DISTRIBUTIONALLY ROBUST COOPERATIVE OPTIMAL SCHEDULING OF RESERVE AND DNE OF INTEGRATED ELECTRICITY AND HEATING SYSTEM FAULT RANDOMNESS

Liu Hongpeng, Li Hongwei, Ma Jianwei, Chen Jikai, Zhang Wei

Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (2) : 318-327.

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Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (2) : 318-327. DOI: 10.19912/j.0254-0096.tynxb.2022-1528

DISTRIBUTIONALLY ROBUST COOPERATIVE OPTIMAL SCHEDULING OF RESERVE AND DNE OF INTEGRATED ELECTRICITY AND HEATING SYSTEM FAULT RANDOMNESS

  • Liu Hongpeng1, Li Hongwei1, Ma Jianwei1,2, Chen Jikai1, Zhang Wei1
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Abstract

To achieve safe and stable operation of the integrated electric heating systems (IEHS) and improve the consumption of renewable energy, a distributionally robust cooperative optimal dispatching model of reserve and do-not-exceed (DNE) of IEHS considering the equipment fault randomness is proposed. Firstly, the deterministic optimal dispatching model of IEHS is established with the minimum operation cost of conventional units and combined heat and power units as the comprehensive optimization objective, and the power/heat balance and safety constraints as the constraints conditions; Secondly, the distributionally robust optimal dispatching model of IEHS is established, which comprehensively considers the wind power, equipment fault randomness and DNE limit. Finally, taking a modified 9-bus system is taken as an example, it is verified that the proposed model can effectively improve the wind power consumption rate and system economy.

Key words

integrated electricity and heating systems / distributionally robust optimization / wind power uncertainty / equipment fault randomness / DNE limit

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Liu Hongpeng, Li Hongwei, Ma Jianwei, Chen Jikai, Zhang Wei. DISTRIBUTIONALLY ROBUST COOPERATIVE OPTIMAL SCHEDULING OF RESERVE AND DNE OF INTEGRATED ELECTRICITY AND HEATING SYSTEM FAULT RANDOMNESS[J]. Acta Energiae Solaris Sinica. 2024, 45(2): 318-327 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1528

References

[1] 康重庆, 姚良忠. 高比例可再生能源电力系统的关键科学问题与理论研究框架[J]. 电力系统自动化, 2017, 41(9): 2-11.
KANG C Q, YAO L Z.Key scientific issues and theoretical research framework for power systems with high proportion of renewable energy[J]. Automation of electric power systems, 2017, 41(9): 2-11.
[2] PAPAVASILIOU A, OREN S S, O’NEILL R P. Reserve requirements for wind power integration: a scenario-based stochastic programming framework[J]. IEEE transactions on power systems, 2011, 26(4): 2197-2206.
[3] WANG Q F, GUAN Y P, WANG J H.A chance-constrained two-stage stochastic program for unit commitment with uncertain wind power output[J]. IEEE transactions on power systems, 2012, 27(1): 206-215.
[4] HUO D, GU C H, MA K, et al.Chance-constrained optimization for multienergy hub systems in a smart city[J]. IEEE transactions on industrial electronics, 2019, 66(2): 1402-1412.
[5] JIANG R W, WANG J H, GUAN Y P.Robust unit commitment with wind power and pumped storage hydro[J]. IEEE transactions on power systems, 2012, 27(2): 800-810.
[6] 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.
[7] LU X H, LIU Z X, MA L, et al.A robust optimization approach for optimal load dispatch of community energy hub[J]. Applied energy, 2020, 259: 114195.
[8] WEI W, LIU F, MEI S W.Dispatchable region of the variable wind generation[J]. IEEE transactions on power systems, 2015, 30(5): 2755-2765.
[9] SHAO C C, WANG X F, SHAHIDEHPOUR M, et al.Security-constrained unit commitment with flexible uncertainty set for variable wind power[J]. IEEE transactions on sustainable energy, 2017, 8(3): 1237-1246.
[10] ZHAO J Y, ZHENG T X, LITVINOV E.Variable resource dispatch through do-not-exceed limit[J]. IEEE transactions on power systems, 2015, 30(2): 820-828.
[11] WEI W, LIU F, MEI S W.Real-time dispatchability of bulk power systems with volatile renewable generations[J]. IEEE transactions on sustainable energy, 2015, 6(3): 738-747.
[12] 田坤鹏, 孙伟卿, 韩冬, 等. 基于两阶段鲁棒优化的可再生能源DNE极限评估[J]. 电力系统保护与控制, 2020, 48(19): 73-80.
TIAN K P, SUN W Q, HAN D, et al.DNE limit assessment of renewable energy based on two-stage robust optimization[J]. Power system protection and control, 2020, 48(19): 73-80.
[13] SHAO C C, WANG X F, SHAHIDEHPOUR M, et al.Power system economic dispatch considering steady-state secure region for wind power[J]. IEEE transactions on sustainable energy, 2017, 8(1): 268-278.
[14] LI Z G, WU W C, ZHANG B M, et al.Adjustable robust real-time power dispatch with large-scale wind power integration[J]. IEEE transactions on sustainable energy, 2015, 6(2): 357-368.
[15] WEI W, WANG J H, MEI S W.Dispatchability maximization for co-optimized energy and reserve dispatch with explicit reliability guarantee[J]. IEEE transactions on power systems, 2016, 31(4): 3276-3288.
[16] 税月, 刘俊勇, 高红均, 等. 考虑风电不确定性的电热综合系统分布鲁棒协调优化调度模型[J]. 中国电机工程学报, 2018, 38(24): 7235-7247, 7450.
SHUI Y, LIU J Y, GAO H J, et al.A distributionally robust coordinated dispatch model for integrated electricity and heating systems considering uncertainty of wind power[J]. Proceedings of the CSEE, 2018, 38(24): 7235-7247, 7450.
[17] LU X, CHAN K W, XIA S W, et al.Security-constrained multiperiod economic dispatch with renewable energy utilizing distributionally robust optimization[J]. IEEE transactions on sustainable energy, 2019, 10(2): 768-779.
[18] YANG Y, WU W C.A distributionally robust optimization model for real-time power dispatch in distribution networks[J]. IEEE transactions on smart grid, 2019, 10(4): 3743-3752.
[19] 贺帅佳, 阮贺彬, 高红均, 等. 分布鲁棒优化方法在电力系统中的理论分析与应用综述[J]. 电力系统自动化, 2020, 44(14): 179-191.
HE S J, RUAN H B, GAO H J, et al.Overview on theory analysis and application of distributionally robust optimization method in power system[J]. Automation of electric power systems, 2020, 44(14): 179-191.
[20] MA H Y, JIANG R W, YAN Z.Distributionally robust co-optimization of power dispatch and do-not-exceed limits[J]. IEEE transactions on power systems, 2020, 35(2): 887-897.
[21] LI R, WANG M Q, YANG M, et al.A distributionally robust model for reserve optimization considering contingency probability uncertainty[J]. International journal of electrical power & energy systems, 2022, 134: 107174.
[22] WOOD J, WOLLENBERG F.Power generation, operation, and control[M]. 2nd ed. New York: J. Wiley & Sons, 1996.
[23] BILLINTON R, ALLAN R N.Reliability evaluation of power systems[M]. 2nd ed. New York, London: Plenum Press, 1996.
[24] BOUFFARD F,GALIANA F D, CONEJO A J.Market-clearing with stochastic security-part I: formulation[J].IEEE transactions on power systems, 2005, 20(4): 1818-1826.
[25] BOUFFARD F, GALIANA F D, CONEJO A J.Market-clearing with stochastic security-part II: case studies[J].IEEE transactions on power systems, 2005, 20(4): 1827-1835.
[26] ZHAO C Y, JIANG R W.Distributionally robust contingency-constrained unit commitment[J]. IEEE transactions on power systems, 2018, 33(1): 94-102.
[27] ZHU R J, WEI H, BAI X Q.Wasserstein metric based distributionally robust approximate framework for unit commitment[J]. IEEE transactions on power systems, 2019, 34(4): 2991-3001.
[28] WEI W, LIU F, MEI S W, et al.Two-level unit commitment and reserve level adjustment considering large-scale wind power integration[J]. International transactions on electrical energy systems, 2014, 24(12): 1726-1746.
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