Demand shifting bids in energy auction with non-convexities and transmission constraints
AbstractThe major objective of this paper was to propose clearing and pricing models suitable for demand shifting bids in the efficient, but non-convex pool-based auction. Complex generators' offers bring non-convexities into the efficient auctions due to e.g. start-up costs and times. This paper focused on the responsive demands, introducing simple, yet adequate linear constraints into a multi-period bid/offer-based optimal power flow (OPF DC) model. As the standard locational marginal prices (LMPs) may not support the auction outcomes due to non-convexities, uplifts are needed to reduce generators' loss. Previous work has developed a minimum-uplift pricing model that directly optimizes prices, so that uplifts arising from generators' profit-suboptimality and simple, elastic demands' benefit-suboptimality are minimized. This work extended the mixed integer linear programming (MILP) formulation of the previous model to incorporate new linear constraints defining benefit-suboptimality of demand shifting bids. Furthermore, the transmission constrained market was attempted. As a result, the buyers were protected against over-curtailment; moreover, prices complemented with minimum uplifts were fair for both generators and demands. The models were validated on the literature-based cases, including IEEE RTS 24-node 24-hour system.
|Journal series||Energy Economics, ISSN 0140-9883|
|Publication size in sheets||0.5|
|Keywords in English||Double auction; Unit commitment; Energy pricing; Minimum uplift; Individual maximum profits|
|Project||Development of incentive compatible models and mechanisms in multi-agent systems. Project leader: Toczyłowski Eugeniusz,
, Phone: 7950, start date 02-04-2010, end date 01-04-2013, 505/G/1031/0032, Completed
|Score|| = 40.0, 02-02-2020, ArticleFromJournal|
= 45.0, 02-02-2020, ArticleFromJournal
|Publication indicators||= 4; = 2; : 2016 = 1.974; : 2016 = 3.199 (2) - 2016=4.41 (5)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.