Distribution System State Estimation Using Hybrid Traditional and Advanced Measurements for Grid Modernization
نویسندگان
چکیده
Distribution System State Estimation (DSSE) techniques have been introduced to monitor and control Active Networks (ADNs). DSSE calculations are commonly performed using both conventional measurements pseudo-measurements. Conventional typically asynchronous low update rates, thus leading inaccurate results for dynamically changing ADNs. Because of this, smart measurement devices, which synchronous at high frame recently enhance the monitoring ADNs in modern power networks. However, replacing all traditional devices with is not feasible over a short time. Thus, an essential part grid modernization process use advanced improve results. In this paper, new method proposed hybridize online machine learning model. work, we assume that ADN has monitored Weighted Least Square (WLS) obtain results, voltage magnitude phase angle each bus considered as state vectors. After period time, network modified by installation such Phasor Measurement Units (PMUs), facilitate desired performance. Our work proposes taking advantage available First, machine-learning-based regression model was trained from obtained only before devices. were added network, predicted when those enable synchronization between sensors, despite their different refresh rates. We show had improved performance under condition it continued be updated regularly more data collected way, training became robust performance, even presence Distributed Generations (DGs). The compared incorporated into calculation sample-and-hold technique. present terms Mean Absolute Error (MAE) Root (RMSE) values approaches. effectiveness validated two case studies DGs: one IEEE 33-bus distribution system loads DGs based on Monte Carlo simulation other 69-bus actual DGs. illustrate better than method.
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2023
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app13126938