Dong Jiuling, Song Zilong, Zheng Yuanshuo, Luo Jingtang, Zhang Min, Yang Xiaolong, Ma Hongbing
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China.
School of Information Science and Technology, Hainan Normal University, Haikou 571158, China.
Entropy (Basel). 2024 Sep 17;26(9):795. doi: 10.3390/e26090795.
To mitigate the impact of wind power uncertainty and power-communication coupling on the robustness of a new power system, a bi-level mixed-integer robust optimization strategy is proposed. Firstly, a coupled network model is constructed based on complex network theory, taking into account the coupled relationship of energy supply and control dependencies between the power and communication networks. Next, a bi-level mixed-integer robust optimization model is developed to improve power system resilience, incorporating constraints related to the coupling strength, electrical characteristics, and traffic characteristics of the information network. The upper-level model seeks to minimize load shedding by optimizing DC power flow using fuzzy chance constraints, thereby reducing the risk of power imbalances caused by random fluctuations in wind power generation. Furthermore, the deterministic power balance constraints are relaxed into inequality constraints that account for wind power forecasting errors through fuzzy variables. The lower-level model focuses on minimizing traffic load shedding by establishing a topology-function-constrained information network traffic model based on the maximum flow principle in graph theory, thereby improving the efficiency of network flow transmission. Finally, a modified IEEE 39-bus test system with intermittent wind power is used as a case study. Random attack simulations demonstrate that, under the highest link failure rate and wind power penetration, Model 2 outperforms Model 1 by reducing the load loss ratio by 23.6% and improving the node survival ratio by 5.3%.
为减轻风电不确定性和电力 - 通信耦合对新型电力系统鲁棒性的影响，提出了一种双层混合整数鲁棒优化策略。首先，基于复杂网络理论构建耦合网络模型，考虑电力网络与通信网络之间的能量供应耦合关系以及控制依赖关系。其次，建立双层混合整数鲁棒优化模型以提高电力系统弹性，纳入与信息网络耦合强度、电气特性和流量特性相关的约束。上层模型通过使用模糊机会约束优化直流潮流来寻求最小化负荷削减，从而降低风电随机波动导致功率不平衡的风险。此外，确定性功率平衡约束被放宽为考虑风电预测误差的不等式约束，通过模糊变量来实现。下层模型通过基于图论中的最大流原理建立拓扑 - 功能 - 约束信息网络流量模型来关注最小化流量负荷削减，从而提高网络流量传输效率。最后，以具有间歇性风电的改进IEEE 39节点测试系统为例进行研究。随机攻击模拟表明，在最高链路故障率和风电渗透率下，模型2比模型1表现更优，负荷损失率降低了23.6%，节点存活率提高了5.3%。
