THESIS
2020
1 online resource (xi, 95 pages) : illustrations (some color)
Abstract
The Locational marginal price (LMP) is the most important pricing scheme in electricity
markets, and the corresponding LMP-based economic dispatch is the most significant
operating model in power systems. However, the deepening penetration of renewable supply
and distributed energy resources poses fundamental challenges to the current market
design. We focus on analyzing and proposing new market designs to accommodate these
energy resources in future power systems.
First, we deal with the challenge brought by the strategic aggregators of demand-side flexibility. Based on our theoretical analysis of the formulated bi-level program, we find
that the strategic aggregators can potentially gain benefits at the cost of other market
participants or even system-wide performance, highly dependin...[
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The Locational marginal price (LMP) is the most important pricing scheme in electricity
markets, and the corresponding LMP-based economic dispatch is the most significant
operating model in power systems. However, the deepening penetration of renewable supply
and distributed energy resources poses fundamental challenges to the current market
design. We focus on analyzing and proposing new market designs to accommodate these
energy resources in future power systems.
First, we deal with the challenge brought by the strategic aggregators of demand-side flexibility. Based on our theoretical analysis of the formulated bi-level program, we find
that the strategic aggregators can potentially gain benefits at the cost of other market
participants or even system-wide performance, highly depending on their bus locations.
We propose to additionally charge the strategic aggregators for the newly introduced
congestion to mitigate these negative effects.
Second, we deal with the challenge posed by the strategic distribution system operators
(DSOs) equipped with renewable generations. We theoretically identify that the
LMP-based pricing scheme leaves arbitrage opportunities between day-ahead and real-time
markets for DSOs via strategic bidding, especially under high uncertainties. We
propose a Nash bargaining solution-based pricing scheme for real-time coordination between
operators, to effectively prevent these strategic behaviors and help the system.
Finally, we focus on the stochastic economic dispatch, to meet the challenge of system
inefficiency under high renewable uncertainties. For individual scenarios, we mathematically
address the reason for the potential short-run failure of cost recovery and revenue
adequacy, recognizing the unfairness among different market participants. However, we
theoretically demonstrate that, in expectation, the stochastic approach could bring more
long-run benefits to the system beyond improved cost-efficiency, motivating its promotion
regardless of the short-run disadvantages.
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