Robust Optimal Scheduling of Micro Energy Grid Considering Multi-Interval Uncertainty Set of Source-Load and Integrated Demand Response

doi:10.16183/j.cnki.jsjtu.2023.022

Abstract

Abstract:

Aiming at the uncertainty of the source and load in micro energy grid, a robust optimal scheduling model considering multi-interval uncertainty set of source-load and integrated demand response is proposed. First, considering the uncertainty of wind power, photovoltaic output and electric, and thermal and cooling loads in the micro energy grid, a multi-interval uncertainty set of source-load is established. Then, in order to fully tap the potential of load side dispatching, an integrated demand response model is established, which includes reducible electric load, transferable electric load, flexible cooling, heating load, and replaceable load, based on which, the uncertainty of integrated demand response is considered. Afterwards, with the lowest dispatching cost of micro energy grid as the objective function, a two-stage robust optimal scheduling model of micro energy network is constructed, which considers the multi-interval uncertainty set of source load and the integrated demand response. The model is solved by the column and constraint generation algorithm, the strong duality theory, and the large M method. Finally, the rationality and effectiveness of the proposed model are verified through the analysis of numerical examples.

Key words: micro energy grid, two-stage robust optimization, integrated demand response, multi interval uncertainty set of source-load, column and constraint generation algorithm

CLC Number:

TM732

MI Yang, FU Qixin, ZHAO Haihui, MA Siyuan, WANG Yufei. Robust Optimal Scheduling of Micro Energy Grid Considering Multi-Interval Uncertainty Set of Source-Load and Integrated Demand Response[J]. Journal of Shanghai Jiao Tong University, 2024, 58(9): 1323-1333.

Figures/Tables 15

Fig.1

Fig.2

Fig.3

Tab.1

Tab.2

Fig.4

Fig.5

Fig.6

Fig.7

Tab.3

Fig.8

Fig.9

Fig.10

Tab.4

Tab.5

References 22

[1]	刘方泽, 牟龙华, 张涛, 等. 微能源网多能源耦合枢纽的模型搭建与优化[J]. 电力系统自动化, 2018, 42(14): 91-98.
	LIU Fangze, MU Longhua, ZHANG Tao, et al. Modelling and optimization of multi-energy coupling hub for micro-energy network[J]. Automation of Electric Power Systems, 2018, 42(14): 91-98.
[2]	MA T F, WU J Y, HAO L L. Energy flow modeling and optimal operation analysis of the micro energy grid based on energy hub[J]. Energy Conversion and Management, 2017, 133: 292-306.
[3]	张峰, 杨志鹏, 张利, 等. 计及多类型需求响应的孤岛型微能源网经济运行[J]. 电网技术, 2020, 44(2): 547-557.
	ZHANG Feng, YANG Zhipeng, ZHANG Li, et al. Optimal operation of islanded micro energy grid with multi-type demand responses[J]. Power System Technology, 2020, 44(2): 547-555.
[4]	张彼德, 陈颖倩, 李孟洁, 等. 含热泵和相变储能的多能互补微能源网运行优化方法研究[J]. 电力系统保护与控制, 2021, 49(1): 106-114.
	ZHANG Bide, CHEN Yingqian, LI Mengjie, et al. Research on an operational optimization method of multi-energy complementary micro energy grid with heat pump and phase change energy storage[J]. Power System Protection and Control, 2021, 49(1): 106-114.
[5]	HU B, WANG H, YAO S. Optimal economic operation of isolated community microgrid incorporating temperature controlling devices[J]. Protection and Control of Modern Power Systems, 2017, 2(1): 1-11.
[6]	冯奕, 应展烽, 颜建虎. 考虑碳排放成本的多能互补微能源网储能装置优化运行[J]. 电力系统保护与控制, 2021, 49(8): 92-99.
	FENG Yi, YING Zhanfeng, YAN Jianhu. Optimized operation of energy storage in a multi-energy complementary micro-energy network considering carbon emission cost[J]. Power System Protection and Control, 2021, 49(8): 92-99.
[7]	TALARI S, YAZDANINEJAD M, HAGHIFAM M R. Stochastic-based scheduling of the microgrid operation including wind turbines, photovoltaic cells, energy storages and responsive loads[J]. IET Generation, Transmission & Distribution, 2015, 9(12): 1498-1509.
[8]	SHAMS M H, SHAHABI M, KIA M, et al. Optimal operation of electrical and thermal resources in microgrids with energy hubs considering uncertainties[J]. Energy, 2019, 187: 115949.
[9]	随权, 林湘宁, 童宁, 等. 基于改进两阶段鲁棒优化的主动配电网经济调度[J]. 中国电机工程学报, 2020, 40(7): 2166-2179.
	SUI Quan, LIN Xiangning, TONG Ning, et al. Economic dispatch of active distribution network based on improved two-stage robust optimization[J]. Proceedings of the CSEE, 2020, 40(7): 2166-2179.
[10]	梁子鹏, 陈皓勇, 王勇超, 等. 含电动汽车的微网鲁棒经济调度[J]. 电网技术, 2017, 41(8): 2647-2656.
	LIANG Zipeng, CHEN Haoyong, WANG Yongchao, et al. Robust economic dispatch of microgrid with electric vehicle[J]. Power System Technology, 2017, 41(8): 2647-2656.
[11]	陈皓勇, 王勇超, 禤培正, 等. 含高渗透率风电的微网系统鲁棒经济调度方法[J]. 控制理论与应用, 2017, 34(8): 1104-1111.
	CHEN Haoyong, WANG Yongchao, XUAN Peizheng, et al. Robust economic dispatch method of microgrid containing high propotion of wind power[J]. Control Theory & Applications, 2017, 34(8): 1104-1111.
[12]	陈灵敏, 吴杰康, 张文杰, 等. 基于鲁棒优化的微能源网综合需求响应协同调度策略[J]. 电力系统自动化, 2021, 45(21): 159-169.
	CHEN Lingmin, WU Jiekang, ZHANG Wenjie, et al. Robust optimization based coordinated scheduling strategy for integrated demand response in micro energy grid[J]. Automation of Electric Power Systems, 2021, 45(21): 159-169.
[13]	朱嘉远, 刘洋, 许立雄, 等. 考虑风电消纳的热电联供型微网日前鲁棒经济调度[J]. 电力系统自动化, 2019, 43(4): 40-48.
	ZHU Jiayuan, LIU Yang, XU Lixiong, et al. Robust day-ahead economic dispatch of microgrid with combined heat and power system considering wind power accommodation[J]. Automation of Electric Power Systems, 2019, 43(4): 40-48.
[14]	盛四清, 张佳欣, 李然, 等. 考虑综合需求响应的综合能源系统多能协同优化调度[J]. 电力自动化设备, 2023, 43(6): 1-9.
	SHENG Siqing, ZHANG Jiaxin, LI Ran, et al. Multi-energy collaborative optimization scheduling of integrated energy system considering integrated demand response[J]. Electric Power Automation Equipment, 2023, 43(6): 1-9.
[15]	彭春华, 陈婧, 郑聪. 基于机会约束高斯混合模型的含光热电站热电联供型微网鲁棒经济调度[J]. 电力自动化设备, 2021, 41(4): 77-84.
	PENG Chunhua, CHEN Jing, ZHENG Cong. Robust economic dispatch of CSP-CHPMG based on chance constrained Gaussian mixture model[J]. Electric Power Automation Equipment, 2021, 41(4): 77-84.
[16]	邹云阳, 杨莉, 李佳勇, 等. 冷热电气多能互补的微能源网鲁棒优化调度[J]. 电力系统自动化, 2019, 43(14): 65-72.
	ZOU Yunyang, YANG Li, LI Jiayong, et al. Robust optimal dispatch of micro-energy grid with multi-energy complementation of cooling heating power and natural gas[J]. Automation of Electric Power Systems, 2019, 43(14): 65-72.
[17]	EBRAHIMI M R, AMJADY N. Adaptive robust optimization framework for day-ahead microgrid scheduling[J]. International Journal of Electrical Power & Energy Systems, 2019, 107: 213-223.
[18]	朱兰, 牛培源, 唐陇军, 等. 考虑直接负荷控制不确定性的微能源网鲁棒优化运行[J]. 电网技术, 2020, 44(4): 1400-1409.
	ZHU Lan, NIU Peiyuan, TANG Longjun, et al. Robust optimal operation for micro-energy grid considering uncertainties of direct load control[J]. Power System Technology, 2020, 44(4): 1400-1409.
[19]	QIU H F, GU W, XU Y L, et al. Interval-partitioned uncertainty constrained robust dispatch for AC/DC hybrid microgrids with uncontrollable renewable generators[J]. IEEE Transactions on Smart Grid, 2019, 10(4): 4603-4614.
[20]	李鹏, 吴迪凡, 李雨薇, 等. 基于综合需求响应和主从博弈的多微网综合能源系统优化调度策略[J]. 中国电机工程学报, 2021, 41(4): 1307-1321.
	LI Peng, WU Difan, LI Yuwei, et al. Optimal dispatch of multi-microgrids integrated energy system based on integrated demand response and stackelberg game[J]. Proceedings of the CSEE, 2021, 41(4): 1307-1321.
[21]	ZENG B, ZHAO L. Solving two-stage robust optimization problems using a column-and-constraint generation method[J]. Operations Research Letters, 2013, 41(5): 457-461.
[22]	BERTSIMAS D, LITVINOV E, SUN X A, et al. Adaptive robust optimization for the security constrained unit commitment problem[J]. IEEE Transactions on Power Systems, 2013, 28(1): 52-63.

设备名称	效率	容量	运维费用/ [元·( kW·h)^-1]
热电联产机组	0.25(电), 0.48(热)	500 kW	0.0045
燃气锅炉	0.8	400 kW	0.0043
吸收式制冷机	1.1	200 kW	0.003
电储能设备	0.95	200 kW·h	0.1
热储能设备	0.9	150 kW·h	0.05
气储能设备	0.95	200 kW·h	0.05
冷储能设备	0.88	100 kW·h	0.05

时间	购/售电价格	购气价格
1:00—7:00	0.41/0.246	0.21
8:00—10:00, 23:00—24:00	0.74/0.444	0.33
11:00—22:00	1.10/0.660	0.41

场景	总成本	购能成本	设备维护成本	IDR成本
1	8528.4	8410.8	117.6	0
2	8279.7	7823.5	117.6	338.5
3	8173.7	7534.6	114.5	524.5
4	8090.3	7454.3	111.4	524.5

模型	总成本	购能成本	设备维护成本	IDR成本
1	7695.7	6946.9	109.0	639.8
2	8236.7	7486.5	110.4	639.8
3	7994.9	7245.3	109.8	639.8
4	8090.3	7454.3	111.4	524.5

Γ_pv,_k	Γ_wt,_k	Γ_e,_k	Γ_c,_k	Γ_h,_k	Γ_IDR	总成本/元
(0, 0, 0)	(0, 0, 0)	(0, 0)	(0, 0)	(0, 0)	0	7695.7
(0, 2, 1)	(2, 3, 1)	(4, 2)	(4, 2)	(4, 2)	6	7926.4
(2, 3, 1)	(5, 5, 2)	(9, 3)	(9, 3)	(9, 3)	12	8090.3
(5, 5, 2)	(10, 10, 4)	(18, 6)	(18, 6)	(18, 6)	24	8271.3