Information Geometry for Model Reduction in Power Systems
Youn, Clifford.
2018
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Abstract: Load
modeling has been extensively studied to understand the behavior of power systems. The
essential problem of load modeling is that it is very hard to precisely describe a large
collection of heterogeneous physical devices. These devices not only have different
characteristics but also change depending on the various conditions such as weather,
time, economic conditions, etc. To ... read moreanalyze the behavior, a large number of devices are
first grouped into similar loads. Then, these loads are replaced with equivalent
circuits and logics for calculation. Many parameters are typically needed to describe
the load characteristics. One aspect of model simplification has to do with the number
of parameters, as more parameters definitely have the potential to offer better
accuracy. However, more parameters will also make the system and computation more
complicated. This dissertation introduces a new approach to simplify complex load models
and estimate the parameters. One of emerging trends in power systems involves the use of
information technology. This dissertation focuses on a method based on information
geometry which combines information theory with computational differential geometry to
derive global estimation results. The approach sheds a new light on difficulties
commonly encountered when fitting widely used models to the measurement data.
Simulations are performed based on a conventional composite load model and the new WECC
Composite Load Model. The results are then compared with the full original model and the
reduced parameter model to verify the effectiveness of reduction via information
geometry.
Thesis (Ph.D.)--Tufts University, 2018.
Submitted to the Dept. of Electrical Engineering.
Advisor: Aleksandar Stanković.
Committee: Christoph Börgers, Usman Khan, and Mark Transtrum.
Keyword: Electrical engineering.read less - ID:
- q237j444s
- Component ID:
- tufts:25095
- To Cite:
- TARC Citation Guide EndNote
