RISK-AVERSE INVESTMENT MODELS AND DISTRIBUTED SOLUTION STRATEGIES FOR POWER SYSTEMS

Tian Kunpeng; Han Jianzhen; Zang Yi; Wang Jun

doi:10.19912/j.0254-0096.tynxb.2023-1048

PDF(1755 KB)

Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (11) : 34-39. DOI: 10.19912/j.0254-0096.tynxb.2023-1048

RISK-AVERSE INVESTMENT MODELS AND DISTRIBUTED SOLUTION STRATEGIES FOR POWER SYSTEMS

Tian Kunpeng¹, Han Jianzhen², Zang Yi¹, Wang Jun¹

Author information +

History +

Abstract

A mathematical model is established for generation, transmission, controllable load, and energy storage. The conditional value-at-risk is used to measure renewable energy uncertainty. A coordinated framework of “source-grid-load-storage” is proposed for the interconnected power system. A solution method is proposed to consider the information security and privacy of each regional power system. The centralized optimization model is decoupled into a distributed optimization model using inter-regional contact lines as coupling variables. The dynamic penalty parameters and prediction correction strategy are integrated into the alternating direction multiplier algorithm to improve the convergence speed. The numerical results verify the effectiveness of the risk-averse investment model based on distributed optimization.

Key words

mathematical models / regional planning / renewable energy / energy storage / risk analysis / power system simulation / distributed optimization

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Tian Kunpeng, Han Jianzhen, Zang Yi, Wang Jun. RISK-AVERSE INVESTMENT MODELS AND DISTRIBUTED SOLUTION STRATEGIES FOR POWER SYSTEMS[J]. Acta Energiae Solaris Sinica. 2024, 45(11): 34-39 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1048

References

[1] 徐潇源, 王晗, 严正, 等. 能源转型背景下电力系统不确定性及应对方法综述[J]. 电力系统自动化, 2021, 45(16): 2-13.
XU X Y, WANG H, YAN Z, et al.Overview of power system uncertainty and its solutions under energy transition[J]. Automation of electric power systems, 2021, 45(16): 2-13.
[2] MUÑOZ-DELGADO G, CONTRERAS J, ARROYO J M, et al. Integrated transmission and distribution system expansion planning under uncertainty[J]. IEEE transactions on smart grid, 2021, 12(5): 4113-4125.
[3] HUANG W J, ZHANG X, LI K P, et al.Resilience oriented planning of urban multi-energy systems with generalized energy storage sources[J]. IEEE transactions on power systems, 2022, 37(4): 2906-2918.
[4] PUVVADA N Y, MOHAPATRA A, SRIVASTAVA S C.Robust AC transmission expansion planning using a novel dual-based Bi-level approach[J]. IEEE transactions on power systems, 2022, 37(4): 2881-2893.
[5] 张晓辉, 李阳, 钟嘉庆, 等. 基于安全因子及协同因子的源网多目标协调规划[J]. 电工技术学报, 2021, 36(9): 1842-1856.
ZHANG X H, LI Y, ZHONG J Q, et al.Multi-objective coordinated planning of source network based on safety factor and coordination factor[J]. Transactions of China Electrotechnical Society, 2021, 36(9): 1842-1856.
[6] 张虹, 孟庆尧, 马鸿君, 等. 面向提升绿证需求的跨区互联系统经济低碳调度策略[J]. 电力系统自动化, 2022, 46(22): 51-61.
ZHANG H, MENG Q Y, MA H J, et al.Economic and low-carbon dispatching strategy of cross-region interconnected system for promoting green certificate demand[J]. Automation of electric power systems, 2022, 46(22): 51-61.
[7] 申家锴, 刘洋, 李卫东, 等. 考虑频率与区间联络线功率安全约束的两区互联电力系统机组组合[J]. 电力自动化设备, 2022, 42(11): 167-175, 189.
SHEN J K, LIU Y, LI W D, et al.Unit commitment considering safety constraints of frequency and inter-areal tie-line power in two-area interconnected power system[J]. Electric power automation equipment, 2022, 42(11): 167-175, 189.
[8] 喻文翔, 韩子熙, 许洵, 等. 考虑解耦功率优化分配的多端混合直流互联系统频率响应控制策略[J]. 电网技术, 2023, 47(5): 1798-1810.
YU W X, HAN Z X, XU X, et al.Frequency response control strategy for multi-terminal hybrid DC interconnected systems considering decoupling of optimal power allocation[J]. Power system technology, 2023, 47(5): 1798-1810.
[9] YANG Y, QIU J, MA J, et al.Integrated grid, coal-fired power generation retirement and GESS planning towards a low-carbon economy[J]. International journal of electrical power & energy systems, 2021, 124: 106409.
[10] 刘俊磊, 田鹏飞, 钱峰, 等. 风电不确定性波动下的交直流输电容量优化模型[J]. 太阳能学报, 2021, 42(7): 431-436.
LIU J L, TIAN P F, QIAN F, et al.Optimization model of AC-DC transmission capacity under uncertainty fluctuation of wind power[J]. Acta energiae solaris sinica, 2021, 42(7): 431-436.
[11] 孟庆强, 李湘旗, 禹海峰, 等. 考虑源-荷不确定性的储能电站优化规划[J]. 太阳能学报, 2021, 42(10): 415-423.
MENG Q Q, LI X Q, YU H F, et al.Optimal planning of energy storage power station considering source-charge uncertainty[J]. Acta energiae solaris sinica, 2021, 42(10): 415-423.
[12] 杨丽君, 黄凯婷, 孔晓磊, 等. 考虑柔性负荷的并网型微电网系统容量优化配置[J]. 太阳能学报, 2021, 42(2): 309-316.
YANG L J, HUANG K T, KONG X L, et al.Capacity optimization configuration of grid-connected microgrid system considering flexible load[J]. Acta energiae solaris sinica, 2021, 42(2): 309-316.
[13] SABER H, HEIDARABADI H, MOEINI-AGHTAIE M, et al.Expansion planning studies of independent-locally operated battery energy storage systems (BESSs): a CVaR-based study[J]. IEEE transactions on sustainable energy, 2020, 11(4): 2109-2118.
[14] BOYD S PARIKH N,CHU E, et al. Distributed optimization and statistical learning via the alternating direction method of multipliers[J]. Foundations and trends® in machine learning, 2010, 3(1): 1-122.
[15] GOLDSTEIN T, O’DONOGHUE B, SETZER S, et al. Fast alternating direction optimization methods[J]. SIAM journal on imaging sciences, 2014, 7(3): 1588-1623.
[16] ZIMMERMAN R D, MURILLO-SÁNCHEZ C E, THOMAS R J. MATPOWER: steady-state operations, planning, and analysis tools for power systems research and education[J]. IEEE transactions on power systems, 2011, 26(1): 12-19.
[17] TIAN K P, SUN W Q, HAN D.Strategic investment in transmission and energy storage in electricity markets[J]. Journal of modern power systems and clean energy, 2022, 10(1): 179-191.