Using load switches to control aggregated electricity demand for load following and regulation

IEEE Power and Energy Society General Meeting

Volumn , Issue , 2011, Pages

  Keep, Taylor M ^a   Sifuentes, Froylan E ^a   Auslander, David M ^b   Callaway, Duncan S ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGGREGATE LOAD; AGGREGATED MODELING; BASIC PRINCIPLES; ELECTRICITY DEMANDS; END-USES; FORECAST ERRORS; LOAD FOLLOWING; LOCAL CONTROL; RENEWABLE GENERATION; SECOND ORDERS; SWITCH CONTROL; TEMPERATURE DEVIATION;

ELECTRIC SWITCHES; ELECTRIC UTILITIES;

ELECTRIC LOAD FORECASTING;

EID: 82855171103     PISSN: 19449925     EISSN: 19449933     Source Type: Conference Proceeding    
DOI: 10.1109/PES.2011.6039039     Document Type: Conference Paper

References (18)

1. Y.V. Makarov, C. Loutan, Jian Ma, and P. de Mello. Operational impacts of wind generation on California power systems. IEEE Transactions on Power Systems, 24(2):1039-1050, May 2009.
2. C. Loutan and D. Hawkins. Integration of Renewable Resources: Transmission and Operating Issues and Recommendations for Integrating Renewable Resources on the California ISO-Controlled Grid. California ISO, 2007.
3. B. Ramanathan and V. Vittal. A framework for evaluation of advanced direct load control with minimum disruption. IEEE Transactions on Power Systems, 23(4):1681-1688, November 2008.
4. D.S. Callaway. Tapping the energy storage potential in electric loads to deliver load following and regulation, with application to wind energy. Energy Conversion and Management, 50(9):1389-1400, May 2009.
5. S Koch, F. Soto Barcenas, and G. Andersson. Using controllable thermal household appliances for wind forecast error reduction. In IFAC Conference on Control Methodologies and Technology for Energy Efficiency, Vilamoura, Portugal, 2010.
6. L. Hughes. Meeting residential space heating demand with wind-generated electricity. Renewable Energy, 35(8):1765-1772, 2010.
7. J.H. Eto, J. Nelson-Hoffman, C. Torres, S. Hirth, B. Yinger, J. Kueck, B. Kirby, C. Bernier, R. Wright, A. Barat, and D.S. Watson. Demand response spinning reserve demonstration. Technical Report LBNL-62761, Lawrence Berkeley National Laboratory, May 2007.
8. L. Ljung. System identification: theory for the user. 1999.
9. K.J. Aström. Introduction to stochastic control theory. Academic Press, 1970.
10. PM Weaver, MF Ashby, S. Burgess, and N. Shibaike. Selection of materials to reduce environmental impact: a case study on refrigerator insulation. Materials & Design, 17(1):11-17, 1996. (Pubitemid 126660908)
11. C.J.L. Hermes and C. Melo. Assessment of the energy performance of household refrigerators via dynamic simulation. Applied Thermal Engineering, 29(5-6):1153-1165, 2009.
12. DW Gerlach and TA Newell. Dual Evaporator Household Refrigerator Performance Testing and Simulation. Air Conditioning and Refrigeration Center CR-40, 2001.
13. A. Meier. Refrigerator energy use in the laboratory and in the field. Energy and buildings, 22(3):233-243, 1995.
14. WH Coulter and CW Bullard. An experimental analysis of cycling losses in domestic refrigerator-freezers. Air Conditioning and Refrigeration Center TR-77, 1995.
15. D.S. Parker and T.C. Stedman. Measured Electricity Savings of Refrigerator Replacement: Case Study and Analysis. In Proceedings, page 199. American Council for an Energy-Efficient Economy, 1992.
16. S.J. James and J. Evans. The temperature performance of domestic refrigerators. International Journal of Refrigeration, 15(5):313-319, 1992.
17. J. Cavallo, J. Mapp, et al. Monitoring refrigeration energy useage. Home Energy Mag., 17(ANL/ES/JA-34563), 2000.
18. R.E. Brown and J.G. Koomey. Electricity use in California: past trends and present usage patterns. Energy Policy, 31(9):849-864, 2003. (Pubitemid 36339742)