2020
DOI: 10.1109/tpwrs.2019.2961231
|View full text |Cite
|
Sign up to set email alerts
|

A Chance-Constrained Stochastic Electricity Market

Abstract: Efficiently accommodating uncertain renewable resources in wholesale electricity markets is among the foremost priorities of market regulators in the US, UK and EU nations. However, existing deterministic market designs fail to internalize the uncertainty and their scenario-based stochastic extensions are limited in their ability to simultaneously maximize social welfare and guarantee non-confiscatory market outcomes in expectation and per each scenario. This paper proposes a chance-constrained stochastic mark… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

1
57
0

Year Published

2020
2020
2023
2023

Publication Types

Select...
7
1
1

Relationship

0
9

Authors

Journals

citations
Cited by 61 publications
(58 citation statements)
references
References 34 publications
1
57
0
Order By: Relevance
“…One can think of alternative ways to model uncertainty. For example, one potential alternative is to use chance-constrained programming, resulting in a chance-constrained electricity market design (Dvorkin, 2020). In addition, it is relevant to relax the assumption of information symmetry among the market players (Dvorkin et al, 2019b), which are the interface optimizer, TSO and DSOs in this study, and explore how the resulting model can be solved and how asymmetric information among players impacts the overall social welfare.…”
Section: Discussionmentioning
confidence: 99%
“…One can think of alternative ways to model uncertainty. For example, one potential alternative is to use chance-constrained programming, resulting in a chance-constrained electricity market design (Dvorkin, 2020). In addition, it is relevant to relax the assumption of information symmetry among the market players (Dvorkin et al, 2019b), which are the interface optimizer, TSO and DSOs in this study, and explore how the resulting model can be solved and how asymmetric information among players impacts the overall social welfare.…”
Section: Discussionmentioning
confidence: 99%
“…1) Obtain CDFs of the actual value and forecasting value of wind power in each time period based on the historical data. Calculate the covariance matrix R via (2)- (5).…”
Section: A Gaussian Copula-based Wind Power Samplingmentioning
confidence: 99%
“…A marginal pricing mechanism including pool energy prices and balancing energy prices is established. Reference [5] designs a chance-constrained stochastic market, which is capable of providing effective price signals that internalize the uncertainty of renewable generation resources and risk tolerance of the market operators. Reference [6] proposes an energy and reserve pricing mechanism that takes into account the RES stochasticity with the intention to produce more accurate signals to market participants.…”
Section: Introductionmentioning
confidence: 99%
“…As the aggregations of DERs reach a substantial fraction of suppliers/consumers, they cannot be neglected as market participants in day-ahead (DA) and real-time (RT) markets any more. However, under current electricity market rules, DERs face high deliverable risks due to the unpredictable nature of renewable energy [2,3,4], which leads to security and reliability issues for distribution network operations. This motivates us to design a future electricity market mechanism that explicitly incorporates the stochasticity of aggregated DERs to manage these risks.…”
Section: Introductionmentioning
confidence: 99%