Bilevel optimization applied to strategic pricing in competitive electricity markets

In this paper, we present a bilevel programming formulation for the problem of strategic bidding under uncertainty in a wholesale energy market (WEM), where the economic remuneration of each generator depends on the ability of its own management to submit price and quantity bids. The leader of the bilevel problem consists of one among a group of competing generators and the follower is the electric system operator. The capability of the agent represented by the leader to affect the market price is considered by the model. We propose two solution approaches for this non-convex problem. The first one is a heuristic procedure whose efficiency is confirmed through comparisons with the optimal solutions for some instances of the problem. These optimal solutions are obtained by the second approach proposed, which consists of a mixed integer reformulation of the bilevel model. The heuristic proposed is also compared to standard solvers for nonlinearly constrained optimization problems. The application of the procedures is illustrated in case studies with configurations derived from the Brazilian power system.     

Compact bidding languages and supplier selection for markets with economies of scale and scope

Combinatorial auctions have been used in procurement markets with economies of scope. Preference elicitation is already a problem in single-unit combinatorial auctions, but it becomes prohibitive even for small instances of multi-unit combinatorial auctions, as suppliers cannot be expected to enumerate a sufficient number of bids that would allow an auctioneer to find the efficient allocation. Auction design for markets with economies of scale and scope are much less well understood. They require more compact and yet expressive bidding languages, and the supplier selection typically is a hard computational problem. In this paper, we propose a compact bidding language to express the characteristics of a supplier’s cost function in markets with economies of scale and scope. Bidders in these auctions can specify various discounts and markups on overall spend on all items or selected item sets, and specify complex conditions for these pricing rules. We propose an optimization formulation to solve the resulting supplier selection problem and provide an extensive experimental evaluation. We also discuss the impact of different language features on the computational effort, on total spend, and the knowledge representation of the bids. Interestingly, while in most settings volume discount bids can lead to significant cost savings, some types of volume discount bids can be worse than split-award auctions in simple settings.     

A Stochastic Model for Bidding

Competitive bidding situations involve considering a multiplicity of factors. Organizations must be able to weigh the relative probability of potential projects based on resource usage, project duration and competitor actions to decide which of many possible bids to submit. A bidding strategy designed to maximize expected long run return is crucial, since an organization can usually submit only one bid per project.This paper presents a family of stochastic dynamic programming models considering different bidding situations. Several projects, each with several potential bids, are available for each situation. The objective is to determine what bidding strategy will maximize expected returns. Models are developed for two principle bidding situations: sequential, where projects are bid individually; and simultaneous, where several projects are bid at one time. Next, the effects of over- or under-commitment of resources are incorporated into the models. Finally, changes in project timing and the resultant effects on bidding strategy are included.A numerical example traces the changes in bidding strategy which occur as the models are expanded. The general formulation of bidding problems is also discussed, including changing the bid success probabilities due to competitor actions, the possibility of crashing projects and alternate methods of performing projects.     

An auction model arising from an Internet search service provider

Most search service providers such as Lycos and Google either produce irrelevant search results or unstructured company listings to the consumers. To overcome these two shortcomings, search service providers such as GoTo.com have developed mechanisms for firms to advertise their services and for consumers to search for the right services. To provide relevant search results, each firm who wishes to advertise at the GoTo site must specify a set of keywords. To develop structured company listings, each firm bids for priority listing in the search results that appear on the GoTo site. Since the search results appear in descending order of bid price, each firm has some control over the order in which the firm appears on the list resulting from the search. In this paper, we present a one-stage game for two firms that captures the advertising mechanism of a search service provider (such as GoTo). This model enables us to examine the firm’s optimal bidding strategy and evaluate the impact of various parameters on the firm’s strategy. Moreover, we analyze the conditions under which all firms would increase their bids at the equilibrium. These conditions could be helpful to the service provider when developing mechanisms to entice firms to submit higher bids.     

面向电子逆向拍卖的多属性报价建议模型

针对多属性拍卖中报价的复杂性和现有报价指导模型的局限性,提出了一个以拍卖方的总价值提升为基本约束,以投标人的利润最大化为目标的多属性报价建议模型,并引入二元变量解决了定性属性的推荐问题。当投标人具有不同的投标能力和偏好时,模型可根据投标人的投标要求进行报价推荐;当存在单位价值相同的推荐报价时,模型设置了相应的约束以鼓励早投标行为。最后,还从理论上证明了该模型的稳定性,并通过算例说明了模型的可行性。     

All-pay auctions with pre- and post-bidding options

Motivated by the emergence of online penny or pay-to-bid auctions, in this study, we analyze the operational consequences of all-pay auctions competing with fixed list price stores. In all-pay auctions, bidders place bids, and highest bidder wins. Depending on the auction format, the winner pays either the amount of their bid or that of the second-highest bid. All losing bidders forfeit their bids, regardless of the auction format. Bidders may visit the store, both before and after bidding, and buy the item at the fixed list price. In a modified version, we consider a setting where bidders can use their sunk bid as a credit towards buying the item from the auctioneer at a fixed price (different from the list price). We characterize a symmetric equilibrium in the bidding/buying strategy and derive optimal list prices for both the seller and auctioneer to maximize expected revenue. We consider two situations: (1) one firm operating both channels (i.e. fixed list price store and all-pay auction), and (2) two competing firms, each operating one of the two channels.     

Recurrent Competitive Bidding

A competitive bidding policy can be formulated if prior probability distributions of competitors' bids for future contracts have been determined. A method for determining these prior probability distributions is described for markets where there are a large number of customers. The identity of each winning company and its bid are assumed to be available to competitors and other customers so that the market reacts quickly to changes. A real example of the use of the method is given. The suppliers' general levels of bidding and their variation with individual types of customer are evaluated quantitatively. The results are consistent with qualitative knowledge of the market.     

Repeated games with asymmetric information and random price fluctuations at finance markets

This paper is concerned with multistage bidding models introduced in De Meyer and Moussa Saley (Int J Game Theory 31:285–319, 2002) to analyze the evolution of the price system at finance markets with asymmetric information. The repeated games are considered modelling the biddings with the admissible bids k/m, unlike the above mentioned paper, where arbitrary bids are allowed. It is shown that the sequence of values of n-step games is bounded from above and converges to the value of the game with infinite number of steps. The optimal strategies of infinite game generate a symmetric random walk of transaction prices over admissible bids with absorbing extreme points. The value of infinite game is equal to the expected duration of this random walk multiplied by the constant one-step gain of informed Player 1. This study was supported by the grant 04-06-80430 of Russian Foundation of Basic Research which is gratefully acknowledged. I am thankful to anonymous referees and to William Thomson for instructive and helpful remarks and comments.     

Day-ahead market bidding for a Nordic hydropower producer: taking the Elbas market into account

In many power markets around the world the energy generation decisions result from two-sided auctions in which producing and consuming agents submit their price-quantity bids. The determination of optimal bids in power markets is a complicated task that has to be undertaken every day. In the present work, we propose an optimization model for a price-taker hydropower producer in Nord Pool that takes into account the uncertainty in market prices and both production and physical trading aspects. The day-ahead bidding takes place a day before the actual operation and energy delivery. After this round of bidding, but before actual operation, some adjustments in the dispatched power (accepted bids) have to be done, due to uncertainty in prices, inflow and load. Such adjustments can be done in the Elbas market, which allows for trading physical electricity up to one hour before the operation hour. This paper uses stochastic programming to determine the optimal bidding strategy and the impact of the possibility to participate in the Elbas. ARMAX and GARCH techniques are used to generate realistic market price scenarios taking into account both day-ahead price and Elbas price uncertainty. The results show that considering Elbas when bidding in the day-ahead market does not significantly impact neither the profit nor the recommended bids of a typical hydro producer.     

A profit sharing scheme for a two-firm joint venture

Consider the scenario when two firms are setting up a joint venture. One firm has a set of technologies and knowhow for a new product while the other contributes the necessary capital for setting up and running the venture. The key issue that the two firms face in negotiating the joint venture is to determine a fair value for the technologies and knowhow. This paper presents an approach by which each firm bids a price for the technology with an objective to maximize their own profits from the joint venture. Provided that their bids satisfy a cooperation condition, the two firms settle on a price using a simple valuation formula. We analyze the impact of various factors on the decision process and provide numerical results to illustrate the bidding strategies. We conclude that in order to maximize their profits, it is often more important for both firms to increase the chance of cooperation than to increase their own shares of the joint venture.     

Heuristics for sourcing from multiple suppliers with alternative quantity discounts

In this paper, we analyze the impact of supplier pricing schemes and supplier capacity limitations on the optimal sourcing policy for a single firm. We consider the situation where the total quantity to be procured for a single period is known by the firm and communicated to the supplier set. In response to this communication, each supplier quotes a price and a capacity limit in terms of a maximum quantity that can be supplied to the buyer. Based on this information, the buyer makes a quantity allocation decision among the suppliers and corresponding to this decision is the choice of a subset of suppliers who will receive an order. Based on industry observations, a variety of supplier pricing schemes from the constituent group of suppliers are analyzed, including linear discounts, incremental units discounts, and all units discounts. Given the complexity of the optimization problem for certain types of pricing schemes, heuristic solution methodologies are developed to identify a quantity allocation decision for the firm. Through an extensive computational comparison, we find that these heuristics generate near-optimal solutions very quickly. Data from a major office products retailer is used to illustrate the resulting sourcing strategies given different pricing schemes and capacity limitations of suppliers in this industry. We find for the case of capacity constrained suppliers, the optimal quantity allocations for two complex pricing schemes (linear discount, and incremental units discount) are such that at most one selected supplier will receive an order quantity that is less than its capacity.     

Pure equilibria in a simple dynamic model of strategic market game

We present a discrete model of two-person constant-sum dynamic strategic market game. We show that for every value of discount factor the game with discounted rewards possesses a pure stationary strategy equilibrium. Optimal strategies have some useful properties, such as Lipschitz property and symmetry. We also show value of the game to be nondecreasing both in state and discount factor. Further, for some values of discount factor, exact form of optimal strategies is found. For β less than , there is an equilibrium such that players make large bids. For β close to 1, there is an equilibrium with small bids. Similar result is obtained for the long run average reward game.     

Pareto Optimal Allocation and Price Equilibrium for a Duopoly with Negative Externality

A spatial competition model involving decisions made by consumers and firms is proposed. A regulating agent assigns the demand, taking into account the price, transport and externality cost, and minimizing the joint consumer cost to obtain a Pareto optimal allocation. Assuming the Pareto optimal allocation, firms fix prices in order to maximize the profit. An equilibrium problem is studied and some results are presented. The problem and results are illustrated with an example.     

预算约束下广义第二价格关键字拍卖均衡分析

在关键字拍卖中,广告主预算约束是影响投标策略均衡的重要因素。针对广泛应用的广义第二价格机制,分析了预算约束下的关键字拍卖均衡性质。按照广告主的点击估价和预算分布情况,将广告主划分为天然完全赢家、天然部分赢家和天然输家这三种类型,提出了广告主投标临界值与关键值的概念,基于关键字拍卖不断重复进行的特点,分别从长期视角与短期视角建立了静态模型与动态模型,研究结果表明:静态环境下拍卖存在唯一的纯策略纳什均衡;动态环境下当广告主采用最优反应投标策略时拍卖将收敛至唯一的纳什均衡点,并且动态环境下拍卖商收入不低于静态环境下的拍卖收入。数值算例的结果表明在动态环境下不同的初始报价会导致拍卖收敛至不同的均衡点。研究结果为拍卖商提供了拍卖收入预测和拍卖机制优化的决策依据。     

Multi-criteria auctions without full comparability of bids

The emergence of auction mechanisms that support bids characterized by several attributes is one of the most recent evolutions within auction theory. These mechanisms, referred to as multi-attribute, multiple issue or multi-dimensional auctions, are at the intersection between multi-criteria decision and auction theories. The purpose of this paper is to introduce multi-criteria auctions the originality of which is not to require full comparability between bids. We claim that this distinctive feature is of great interest, especially in procurement situations. Furthermore, the existence of potential incomparability between multi-dimensional offers will permit us to manage different bidding niches coexisting within the same bidding space. A theoretical framework based on a general preference structure will be introduced and then referenced to existing approaches such as multi-attribute auctions or new ones such as dominance based multi-criteria auctions or butterfly auctions.     

Allocative efficiency in simulated multiple-unit combinatorial auctions with quantity support

We study the behavior of the Quantity Support Mechanism, a support tool, which suggests new bids for bidders in semi-sealed-bid combinatorial auctions. The support tool gives bidders a shortlist of provisionally winning bids (price–quantity combinations) they can choose from. We conducted a series of simulations to test the efficiency of the final allocations in the auctions. Our results indicate that quantity support auctions are more efficient than auctions without it, although the theoretical optimum is not always reached. Also, in our experiments, quantity support auctions led to a lower total cost to the buyer than non-combinatorial auctions, where the items were auctioned individually. The simulation results also show that the QSM cannot entirely overcome the threshold problem and what we call the “puzzle problem”.     

Nash equilibrium in a pay-as-bid electricity market Part 2 - best response of a producer

We consider a multi-leader-common-follower model of a pay-as-bid electricity market in which the producers provide the regulator with either linear or quadratic bids. We prove that for a given producer only linear bids can maximize his profit. Such linear bids are referred as the ‘best response’ of the given producer. They are obtained assuming the demand is known and some estimate of the bids of the other producers is available. Nevertheless we also show that whenever no best response exists, the optimal profit can be asymptotically attained by a sequence of quadratic bids converging to the so-called ‘limiting best response’. An explicit formula for such a sequence is provided.     

Equilibrium charges of multi-period allocation mechanisms for network services

Several new network services require a periodical resource allocation. For this purpose several auction-based multi-period allocation mechanisms have been proposed. This article derives explicitly resulting equilibrium charges in a simple mathematical model, i.e., constant session holding times, identical bandwidth request and independently identically uniformly distributed bids for the multi-period VCG and the PRENORM mechanism. In the same manner the expected revenue of the network provider can be calculated. Moreover, the analysis leads to an important condition for the protection parameter α of the PRENORM mechanism, such that the charging system does not break down. This research was partly financed by the Austrian Science Fund under contract number P18161-N13 (“Control of heterogenous systems”).     

Stochastic models for bidding strategies on oligopoly electricity market

In this paper we consider the forward/futures contracts and Asian-type call options for power delivery as important components of the bidding strategies of the players’ profits on the electricity market. We show how these derivatives can affect their profit. We use linear asymmetric supply function equilibrium (SFE) and Cournot models to develop firms’ optimal bidding strategies by including forward/futures contracts and Asian-type options. We extend the methodology proposed by Niu et al. (IEEE Trans Power Syst 20(4):1859–1867, 2005), where only forward contracts for power delivery were considered in the SFE model.