energy_2011_4_40_50165 - ENERGY 2011 The First...

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Smard Grid Software Applications for Distribution Network Load Forecasting Eugene A. Feinberg, Jun Fei Stony Brook University Stony Brook, NY 11794, USA [email protected] [email protected] Janos T. Hajagos, Richard J. Rossin Long Island Power Authority Hicksville, NY 11801, USA [email protected] [email protected] Abstract — This paper describes three software applications for distribution network load forecasting in a Smart Grid environment: (i) short-term feeder load forecasting, (ii) short- term substation transformer load forecasting and transformer rating, and (iii) next-year load pocket forecasting. The short- term feeder load forecasting allows a utility to reduce the possibility of feeder overloading. The substation transformer load forecasting and transformer rating application achieves similar goals at the distribution substation level. The load pocket forecasting software allows a utility to estimate load trends at different locations (called load pockets), to estimate next-year peaks, to calculate weather normalized factors, and to estimate the probability distribution of the next-year peak load. The use of these software applications significantly improved the efficiency and reliability of the distribution network. Keywords: load forecasting, feeder, transformer, load pocket, SmartGrid I. INTRODUCTION One of the important aspects of emerging Smart Grid technologies is measuring, transmitting, storing and processing electric power system data, such as voltage, current, phase angle, etc., and using this information for system control and management. In particular, operators of traditional distribution networks often do not have complete information about certain parts of the network such as three- phase measurements at substations and feeders, measurements along feeders, and so on. In many cases, certain SCADA data are monitored, but not stored. This paper describes particular applications that demonstrate how measuring, storing and processing substation and feeder load measurements can help improve the distribution network efficiency and reliability. The monitored data have been used to develop transformer and feeder load models and apply these models to load forecasting in the distribution network. In particular, this paper describes three applications: (i) short term (from one hour up to seven days) feeder load forecasting, (ii) short-term substation transformer load forecasting and transformer rating, and (iii) next-year load pocket forecasting and Weather Normalization Factor (WNF) computations. The goal of the first application, the short-term feeder load forecasting, is to provide the system operators with advanced warnings on potential normal feeder overloading. Once such overloading signal is received, the operators can take several measures to avoid the undesired event. These measures include load switching, feeder reconfiguration, load reductions, and voltage control. In future Smart Grid applications, load reductions can be implemented by time- differentiated pricing.
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This note was uploaded on 12/06/2011 for the course MATH 101 taught by Professor Eugenea.feinberg during the Fall '11 term at State University of New York.

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energy_2011_4_40_50165 - ENERGY 2011 The First...

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