DYNAMIC PRICING DESIGN FOR DEMAND RESPONSE INTEGRATION IN POWER DISTRIBUTION NETWORKS
Author’s Name : D Sabapathi | P Venkatachalam
Volume 02 Issue 03 Year 2015 ISSN No: 2349-2503 Page no: 11-16
This paper presents optimal pricing design for demand response (DR) integration in the distribution network. In particular, we study the energy scheduling problem for a load serving entity (LSE) that serves two types of loads, namely in- exible and exible loads. Inexible loads are charged under a regular pricing tariff while exible loads enjoy a dynamic pricing tariff that ensures cost saving for them. Moreover, exible load are assumed to be aggregated by several DR aggregators. The nteraction between the LSE and its customers is formulated as a bi level optimization problem where the LSE is the leader and DR aggregators are the followers. The optimal solution of this problem corresponds to the optimal pricing tariff for exible loads. The key advantage of the proposed model is that it can be readily implemented thanks to its compatibility with existing pricing structures in the retail market. Extensive numerical results show that the proposed approach provides a win-win solute the LSE and its customers.
Bilevel programming, complementarity modeling, demand response, dynamic pricing, load serving entity
- F. Rahimi and A. Ipakchi, “Demand response as a market resource under the smart grid paradigm,” IEEE Trans. Smart Grid, vol. 1, no. 1, pp. 82–88, Jun. 2010.
- D. T. Nguyen and L. B. Le, “Optimal bidding strategy for microgrids considering renewable energy and building thermal dynamics,” IEEE Trans. Smart Grid, vol. 5, no. 4, pp. 1608–1620, Jul. 2014.
- D. T. Nguyen and L. B. Le, “Risk-constrained prot maximization for microgrid aggregators with demand response,” IEEE Trans. Smart Grid, vol. 6, no. 1, pp. 135–146, Jan. 2015.
- M. Parvania and M. Fotuhi-Firuzabad, “Demand response scheduling by stochastic SCUC,” IEEE Trans. Smart Grid, vol. 1, no. 1, pp. 89–98, Jun. 2010.
- M. Parvania, M. Fotuhi-Firuzabad, and M. Shahidehpour, “Optimal demand response aggregation in wholesale electricity markets,” IEEE Trans. Smart Grid, vol. 4, no. 4, pp. 1957–1965, Dec. 2013.
- Z. Zhao, L. Wu, and G. Song, “Convergence of volatile power markets with price-based demand response,” IEEE Trans. Power Syst., vol. 29, no. 5, pp. 2107–2118, Sep. 2014.
- S. A. Pourmousavi and M. H. Nehrir, “Real-time central demand re- sponse for primary frequency regulation in microgrids,” IEEE Trans. Smart Grid, vol. 3, no. 4, pp. 1988–1996, Dec. 2012.
- A. J. Conejo, J. M. Morales, and L. Baringo, “Real-time demand re- sponse model,” IEEE Trans. Smart Grid, vol. 1, no. 3, pp. 236–242, Dec. 2010.
- M. Rahimiyan, L. Baringo, and A. J. Conejo, “Energy management of a cluster of interconnected price-responsive demands,” IEEE Trans. Power Syst., vol. 29, no. 2, pp. 645–655, Mar. 2014.
- S. J. Kazempour, A. J. Conejo, and C. Ruiz, “Strategic bidding for a large consumer,” IEEE Trans. Power Syst., vol. 30, no. 2, pp. 848–856, Mar. 2015.