al.Transfer laws and equations of energy networks[J]. Journal of Xi’an Jiaotong University, 2014, 48(10): 66-76(in Chinese). [百度学术]

      33. [33]

        陈彬彬,孙宏斌,尹冠雄,等. 综合能源系统分析的统一能路理论(二): 水路与热路[J]. 中国电机工程学报,2020,40(7):2133-2142.CHEN Binbin, SUN Hongbin, YIN Guanxiong, et al. Energy circuit theory of integrated energy system analysis(II): hydraulic circuit and thermal circuit[J]. Proceedings of the CSEE, 2020,40(7): 2133-2142(in Chinese). [百度学术]

      34. [34]

        陈瑜玮,孙宏斌,郭庆来. 综合能源系统分析的统一能路理论(五):电-热-气耦合系统优化调度[J]. 中国电机工程学报,2020,40(24):7928-7937.CHEN Yuwei, SUN Hongbin, GUO Qinglai. Energy circuit theory of integrated energy system analysis (Ⅴ): integrated electricity-heat-gas dispatch[J]. Proceedings of the CSEE,2020, 40(24): 7928-7937(in Chinese). [百度学术]

      35. [35]

        LI Z G, WU W C, SHAHIDEHPOUR M, et al. Combined heat and power dispatch considering pipeline energy storage of district heating network[J]. IEEE Transactions on Sustainable Energy, 2016, 7(1): 12-22. [百度学术]

      36. [36]

        徐飞,郝玲,陈磊,等. 电热综合能源系统中热力管网动态建模及协调运行研究综述[J]. 全球能源互联网,2021,4(1):55-63.XU Fei, HAO Ling, CHEN Lei, et al. Review of district energy network dynamic modeling and coordinate optimal operation in integrated electricity and heat energy systems[J]. Journal of Global Energy Interconnection, 2021, 4(1): 55-63(in Chinese). [百度学术]

      37. [37]

        顾泽鹏,康重庆,陈新宇,等. 考虑热网约束的电热能源集成系统运行优化及其风电消纳效益分析[J]. 中国电机工程学报,2015,35(14):3596-3604.GU Zepeng, KANG Chongqing, CHEN Xinyu, et al. Operation optimization of integrated power and heat energy systems and the benefit on wind power accommodation considering heating network constraints[J]. Proceedings of the CSEE, 2015, 35(14):3596-3604(in Chinese). [百度学术]

      38. [38]

        王明军,穆云飞,孟宪君,等. 考虑热能输运动态特性的电-热综合能源系统优化调度方法[J]. 电网技术,2020,44(1):132-142.WANG Mingjun, MU Yunfei, MENG Xianjun, et al. Optimal scheduling method for integrated electro-thermal energy system considering heat transmission dynamic characteristics[J].Power System Technology, 2020, 44(1): 132-142(in Chinese).[39]ZHU J Z. OPTIMIZATION OF POWER SYSTEM OPERATION[M]. Hoboken, NJ, USA: John Wiley & Sons,Inc, 2015. [百度学术]

      39. [40]

        袁亚湘. 非线性优化计算方法[M]. 北京:科学出版社,2008. [百度学术]

      40. [41]

        HUANG S J, TANG W C, WU Q W, et al. Network constrained economic dispatch of integrated heat and electricity systems through mixed integer conic programming[J]. Energy,2019, 179: 464-474. [百度学术]

      41. [42]

        JUBRIL A M, ADEDIJI A O, OLANIYAN O A. Solving the combined heat and power dispatch problem: a semi-definite programming approach[J]. Electric Power Components and Systems, 2012, 40(12): 1362-1376. [百度学术]

      42. [43]

        CHEN H H, LIN C Q, FU L B, et al. Collaborative optimal operation of transmission system with integrated active distribution system and district heating system based on semidefinite programming relaxation method[J]. Energy, 2021, 227:120465. [百度学术]

      43. [44]

        KIM J S, EDGAR T F. Optimal scheduling of combined heat and power plants using mixed-integer nonlinear programming[J]. Energy, 2014, 77: 675-690. [百度学术]

      44. [45]

        CHEN Y W, GUO Q L, SUN H B, et al. A water mass method and its application to integrated heat and electricity dispatch considering thermal inertias[J]. Energy, 2019, 181: 840-852. [百度学术]

      45. [46]

        SASHIREKHA A, PASUPULETI J, MOIN N H, et al.Combined heat and power (CHP) economic dispatch solved using Lagrangian relaxation with surrogate subgradient multiplier updates[J]. International Journal of Electrical Power& Energy Systems, 2013, 44(1): 421-430. [百度学术]

      46. [47]

        WANG L X, ZHENG J H, LI M S, et al. Multi-time scale dynamic analysis of integrated energy systems: an individualbased model[J]. Applied Energy, 2019, 237: 848-861. [百度学术]

      47. [48]

        朱继忠,骆腾燕,吴皖莉,等. 综合能源系统运行可靠性评估评述Ⅱ:数据驱动法与模型-数据混合驱动法[J/OL].电工技术学报,2022:1-13.ZHU Jizhong, LUO Tengyan, WU Wanli, et al. A review of operational reliability assessment of integrated energy systemsⅡ: data-driven method and model-data hybrid driven method[J/OL]. Transactions of China Electrotechnical Society, 2022:1-13(in Chinese). [百度学术]

      48. [49]

        MORVAJ B, EVINS R, CARMELIET J. Optimising urban energy systems: simultaneous system sizing, operation and district heating network layout[J]. Energy, 2016, 116: 619-636. [百度学术]

      49. [50]

        LU S, GU W, ZHANG C, et al. Hydraulic-thermal cooperative optimization of integrated energy systems: a convex optimization approach[J]. IEEE Transactions on Smart Grid,2020, 11(6): 4818-4832. [百度学术]

      50. [51]

        JIANG Y B, WAN C, BOTTERUD A, et al. Convex relaxation of combined heat and power dispatch[J]. IEEE Transactions on Power Systems, 2021, 36(2): 1442-1458. [百度学术]

      51. [52]

        QIN X, GUO Y, SHEN X W, et al. Increasing flexibility of combined heat and power systems through optimal dispatch with variable mass flow[J]. IEEE Transactions on Sustainable Energy, 2022, 13(2): 986-997. [百度学术]

      52. [53]

        GU W, TANG Y Y, PENG S Y, et al. Optimal configuration and analysis of combined cooling, heating, and power microgrid with thermal storage tank under uncertainty[J].Journal of Renewable and Sustainable Energy, 2015, 7(1):013104. [百度学术]

      53. [54]

        吕泉,王海霞,陈天佑,等. 考虑风电不确定性的热电厂蓄热罐运行策略[J]. 电力系统自动化,2015,39(14):23-29.LYU Quan, WANG Haixia, CHEN Tianyou, et al. Operation strategies of heat accumulator in combined heat and power plant with uncertain wind power[J]. Automation of Electric Power Systems, 2015, 39(14): 23-29(in Chinese). [百度学术]

      54. [55]

        CHEN X, KANG C Q, O’MALLEY M, et al. Increasing the flexibility of combined heat and power for wind power integration in China: Modeling and implications[J]. IEEE Transactions on Power Systems, 2014, 30(4): 1848-1857. [百度学术]

      55. [56]

        刘洪,王亦然,李积逊,等. 考虑建筑热平衡与柔性舒适度的乡村微能源网电热联合调度[J]. 电力系统自动化,2019,43(9):50-58.LIU Hong, WANG Yiran, LI Jixun, et al. Coordinated heat and power dispatch of micro-energy network of countryside considering heat balance model of building and flexible indoor comfort constraint[J]. Automation of Electric Power Systems,2019, 43(9): 50-58(in Chinese). [百度学术]

      56. [57]

        GU W, WANG J, LU S, et al. Optimal operation for integrated energy system considering thermal inertia of district heating network and buildings[J]. Applied Energy, 2017, 199: 234-246. [百度学术]

      57. [58]

        DECAROLIS J F. Using modeling to generate alternatives(MGA) to expand our thinking on energy futures[J]. Energy Economics, 2011, 33(2): 145-152. [百度学术]

      58. [59]

        DECAROLIS J F, BABAEE S, LI B, et al. Modelling to generate alternatives with an energy system optimization model[J]. Environmental Modelling & Software, 2016, 79:300-310. [百度学术]

      59. [60]

        PRICE J, KEPPO I. Modelling to generate alternatives: a technique to explore uncertainty in energy-environmenteconomy models[J]. Applied Energy, 2017, 195: 356-369. [百度学术]

      60. [61]

        SHUI Y, GAO H J, WANG L F, et al. A data-driven distributionally robust coordinated dispatch model for integrated power and heating systems considering wind power uncertainties[J]. International Journal of Electrical Power &Energy Systems, 2019, 104: 255-258. [百度学术]

      61. [62]

        ZHOU H S, LI Z G, ZHENG J H, et al. Robust scheduling of integrated electricity and heating system hedging heating network uncertainties[J]. IEEE Transactions on Smart Grid,2020, 11(2): 1543-1555. [百度学术]

      62. [63]

        ZHENG W Y, WU W C, LI Z G, et al. A non-iterative decoupled solution for robust integrated electricity-heat scheduling based on network reduction[J]. IEEE Transactions on Sustainable Energy, 2021, 12(2): 1473-1488. [百度学术]

      63. [64]

        吴文传,李志刚,王中冠. 可再生能源发电集群控制与优化调度[M]. 北京:科学出版社,2020. [百度学术]

      64. [65]

        ZHANG M L, WU Q W, WEN J Y, et al. Two-stage stochastic optimal operation of integrated electricity and heat system considering reserve of flexible devices and spatial-temporal correlation of wind power[J]. Applied Energy, 2020, 275:115357. [百度学术]

      65. [66]

        ALIPOUR M, ZARE K, SEYEDI H. A multi-follower bilevel stochastic programming approach for energy management of combined heat and power micro-grids[J]. Energy, 2018, 149:135-146. [百度学术]

      66. [67]

        KARAMI H, SANJARI M J, GOOI H B, et al. Stochastic analysis of residential micro combined heat and power system[J]. Energy Conversion and Management, 2017, 138: 190-198. [百度学术]

      67. [68]

        LI Y, ZOU Y, TAN Y, et al. Optimal stochastic operation of integrated low-carbon electric power, natural gas, and heat delivery system[J]. IEEE Transactions on Sustainable Energy,2018, 9(1): 273-283. [百度学术]

      68. [69]

        LI S L, ZHU J Z, DONG H J, et al. A novel rolling optimization strategy considering grid-connected power fluctuations smoothing for renewable energy microgrids[J].Applied Energy, 2022, 309: 118441. [百度学术]

      69. [70]

        朱兰,王吉,唐陇军,等. 计及电转气精细化模型的综合能源系统鲁棒随机优化调度[J]. 电网技术,2019,43(1):116-126.ZHU Lan, WANG Ji, TANG Longjun, et al. Robust stochastic optimal dispatching of integrated energy systems considering refined power-to-gas model[J]. Power System Technology,2019, 43(1): 116-126(in Chinese). [百度学术]

      70. [71]

        刘春明,李瑞月,尹钰君,等. 基于鲁棒随机模型预测控制的园区综合能源系统两阶段优化[J]. 电力自动化设备,2022,42(5):1-7.LIU Chunming, LI Ruiyue, YIN Yujun, et al. Two-stage optimization for community integrated energy system based on robust stochastic model predictive control[J]. Electric Power Automation Equipment, 2022, 42(5): 1-7(in Chinese). [百度学术]

      71. [72]

        LIN C H, WU W C, ZHANG B M, et al. Decentralized solution for combined heat and power dispatch through benders decomposition[J]. IEEE Transactions on Sustainable Energy,2017, 8(4): 1361-1372. [百度学术]

      72. [73]

        ZHENG W Y, DAVID J H. Distributed real-time dispatch of integrated electricity and heat systems with guaranteed feasibility[J]. IEEE Transactions on Industrial Informatics,2021, 18(2): 1175-1185. [百度学术]

      73. [74]

        HUANG J B, LI Z G, WU Q H. Coordinated dispatch of electric power and district heating networks: a decentralized solution using optimality condition decomposition[J]. Applied Energy, 2017, 206: 1508-1522. [百度学术]

      74. [75]

        XUE Y X, LI Z S, LIN C H, et al. Coordinated dispatch of integrated electric and district heating systems using heterogeneous decomposition[J]. IEEE Transactions on Sustainable Energy, 2020, 11(3): 1495-1507. [百度学术]

      75. [76]

        TRAN H N, NARIKIYO T, KAWANISHI M, et al. Wholeday optimal operation of multiple combined heat and power systems by alternating direction method of multipliers and consensus theory[J]. Energy Conversion and Management,2018, 174: 475-488. [百度学术]

      76. [77]

        LIANG X Y, LI Z G, HUANG W J, et al. Relaxed alternating direction method of multipliers for hedging communication packet loss in integrated electrical and heating system[J].Journal of Modern Power Systems and Clean Energy, 2020,8(5): 874-883. [百度学术]

      77. [78]

        ZHANG T, LI Z G, WU Q H, et al. Decentralized state estimation of combined heat and power systems using the asynchronous alternating direction method of multipliers[J].Applied Energy, 2019, 248: 600-613. [百度学术]

      78. [79]

        SUBBARAJ P, RENGARAJ R, SALIVAHANAN S.Enhancement of combined heat and power economic dispatch using self adaptive real-coded genetic algorithm[J]. Applied Energy, 2009, 86(6): 915-921. [百度学术]

      79. [80]

        LIU M, WANG S, YAN J J. Operation scheduling of a coalfired CHP station integrated with power-to-heat devices with detail CHP unit models by particle swarm optimization algorithm[J]. Energy, 2021, 214: 119022. [百度学术]

      80. [81]

        BASU M. Combined heat and power economic dispatch by using differential evolution[J]. Electric Power Components and Systems, 2010, 38(8): 996-1004. [百度学术]

      81. [82]

        BASU M. Combined heat and power economic dispatch using opposition-based group search optimization[J]. International Journal of Electrical Power & Energy Systems, 2015, 73: 819-829. [百度学术]

      82. [83]

        MELLAL M A, WILLIAMS E J. Cuckoo optimization algorithm with penalty function for combined heat and power economic dispatch problem[J]. Energy, 2015, 93: 1711-1718. [百度学术]

      83. [84]

        JAYAKUMAR N, SUBRAMANIAN S, GANESAN S, et al. Grey wolf optimization for combined heat and power dispatch with cogeneration systems[J]. International Journal of Electrical Power & Energy Systems, 2016, 74: 252-264. [百度学术]

      84. [85]

        KHORRAM E, JABERIPOUR M. Harmony search algorithm for solving combined heat and power economic dispatch problems[J]. Energy Conversion and Management, 2011,52(2): 1550-1554. [百度学术]

      85. [86]

        RABIEE A, JAMADI M, MOHAMMADI-IVATLOO B, et al. Optimal non-convex combined heat and power economic dispatch via improved artificial bee colony algorithm[J].Processes, 2020, 8(9): 1036. [百度学术]

      86. [87]

        JAYABARATHI T, YAZDANI A, RAMESH V, et al.Combined heat and power economic dispatch problem using the invasive weed optimization algorithm[J]. Frontiers in Energy, 2014, 8(1): 25-30. [百度学术]

      87. [88]

        ROY P K, PAUL C, SULTANA S. Oppositional teaching learning based optimization approach for combined heat and power dispatch[J]. International Journal of Electrical Power &Energy Systems, 2014, 57: 392-403. [百度学术]

      88. [89]

        BASU M. Artificial immune system for combined heat and power economic dispatch[J]. International Journal of Electrical Power & Energy Systems, 2012, 43(1): 1-5. [百度学术]

      89. [90]

        YAZDANI A, JAYABARATHI T, RAMESH V, et al.Combined heat and power economic dispatch problem using firefly algorithm[J]. Frontiers in Energy, 2013, 7(2): 133-139. [百度学术]

      90. [91]

        A D H V A R Y Y U P K, C H A T T O P A D H Y A Y P K,BHATTACHARYA A. Dynamic optimal power flow of combined heat and power system with valve-point effect using Krill Herd algorithm[J]. Energy, 2017, 127: 756-767. [百度学术]

      91. [92]

        MENG A B, MEI P, YIN H, et al. Crisscross optimization algorithm for solving combined heat and power economic dispatch problem[J]. Energy Conversion and Management,2015, 105: 1303-1317. [百度学术]

      92. [93]

        SHI B, YAN L X, WU W. Multi-objective optimization for combined heat and power economic dispatch with power transmission loss and emission reduction[J]. Energy, 2013, 56:135-143. [百度学术]

      93. [94]

        GHORBANI N. Combined heat and power economic dispatch using exchange market algorithm[J]. International Journal of Electrical Power & Energy Systems, 2016, 82: 58-66. [百度学术]

      94. [95]

        BEIGVAND S D, ABDI H, LA SCALA M. Hybrid gravitational search algorithm-particle swarm optimization with time varying acceleration coefficients for large scale CHPED problem[J]. Energy, 2017, 126: 841-853. [百度学术]

      95. [96]

        ZHOU S Y, HU Z J, GU W, et al. Combined heat and power system intelligent economic dispatch: a deep reinforcement learning approach[J]. International Journal of Electrical Power& Energy Systems, 2020, 120: 106016. [百度学术]

      96. [97]

        ZHANG B, HU W H, CAO D, et al. Deep reinforcement learning-based approach for optimizing energy conversion in integrated electrical and heating system with renewable energy[J]. Energy Conversion and Management, 2019, 202:112199. [百度学术]

      97. [98]

        瞿凯平,张孝顺,余涛,等. 基于知识迁移Q学习算法的多能源系统联合优化调度[J]. 电力系统自动化,2017,41(15): 18-25.QU Kaiping, ZHANG Xiaoshun, YU Tao, et al. Knowledge transfer based Q-learning algorithm for optimal dispatch of multi-energy system[J]. Automation of Electric Power Systems, 2017, 41(15): 18-25(in Chinese). [百度学术]

      98. [99]

        WANG X D, LIU Y B, ZHAO J B, et al. Surrogate model enabled deep reinforcement learning for hybrid energy community operation[J]. Applied Energy, 2021, 289: 116722. [百度学术]

      99. [100]

        CONNOLLY D, LUND H, MATHIESEN B V, et al. A review of computer tools for analysing the integration of renewable energy into various energy systems[J]. Applied Energy, 2010, 87(4): 1059-1082. [百度学术]

      100. [101]

        KALOGIROU S A. Use of TRNSYS for modelling and simulation of a hybrid pv-thermal solar system for Cyprus[J].Renewable Energy, 2001, 23(2): 247-260. [百度学术]

      101. [102]

        王梦雪,赵浩然,田航,等. 典型综合能源系统仿真与规划平台综述[J]. 电网技术,2020,44(12):4702-4712.WANG Mengxue, ZHAO Haoran, TIAN Hang, et al. Review of typical simulation and planning platforms for integrated energy system[J]. Power System Technology, 2020, 44(12):4702-4712(in Chinese). [百度学术]

      102. [103]

        黎静华,朱梦姝,陆悦江,等. 综合能源系统优化调度综述[J]. 电网技术,2021,45(6):2256-2272.LI Jinghua, ZHU Mengshu, LU Yuejiang, et al. A review on the optimal scheduling of integrated energy systems[J]. Power System Technology, 2021, 45(6): 2256-2272(in Chinese). [百度学术]

      103. [104]

        谢珊,贾跃龙,白雪涛,等. 城市能源系统规划设计及能耗分析工具综述[J]. 全球能源互联网,2021,4(2):163-177.XIE Shan, JIA Yuelong, BAI Xuetao, et al. A review of tools for urban energy systems planning and energy consumption analysis[J]. Journal of Global Energy Interconnection, 2021,4(2): 163-177(in Chinese). [百度学术]

      基金项目

      国家自然科学基金面上项目(52177087)。

      National Natural Science Foundation of China (52177087).

      作者简介

      • 朱浩昊

        朱浩昊(1997),男,硕士研究生,研究方向为热电联合调度,E-mail:epzhh@mail.scut.edu.cn。

      • 朱继忠*

        朱继忠(1966),男,教授,博士生导师,IEEE Fellow, 研究方向为综合能源系统优化运行与控制。通信作者,E-mail:zhujz@scut.edu.cn。

      • 李盛林

        李盛林(1992),男,博士研究生,研究方向为微网能量管理,E-mail:iamlshl@126.com。

      • 董瀚江

        董瀚江(1998),男,博士研究生,研究方向为电力系统运行优化与控制,E-mail:epdonghj@mail.scut.edu.cn。

      • 何晨可

        何晨可(1993),男,博士研究生,研究方向为考虑电动汽车的综合能源优化规划,E-mail:1197958177@qq.com。

      出版信息

      文章编号:2096-5125 (2022) 04-0383-15

      中图分类号:TM73

      文献标志码:A

      DOI:10.19705/j.cnki.issn2096-5125.2022.04.009

      收稿日期:2022-04-29

      修回日期:

      出版日期:2022-07-25

      引用信息: 朱浩昊,朱继忠*,李盛林等.电-热综合能源系统优化调度综述[J].全球能源互联网,2022,5(4):383-397 .,,,et al.Review of Optimal Scheduling of Integrated Electricity and Heat Systems[J].Journal of Global Energy Interconnection,2022,5(4):383-397 (in Chinese).

      (责任编辑 张宇)
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