Title :
Estimating substation peaks from load research data
Author :
Broadwater, Robert P. ; Sargent, Al ; Yarali, Abdulrahman ; Shaalan, Hesham E. ; Nazarko, Joanicjusz
Author_Institution :
Dept. of Electr. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA
fDate :
1/1/1997 12:00:00 AM
Abstract :
Load research data is used to develop kWh-to-peak-kW conversion factors, diversity factors, and average time-varying load data as a function of customer class, month, and type of day. A new method, nonlinear load research based estimation (NLRE), is used to derive monthly load shapes by customer class for estimating the peak MW load on substations as a function of total MWh usage by customer class, type of day, and month. Four substations at Hot Springs, Arkansas are used for estimation of monthly peak and the results are compared with measured values from a SCADA system. The results show improved accuracy of the NLRE estimated substation peaks in comparison with the previous method
Keywords :
load forecasting; substations; Arkansas; Hot Springs; SCADA system; average time-varying load data; customer class; diversity factors; kWh-to-peak-kW conversion factors; load research data; monthly load shapes; nonlinear load research based estimation; peak MW load; substation peaks estimation; total MWh usage; Adders; Capacitors; Conductors; Integrated circuit interconnections; Power & Energy Society; SCADA systems; Samarium; Shape; Springs; Substations;
Journal_Title :
Power Delivery, IEEE Transactions on
