多类型灵活资源的建模与分层式协调控制架构

田新成; 文艺林; 卢泽汉; 侯鑫垚; 胡泽春

doi:10.16513/j.2096-2185.DE.2409102

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分布式能源 ›› 2024, Vol. 9 ›› Issue (1) : 10-18. DOI: 10.16513/j.2096-2185.DE.2409102

学术研究

多类型灵活资源的建模与分层式协调控制架构

田新成 ¹ ,
文艺林 ² ,
卢泽汉 ¹ ,
侯鑫垚 ¹ ,
胡泽春 ²

作者信息 +

Modeling Techniques and a Hierarchical Coordinated Control Framework for Various-Type Flexible Resources

Author information +

文章历史 +

摘要

电力需求侧可控的负荷、发电和储能资源统称为灵活资源，这些资源对智能电网的优化运行和消纳新能源发电具有重要作用。首先提出了一种通用灵活资源模型，该模型能够统一描述需求侧居民、商业、工业多类型灵活资源的特性，并能同时描述大规模灵活资源的集总用电需求。基于所提的通用灵活资源模型，构建了一种包含日前和实时阶段大规模多类型需求侧灵活资源的分层协调控制架构，该构架考虑了垂直调度和电力市场条件下电力系统的运行机制，在2种运行机制下都能够有效地利用多类型灵活资源的可调节能力提升电网整体的运行效率。将所提灵活资源模型嵌入到IEEE 30节点系统的机组组合问题中进行仿真，验证了所提分层式协调控制架构的有效性。

Abstract

Controllable loads, on-site generation and energy storages at demand-side are termed as distributed energy resources. These resources are vital for optimal operation of smart grid and renewable integration. This paper first proposes a generalized flexible resource model to characterize a variety of flexible resources at the residential, commercial and industrial sectors. The characteristics of an aggregation of heterogeneous distributed energy resources can be also described via this proposed model. This paper then presents a hierarchical control framework to coordinate their energy consumption in day-ahead and real time under both regulated and deregulated scenarios. This framework can utilize the flexibility of distributed energy resources to improve the operational efficiency of the whole system. Finally, This paper presents numerical simulations on a unit commitment problem of IEEE 30-bus system to verify the effectiveness of the proposed hierarchical control framework.

导出引用

田新成, 文艺林, 卢泽汉, 等. 多类型灵活资源的建模与分层式协调控制架构[J]. 分布式能源. 2024, 9(1): 10-18 https://doi.org/10.16513/j.2096-2185.DE.2409102

Xincheng TIAN, Yilin WEN, Zehan LU, et al. Modeling Techniques and a Hierarchical Coordinated Control Framework for Various-Type Flexible Resources[J]. Distributed Energy Resources. 2024, 9(1): 10-18 https://doi.org/10.16513/j.2096-2185.DE.2409102

中图分类号： TM732

参考文献

列表( 原文顺序 | 文献年度倒序 | 文中引用次数倒序 ) 可视化分析

[1]	KANG C, CHEN X, XU Q, 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. 本文引用 [1]

[2]	CALLAWAY D, HISKENS I. Achieving controllability of electric loads[J]. Proceedings of IEEE, 2011, 99(1): 184-199. 本文引用 [1]

[3]	OSKOUEI M Z, ZEINAL-KHEIRI S, MOHAMMADI-IVATLOO B, et al. Optimal scheduling of demand response aggregators in industrial parks based on load disaggregation algorithm[J]. IEEE Systems Journal, 2021, 16(1): 945-953. 本文引用 [1]

[4]	XU Z, SU W, HU Z, et al. A hierarchical framework for coordinated charging of plug-in electric vehicles in China[J]. IEEE Transactions on Smart Grid, 2015, 7(1): 428-438. 本文引用 [1]

[5]	贾俊，范炜豪，吕志鹏，等. 用于电动汽车集群并网的直流变压器启动研究[J]. 发电技术，2023, 44(6): 875-882. JIA Jun, FAN Weihao, LÜ Zhipeng, et al. Research on startup of DC transformer for electric vehicle cluster grid-connection[J]. Power Generation Technology, 2023, 44(6): 875-882. 本文引用 [1]

[6]	马子钦，廖凯，李波，等. 含分布式电源和电动汽车的城市电网半不变量故障分析方法[J]. 电网技术，2021, 45(2): 696-704. MA Ziqin, LIAO Kai, LI bo, et al. Cumulant failure analysis of urban power grid with distributed generation and electric vehicles[J]. Power System Technology, 2021, 45(2): 696-704. 本文引用 [1]

[7]	高爽，戴如鑫. 电动汽车集群参与调频辅助服务市场的充电调控策略[J]. 电力系统自动化，2023, 47(18): 60-67. GAO Shuang, DAI Ruxin. Charging control strategy for electric vehicle aggregation participating in frequency regulation ancillary service market[J]. Automation of Electric Power Systems, 2023, 47(18): 60-67. 本文引用 [1]

[8]	胡泽春，宋永华，徐智威，等. 电动汽车接入电网的影响与利用[J]. 中国电机工程学报，2012, 32(4): 1-10. HU Zechun, SONG Yonghua, XU Zhiwei, et al. Impacts and utilization of electric vehicles integration into power systems[J]. Proceedings of the CSEE, 2012, 32(4): 1-10. 本文引用 [1]

[9]	HAO H, SANANDAJI B, POOLLA K, et al. Aggregate flexibility of thermostatically controlled loads[J]. IEEE Transactions on Power Systems, 2015, 30(1): 189-198. 本文引用 [1]

[10]	FISCHER D, WOLF T, WAPLER J, et al. Model-based flexibility assessment of a residential heat pump pool[J]. Energy, 2017, 118: 853-864. 本文引用 [1]

[11]	方磊，薛云霞，池宇琪，等. 分布式储能运行规划一体的多目标选址定容方法[J]. 智慧电力，2022, 50(11): 1-8. FANG Lei, XUE Yunxia, CHI Yuqi, et al. Multi-objective location and capacity determination method for distributed battery energy storage system considering operational planning[J]. Smart Power, 2022, 50(11): 1-8. 本文引用 [1]

[12]	WANG L, KWON J, SCHULZ N, et al. Evaluation of aggregated EV flexibility with TSO-DSO coordination[J]. IEEE Transactions on Sustainable Energy, 2022, 13(4): 2304-2315. 本文引用 [1]

[13]	ZHANG X, HUG G. Bidding strategy in energy and spinning reserve markets for aluminum smelters' demand response[C]//Proceedings of 2015 IEEE Power Engineering Society Conference on Innovative Smart Grid Technologies. Washington DC, USA: IEEE, 2015：1-6. 本文引用 [4]

[14]	CHEN C, WANG J, HEO Q. MPC-based appliance scheduling for residential building energy management controller.[J]. IEEE Transactions on Smart Grid, 2013, 4(3): 1401-1410. 本文引用 [1]

[15]	MUKHERJEE S, BAI H, CHAKRABORTTY A. Model-free decentralized reinforcement learning control of distributed energy resources[C]//2020 IEEE Power & Energy Society General Meeting (PESGM). Montreal, QC, Canada: IEEE, 2020: 1-5. 本文引用 [1]

[16]	LI S, PAN Y, XU P, et al. A decentralized peer-to-peer control scheme for heating and cooling trading in distributed energy systems[J]. Journal of Cleaner Production, 2021, 285: 124817. 本文引用 [1]

[17]	RICHARDSON P, FLYNN D, KEANE A. Local versus centralized charging strategies for electric vehicles in low voltage distribution systems[J]. IEEE Transactions on Smart Grid, 2012, 3(2): 1020-1028. 本文引用 [1]

[18]	LI Z, CHENG Z, SI J, et al. Distributed event-triggered hierarchical control to improve economic operation of hybrid AC/DC microgrids[J]. IEEE Transactions on Power Systems, 2021, 37(5): 3653-3668. 本文引用 [1]

[19]	GONG X, CASTILLO-GUERRA E, CARDENAS-BARRERA J L, et al. Robust hierarchical control mechanism for aggregated thermostatically controlled loads[J]. IEEE Transactions on Smart Grid, 2020, 12(1): 453-467. 本文引用 [1]

[20]	SUBRAMANIAN A, GARCIA M, CALLAWAY D, et al. Real-time scheduling of distributed resources[J] IEEE Transactions on Smart Grid, 2014, 4(1): 2122-2130. 本文引用 [4]

[21]	傅鹏，杨凤玖，张禄郗. 电动汽车充、换电模式经济性研究[J]. 内蒙古电力技术，2022, 40(2): 22-27. FU Peng, YANG Fengjiu, ZHANG Luxi. Research on economics of electric vehicle charging and switching mode[J]. Inner Mongolia Electric Power, 2022, 40(2): 22-27. 本文引用 [1]

[22]	XU Z, CALLAWAY D S, HU Z, et al. Hierarchical coordination of heterogeneous flexible loads[J]. IEEE Transactions on Power Systems, 2016, 31(6): 4206-4216. 本文引用 [2]

[23]	SUNDSTROM O, BINDING C. Flexible charging optimization for electric vehicles considering distribution grid constraints[J], IEEE Transactions on Smart Grid, 2012, 3(1): 26-37. 本文引用 [3]

[24]	BURSILL J, O'BRIEN L, BEAUSOLEIL-MORRISON I. Multi-zone field study of rule extraction control to simplify implementation of predictive control to reduce building energy use[J]. Energy and Buildings, 2020, 222: 110056. 本文引用 [1]

[25]	CHEN M, GAO C, SONG M, et al. Internet data centers participating in demand response: A comprehensive review[J]. Renewable and Sustainable Energy Reviews, 2020, 117: 109466. 本文引用 [1]

[26]	PAULUS M, BORGGREFE F. The potential of demand-side management in energy-intensive industries for electricity markets in Germany[J]. Applied Energy, 2011, 88: 432-441 本文引用 [1]

[27]	SGOURIDIS S, ALI M, SLEPTCHENKO A, et al. Aluminum smelters in the energy transition: Optimal configuration and operation for renewable energy integration in high insolation regions[J]. Renewable Energy, 2021, 180: 937-953. 本文引用 [1]

[28]	CHEN C, WANG J, KISHORE S. A distributed direct load control approach for large-scale residential demand response[J]. IEEE Transactions on Power Systems, 2014, 29(5): 2219-2228. 本文引用 [1]

[29]	IBM Corporation. IBM ILOG CPLEX optimization studio 12.9[EB/OL]. [2023-07-24]. https://www.ibm.com/products/ilog-cplex-optimization-studio 本文引用 [1]