Abstract:
The expansion planning and operation of all three sectors, generation,
transmission and distribution, of power system essentially require load forecasting.
Weather conditions have significant impacts on forecasted load, especially short-term and
mid-term. A momentous portion of the electrical energy is consumed, especially in cold
or hot countries, to mitigate the impact of weather on the daily life of human society. The
objective of this thesis is to develop a methodology to identifY the component of
electrical demand generated due to the weather. Usually, weather dependent component
of load is identified by fitting appropriate non-linear curve to the scatter plot of we~iher- .
load model. This technique some times shows lower correlation with weather variables ....,-.
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So far, empirical mode decomposition (EMD) technique is used for nOIse
suppression of speech signal and biomedical signal processing in the field of Electrical
and Electronic Engineering. Electrical load has, to some extent, similarity with speech
and biomedical signal. So, like other non-stationary time series signal, electrical load can
be decomposed using EMD technique. In this thesis, a methodology has been developed
to identifY the weather sensitive component of electrical load using empirical mode
decomposition (EMD) technique.
In this thesis, EMD technique is used to decompose the load into several
components. The characteristic features of each. decomposed component of load are
compared with the weather pattern, especially the variation characteristics of temperature
and humidity. The characteristics of different combination of different components of
load are also compared with that of weather variables. The correlation between load
component or that of combination and weather component is evaluated. From the degree
of correlation the weather sensitive components of loads is identified. The proposed methodology is applied to the historical load of Bangladesh Power
System (BPS). The temperature and humidity data of Bangladesh for the corresponding
duration are considered in this process of load decomposition. The proposed
methodology is validated by comparing the results obtained through this technique with
those obtained using the conventional technique. The accuracy of results is also verified.
The developed methodology is applied to the peak loads and the hourly loads of
Bangladesh Power System to disintegrate them into weather sensitive portion and nonweather
sensitive portion and interesting observations are made.
