Intelligent Load Management is one most important function in a smart grid that allows customers to make informed decisions regarding their energy consumption. Therefore the energy providers may reduce the peak loads and smooth the load profile by motivating customer load shifting to low price periods. This project explores the optimal load scheduling in the presence of dynamic electricity pricing in a distribution network with locally available solar PV or wind-base renewable generation. The goal is to reduce electricity cost and encourage installation of distributed renewables with consideration of power quality constraints and customer convenience.
[5] S. H. Elyas, H. Alwan, H. Sadeghian, Z. Wang
"Optimized Household Demand Management with Local Distributed Solar Generation"
, 2017 North American Power Symposium (NAPS), Sep 17-19, 2017. Link to Publication
[4] F. Liu, Z. Wang,
"Electric Load Forecasting Using Parallel RBF Neural Network",
invited paper to the special session "Information Processing in the Smart Grid", 1st IEEE Global Conference on Signal and Information Processing, Austin, Texas, December 2013, p.531-534. Link to Publication
[3] Z. Wang, X. Li, V. Muthukumar A. Scaglione, S. Peisert, C. McParland
"Networked Loads in the Distribution Grid",
Invited Paper to the special session "Information processing for smart grid" 2012
APSIPA Conference, Hollywood, CA, Dec 2012. Link to Publication
[2] C. Chen, S. Kishore, Z. Wang, M. Alizadeh, A. Scaglione,
"A Cournot Game Analysis on Market Effects of Queuing Energy Request as Demand Response"
,2012 IEEE Power & Energy Society General Meeting, San Diego, CA, July 2012. Link to Publication
[1] M. Alizadeh, Z. Wang, A. Scaglione, C. Chen, S. Kishore,
"On the Market Effects of Queueing Energy Requests as an Alternative to Storing Electricity"
, 2012 IEEE Power & Energy Society General Meeting, San Diego, CA, July 2012. Link to Publication