纸质出版:2026
移动端阅览
于娜, 黄鑫鑫, 黄大为, 等. 基于自适应初值调整的全纯嵌入法最优潮流计算[J]. 电力系统保护与控制, 2026,54(13).
YU Na, HUANG Xinxin, HUANG Dawei, et al. Optimal power flow calculation based on the holomorphic embedding method with adaptive initial value adjustment[J]. Power System Protection and Control, 2026, 54(13).
于娜, 黄鑫鑫, 黄大为, 等. 基于自适应初值调整的全纯嵌入法最优潮流计算[J]. 电力系统保护与控制, 2026,54(13). DOI: 10.19783/j.cnki.pspc.251374.
YU Na, HUANG Xinxin, HUANG Dawei, et al. Optimal power flow calculation based on the holomorphic embedding method with adaptive initial value adjustment[J]. Power System Protection and Control, 2026, 54(13). DOI: 10.19783/j.cnki.pspc.251374.
为解决全纯嵌入法 (holomorphic embedding method
HEM) 求解最优潮流 (optimal power flow
OPF) 时难以处理不等式 Karush-Kuhn-Tucker (KKT) 条件而引起的变量与乘子冲突的问题,提出一种基于 HEM 的 OPF 求解框架。该框架将不等式乘子以平方形式参数化以避免乘子取负时的路径失效,并将 KKT 变量划分为潮流物理变量与乘子变量。以直流最优潮流 (direct current optimal power flow
DC OPF) 解作为部分变量的预设初值,并由无功平衡关系确定无功变量的预设初值。提出基于惩罚机制的自适应不等式乘子初值调整策略,引导解析延拓过程。在 5 节点及 IEEE6/9/14/30 节点系统中与中心轨迹内点法进行对比,HEM 经较少次数的递归即可逼近 OPF 目标解。结果表明,该方法提升了 OPF 求解的准确性与可行性,为含有不等式约束的 OPF 计算提供一种解析化求解方法。
To address the conflict between variables and multipliers caused by the difficulty of handling inequality-constrained Karush-Kuhn-Tucker (KKT) conditions in the solution of optimal power flow (OPF) problems using the holomorphic embedding method (HEM)
a novel HEM-based OPF solution framework is proposed. In this framework
inequality multipliers are parameterized in squared form to prevent path failure caused by negative multiplier values
and the KKT variables are partitioned into power-flow physical variables and multipliers. The direct current OPF solution is employed as the preset initial values for a subset of variables
while the preset initial values of reactive-power are derived from reactive power balance relations. Furthermore
an adaptive penalty-based initialization strategy adjusts inequality multipliers to guide analytical continuation toward the solution. Compared with the central-trajectory interior-point method on a 5-bus and the IEEE 6/9/14/30-bus systems
the proposed HEM approach can converge to the OPF solution with only a small number of recursive iterations. The results show that the proposed method improves the accuracy and feasibility of OPF computation
offering an analytical approach for OPF problems under inequality constraints.
XIAO J, ZHOU Y, SHE B, et al. A general simplification and acceleration method for distribution system optimization problems[J]. Protection and Control of Modern Power Systems, 2025, 10(1): 148-167.
DOMMEL H W, TINNEY W F. Optimal power flow solutions[J]. IEEE Transactions on Power Apparatus and Systems, 1968, 87(10): 1866-1876.
STOTT B, ALSAC O. Fast decoupled load flow[J]. IEEE Transactions on Power Apparatus and Systems, 1974, 93(3): 859-869.
TRIAS A. The holomorphic embedding load flow method[C] // Proceedings of the 2012 IEEE Power and Energy Society General Meeting, July 22-26, 2012, San Diego, California, USA: 1-8.
SUBRAMANIAN M K, FENG Y, TYLAVSKY D. PV bus modeling in a holomorphically embedded power-flow formulation[C] // 2013 North American Power Symposium (NAPS 2013), September 22-24, 2013, Manhattan, Kansas, USA: 1-6.
TRIAS A, MARIN J L. The holomorphic embedding load-flow method for DC power systems and nonlinear DC circuits[J]. IEEE Transactions on Circuits and Systems I: Regular Papers, 2016, 63(2): 322-333.
CHEVALIER S C, HINES P D H. Mitigating the risk of voltage collapse using statistical measures from PMU data[J]. IEEE Transactions on Power Systems, 2019, 34(1): 120-128.
SINGH P, TIWARI R. Extended holomorphic embedded load-flow method and voltage stability assessment of power systems[J]. Electric Power Systems Research, 2020, 185.
RAO S, TYLAVSKY D J, FENG Y. Estimating the saddle-node bifurcation point of static power systems using the holomorphic embedding method[J]. International Journal of Electrical Power Energy Systems, 2017, 84: 1-12.
LIU C, SUN K, WANG B, et al. Probabilistic power flow analysis using multidimensional holomorphic embedding and generalized cumulants[J]. IEEE Transactions on Power Systems, 2018, 33(6): 7132-7142.
PAN S, LI Z, ZHENG J, et al. A non-iterative solution method for DC optimal power flow based on holomorphic embedding[C] // 2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2 2021), October 22-24, 2021, Taiyuan, China: 1865-1870.
RAO B V, KUPZOG F, KOZEK M. Three-phase unbalanced optimal power flow using holomorphic embedding load flow method[J]. Sustainability, 2019, 11(6).
SAYED A R, ZHANG X, WANG G, et al. Optimal operable power flow: Sample-efficient holomorphic embedding-based reinforcement learning[J]. IEEE Transactions on Power Systems, 2024, 39(1): 1739-1751.
CAIN M B, O’NEILL R P, CASTILLO A. History of optimal power flow and formulations[R]. Washington: Federal Energy Regulatory Commission, 2012.
RANGE R M. Holomorphic functions and integral representations in several complex variables[M]. New York, USA: Springer Science Business Media, 1998.
0
浏览量
14
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621