This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON POWER SYSTEMS 1 Market Implications and Pricing of Dynamic Reserve Policies for Systems With Renewables Joshua D. Lyon, Student Member, IEEE, Fengyu Wang, Student Member, IEEE, Kory W. Hedman, Member, IEEE, and Muhong Zhang Abstract—Static reserve policies are used within security-con- strained unit commitment (SCUC) and security constrained eco- nomic dispatch (SCED) to ensure reliability. A common policy is that 10-min reserve must exceed the largest contingency. However, this condition does not guarantee reliability because voltage and thermal limits can hinder reserve deliverability. Many operators use zonal reserve markets to ensure reserves are dispersed across the grid. Such zonal models attempt to anticipate transmission bot- tlenecks, which is a difficult task when the future system state is un- certain. This paper examines the market implications of dynamic reserve policies used to mitigate uncertainty from renewable re- sources and contingencies. We study the market implications of policies recently proposed in the literature, such as hourly zones within day-ahead SCUC and an algorithm that formally disqual- ifies reserves that are expected to be undeliverable. A locational reserve pricing scheme is also proposed in connection with sce- nario-based reserve disqualification. Analysis on the RTS-96 test case shows that dynamic zones and reserve disqualification, along with the proposed compensation scheme, help direct reserve pay- ments toward resources that more effectively respond to contin- gencies. Index Terms—Electric energy markets, locational reserve pay- ments, power generation dispatch, power system economics, power system reliability, renewable energy, reserve requirements, reserve zones, unit commitment. NOMENCLATURE Sets: Generator contingencies; are in zone . Generators and reserve providers; are in zone and are at node . Transmission lines and transformers. Nodes. Time periods. Manuscript received February 10, 2014; revised July 10, 2014 and September 21, 2014; accepted November 02, 2014. This work was supported in part by the National Science Foundation under award #1333646 and in part by the Power Systems Engineering Research Center (PSERC). Paper no. TPWRS- 00202-2014. J. D. Lyon and M. Zhang are with the Department of Industrial Engineering, Arizona State University, Tempe, AZ 85287 USA (e-mail: joshua.lyon@asu. edu; muhong.zhang@asu.edu). F. Wang and K. W. Hedman are with the School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ 85287 USA (e-mail: fengyu.wang@asu.edu; kory.hedman@asu.edu). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TPWRS.2014.2377044 Wind scenarios. Zones; is the zone of generator . Parameters (Index Denotes Period): Power flow limit on line . Net injection at node after contingency but prior to re-dispatch. Sensitivity of flow on line to injection at node . Proportion of reserve from resource cleared in the day-ahead market that is deliverable in real-time for contingency . Available up and down reserve from generator . Weight indicating the criticality of line . Reserve disqualification indicator for generator ( means is disqualified for contingency ). Reserve quantity from generator that receives payment for contingency . Total reserve payment to generator . Variables (Index Denotes Period): Net injection at node following re-dispatch for contingency . Power produced by generator . Reserve provided by generator . Total reserve designated as deliverable from zone to contingency . Reserve import capability from zone to zone . Cleared reserve from resource that cannot be dispatched in response to contingency . Up and down reserve deployment from generator in response to contingency . Dual variable for the constraint classifying reserve in zone as deliverable for contingency . I. INTRODUCTION I NDEPENDENT system operators (ISOs) manage the power grid with the goal of maximizing the market surplus. The day-ahead markets (DAMs) and the real-time markets (RTMs) are cleared using security-constrained unit commit- ment (SCUC) and security-constrained economic dispatch (SCED) models. Important physical constraints include gen- erator capacity, generator ramping, and transmission limits. Important operational constraints include ancillary services requirements, such as reserves, which help avoid the need 0885-8950 © 2015 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.