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Flexible Ramping Product Procurement in Day-Ahead Markets

Journal Article · · IEEE Transactions on Energy Markets, Policy and Regulation
Flexible ramping products (FRPs) emerge as a promising instrument for addressing steep and uncertain ramping needs through market mechanisms. Initial implementations of FRPs in North American electricity markets, however, revealed several shortcomings in existing FRP designs. Here, in many instances, FRP prices failed to signal the true value of ramping capacity, most notably evident in zero FRP prices observed in a myriad of periods during which the system was in acute need for rampable capacity. These periods were marked by scheduled but undeliverable FRPs, often calling for operator out-of-market actions. On top of that, the methods used for procuring FRPs have been primarily rule-based, lacking explicit economic underpinnings. In this paper, we put forth an alternative framework for FRP procurement, which seeks to set FRP requirements and schedule FRP awards such that the expected system operation cost is minimized. Using real-world data from U.S. ISOs, we showcase the relative merits of the framework in (i) reducing the total system operation cost, (ii) improving price formation, (iii) enhancing the the deliverability of FRP awards, and (iv) reducing the need for out-of-market actions.
Research Organization:
Argonne National Laboratory (ANL), Argonne, IL (United States)
Sponsoring Organization:
USDOE Office of Electricity (OE), Advanced Grid Research & Development
Grant/Contract Number:
AC02-06CH11357; OE0000875
OSTI ID:
2575063
Journal Information:
IEEE Transactions on Energy Markets, Policy and Regulation, Journal Name: IEEE Transactions on Energy Markets, Policy and Regulation Journal Issue: 1 Vol. 3; ISSN 2771-9626
Publisher:
IEEECopyright Statement
Country of Publication:
United States
Language:
English

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Day-Ahead Operational Scheduling With Enhanced Flexible Ramping Product: Design and Analysis journal May 2022
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A Data-Driven Methodology for Contextual Unit Commitment Using Regression Residuals journal November 2024

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