A Research of Real-Time Pricing Mechanism and Its Characteristics

DOI: 10.4236/jpee.2015.34033   PDF   HTML     4,834 Downloads   5,414 Views   Citations

Abstract

Real-Time Pricing (RTP) is proposed as an effective Demand-Side Management (DSM) to adjust the load curve in order to achieve the peak load shifting. At the same time, the RTP mechanism can also raise the revenue of the supply-side and reduce the electricity expenses of consumers to achieve a win-win situation. In this paper, a real-time pricing algorithm based on price elasticity theory is proposed to analyze the energy consumption and the response of the consumers in smart grid structure. We consider a smart grid equipped with smart meters and two-way communication system. By using real data to simulate the proposed model, some characteristics of RTP are summarized as follows: 1) Under the condition of the real data, the adjustment of load curve and reducing the expenses of consumers is obviously. But the profit of power supplier is difficult to ensure. If we balance the profits of both sides, the supplier and consumers, the profits of both sides and the adjustment of load curve will be relatively limited. 2) If assuming the response degree of consumers to real-time prices is high enough, the RTP mechanism can achieve the expected effect. 3, If the cost of supply-side (day-ahead price) fluctuates dramatically, the profits of both sides can be ensured to achieve the expected effect.

Share and Cite:

Dong, Y. and Zou, B. (2015) A Research of Real-Time Pricing Mechanism and Its Characteristics. Journal of Power and Energy Engineering, 3, 240-249. doi: 10.4236/jpee.2015.34033.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Doostizadeh, M. and Ghasemi, H. (2012) A Day-Ahead Electricity Pricing Model Based on Smart Metering and Demand-Side Management. Energy, 46, 221-230. http://dx.doi.org/10.1016/j.energy.2012.08.029
[2] Ameren Services (2012) Real-Time Pricing for Residential Customers. http://www.ameren.com/sites/aiu/ElectricChoice/Pages/ResRealTimePricing.aspx
[3] Edison Electric Institute (2012) Retail Electricity Pricing and Rate Design in Evolving Markets. http://www.eei.org/ourissues/electricitydistribution/Documents/Retail-Electricity-Pricing.pdf; Ontario Energy Board (OEB), Ontario, Canada. http://www.ontarioenergyboard.ca/OEB/Consumers/Electricity/ElectricitytPrices
[4] Samadi, P., Mohsenian-Rad, A., Schober, R., Wong, V. and Jatskevich, J. (2010) Optimal Real-Time Pricing Algorithm Based on Utility Maximization for Smart Grid. First IEEE International Conference on Smart Grid Communications (Smart GridComm).
[5] Alexander, B. (2007) Smart Meters, Real Time Pricing, and Demand Response Programs: Implications for Low Income Electric Customers. Oak Ridge Natl. Lab., Tech. Rep. http://www.smartgridinformation.info/pdf/2438-doc-1.pdf
[6] Zhong, F. (2012) A Distributed Demand Response Algorithm and Its Application to PHEV Charging in Smart Grids. IEEE Transactions on Smart Grid, 3.
[7] Tushar, W., Saad, W., Poor, H.V. and Smith, D.B. (2012) Economics of Electric Vehicle Charging: A Game Theoretic Approach. IEEE Transactions on Smart Grid, 3.
[8] Li, P.Q., Ying, J., Zhang, A., Huang, J.W. and Wu, Y. (2013) Demand Response Management via Real-Time Electricity Price Control in Smart Grids. IEEE Journal on Selected Areas in Communications, 31.
[9] Weckx, S. and Driesen, J. Optimal Real-Time Pricing for Unbalanced Distribution Grids with Network Constraints.
[10] Zhong, H.W., Xie, L. and Xia, Q. (2013) Coupon Incentive-Based Demand Response: Theory and Case Study. IEEE Transactions on Power Systems, 28. http://dx.doi.org/10.1109/TPWRS.2012.2218665
[11] Qian, K.J., Zhou, C.K., Allan, M. and Yuan, Y. (2011) Modeling of Load Demand Due to EV Battery Charging in Distribution System. IEEE Transactions on power system, 26. http://dx.doi.org/10.1109/TPWRS.2010.2057456
[12] Baran, M.E. and Wu, F.F. (1989) Network Recon?guration in Distribution Systems for Loss Reduction and Load Balancing. IEEE Transactions on Power Delivery, 4.
[13] Deal, K. (2012) Assessing Whether Firm Day-Ahead Prices Lead to Changes in Elasticity of Demand and Greater Customer Ef?ciencies. http://www.ieso.ca/imoweb/pubs/mear/Deal-Mountain-Report-April2008.pdf
[14] US Department of Energy (2006) Bene?ts of Demand Response in Electricity Markets and Recommendations for Achieving Them. Report to the United States Congress. http://eetd.lbl.gov/EA/EMS/reports/congress-1252d.pdf
[15] Independent Electricity System Operator (IESO), Ontario, Canada. http://www.ieso.ca/; GAMS. Development Corporation, General algebraic modeling system (GAMS). http://www.gams.com; CONOPT Solver. http://www.gams.com/dd/docs/solvers/conopt.pdf
[16] Ontario Energy Board (OEB). Regulated Price Plan Manual. http://www.ontarioenergyboard.ca/OEB/Documents/EB-2004-0205/RPP-Manual.pdf

  
comments powered by Disqus

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.