Demand Response from Residential Air Conditioning Load Using a Programmable Communication Thermostat
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32804
Demand Response from Residential Air Conditioning Load Using a Programmable Communication Thermostat

Authors: Saurabh Chanana, Monika Arora

Abstract:

Demand response is getting increased attention these days due to the increase in electricity demand and introduction of renewable resources in the existing power grid. Traditionally demand response programs involve large industrial consumers but with technological advancement, demand response is being implemented for small residential and commercial consumers also. In this paper, demand response program aims to reduce the peak demand as well as overall energy consumption of the residential customers. Air conditioners are the major reason of peak load in residential sector in summer, so a dynamic model of air conditioning load with thermostat action has been considered for applying demand response programs. A programmable communicating thermostat (PCT) is a device that uses real time pricing (RTP) signals to control the thermostat setting. A new model incorporating PCT in air conditioning load has been proposed in this paper. Results show that introduction of PCT in air conditioner is useful in reducing the electricity payments of customers as well as reducing the peak demand. 

Keywords: Demand response, Home energy management Programmable communicating thermostat, Thermostatically controlled appliances.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1335910

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2975

References:


[1] F. Rahimi, A. Ipakchi, "Overview of demand response under the smart grid and market paradigms", in Proc. Of Innovative Smart Grid Technologies (ISGT), Gaithersburg, MD, 2010.
[2] M. H. Albadi and E. F. El-Saadany, "A summary of demand response in electricity market,” Electric Power System Research, Vol. 78, No. 11, pp. 1989-96.
[3] N. Lu and S. Katipamula "Control strategies of thermostatically controlled appliances in a competitive electricity market", Proc. IEEE Power Eng. Soc. Gen. Meet., pp. 202--207, Jun. 2005.
[4] Ninghui Zhu, Xiaomin Bai, Junxia Meng, "Benefits Analysis of All Parties Participating in Demand Response,” Power and Energy Engineering Conference (APPEEC), 2011.
[5] Canbolat Ucak and Ramazan Caglar, "The effects of load parameter dispersion and direct load control action on aggregated load”, Proceedings of International Conference on Power System Technology, POWERCON’98, Beijing, vol 1., pp 280-284, 1998.
[6] Saurabh Chanana and Ashwani Kumar, "Demand response by dynamic demand control using frequency linked real time prices,” International Journal of Energy Sector Management, vol. 4. no. 1, 2010.
[7] A.-H. Mohsenian-Rad, A. Leon-Garcia, "Optimal Residential Load Control with Price Prediction in Real-Time Electricity Pricing Environments," IEEE Transactions on Smart Grid, vol. 1, no. 2, pp. 120-133, 2010.
[8] Pengwei Du and Ning Lu, "Appliance commitment for household load scheduling,” IEEE Transaction on Smart Grid, vol.2, no.2, June 2011.
[9] A. Saha, M. Kuzlu, M. Pipattanasomporn, "Demonstration of a Home Energy Management System with Smart Thermostat Control,” Innovative Smart Grid Technologies (ISGT), IEEE PES, pp. 1-8. 2013.
[10] R. E. Mortensen and K. P. Haggerty, "A stochastic computer model for heating and cooling loads” IEEE Transaction in Power Systems, vol. 3, no. 3, pp. 1213-1219, 1998.
[11] Indian Energy Exchange http://www.iexindia.com/Reports/ AreaPrice.aspx.