Model-centric Distribution Automation: Capacity, Reliability, and Efficiency. Issue 5 (15th March 2016)

• Record Type: Journal Article
• Authors: Onen, Ahmet; Jung, Jaesung; Dilek, Murat; Cheng, Danling; Broadwater, Robert P.; Scirbona, Charlie; Cocks, George; Hamilton, Stephanie; Wang, Xiaoyu
• Is Part Of: Electric power components and systems. Volume 44:Issue 5(2016)
• Page Start: 495
• Page End: 505
• Publication Date: 2016-03-15
• Subjects: distribution automation -- Monte Carlo simulation -- coordinated control -- power system reliability -- power system efficiency -- power system capacity; Electric machinery -- Periodicals; 621.3104205
• DOI: 10.1080/15325008.2015.1121416
• Languages: English
• ISSNs: 1532-5008

Abstract

Abstract: A series of analyses along with field validations that evaluate efficiency, reliability, and capacity improvements of model-centric distribution automation are presented. With model-centric distribution automation, the same model is used from design to real-time control calculations. A 14-feeder system with 7 substations is considered. The analyses involve hourly time-varying loads and annual load growth factors. Phase balancing and capacitor redesign modifications are used to better prepare the system for distribution automation, where the designs are performed considering time-varying loads. Coordinated control of load tap changing transformers, line regulators, and switched capacitor banks is considered. In evaluating distribution automation versus traditional system design and operation, quasi-steady-state power flow analysis is used. In evaluating distribution automation performance for substation transformer failures, reconfiguration for restoration analysis is performed. In evaluating distribution automation for storm conditions, Monte Carlo simulations coupled with reconfiguration for restoration calculations are used. The evaluations demonstrate that model-centric distribution automation has positive effects on system efficiency, capacity, and reliability.