OPTIMAL ALLOCATION OF WIND-PHOTOVOLTAIC-THERMAL-STORAGE COMBINED TRANSMISSION SYSTEM WITH CSP STATION

Mei Hui; Gao Bingtuan; Cao Zeyu; Chen Ning

doi:10.19912/j.0254-0096.tynxb.2021-0747

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Acta Energiae Solaris Sinica ›› 2022, Vol. 43 ›› Issue (12) : 124-133. DOI: 10.19912/j.0254-0096.tynxb.2021-0747

OPTIMAL ALLOCATION OF WIND-PHOTOVOLTAIC-THERMAL-STORAGE COMBINED TRANSMISSION SYSTEM WITH CSP STATION

Mei Hui¹, Gao Bingtuan¹, Cao Zeyu¹, Chen Ning²

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Abstract

In order to solve the problem of renewable energy accommodation in northwestern China, a method for optimal allocation of wind-photovoltaic-thermal-storage combined transmission system with CSP is proposed. Firstly, based on the complementary characteristics of wind-photovoltaic-thermal-storage, establish a typical architecture of wind-photovoltaic-thermal-storage combined transmission system with CSP, and analyze its working mechanism. Secondly, combine Latin hypercube sampling and timing reconstruction, timing combination and scene selection based on timing autocorrelation and cross-correlation, generate a set of random scenes considering time series auto-correlation and cross-correlation. Then, a multi-objective optimal allocation model of the wind-photovoltaic-thermal-storage combined transmission system with CSP is constructed based on the optimal system benefits including carbon emission costs and the system’s new energy absorption capacity. The model was solved by the augmented ε-constraint method combined with the commercial software CPLEX. Finally, an example of power grid planning data construction in a northwest region in 2025 is used for simulation, and it is verified that the configuration method can effectively improve the system revenue, promote the scenery absorption, and improve the power delivery capacity of the system.

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optimal allocation / concentrating solar power station / new energy accommodation / carbon emission / wind-photovoltaic-thermal-storage

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Mei Hui, Gao Bingtuan, Cao Zeyu, Chen Ning. OPTIMAL ALLOCATION OF WIND-PHOTOVOLTAIC-THERMAL-STORAGE COMBINED TRANSMISSION SYSTEM WITH CSP STATION[J]. Acta Energiae Solaris Sinica. 2022, 43(12): 124-133 https://doi.org/10.19912/j.0254-0096.tynxb.2021-0747

References

[1] ADRIANA Z, CARLOS M T, JOSÉ M C, et al.Assessment of time resolution impact on the modeling of a hybrid CSP-PV plant: a case of study in China[J]. Solar energy, 2020, 202: 553-570.
[2] 姚元玺. 计及调度经济性的CSP电站储热容量配置方法[J]. 太阳能学报, 2019, 40(11): 3039-3045.
YAO Y X.A method for allocation heat storage capacity of concentrating solar power considering scheduling economy[J]. Acta energiae solaris sinica, 2019, 40(11): 3039-3045.
[3] 卢延国. “风光配储”必须坚持市场化发展[N]. 中国能源报, 2020-09-28(004).
LU Y G. "Wind-solar-storage " must adhere to market-oriented development[N]. China Energy News, 2020-09-28(004).
[4] 曹建伟, 穆川文, 孙可, 等. 考虑碳交易的区域电网风光储容量配置优化方法[J]. 武汉大学学报(工学版), 2020, 53(12): 1091-1096, 1105.
CAO J W, MU C W, SUN K, et al.Optimal configuration method of wind-photovoltaic-storage capacities for regional power grid considering carbon trading[J]. Engineering Journal of Wuhan University(engineering edition), 2020, 53(12): 1091-1096, 1105.
[5] 沙韵, 周明, 杨宏基, 等. 考虑CSP电站和直流联络线灵活性的高比例新能源互联系统优化运行[J]. 电网技术, 2020, 44(9): 3306-3313.
SHA Y, ZHOU M, YANG H J, et al.Optimal operation of interconnected power systems with high share of renewables generation considering flexibility of concentrating solar power plants and HVDC tie-line[J]. Power system technology, 2020, 44(9): 3306-3313.
[6] 吕凯, 唐昊, 王珂, 等. 计及源荷双侧不确定性的跨区互联电网源网荷协同调度[J]. 电力系统自动化, 2019, 43(22): 38-45, 150.
LYU K, TANG H, WANG K, et al.Design and key technologies of mobile terminal for dispatching and control system in large-scale power grid[J]. Automation of electric power systems, 2019, 43(22): 38-45, 150.
[7] 夏鹏, 刘文颖, 张雨薇, 等. 大规模风电送端电网风、火电耦合外送多目标优化模型及算法[J]. 可再生能源, 2019, 37(12): 1826-1834.
XIA P, LIU W Y, ZHANG Y W, et al.Multi-objective optimization model and algorithm of the coupling delivery of wind & thermal power in large-scale wind power transmission network[J]. Renewable energy resources, 2019, 37(12): 1826-1834.
[8] 钟嘉庆, 王一鸣, 赵志锋, 等. 低碳电源规划不确定性多目标鲁棒优化研究[J]. 太阳能学报, 2020, 41(9): 114-120.
ZHONG J Q, WANG Y M, ZHAO Z F, et al.Research on multi-objective robust optimization about low carbon generation expansion planning considering uncertainty[J]. Acta energiae solaris sinica, 2020, 41(9): 114-120.
[9] 吴玮坪, 胡泽春, 宋永华. 结合随机规划和序贯蒙特卡洛模拟的风电场储能优化配置方法[J]. 电网技术, 2018, 42(4): 1055-1062.
WU W P, HU Z C, SONG Y H.Optimal sizing of energy storage system for wind farms combining stochastic programming and sequential monte carlo simulation[J]. Power system technology, 2018, 42(4): 1055-1062.
[10] ZHANG C M, CHENG H Z, LIU L, et al.Coordination planning of wind farm, energy storage and transmission network with high-penetration renewable energy[J]. International journal of electrical power and energy systems, 2020, 120: 105944.
[11] YI B W, XU J H, YING F.Inter-regional power grid planning up to 2030 in China considering renewable energy development and regional pollutant control: a multi-region bottom-up optimization model[J]. Applied energy, 2016, 184.
[12] 李昀昊, 王建学, 曹晓宇, 等. 面向风电场-储能-输电网联合规划的机会约束IGDT模型[J]. 电网技术, 2019, 43(10): 3715-3724.
LI Y H, WANG J X, CAO X Y, et al.A chance-constrained IGDT model for joint planning of wind farm, energy storage and transmission[J]. Power system technology, 2019, 43(10): 3715-3724.
[13] 崔杨, 张汇泉, 仲悟之, 等. 基于分时能量互补的风电-光热联合外送容量优化配置方法[J]. 电网技术, 2019, 43(11): 3875-3882.
CUI Y, ZHANG H Q, ZHONG W Z, et al.An optimization method to determine power delivery capacity of combined wind-CSP system based on time-sharing energy complementation[J]. Power system technology, 2019, 43(11): 3875-3882.
[14] 刘树桦, 王建学, 秦绪武, 等. 基于个体优化和系统多能互补的CSP电站优化配置方法[J]. 电网技术, 2020, 44(7): 2503-2512.
LIU S Y, WANG J X, QIN X W, et al.Research on optimal configuration of concentrating solar power based on individual optimization and multi-energy complementary[J]. Power system technology, 2020, 44(7): 2503-2512.
[15] CARTA J A, RAMIREZ P, VELAZQUEZ S.A review of wind speed probability distributions used in wind energy analysis: case studies in the Canary Islands[J]. Renewable and sustainable energy reviews, 2009, 13(5): 933-955.
[16] ATWA Y M, EL-SAADANY E F, SALAMA M M A, et al. Optimal renewable resources mix for distribution system energy loss minimization[J]. IEEE transactions on power systems, 2010, 25(1): 360-370.
[17] 邹泽宇, 刘文泽, 蔡泽祥. 基于增广ε-约束法的冷热电联供系统容量优化配置[J]. 广东电力, 2019, 32(10): 36-44.
ZOU Z Y, LIU W Z, CAI Z X.Capacity optimization configuration of CCHP system based on augmented ε-constraint method[J]. Guangdong electric power, 2019, 32(10): 36-44.
[18] 孙偲, 陈来军, 邱欣杰, 等. 基于合作博弈的发电侧共享储能规划模型[J]. 全球能源互联网, 2019, 2(4): 360-366.
SUN C, CHEN L J, QIU X J, et al.A generation-side shared energy storage planning model based on cooperative game[J]. Journal of global energy interconnection, 2019, 2(4): 360-366.
[19] 史昭娣, 王伟胜, 黄越辉, 等. 考虑决策相关随机规划的CSP电站容量配置[J]. 中国电机工程学报, 2020, 40(23): 7511-7522.
SHI Z D, WANG W S, HUANG Y H, et al.Capacity optimization of concentrating solar power plant based on decision-dependent stochastic programming[J]. Proceedings of the CSEE, 2020, 40(23): 7511-7522.
[20] 崔杨, 张家瑞, 王铮, 等. 计及价格型需求响应的风-光-光热联合发电系统日前调度策略[J]. 中国电机工程学报, 2020, 40(10): 3103-3114.
CUI Y, ZHANG J R, WANG Z, et al.Day-ahead scheduling strategy of wind-PV-CSP hybrid power generation system by considering PDR[J]. Proceedings of the CSEE, 2020, 40(10): 3103-3114.