1. Online Estimation of Steady-State Load Models Considering Data Anomalies.
- Author
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Tushar, Pandey, Shikhar, Srivastava, Anurag K., Markham, Penn, and Patel, Mahendra
- Subjects
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ANOMALY detection (Computer security) , *SMART power grids , *RECURSIVE filters , *LEAST squares , *PARAMETER estimation - Abstract
Several techniques have been developed to estimate the load parameters in power systems. Most of the existing algorithms mainly focus on estimating the parameters for offline studies. With on-going smart grid development, high-resolution data at faster rates are available to allow estimation of load parameters in real time. This paper addresses the challenges in online estimation of the load parameters using phasor measurement unit data. A novel adaptive search-based algorithm to estimate load model parameters is presented here. In this paper, a static load model is used with the Z (constant impedance), I (constant current), and P (constant power) components of the load. Developed estimation algorithms for the ZIP parameter estimation are validated using the IEEE 14-bus system and data provided by the industry collaborators. Simulation results demonstrate the accurate estimation of the ZIP load model using the developed method. Also, various techniques to eliminate anomalies in the input data for accurate estimation of the load parameters have been presented in this paper. [ABSTRACT FROM AUTHOR]
- Published
- 2018
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