Abstract

Southern California Edison (SCE) is in the process of implementing Smart Grid applications as part of an ongoing grid modernization effort to improve reliability and asset utilization, integrate Distributed Energy Resources, and timely demand response to market and other signals. A Distribution System State Estimator (DSSE) uses telemetry and operational forecasting to ensure optimal execution of applications such as Volt-Var Optimization (VVO) and Fault Location, Isolation, Restoration (FLISR) while avoiding voltage and capacity violations.

 

Over the last years, EnerNex and SCE developed a methodology to support SCE’s deployment of a DSSE, which they published in an IEEE Journal paper1, various IEEE /  DistribuTECH conferences, and webinars. The developed methodology informs sensor deployment decisions that avoid costly investments in “too much” telemetry and violations that can be consequences of “not enough” telemetry. It was applied to 9 real-world distribution circuits. A key take-away from this study was that a circuit-by-circuit analysis is required to inform sensor deployments, which was infeasible to do at the time for all distribution circuits in SCE’s service territory due to the time-consuming analysis process.

 

Since then, EnerNex and SCE made significant strides in automating and refining the analysis so that it can be applied to a large number of circuits. The current work focuses on the development of a tool to guide the wide-scale deployment of sensors and operational forecasting on utility circuits, and illuminate the following questions related to the development and application of this tool:

  • What is the availability and quality of circuit models needed for the evaluation?
  • What are the challenges related to bad data, and how can the data be cleansed?
  • Are there any patterns regarding sensor schemes’ effectiveness that emerge from applying the developed DSSE performance methodology on a large number of circuits?

 

1 J. Schoene, M. Humayun, B. Russell, G. Sun, J. Bui, A. Salazar, N. Badayos, M. Zhong, M. Lak and C. Clarke, “Quantifying Performance of Distribution System State Estimators in Supporting Advanced Applications,” IEEE Power and Energy Technology Systems Journal, 2020.

 

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