Near-Optimal Scheduling in Day-Ahead Markets: Pricing Models and Payment Redistribution Bounds

Near-optimal unit commitment (UC) scheduling is a practical reality in wholesale electricity markets. This paper revisits previous work that has found that minor differences in cost among near-optimal schedules can result in a large redistribution of market payments (i.e., changes in generator profits and consumer surplus). It has been believed that this instability is unavoidable, but previous studies have only calculated prices using what we call the Restricted pricing model. This paper compares previous results to three additional models that are based on integer relaxation, and which we call the Partial, Tight, and Loose Dispatchable pricing models. Results are presented for a suite of test cases, including four ISO-scale cases. Similar to previous findings, the Restricted and Partial Dispatchable models both result in large payment redistributions among alternative solutions. In contrast, theoretical and experimental results for the Tight and Loose Dispatchable models show that pricing models with unconditional integer relaxation will have bounded payment redistributions, and, further, this bound can become quite small by tightening the UC problem's convex relaxation. In the presence of market power, stable financial outcomes may improve market efficiency by reducing incentives to bid strategically.

[1]  Walter W Garvin,et al.  Introduction to Linear Programming , 2018, Linear Programming and Resource Allocation Modeling.

[2]  Herbert E. Scarf,et al.  The Allocation of Resources in the Presence of Indivisibilities , 1994 .

[3]  B. J. Ring,et al.  Using mathematical programming for electricity spot pricing , 1996 .

[4]  S. Oren,et al.  Equity and efficiency of unit commitment in competitive electricity markets , 1997 .

[5]  Mohammad Shahidehpour,et al.  The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee , 1999 .

[6]  Samer Takriti,et al.  Incorporating Fuel Constraints and Electricity Spot Prices into the Stochastic Unit Commitment Problem , 2000, Oper. Res..

[7]  Claude Lemaréchal,et al.  A geometric study of duality gaps, with applications , 2001, Math. Program..

[8]  F. Galiana,et al.  Equilibrium of Auction Markets with Unit Commitment: The Need for Augmented Pricing , 2002, IEEE Power Engineering Review.

[9]  Benjamin F. Hobbs,et al.  Efficient market-clearing prices in markets with nonconvexities , 2005, Eur. J. Oper. Res..

[10]  William W. Hogan,et al.  Market-Clearing Electricity Prices and Energy Uplift , 2008 .

[11]  R. Sioshansi,et al.  Economic Consequences of Alternative Solution Methods for Centralized Unit Commitment in Day-Ahead Electricity Markets , 2008, IEEE Transactions on Power Systems.

[12]  O. Alsaç,et al.  DC Power Flow Revisited , 2009, IEEE Transactions on Power Systems.

[13]  M. V. Vyve,et al.  Linear prices for non-convex electricity markets: models and algorithms , 2011 .

[14]  S. Gabriel,et al.  Pricing Non-Convexities in an Electricity Pool , 2012, IEEE Transactions on Power Systems.

[15]  Mar Reguant,et al.  Complementary Bidding Mechanisms and Startup Costs in Electricity Markets , 2014, SSRN Electronic Journal.

[16]  Lisa Tang,et al.  Collection of Power Flow models: Mathematical formulations , 2015 .

[17]  Kory W. Hedman,et al.  The Role of Out-of-Market Corrections in Day-Ahead Scheduling , 2015, IEEE Transactions on Power Systems.

[18]  Carlos Batlle,et al.  Electricity market-clearing prices and investment incentives: The role of pricing rules , 2015 .

[19]  George Liberopoulos,et al.  Critical Review of Pricing Schemes in Markets with Non-Convex Costs , 2016, Oper. Res..

[20]  Alper Atamtürk,et al.  A polyhedral study of production ramping , 2016, Math. Program..

[21]  Tongxin Zheng,et al.  Convex Hull Pricing in Electricity Markets: Formulation, Analysis, and Implementation Challenges , 2016, IEEE Transactions on Power Systems.

[22]  Robin Broder Hytowitz,et al.  Dual Pricing Algorithm in ISO Markets , 2017, IEEE Transactions on Power Systems.

[23]  Ross Baldick,et al.  A Convex Primal Formulation for Convex Hull Pricing , 2016, IEEE Transactions on Power Systems.

[24]  Claudio Gentile,et al.  A tight MIP formulation of the unit commitment problem with start-up and shut-down constraints , 2017, EURO J. Comput. Optim..

[25]  Daniel Huppmann,et al.  An Exact Solution Method for Binary Equilibrium Problems with Compensation and the Power Market Uplift Problem , 2015, Eur. J. Oper. Res..

[26]  R. O'Neill,et al.  Investment Effects of Pricing Schemes for Non-Convex Markets , 2018 .

[27]  Jianhui Wang,et al.  The Ramping Polytope and Cut Generation for the Unit Commitment Problem , 2018, INFORMS J. Comput..

[28]  B. Hobbs,et al.  Pricing in Day-Ahead Electricity Markets with Near-Optimal Unit Commitment , 2018 .