MULTI-TIME SCALE SOURCE-LOAD INTERACTIVE OPTIMAL SCHEDULING OF INTEGRATED ENERGY SYSTEM CONSIDERING LOW-CARBON DEMAND RESPONSE

Li Yunzhi; Liu Jizhen; Hu Yang

doi:10.19912/j.0254-0096.tynxb.2023-1115

PDF(2347 KB)

Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (11) : 84-98. DOI: 10.19912/j.0254-0096.tynxb.2023-1115

MULTI-TIME SCALE SOURCE-LOAD INTERACTIVE OPTIMAL SCHEDULING OF INTEGRATED ENERGY SYSTEM CONSIDERING LOW-CARBON DEMAND RESPONSE

Li Yunzhi^1,2, Liu Jizhen^1,2, Hu Yang²

Author information +

History +

Abstract

To realize the secure, flexible, and low-carbon operation of integrated energy system, an optimal scheduling strategy that considers the low-carbon demand response is proposed. This strategy considers the interaction between source and load sides and conducts research at multi-time scales, including day-ahead and intra-day. Firstly, a hybrid energy hub model is established based on the system structure and multi-energy complementary, incorporating elements of demand response load and energy storage. Then, a demand response strategy is devised for contracted and real-time response loads that possess varying response speeds, and within the system, scheduling information is communicated to attain a low-carbon demand response through interactive means. Finally, the day-ahead optimal scheduling considering the shared cost of carbon emission is implemented, with the aim of achieving the lowest economic cost, the lowest carbon emission, and the highest user comfort. The day-ahead plan guides the performance of intra-day rolling and real-time optimal scheduling. The simulation results indicate that the proposed strategy can efficiently exploit the scheduling potential of both source and load resources, mitigate the accommodation issue of renewable energy, and furnish insights for the economic and low-carbon scheduling of integrated energy systems.

Key words

integrated energy system / demand response / low emission / optimization scheduling / source-load interaction / multi-time scale

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Li Yunzhi, Liu Jizhen, Hu Yang. MULTI-TIME SCALE SOURCE-LOAD INTERACTIVE OPTIMAL SCHEDULING OF INTEGRATED ENERGY SYSTEM CONSIDERING LOW-CARBON DEMAND RESPONSE[J]. Acta Energiae Solaris Sinica. 2024, 45(11): 84-98 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1115

References

[1] 崔杨, 邓贵波, 曾鹏, 等. 计及碳捕集电厂低碳特性的含风电电力系统源-荷多时间尺度调度方法[J]. 中国电机工程学报, 2022, 42(16): 5869-5886.
CUI Y, DENG G B, ZENG P, et al.Multi-time scale source-load dispatch method of power system with wind power considering low-carbon characteristics of carbon capture power plant[J]. Proceedings of the CSEE, 2022, 42(16): 5869-5886.
[2] 施泉生, 丁建勇, 刘坤, 等. 含电、气、热3种储能的微网综合能源系统经济优化运行[J]. 电力自动化设备, 2019, 39(8): 269-276, 293.
SHI Q S, DING J Y, LIU K, et al.Economic optimal operation of microgrid integrated energy system with electricity, gas and heat storage[J]. Electric power automation equipment, 2019, 39(8): 269-276, 293.
[3] ZHOU J, WU Y, ZHONG Z, et al.Modeling and configuration optimization of the natural gas-wind-photovoltaic-hydrogen integrated energy system: a novel deviation satisfaction strategy[J]. Energy conversion and management, 2021, 243(1): 114340.
[4] 蔡钦钦, 肖宇, 朱永强. 计及电转氢和燃料电池的电热微网日前经济协调调度模型[J]. 电力自动化设备, 2021, 41(10): 107-112, 161.
CAI Q Q, XIAO Y, ZHU Y Q.Day-ahead economic coordination dispatch model of electricity-heat microgrid considering P2H and fuel cells[J]. Electric power automation equipment, 2021, 41(10): 107-112, 161.
[5] 吴江, 王晶晶, 张强, 等. 考虑电转气消纳风电的电-气综合能源系统两阶段鲁棒协同调度[J]. 太阳能学报, 2022, 43(2): 436-443.
WU J, WANG J J, ZHANG Q, et al.Two-stage robust cooperative scheduling for electricity-gas integrated energy system considering power-to-gas for wind power accommodation[J]. Acta energiae solaris sinica, 2022, 43(2): 436-443.
[6] 隋鑫, 卢盛阳, 苏安龙, 等. 计及风电和柔性负荷的核电多目标优化调度研究[J]. 中国电机工程学报, 2019, 39(24): 7232-7241.
SUI X, LU S Y, SU A L, et al.Research on multi-objective optimal scheduling of nuclear power considering wind power and flexible load[J]. Proceedings of the CSEE, 2019, 39(24): 7232-7241.
[7] 段佳南, 谢俊, 冯丽娜, 等. 基于合作博弈论的风-光-水-氢多主体能源系统增益分配策略[J]. 电网技术, 2022, 46(5): 1703-1711.
DUAN J N, XIE J, FENG L N, et al.Synergistic gains allocation for multi-stakeholder wind-solar-hydro-hydrogen energy system based on cooperative game theory[J]. Power system technology, 2022, 46(5): 1703-1711.
[8] FENG C S, WEN F S, YOU S, et al.Coalitional game-based transactive energy management in local energy communities[J]. IEEE transactions on power systems, 2020, 35(3): 1729-1740.
[9] 周鑫, 韩肖清, 李廷钧, 等. 计及需求响应和电能交互的多主体综合能源系统主从博弈优化调度策略[J]. 电网技术, 2022, 46(9): 3333-3346.
ZHOU X, HAN X Q, LI T J, et al.Master-slave game optimal scheduling strategy for multi-agent integrated energy system based on demand response and power interaction[J]. Power system technology, 2022, 46(9): 3333-3346.
[10] 许周, 孙永辉, 谢东亮, 等. 计及电/热柔性负荷的区域综合能源系统储能优化配置[J]. 电力系统自动化, 2020, 44(2): 53-59.
XU Z, SUN Y H, XIE D L, et al.Optimal configuration of energy storage for integrated region energy system considering power/thermal flexible load[J]. Automation of electric power systems, 2020, 44(2): 53-59.
[11] 周丽红, 于浩, 李鹏. 考虑居民热负荷主动需求响应的园区综合能源系统分布式优化运行方法[J]. 电网技术, 2023, 47(5): 1989-2000.
ZHOU L H, YU H, LI P.Distributed optimal operation method of park-level integrated energy system considering active demand response of residential heat loads[J]. Power system technology, 2023, 47(5): 1989-2000.
[12] 李虹, 林兰心, 赵小军. 基于需求侧用户响应分析的电-气-热综合能源系统低碳经济调度[J]. 太阳能学报, 2023, 44(5): 97-105.
LI H, LIN L X, ZHAO X J.Low carbon economic scheduling of electricity-gas-heat integrated energy system based on demand-side user response analysis[J]. Acta energiae solaris sinica, 2023, 44(5): 97-105.
[13] WANG L, HOU C Q, YE B, et al.Optimal operation analysis of integrated community energy system considering the uncertainty of demand response[J]. IEEE transactions on power systems, 2021, 36(4): 3681-3691.
[14] HE C, ZHANG X P, LIU T Q, et al.Distributionally robust scheduling of integrated gas-electricity systems with demand response[J]. IEEE transactions on power systems, 2019, 34(5): 3791-3803.
[15] 郑若楠, 李志浩, 唐雅洁, 等. 考虑居民用户参与度不确定性的激励型需求响应模型与评估[J]. 电力系统自动化, 2022, 46(8): 154-162.
ZHENG R N, LI Z H, TANG Y J, et al.Incentive demand response model and evaluation considering uncertainty of residential customer participation degree[J]. Automation of electric power systems, 2022, 46(8): 154-162.
[16] MASSRUR H R, NIKNAM T, FOTUHI-FIRUZABAD M.Investigation of carrier demand response uncertainty on energy flow of renewable-based integrated electricity-gas-heat systems[J]. IEEE transactions on industrial informatics, 2018, 14(11): 5133-5142.
[17] ZHANG X H, RAM'IREZ-MENDIOLA J L, LI M T, et al. Electricity consumption pattern analysis beyond traditional clustering methods: a novel self-adapting semi-supervised clustering method and application case study[J]. Applied energy, 2022, 308: 118335.
[18] 黄冬梅, 吴涵文, 孙锦中, 等. 计及阶梯式碳交易机制的海岛综合能源优化调度[J]. 电力系统及其自动化学报, 2023, 35(4): 93-99.
HUANG D M, WU H W, SUN J Z, et al.Optimal scheduling of comprehensive energy in island considering step-by-step carbon trading mechanism[J]. Proceedings of the CSU-EPSA, 2023, 35(4): 93-99.
[19] 骆钊, 秦景辉, 梁俊宇, 等. 含碳-绿色证书联合交易机制的综合能源系统日前优化调度[J]. 电力自动化设备, 2021, 41(9): 248-255.
LUO Z, QIN J H, LIANG J Y, et al.Day-ahead optimal scheduling of integrated energy system with carbon-green certificate coordinated trading mechanism[J]. Electric power automation equipment, 2021, 41(9): 248-255.
[20] CHEN S Y, LIU P, LI Z.Low carbon transition pathway of power sector with high penetration of renewable energy[J]. Renewable and sustainable energy reviews, 2020, 130: 109985.
[21] 祝荣, 任永峰, 孟庆天, 等. 基于合作博弈的综合能源系统电-热-气协同优化运行策略[J]. 太阳能学报, 2022, 43(4): 20-29.
ZHU R, REN Y F, MENG Q T, et al.Electricity-heat-gas cooperative optimal operation strategy of integrated energy system based on cooperative game[J]. Acta energiae solaris sinica, 2022, 43(4): 20-29.
[22] 崔杨, 邓贵波, 赵钰婷, 等. 考虑源荷低碳特性互补的含风电电力系统经济调度[J]. 中国电机工程学报, 2021, 41(14): 4799-4815.
CUI Y, DENG G B, ZHAO Y T, et al.Economic dispatch of power system with wind power considering the complementarity of low-carbon characteristics of source side and load side[J]. Proceedings of the CSEE, 2021, 41(14): 4799-4815.
[23] GUO J C, LIU Z J, WU X, et al.Two-layer co-optimization method for a distributed energy system combining multiple energy storages[J]. Applied energy, 2022, 322: 119486.
[24] 李云鸷, 刘吉臻, 马素玲, 等. 基于变工况模型的综合能源系统源-荷互动多目标优化调度[J]. 电网技术, 2022, 46(7): 2472-2482.
LI Y Z, LIU J Z, MA S L, et al.Source-load interactive multi-objective optimal dispatching of integrated energy system based on off-design model[J]. Power system technology, 2022, 46(7): 2472-2482.
[25] DEB K, JAIN H.An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints[J]. IEEE transactions on evolutionary computation, 2014, 18(4): 577-601.