Dynamic pricing of power in Smart-Grid networks

In this paper we introduce the problem of dynamic pricing of power for smart-grid networks. We consider a network utility maximization (NUM) framework in a deterministic setting with a single provider, multiple users and a finite horizon. The provider produces power or buys power in a (deterministic) spot market, and determines a dynamic price to charge the users. The users then adjust their demand in response to the time-varying prices. This is typically categorized as the problem of demand response, and we study a progression of related models by focusing on the characterization of the structure of the optimal dynamic prices in the Smart Grid and the optimal demand and supply under various interaction with a spot market.

[1]  W. Marsden.  I and J , 2012 .

[2]  Rahul Jain,et al.  Stochastic resource auctions for renewable energy integration , 2011, 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[3]  A. Banerjee.  Convex Analysis and Optimization , 2006 .

[4]  P. Klemperer,et al.  Supply Function Equilibria in Oligopoly under Uncertainty , 1989 .

[5]  Munther A. Dahleh,et al.  On the stability of wholesale electricity markets under real-time pricing , 2010, 49th IEEE Conference on Decision and Control (CDC).

[6]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[7]  A. Robert Calderbank,et al.  Layering as Optimization Decomposition: A Mathematical Theory of Network Architectures , 2007, Proceedings of the IEEE.

[8]  Frank Kelly,et al.  Rate control for communication networks: shadow prices, proportional fairness and stability , 1998, J. Oper. Res. Soc..

[9]  Ahmad Faruqui,et al.  The Power of Dynamic Pricing , 2009 .

[10]  Daniel Pérez Palomar,et al.  A tutorial on decomposition methods for network utility maximization , 2006, IEEE Journal on Selected Areas in Communications.

[11]  Frank Kelly,et al.  Charging and rate control for elastic traffic , 1997, Eur. Trans. Telecommun..

[12]  P. Varaiya,et al.  Bringing Wind Energy to Market , 2012, IEEE Transactions on Power Systems.

[13]  Asuman E. Ozdaglar,et al.  A distributed Newton method for Network Utility Maximization , 2010, 49th IEEE Conference on Decision and Control (CDC).

[14]  S. Low,et al.  Zero Duality Gap in Optimal Power Flow Problem , 2012, IEEE Transactions on Power Systems.

[15]  Asuman E. Ozdaglar,et al.  A distributed newton method for network optimization , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[16]  K. Schittkowski,et al.  NONLINEAR PROGRAMMING , 2022 .

[17]  Na Li,et al.  Two Market Models for Demand Response in Power Networks , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[18]  Pravin Varaiya,et al.  Smart Operation of Smart Grid: Risk-Limiting Dispatch , 2011, Proceedings of the IEEE.

[19]  Ufuk Topcu,et al.  A simple optimal power flow model with energy storage , 2010, 49th IEEE Conference on Decision and Control (CDC).

[20]  Na Li,et al.  Optimal demand response based on utility maximization in power networks , 2011, 2011 IEEE Power and Energy Society General Meeting.