Electricity markets are cleared by a two-stage, sequential process consisting of a forward (day-ahead) market and a spot (real-time) market. While their design goal is to achieve efficiency, the lack of sufficient competition introduces many opportunities for price manipulation. To discourage this phenomenon, some Independent System Operators (ISOs) mandate generators to submit (approximately) truthful bids in the day-ahead market. However, without fully accounting for all participants' incentives (generators and loads), the application of such a mandate may lead to unintended consequences. In this paper, we model and study the interactions of generators and inelastic loads in a two-stage settlement where generators are required to bid truthfully in the day-ahead market. We show that such mandate, when accounting for generator and load incentives, leads to a {generalized} Stackelberg-Nash game where load decisions (leaders) are performed in day-ahead market and generator decisions (followers) are relegated to the real-time market. Furthermore, the use of conventional supply function bidding for generators in real-time, does not guarantee the existence of a Nash equilibrium. This motivates the use of intercept bidding, as an alternative bidding mechanism for generators in the real-time market. An equilibrium analysis in this setting, leads to a closed-form solution that unveils several insights. Particularly, it shows that, unlike standard two-stage markets, loads are the winners of the competition in the sense that their aggregate payments are less than that of the competitive equilibrium. Moreover, heterogeneity in generators cost has the unintended effect of mitigating loads market power. Numerical studies validate and further illustrate these insights.
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This content will become publicly available on December 31, 2024
Social Cost Analysis of Shared/Buy-in Computing Systems
Shared/buy-in computing systems offer users the option to select between buy-in and shared services. In such systems, idle buy-in resources are made available to other users for sharing. With strategic users, resource purchase and allocation in such systems can be cast as a non-cooperative game, whose corresponding Nash equilibrium does not necessarily result in the optimal social cost. In this study, we first derive the optimal social cost of the game in closed form, by casting it as a convex optimization problem and establishing related properties. Next, we derive a closed-form expression for the social cost at the Nash equilibrium, and show that it can be computed in linear time. We further show that the strategy profiles of users at the optimum and the Nash equilibrium are directly proportional. We measure the inefficiency of the Nash equilibrium through the price of anarchy, and show that it can be quite large in certain cases, e.g., when the operating expense ratio is low or when the distribution of user workloads is relatively homogeneous. To improve the efficiency of the system, we propose and analyze two subsidy policies, which are shown to converge using best-response dynamics.
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- Award ID(s):
- 1908087
- NSF-PAR ID:
- 10496686
- Publisher / Repository:
- IEEE
- Date Published:
- Journal Name:
- ACM Transactions on Economics and Computation
- Volume:
- 11
- Issue:
- 3-4
- ISSN:
- 2167-8375
- Page Range / eLocation ID:
- 1 to 36
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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