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 shortterm 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. Usually, weather dependent component of load is identified by fitting appropriate non-linear curve to the scatter plot of weather-load model. This technique some times shows lower correlation with weather variables. This paper proposes a new methodology to identify the weather sensitive component of electrical load using empirical mode decomposition (EMD) technique. The proposed methodology is applied to the daily peak load of Dhaka zone of Bangladesh Power System (BPS) of the year 2012. A detailed numerical process to evaluate the weather sensitive portion of the load is also presented. The proposed methodology is validated through statistical error evaluation process. Finally the salient features of the results are discussed.

This paper presents the correlation between the reliability and the weather scenario of Bangladesh Power System (BPS). Reliability of the power system is one of the major features of power quality. The variation of electrical demand above its base value is its common characteristic. The weather dependent variation of demand, especially where the weather is severe in nature, requires a significant reserve margin to ensure an acceptable level of reliability of the generation system. In Bangladesh, a significant difference in demands of winter and summer is generated due to weather variation. As a result the utility has to ensure an additional seasonal generation reserve capacity to maintain an acceptable level of reliability. This paper determines the correlation between the weather variables, namely temperature and relative humidity, and the reliability of Bangladesh Electricity Network. It also investigates the additional generation requirement during summer season to maintain an acceptable reliability level.