BI-LEVEL OPTIMISATION OF VIRTUAL POWER PLANT CONSIDERING SOURCE-LOAD COORDINATED RESPONSE AND DYNAMIC PRICING

Li Bo; Cheng Jing

doi:10.19912/j.0254-0096.tynxb.2023-0879

PDF(1253 KB)

Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (10) : 107-120. DOI: 10.19912/j.0254-0096.tynxb.2023-0879

BI-LEVEL OPTIMISATION OF VIRTUAL POWER PLANT CONSIDERING SOURCE-LOAD COORDINATED RESPONSE AND DYNAMIC PRICING

Li Bo^1,2, Cheng Jing^1,2

Author information +

History +

Abstract

In order to guide the followers to actively participate in the main body operation, a comprehensive dynamic pricing mechanism is proposed in combination with the evaluation indices such as system carbon emissions and load interruption. This mechanism can dynamically adjust the electricity selling price to the lower load according to the information such as carbon emissions and load interruption, and reasonably guide the lower load to participate in the upper optimization, so as to achieve win-win results for multiple stakeholders at the upper and lower levels. At the same time, combined with the demand response characteristics of the electro-hydro-thermal system and the electro-thermal load, a source-load coordinated response mechanism is proposed. The dynamic pricing mechanism is used as a link to realize the deep integration of the demand response characteristics of the upper-level electric-hydrogen thermoelectric system and the lower-level electric-heat load, improve the energy utilization efficiency of the energy side, and jointly realize the coordinated economic operation of the upper and lower layers. In addition, based on the electrical and thermal load dissatisfaction coefficient, the load energy dissatisfaction model is constructed and included in the system operation cost. Secondly, in order to deal with the uncertainty analysis of wind-solar power generation and load, a robust optimization method considering uncertain parameters is introduced to deal with the source-load uncertainty, so as to realize the flexible coordination between economy and robustness of the virtual power plant. At the same time, the influence of uncertain parameters on the operation of the virtual power plant is realized in depth. Finally, CPLEX-C&CG is used to solve the two-layer model iteratively, and the joint optimal solution of the system is selected according to the joint optimal discriminant mechanism. The results of the example verify the effectiveness of the model and method.

Key words

renewable energy / virtual power plant / uncertainty analysis / dynamic pricing / bi-level optimization / demand response

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Li Bo, Cheng Jing. BI-LEVEL OPTIMISATION OF VIRTUAL POWER PLANT CONSIDERING SOURCE-LOAD COORDINATED RESPONSE AND DYNAMIC PRICING[J]. Acta Energiae Solaris Sinica. 2024, 45(10): 107-120 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0879

References

[1] 袁桂丽, 贾新潮, 陈少梁, 等. 虚拟电厂源-荷协调多目标优化调度[J]. 太阳能学报, 2021, 42(5): 105-112.
YUAN G L, JIA X C, CHEN S L, et al.Multiobjective optimal dispatch considering source-load coordination for virtual power plant[J]. Acta energiae solaris sinica, 2021, 42(5): 105-112.
[2] GE L J, LIU H X, YAN J, et al.Optimal integrated energy system planning with DG uncertainty affine model and carbon emissions charges[J]. IEEE transactions on sustainable energy, 2022, 13(2): 905-918.
[3] 张大海, 贠韫韵, 王小君, 等. 计及风光不确定性的新能源虚拟电厂多时间尺度优化调度[J]. 太阳能学报, 2022, 43(11): 529-537.
ZHANG D H, YUN Y Y, WANG X J, et al.Multi-time scale of new energy scheduling optimization for virtual power plant considering uncertainty of wind power and photovoltaic power[J]. Acta energiae solaris sinica, 2022, 43(11): 529-537.
[4] 李东东, 王啸林, 沈运帷, 等. 考虑多重不确定性的含需求响应及电碳交易的虚拟电厂优化调度策略[J]. 电力自动化设备, 2023, 43(5): 210-217, 251.
LI D D, WANG X L, SHEN Y W, et al.Optimal scheduling strategy of virtual power plant with demand response and electricity-carbon trading considering multiple uncertainties[J]. Electric power automation equipment, 2023, 43(5): 210-217, 251.
[5] 齐先军, 蒋中琦, 张晶晶, 等. 考虑碳捕集与综合需求响应互补的综合能源系统优化调度[J].电力自动化设备, 2023, 43(7): 133-141.
QI X J, JIANG Z Q, ZHANG J J, et al.Optimal dispatching of integrated energy system considering complementation of carbon capture and integrated demand response[J]. Electric power automation equipment, 2023, 43(7): 133-141.
[6] 李斯, 周任军, 童小娇, 等. 基于盒式集合鲁棒优化的风电并网最大装机容量[J]. 电网技术, 2011, 35(12): 208-213.
LI S, ZHOU R J, TONG X J, et al.Robust optimization with box set for maximum installed capacity of wind farm connected to grid[J]. Power system technology, 2011, 35(12): 208-213.
[7] 刘一欣, 郭力, 王成山. 微电网两阶段鲁棒优化经济调度方法[J]. 中国电机工程学报, 2018, 38(14): 4013-4022, 4307.
LIU Y X, GUO L, WANG C S.Economic dispatch of microgrid based on two stage robust optimization[J]. Proceedings of the CSEE, 2018,38(14): 4013-4022, 4307.
[8] 刘丽军, 罗宁, 吴桐, 等. 基于混合整数二阶锥规划的考虑需求侧响应虚拟电厂优化调度[J]. 太阳能学报, 2021, 42(8): 96-104.
LIU L J, LUO N, WU T, et al.Optimal scheduling of virtual power plant considering demand side response based on mixed integer second-order cone programming[J]. Acta energiae solaris sinica, 2021, 42(8): 96-104.
[9] GUO Z H, ZHANG R, WANG L, et al.Optimal operation of regional integrated energy system considering demand response[J]. Applied thermal engineering, 2021, 191: 116860.
[10] 师阳, 李宏伟, 陈继开, 等. 计及激励型需求响应的热电互联虚拟电厂优化调度[J]. 太阳能学报, 2023, 44(4): 349-358.
SHI Y, LI H W, CHEN J K, et al.Optimal scheduling of thermoelectric interconnection virtual power plant considerign incentive demand response[J]. Acta energiae solaris sinica, 2023, 44(4): 349-358.
[11] 杨冬锋, 徐扬, 姜超. 考虑多类型需求响应的电-热联合系统多时间尺度协调调度[J]. 太阳能学报, 2021, 42(10): 282-289.
YANG D F, XU Y, JIANG C.Multiple time-scale coordinated scheduling of combined electro-thermal system considering multi-type demand response[J].Acta energiae solaris sinica, 2021, 42(10): 282-289.
[12] 陈锦鹏, 胡志坚, 陈嘉滨, 等. 考虑阶梯式碳交易与供需灵活双响应的综合能源系统优化调度[J]. 高电压技术, 2021, 47(9): 3094-3106.
CHEN J P, HU Z J, CHEN J B, et al.Optimal dispatch of integrated energy system considering ladder-type carbon trading and flexible double response of supply and demand[J]. High voltage engineering, 2021, 47(9): 3094-3106.
[13] LI Y, HAN M, YANG Z, et al.Coordinating flexible demand response and renewable uncertainties for scheduling of community integrated energy systems with an electric vehicle charging station: a Bi-level approach[J]. IEEE transactions on sustainable energy, 2021, 12(4): 2321-2331.
[14] 帅轩越, 马志程, 王秀丽, 等. 基于主从博弈理论的共享储能与综合能源微网优化运行研究[J]. 电网技术, 2023, 47(2): 679-690.
SHUAI X Y, MA Z C, WANG X L, et al.Optimal operation of shared energy storage and integrated energy microgrid based on leader-follower game theory[J]. Power system technology, 2023, 47(2): 679-690.
[15] 张程, 匡宇, 邹复民, 等. 考虑风光不确定性与电动汽车的综合能源系统低碳经济调度[J]. 电力自动化设备, 2022, 42(10): 236-244.
ZHANG C, KUANG Y, ZOU F M, et al.Low carbon economic dispatch of integrated energy system considering wind and solar uncertainty and electric vehicles[J]. Electric power automation equipment, 2022, 42(10): 236-244.
[16] 程宇, 郭权利. 计及动态能源价格和共享储能电站的多主体综合能源系统双层优化调度策略[J]. 现代电力, 2024, 41(1): 10-20.
CHENG Y, GUO Q L.Bi-level optimal scheduling strategy of multi-agent integrated energy system with dynamic energy prices and shared energy storage power station[J]. Modern electric power, 2024, 41(1): 10-20.
[17] 韩丽, 鲁盼盼, 王晓静, 等. 考虑氢燃料电池响应延迟特性的电网日内优化调度[J]. 太阳能学报, 2022, 43(6): 373-381.
HAN L, LU P P, WANG X J, et al.Intraday optimal dispatch of power grid considering response delay characteristics of hydrogen fule cells[J]. Acta energiae solaris sinica, 2022, 43(6): 373-381.
[18] 周磊, 明庆永, 袁全. 考虑需求响应及电能交互的多微电网优化调度[J]. 电工技术, 2023(2): 52-55.
ZHOU L,MING Q Y,YUAN Q.Optimal dispatch of multi-microgrid considering demand response and power interaction[J]. Electric engineering, 2023(2): 52-55.
[19] 崔杨, 曾鹏, 仲悟之, 等. 考虑阶梯式碳交易的电-气-热综合能源系统低碳经济调度[J]. 电力自动化设备, 2021, 41(3): 10-17.
CUI Y,ZENG P,ZHONG W Z, et al.Low-carbon economic dispatch of electricity-gas-heat integrated energy system based on ladder-type carbon trading[J]. Electric power automation equipment, 2021, 41(3): 10-17.
[20] LUO Z, HONG S H, DING Y M.A data mining-driven incentive-based demand response scheme for a virtual power plant[J]. Applied energy, 2019, 239: 549-559.
[21] 姜飞, 肖昌麟, 易子木, 等. 含光伏与生物质能的生态农业综合能源系统多能协同及低碳运行策略[J]. 中国电机工程学报, 2024, 44(4): 1352-1364.
JIANG F, XIAO C L, YI Z M, et al.Multi-energy cooperation and low-carbon operation strategy of eco-agricultural integrated energy system containing photovoltaic and biomass energy[J]. Proceedings of the CSEE, 2024, 44(4): 1352-1364.
[22] 晋旭东, 孙磊, 丁明, 等. 考虑用户响应不确定性的园区综合能源系统分布鲁棒低碳调度[J]. 电力系统自动化, 2023, 47(16): 10-21.
JIN X D, SUN L, DING M, et al.Distributionally robust low-carbon dispatch of park-level integrated energy system considering uncertainty of customer response[J]. Automation of electric power systems, 2023, 47(16): 10-21.