Determining bidding strategies in sequential auctions

2001 ◽  
Author(s):  
Hiromitsu Hattori ◽  
Makoto Yokoo ◽  
Yuko Sakurai ◽  
Toramatsu Shintani
Keyword(s):  
Sequential Auctions ◽  
Bidding Strategies

Determining bidding strategies in sequential auctions: Quasi-linear utility and budget constraints

2007 ◽  
Vol 38 (8) ◽  
pp. 72-83 ◽  
Author(s):  
Hiromitsu Hattori ◽  
Makoto Yokoo ◽  
Yuko Sakurai ◽  
Toramatsu Shintani
Keyword(s):  
Sequential Auctions ◽  
Budget Constraints ◽  
Bidding Strategies ◽  
Linear Utility

scholarly journals Sequential auctions and price anomalies

2014 ◽  
Vol 59 (200) ◽  
pp. 7-42 ◽  
Author(s):  
Dejan Trifunovic
Keyword(s):  
Empirical Research ◽  
Theoretical Models ◽  
Sequential Auctions ◽  
English Auctions ◽  
Bidding Strategies ◽  
Empirical Results ◽  
Heterogeneous Objects ◽  
Increasing Trend ◽  
Private Values ◽  
Equilibrium Bidding

In sequential auctions objects are sold one by one in separate auctions. These sequential auctions might be organized as sequential first-price, second-price, or English auctions. We will derive equilibrium bidding strategies for these auctions. Theoretical models suggest that prices in sequential auctions with private values or with randomly assigned heterogeneous objects should have no trend. However, empirical research contradicts this result and prices exhibit a declining or increasing trend, which is called declining and increasing price anomaly. We will present a review of these empirical results, as well as different theoretical explanations for these anomalies.

Risk-Based Robust Bidding Strategies for EVs’ Aggregators in Day-ahead Markets with Uncertainty

2020 ◽  
Author(s):  
Ahmed Abdelmoaty ◽  
Wessam Mesbah ◽  
Mohammad A. M. Abdel-Aal ◽  
Ali T. Alawami
Keyword(s):  
Robust Optimization ◽  
Electricity Market ◽  
Real Life ◽  
Optimization Approach ◽  
Case Scenario ◽  
Worst Case ◽  
Bidding Strategies ◽  
Wind Generators ◽  
Proposed Model ◽  
Optimal Bidding

In the recent electricity market framework, the profit of the generation companies depends on the decision of the operator on the schedule of its units, the energy price, and the optimal bidding strategies. Due to the expanded integration of uncertain renewable generators which is highly intermittent such as wind plants, the coordination with other facilities to mitigate the risks of imbalances is mandatory. Accordingly, coordination of wind generators with the evolutionary Electric Vehicles (EVs) is expected to boost the performance of the grid. In this paper, we propose a robust optimization approach for the coordination between the wind-thermal generators and the EVs in a virtual<br>power plant (VPP) environment. The objective of maximizing the profit of the VPP Operator (VPPO) is studied. The optimal bidding strategy of the VPPO in the day-ahead market under uncertainties of wind power, energy<br>prices, imbalance prices, and demand is obtained for the worst case scenario. A case study is conducted to assess the e?effectiveness of the proposed model in terms of the VPPO's profit. A comparison between the proposed model and the scenario-based optimization was introduced. Our results confirmed that, although the conservative behavior of the worst-case robust optimization model, it helps the decision maker from the fluctuations of the uncertain parameters involved in the production and bidding processes. In addition, robust optimization is a more tractable problem and does not suffer from<br>the high computation burden associated with scenario-based stochastic programming. This makes it more practical for real-life scenarios.<br>

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