<p>In the US, seven regional transmission organizations (RTOs)
operate wholesale electricity markets within three largely independent
transmission systems, the largest of which includes five RTO regions and many
vertically integrated utilities.</p>
<p>RTOs operate a day-ahead and a real-time market. In the
day-ahead market, generation and demand-side resources are optimally scheduled
based on bids and offers for the next day.
Those schedules are adjusted according to actual operating conditions in
the real-time market. Both markets
involve a unit commitment calculation, a mixed integer program that determines
which generators will be online, and an economic dispatch calculation, an
optimization determines the output of each online generator for every interval
and calculates locational marginal prices (LMPs).</p>
<p>The use of LMPs for the management of congestion in RTO transmission
systems has brought efficiency and transparency to the operation of electric
power systems and provides price signals that highlight the need for investment
in transmission and generation. Through
this work, we aim to extend these efficiency and transparency gains to the
coordination across RTOs. Existing market-based
inter-regional coordination schemes are limited to incremental changes in
real-time markets. </p>
<p>We propose a multi-regional unit-commitment that enables
coordination in the day-ahead timeframe by applying a distributed approach to approximate
a system-wide optimal commitment and dispatch while allowing each region to
largely maintain their own rules, model only internal transmission up to the
boundary, and keep sensitive financial information confidential. A heuristic algorithm based on an extension
of the alternating directions method of multipliers (ADMM) for the mixed
integer program is applied to the unit commitment. </p>
The proposed coordinated solution was simulated and
compared to the ideal single-market scenario and to a representation of the
current uncoordinated solution, achieving at least 58% of the maximum potential
savings, which, in terms of the annual cost of electric generation in the US, could
add up to nearly $7 billion per year. In
addition to the coordinated day-ahead solution, we develop a distributed
solution for financial transmission rights (FTR) auctions with minimal
information sharing across RTOs that constitutes the
first known work to provide a viable option for market participants to seamlessly hedge price
variability exposure on cross-border transactions.
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/14423855 |
| Date | 07 May 2021 |
| Creators | Veronica R Bosquezfoti (10653461) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/Distributed_Optimization_Algorithms_for_Inter-regional_Coordination_of_Electricity_Markets/14423855 |
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