Title :
Assessment of air condition load management by load survey in Taipower
Author_Institution :
Dept. of Electr. Eng., Nat. Kaohsiung Univ. of Appl. Sci., Taiwan
fDate :
11/1/2001 12:00:00 AM
Abstract :
This paper investigates the potential of air conditioning load management by solving the temperature sensitivity of load demand for various customer classes. The load survey system has been applied to record the power consumption of sampling customers in Taiwan Power Company (Taipower) for 4 years. The effect of the temperature change to the customer power consumption is determined by executing the statistical polynomial regression on the load survey results. The increase of system power demand for each 1°C temperature rise is then derived by integrating the load change of all customer classes. To verify the accuracy of the simulation, the actual system power demand collected by Taipower EMS system is applied to find the system load response to the temperature change. It is found that the proposed methodology does provide an effective tool for the utility company to identify the customer classes with good potential for air conditioner load management. Based on this study, the load management programs of cooling energy storage system and direct cycling control of air conditioners (A/C) are promoted by Taipower for the commercial and residential customers respectively
Keywords :
air conditioning; cooling; energy management systems; load management; polynomials; power consumption; sensitivity analysis; statistical analysis; thermal energy storage; 4 y; EMS system; Taipower; Taiwan Power Company; air condition load management assessment; air conditioners; commercial customers; cooling energy storage system; customer classes; customer power consumption; direct cycling control; load change integration; load demand; load survey; power consumption; residential customers; statistical polynomial regression; system load response; temperature change; temperature sensitivity; Air conditioning; Cooling; Energy consumption; Load management; Medical services; Polynomials; Power demand; Sampling methods; Temperature distribution; Temperature sensors;
Journal_Title :
Power Systems, IEEE Transactions on