In this paper optimal bidding strategy problem modeled as a stochastic optimization problem and solved using Genetic Algorithm (GA). In an open electricity market environment, maximizing profit by suppliers is possible through strategic bidding. Because of the gaming by participants (power suppliers and large consumers) in an open electricity market, this is more an oligopoly than a competitive...

We develop a novel auction-based algorithm to allow users to fairly compete for a wireless fading channel. We use the second-price auction mechanism whereby user bids for the channel, during each time-slot, based on the fade state of the channel, and the user that makes the higher bid wins use of the channel by paying the second highest bid. Under the assumption that each user has a limited bud...

In an electricity market, every generation company (GENCO) attempts to maximize profit according to other participants bidding behaviors and power systems operating conditions. The goal of this study is to examine the optimal bidding strategy problem for GENCOs in energy and spinning reserve markets based on a hybrid GA-heuristic optimization algorithm. The heuristic optimization algorithm used...

Locational marginal pricing (LMP) is a widely employed method for pricing electricity in the wholesale electricity market. Although it is well known that the LMP mechanism is vulnerable to market manipulation, there is little literature providing a systematic analysis of this phenomenon. In the first part of this paper, we investigate the economic dispatch outcomes of the LMP mechanism with str...

A major concern in the design of wholesale electricity markets is the potential for the exercise of market power by generating unit owners. To better understand the determinants of generating unit owner market power and how it is exercised, this paper derives a model of bidding behavior in a competitive electricity market which incorporates various sources of uncertainty and the impact of the e...

This paper presents a Nash equilibrium model where the underlying objective functions involve uncertainty and nonsmoothness. The well-known sample average approximation method is applied to solve the problem and the first order equilibrium conditions are characterized in terms of Clarke generalized gradients. Under some moderate conditions, it is shown that with probability one, a statistical e...

We consider auctions in which greedy algorithms, paired with first-price or criticalprice payment rules, are used to resolve multiparameter combinatorial allocation problems. We study the price of anarchy for social welfare in such auctions. We show, for a variety of equilibrium concepts, including Bayes–Nash equilibria, low-regret bidding sequences, and asynchronous bestresponse dynamics, that...

We introduce a bidding language for expressing negative value externalities in position auctions for online advertising. The unit-bidder constraints (UBC) language allows a bidder to condition a bid on its allocated slot and on the slots allocated to other bidders. We introduce a natural extension of the Generalized Second Price (GSP) auction, the expressive GSP (eGSP) auction, that induces tru...

In most wholesale electricity markets generators must submit step-function offers of supply to a uniform price auction, and the market is cleared at the price of the most expensive offer needed to meet realised demand. Such markets can most elegantly be modelled as the pure-strategy, Nash Equilibrium of continuous supply functions, in which each supplier has a unique profit maximising choice of...

Most US consumers are charged a near-constant retail price for electricity, despite substantial hourly variation in the wholesale market price. This paper evaluates a randomized experiment that exposed households to hourly real time pricing (RTP) and applies the demand estimates to counterfactual simulations in a structural model of the Pennsylvania-Jersey-Maryland electricity market. The model...