loadpaper - 1 Load Pocket Forecasting Software E A Feinberg...

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1 Load Pocket Forecasting Software E. A. Feinberg, D. Genethliou, J.T. Hajagos, B.G. Irrgang, and R. J. Rossin Abstract --In this paper we describe the load pocket forecasting software that can be used by electric utilities to estimate and forecast the load growth in different service areas. The software builds statistical load models for various service areas (load pockets), estimates weather-normalized loads, estimates the ratios between the actual peak loads and the loads that would happened on designed days (weather normalized factors), and estimates the next year peak load. In particular, the software can be used to calculate the probability distributions of the next year peak loads for different load pockets. The software can be used for area planning purposes. The software contains user’s tools to design new load pockets and to modify the existing ones. Index Terms —Load forecasting, power system planning I. I NTRODUCTION T HIS paper introduces a load pocket forecasting software system developed at State University of New York at Stony Brook and by GMLI Corporation. The software analyzes and predicts peak loads in particular areas called load pockets. This software can be used to improve area planning for electric utilities. It provides the tools to analyze the dynamics of changes of electrical loads at different areas and to estimate the weather-normalized load trends. The utilities spend significant resources to maintain and upgrade their infrastructure and the described system improves decision- making capabilities relevant to capital expenditures. The appropriate investments in the company infrastructure lead to the increase of the system reliability and reduce the probability of blackouts. The software analyzes the historical weather and load data, estimates weather-normalized electric loads, computes design- day parameters, computes weather normalized factors, estimates trends, and calculates the probability distribution of the peak load for the next year. The software takes into account that weather conditions in different areas can vary from one area to another. In addition, the weather conditions change from one year to another in the same area. The software estimates the weather-normalized load trends and estimates the deviation from these trends for particular years due to specific weather conditions. The software can be used for one or several load pockets. It demonstrated a high level of accuracy of produced models. The software can be used for standard 50-50% planning scenarios traditionally used by utility companies or it can be used to make decisions to satisfy electric demand with higher probabilities. The developed software is designed for PCs. It was coded in SAS programming language and contains a convenient graphical user interface.
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