考虑源网荷储聚合交易的区域电热综合能源系统优化调度

doi:10.12204/j.issn.1000-7229.2021.10.004

摘要/Abstract

摘要：

源网荷储资源的协调利用,是推动区域电热综合能源系统(regional integrated electric and heating system,RIEHS)高效运行的重要手段。提出了一种考虑源网荷储聚合交易的RIEHS优化调度方法。首先,构建了RIEHS的调度框架,设计了考虑源网荷储聚合交易的RIEHS调度组织流程;其次,建立了RIEHS两阶段优化调度模型,第一阶段为虚拟电厂(virtual power plant,VPP)对源网荷储资源的聚合交易优化,第二阶段为基于源网荷储交易结果的RIEHS调度优化;最后,基于改进的IEEE 33节点配电系统和32节点巴厘岛配热系统,构建了包含3个虚拟电厂的RIEHS进行算例分析,结果表明所提方法能够通过交易手段挖掘用户侧资源的响应潜力,提高虚拟电厂的运营收益和系统运行的经济性,验证了调度方法的有效性。

关键词: 区域电热综合能源系统(RIEHS), 源网荷储, 聚合交易, 虚拟电厂(VPP), 优化调度

Abstract:

The coordinated utilization of the resources of generation-grid-load-storage is an important means to promote the efficient operation of the regional integrated electric and heating system (RIEHS). This paper proposes an optimal dispatching method for RIEHS considering aggregation and transaction of generation-grid-load-storage. Firstly, the RIEHS dispatching framework is constructed, and the RIEHS dispatching organization process considering aggregation and transaction of generation-grid-load-storage is designed. Secondly, a two-stage optimization dispatching model of RIEHS is established. The first stage is the optimization of the aggregation and transaction of the resources of generation-grid-load-storage by the virtual power plant. The second stage is RIEHS dispatching optimization based on the transaction results of the resources of generation-grid-load-storage. Finally, based on the improved IEEE 33-node power distribution system and the 32-node Bali heating system, a RIEHS with three virtual power plants is constructed for simulation and analysis. The results show that the method proposed in the paper taps the response potential of user-side resources through transaction means, improves the operating income of virtual power plants and the economy of system operation. The effectiveness of the dispatching method has been verified.

Key words: regional integrated electric and heating system (RIEHS), generation-grid-load-storage, aggregation and transaction, virtual power plant (VPP), optimal dispatching

中图分类号:

TM73

杨冬梅, 王俊, 杜炜. 考虑源网荷储聚合交易的区域电热综合能源系统优化调度[J]. 电力建设, 2021, 42(10): 28-39.

YANG Dongmei, WANG Jun, DU Wei. Optimal Dispatching for Regional Integrated Electric and Heating Systems Considering Aggregation and Transaction of Generation-Grid-Load-Storage[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(10): 28-39.

图/表 17

图1 考虑源网荷储聚合交易的RIEHS调度框架

Fig.1 RIEHS dispatching framework considering aggregation and transaction of generation-grid-load-storage

图2 考虑源网荷储聚合交易的RIEHS调度组织流程

Fig.2 RIEHS dispatching organization process considering aggregation and transaction of generation-grid-load-storage

图3 求解流程

Fig.3 Solution process

图4 RIEHS测试算例

Fig.4 RIEHS test case

表1 源网荷储资源参数

Table 1 Parameters of the resource of generation-grid-load-storage

图5 多能负荷、风电和光伏出力的归一化值

Fig.5 Normalized value of multi-energy load and output of WT and PV

图6 主网电价和天然气价格

Fig.6 Electricity and natural gas prices on the main network

表2 不同的源网荷储资源聚合场景

Table 2 Different aggregation scenarios of the resource of generation-grid-load-storage

表3 Comparison of dispatching results in six scenarios美元

Table 3

图7 各VPP的零售价格

Fig.7 Retail price of each VPP

图8 电交易结果

Fig.8 Electricity transaction results

图9 热交易结果

Fig.9 Heat transaction results

图10 购电和购气结果

Fig.10 Purchase results of electricity and natural gas

图11 VPP1的运行情况

Fig.11 Operation of VPP1

图12 VPP2的运行情况

Fig.12 Operation of VPP2

图13 VPP3的运行情况

Fig.13 Operation of VPP3

图14 储能运行情况

Fig.14 Operation of ES

参考文献 30

[1]	国家发展改革委, 家能源局. 国关于印发《能源技术革命创新行动计划(2016-2030年)》的通知[EB/OL]. (2016-06-01)[2021-04-19]. http://www.nea.gov.cn/2016-06/01/c_135404377.htm.
[2]	郑超铭, 黄博南, 王子心, 等. 计及网络传输损耗的电热综合能源系统多目标优化调度[J]. 电网技术, 2020, 44(1): 141-154.
	ZHENG Chaoming, HUANG Bonan, WANG Zixin, et al. Multi-objective optimization dispatch for integrated electro-heating systems including network transmission losses[J]. Power System Technology, 2020, 44(1): 141-154.
[3]	冯迎春, 李雪松, 范洁, 等. 考虑清洁能源消纳的源网荷储互动交易实践[J]. 电力需求侧管理, 2020, 22(6): 69-74.
	FENG Yingchun, LI Xuesong, FAN Jie, et al. Practice of the source-grid-load-storage interactive transaction considering clean energy consumption[J]. Power Demand Side Management, 2020, 22(6): 69-74.
[4]	GUO T, HENWOOD M I, VAN OOIJEN M. An algorithm for combined heat and power economic dispatch[J]. IEEE Transactions on Power Systems, 1996, 11(4): 1778-1784. doi: 10.1109/59.544642 URL
[5]	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. doi: 10.1016/j.energy.2013.04.066 URL
[6]	SHAABANI Y A, SEIFI A R, KOUHANJANI M J. Stochastic multi-objective optimization of combined heat and power economic/emission dispatch[J]. Energy, 2017, 141: 1892-1904. doi: 10.1016/j.energy.2017.11.124 URL
[7]	张磊, 罗毅, 罗恒恒, 等. 基于集中供热系统储热特性的热电联产机组多时间尺度灵活性协调调度[J]. 中国电机工程学报, 2018, 38(4): 985-998,1275.
	ZHANG Lei, LUO Yi, LUO Hengheng, et al. Scheduling of integrated heat and power system considering multiple time-scale flexibility of CHP unit based on heat characteristic of DHS[J]. Proceedings of the CSEE, 2018, 38(4): 985-998,1275.
[8]	裴玮, 邓卫, 沈子奇, 等. 可再生能源与热电联供混合微网能量协调优化[J]. 电力系统自动化, 2014, 38(16): 9-15.
	PEI Wei, DENG Wei, SHEN Ziqi, et al. Energy coordination and optimization of hybrid microgrid based on renewable energy and CHP supply[J]. Automation of Electric Power Systems, 2014, 38(16): 9-15.
[9]	刘洪, 陈星屹, 李吉峰, 等. 基于改进CPSO算法的区域电热综合能源系统经济调度[J]. 电力自动化设备, 2017, 37(6): 193-200.
	LIU Hong, CHEN Xingyi, LI Jifeng, et al. Economic dispatch based on improved CPSO algorithm for regional power-heat integrated energy system[J]. Electric Power Automation Equipment, 2017, 37(6): 193-200.
[10]	WU Q H, ZHENG J H, JING Z X. Coordinated scheduling of energy resources for distributed DHCs in an integrated energy grid[J]. CSEE Journal of Power and Energy Systems, 2015, 1(1): 95-103. doi: 10.17775/CSEEJPES.2015.00012 URL
[11]	施锦月, 许健, 曾博, 等. 基于热电比可调模式的区域综合能源系统双层优化运行[J]. 电网技术, 2016, 40(10): 2959-2966.
	SHI Jinyue, XU Jian, ZENG Bo, et al. A bi-level optimal operation for energy hub based on regulating heat-to-electric ratio mode[J]. Power System Technology, 2016, 40(10): 2959-2966.
[12]	LIU X Z, WU J Z, JENKINS N, et al. Combined analysis of electricity and heat networks[J]. Applied Energy, 2016, 162: 1238-1250. doi: 10.1016/j.apenergy.2015.01.102 URL
[13]	HUANG B N, ZHENG C M, SUN Q Y, et al. Optimal economic dispatch for integrated power and heating systems considering transmission losses[J]. Energies, 2019, 12(13): 2502. doi: 10.3390/en12132502 URL
[14]	徐业琰, 彭思成, 廖清芬, 等. 考虑用户互补聚合响应与热能传输延时的综合能源园区运营商两阶段短期优化调度[J]. 电力自动化设备, 2017, 37(6): 152-163.
	XU Yeyan, PENG Sicheng, LIAO Qingfen, et al. Two-stage short-term optimal dispatch of MEP considering CAUR and HTTD[J]. Electric Power Automation Equipment, 2017, 37(6): 152-163.
[15]	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.
[16]	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. doi: 10.1016/j.apenergy.2017.05.004 URL
[17]	艾芊, 章健. 基于多代理系统的微电网竞价优化策略[J]. 电网技术, 2010, 34(2): 46-51.
	AI Qian, ZHANG Jian. Optimization bidding strategies of microgrids based on multi-agent system[J]. Power System Technology, 2010, 34(2): 46-51.
[18]	PEI W, DU Y, DENG W, et al. Optimal bidding strategy and intramarket mechanism of microgrid aggregator in real-time balancing market[J]. IEEE Transactions on Industrial Informatics, 2016, 12(2): 587-596. doi: 10.1109/TII.2016.2522641 URL
[19]	刘一欣, 郭力, 王成山. 多微电网参与下的配电侧电力市场竞价博弈方法[J]. 电网技术, 2017, 41(8): 2469-2476.
	LIU Yixin, GUO Li, WANG Chengshan. Optimal bidding strategy for microgrids in electricity distribution market[J]. Power System Technology, 2017, 41(8): 2469-2476.
[20]	杜炜, 窦迅, 王镇, 等. 考虑热电余量交易的微网群优化调度[J]. 电网技术, 2020, 44(10): 3777-3786.
	DU Wei, DOU Xun, WANG Zhen, et al. Optimal scheduling for microgrid clusters considering heat-electricity margin transaction[J]. Power System Technology, 2020, 44(10): 3777-3786.
[21]	王宣元, 刘敦楠, 刘蓁, 等. 泛在电力物联网下虚拟电厂运营机制及关键技术[J]. 电网技术, 2019, 43(9): 3175-3183.
	WANG Xuanyuan, LIU Dunnan, LIU Zhen, et al. Operation mechanism and key technologies of virtual power plant under ubiquitous Internet of Things[J]. Power System Technology, 2019, 43(9): 3175-3183.
[22]	窦迅, 王俊, 叶飞, 等. 考虑虚拟电厂组合策略的售电公司优化调度及购售电决策[J]. 电网技术, 2020, 44(6): 2078-2086.
	DOU Xun, WANG Jun, YE Fei, et al. Optimal dispatching and purchase-sale decision making of electricity retailers considering virtual power plant combination strategies[J]. Power System Technology, 2020, 44(6): 2078-2086.
[23]	叶飞, 邵平, 王宣元, 等. 考虑购售风险的虚拟电厂双层竞标策略[J]. 电力建设, 2020, 41(6): 28-35.
	YE Fei, SHAO Ping, WANG Xuanyuan, et al. Bi-level bidding strategies for virtual power plants considering purchase and sale risks[J]. Electric Power Construction, 2020, 41(6): 28-35.
[24]	顾伟, 任佳依, 高君, 等. 含分布式电源和可调负荷的售电公司优化调度模型[J]. 电力系统自动化, 2017, 41(14): 37-44.
	GU Wei, REN Jiayi, GAO Jun, et al. Optimal dispatching model of electricity retailers considering distributed generator and adjustable load[J]. Automation of Electric Power Systems, 2017, 41(14): 37-44.
[25]	GABASH A, LI P. Active-reactive optimal power flow in distribution networks with embedded generation and battery storage[J]. IEEE Transactions on Power Systems, 2012, 27(4): 2026-2035. doi: 10.1109/TPWRS.2012.2187315 URL
[26]	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. doi: 10.1109/TSTE.2015.2467383 URL
[27]	LI Z G, WU W C, WANG J H, et al. Transmission-constrained unit commitment considering combined electricity and district heating networks[J]. IEEE Transactions on Sustainable Energy, 2016, 7(2): 480-492. doi: 10.1109/TSTE.2015.2500571 URL
[28]	DIW Berlin: DIETER[EB/OL]. (2019-05-17)[2021-03-01]. https://www.diw.de/de/diw_01.c.508843.de/forschung_beratung/nachhaltigkeit/umwelt/verkehr/energie/modelle/dieter/dieter.html.
[29]	CHIRAMBO D. Addressing the renewable energy financing gap in Africa to promote universal energy access: Integrated renewable energy financing in Malawi[J]. Renewable and Sustainable Energy Reviews, 2016, 62: 793-803. doi: 10.1016/j.rser.2016.05.046 URL
[30]	DOU X, WANG J, WANG Z, et al. A dispatching method for integrated energy system based on dynamic time-interval of model predictive control[J]. Journal of Modern Power Systems and Clean Energy, 2020, 8(5): 841-852. doi: 10.35833/MPCE.2019.000234 URL