Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Modeling, equilibrium and market power for electricity capacity markets
Cheng Guo1, Christian Kroer2, Daniel Bienstock2, Yury Dvorkin3
1Clemson University; 2Columbia University; 3Johns Hopkins University
The capacity market is a marketplace for trading generation capacity, and is viewed by its proponents as a mechanism to ensure power system reliability. Based on practice at NYISO, we propose optimization models for capacity markets and analyze outcomes. We find that with capacity markets, more generators are profitable, especially the ones with a lower net cost of new entry. Also, it is possible for a generator to earn more by exercising market power. We conduct case studies on NYISO dataset.
Robust auction design with support information
Jerry Anunrojwong, Santiago Balseiro, Omar Besbes
Columbia Business School, United States of America
The seller wants to sell an item to n i.i.d. buyers and only the support [a,b] are known; a/b quantifies relative support information (RSI). The seller either minimizes worst-case regret or maximizes worst-case approximation ratio. We show that i) with low RSI, second-price auctions (SPA) is optimal; ii) with high RSI, SPA is not optimal, and we introduce a new mechanism, the "pooling auction" (POOL), which is optimal; iii) with moderate RSI, a combination of SPA and POOL is optimal.
Design of resale platforms: pricing, competition, and search
Ilan Morgenstern1, Daniela Saban1, Divya Singhvi2, Somya Singhvi3
1Stanford University; 2New York University; 3University of Southern California
We study resale platforms, a growing type of online marketplaces in developing countries. These platforms allow their users to earn profits by selling products to their contacts, who do not typically shop online. We analyze data from a major resale platform in India and leverage our empirical findings to develop a model of the platform. We provide insights into key design aspects of the platform, such as the structure that determines resellers’ margins and the product ranking algorithm.
