Probabilistic Loss Sensitivity Analysis in Power Distribution Systems

被引:2
|
作者
Abujubbeh, Mohammad [1 ]
Munikoti, Sai [1 ]
Pahwa, Anil [1 ]
Natarajan, Balasubramaniam [1 ]
机构
[1] Kansas State Univ, Elect & Comp Engn Dept, Manhattan, KS 66506 USA
基金
美国国家科学基金会;
关键词
Sensitivity; Monitoring; Resource management; Probabilistic logic; Real-time systems; Generators; Computational complexity; Active consumer; distribution system; sensitivity analysis; power loss; distributed energy resources; JENSEN-SHANNON DIVERGENCE; DISTRIBUTION NETWORKS; OPTIMAL INTEGRATION; OPTIMAL PLACEMENT; GENERATION; FLOW; PENETRATION; DG;
D O I
10.1109/TPWRS.2022.3186349
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Power distribution systems are changing due to renewable energy integration, electric vehicle penetration and active consumers engaging in the energy market. Therefore, utilities need to quantify the impact of such changes on the system. Power loss is one of the tools to quantify system performance. A huge share of losses occurs on the distribution side due to lower voltages compared to transmission systems. Existing methods that quantify the impact of consumer activities on losses are scenario-specific, computationally expensive and do not consider uncertainties associated with power changes. Therefore, the goal of this paper is to develop a simpler, yet accurate, probabilistic loss sensitivity framework for approximating the impact of random power changes on power losses. First, an analytical expression is derived to approximate the change in line losses for any given deterministic power changes. Then, the analytical expression is extended to a probabilistic framework that accommodates variability related to power changes. The proposed approach is validated via simulation against the traditional load flow-based sensitivity method using the IEEE 69 node test system. Results demonstrate that the proposed approach is accurate and computationally efficient. The proposed framework is useful for real-time loss monitoring and optimal asset management.
引用
收藏
页码:2100 / 2110
页数:11
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