DocumentCode :
1786552
Title :
Optimal day-ahead pricing with renewable energy for smart grid
Author :
Te-Chuan Chiu ; Che-Wei Pai ; Yuan-Yao Shih ; Ai-Chun Pang
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ., Taipei, Taiwan
fYear :
2014
fDate :
10-14 June 2014
Firstpage :
472
Lastpage :
476
Abstract :
Thanks to the recent advance on power engineering and wireless communications, the smart grid technology has emerged and users are now capable of deploying renewable energy generators and storage devices at their homes. On the other side, due to the rise of environmental consciousness, electric companies are eager to replace traditional generators with renewable energy. One of the most efficient ways is to provide an electricity buyback scheme for electric companies to encourage users to generate more renewable energy at their homes. Different from the previous works, we consider dynamic pricing with renewable energy buyback as our target scenario. We formulate the dynamic pricing problem as a convex optimization problem and propose a day-ahead time-dependent pricing scheme. The goal of our developed framework is to achieve the maximum benefits for both users and electric companies. To the best of our knowledge, this is one of the very first works to tackle the time-dependent problem with taking the environmental benefit of renewable energy into consideration for smart grid. The numerical results show that our framework can significantly reduce the peak time loading and efficiently balance the system energy provision.
Keywords :
convex programming; power system economics; pricing; renewable energy sources; smart power grids; convex optimization problem; day-ahead time-dependent pricing scheme; dynamic pricing; dynamic pricing problem; optimal day-ahead pricing; peak time loading; renewable energy buyback; smart grid; system energy provision; Carbon dioxide; Companies; Electricity; Energy storage; Pricing; Renewable energy sources; Smart grids; Smart grid; carbon emission trading; convex optimization; day-ahead pricing; renewable energy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications Workshops (ICC), 2014 IEEE International Conference on
Conference_Location :
Sydney, NSW
Type :
conf
DOI :
10.1109/ICCW.2014.6881243
Filename :
6881243
Link To Document :
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