Can we prevent the gaming of ramp constraints?

doi:10.1016/j.dss.2004.05.008

Decision Support Systems

Volume 40, Issues 3–4, October 2005, Pages 461-471

https://doi.org/10.1016/j.dss.2004.05.008 Get rights and content

Abstract

Some electric power markets allow bidders to specify constraints on ramp rates for increasing or decreasing power production. We show in a small example that a bidder could use an overly restrictive constraint to increase profits, and explore the cause by visualizing the feasible region from the linear program corresponding to the power auction. We propose three penalty approaches to discourage bidders from such a tactic: two based on the duality theory of linear programming (LP) and the other based on social cost differences caused by ramp constraints. We evaluate the approaches using a simplified scaled model of the California power system, with actual 2001 California demand data.

Section snippets

Visualization

We wish to visualize the feasible region and optimal solution for our small example, to learn how generator B can profit by specifying a ramp constraint. Our small example has six variables (one for each generator in each period) and two equality constraints (one for demand in each period). Using the equality constraints, we can eliminate two variables. Furthermore, generator A is always assigned 1 GW during peak regardless of us including or excluding generator B's ramp constraint, so we can

Penalty system

If we are to allow bidders to specify ramp constraints, we should ensure that our final dispatch satisfies all of the constraints, since we do not know which are true and which are misleading. That is, in trying to make our auction more incentive-compatible, we have little leeway in the dispatch. We do have some room to adjust the payments, though. One option, explored in Ref. [3], is the Vickrey-Clarke-Groves (VCG) auction. A VCG auction effectively pays companies to bid truthfully. It pays

California 2001 CalECo Simulation

We tested our suggested penalty approaches using generator data from the CalECo system of Refs. [4], [5], which represents a scaled abstraction of the California power system developed for the purpose of evaluating production simulation models. It includes several generators from each fundamental type (nuclear, coal, gas, etc.), and four price-quantity energy blocks for each generator. Further details of the CalECo system are provided in the cited references and will be omitted here.

The demand

Variations on Spain's system

Spain's electricity market rules favor a heuristic solution procedure, rather than a process based on mathematical programming. The market rules for Spain's system include the following restriction [1] (p. 28):

In any case, when the owner of a production unit which includes the rising/start-up or descending/stop load gradient condition in an electric power sale offer, the market operator shall assign the producer a lower quantity of power than the latter would have received if it had not

Conclusions

The PP1 penalties have the advantage of being easily computed from a single run of the auction LP, along with having the usual economic interpretations of dual variables. However, we have seen that PP1 is not particularly effective in recovering social cost losses from generators due to strategic specification of ramp constraints. The cost-based (PP2) penalties require many optimizations to be run, but they perform better on social cost recovery. Neither PP1 nor PP2 performs very well at

Acknowledgements

This work was supported by the Power Systems Engineering Research Center (PSerc) and by the Electric Power Research Institute.

References (5)

Compañía Operadora del Mercado Español de Electricidad, S.A. Electricity market activity rules, April 2001. Available:...
J. Contreras et al.
Auction design in day-ahead electricity markets (republished)
IEEE Transactions on Power Systems
(2001 (Aug.))

There are more references available in the full text version of this article.

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Shmuel S. Oren is Professor of Industrial Engineering and Operations Research at the University of California at Berkeley and a former chairman of that department. He is the Berkeley Site Director of PSerc, a multi-university PowerSystems Engineering Research Center sponsored by the National Science Foundation and industry members. His academic research and consulting focus on planning scheduling and economic analysis of power systems, and in particular on issues concerning market design for competitive electricity. He published numerous papers in this area and has been a consultant on electricity restructuring issues to numerous public and private organizations in the US and abroad. Dr. Oren holds a PhD and MS in Engineering Economic Systems from Stanford and a BSc and MSc in Mechanical Engineering from the Technion, Israel. He is a Fellow of the IEEE.

Andrew M. Ross received the BS degree from Harvey Mudd College, CA, USA in 1996 in Mathematics and the MS and PhD degrees from the University of California, Berkeley, CA, USA in 1997 in Operations Research. He is currently an Assistant Professor at Lehigh University. His research focuses on non-homogeneous queueing systems that are common in the telecommunications industry.

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