دانلود مقاله ISI انگلیسی شماره 7919
عنوان فارسی مقاله

استراتژی مناقصه مبتنی بر تغییر حدسی در بازارهای لحظه ای : اصول و مقایسه با بازی کلاسیک استراتژی های مناقصه نظری

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
7919 2003 7 صفحه PDF سفارش دهید 3790 کلمه
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Conjectural variation based bidding strategy in spot markets: fundamentals and comparison with classical game theoretical bidding strategies
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Electric Power Systems Research, Volume 67, Issue 1, October 2003, Pages 45–51

کلمات کلیدی
بازار برق - مناقصه استراتژی - تنوع حدس - تئوری بازی ها -
پیش نمایش مقاله
پیش نمایش مقاله استراتژی مناقصه مبتنی بر تغییر حدسی در بازارهای لحظه ای : اصول و مقایسه با بازی کلاسیک استراتژی های مناقصه نظری

چکیده انگلیسی

In this paper, the concept of conjectural variation (CV) and its applications in electricity spot markets are introduced. The conjecture of a firm is defined as its belief or expectation of how its rivals will react to the change of its output. CV based bidding strategy (CVBS) method can help generation firms to improve their strategic bidding and maximize their profits in real electricity spot markets with imperfect information. In real applications, a firm using CVBS will integrate its rivals into one fictitious competitor and estimate its generation and reaction to the firm's change of output so that an optimal decision can be made accordingly. It is shown that classical game theoretic bidding strategies (GTBS) are special cases of CVBS families, and the system equilibrium reached via CVBS is a Nash equilibrium. Computer test results support the analytic conclusions very well.

مقدمه انگلیسی

In recent years, competitions have been introduced to power industry in order to improve social welfare and market efficiency. However due to high barriers for new entrants to enter electricity markets caused by long construction period of power plants and huge amount of capital investment, the electricity market appears closer to an oligopolistic market with fewer power suppliers. Therefore, each generation firm will rationally conduct strategic bidding to maximize its own profit. Three main approaches, i.e. market clearing price (MCP) forecasting, rivals’ bidding curve modeling and game based rivals’ strategic behavior simulating [1], [2], [3], [4], [5] and [6] are often used for generation firm strategic bidding. Among them the game theory based method is most suitable to analyze the behavior in an oligopolistic electricity market. However, its application is limited by the requirement of common knowledge on all firms’ actual production costs. Recently, the conjectural variation (CV) based method is proposed to estimate the strategic behavior in game-theoretic context in terms of imperfect information available in actual electricity market [7] and [8]. The concept of conjectural variation was brought forward by Bowley in 1924, but named as ‘conjectural variation’ by Frisch in 1933 [9] and [10]. In conjectural variation models each firm in an oligopolitic market rationally maximizes its own profit while taking account of reactions of its competitors. The method can easily model a market with different players, such as leaders, followers, and price takers. The consistency of conjecture has been discussed by economists in [10], [11] and [12] to show the dynamic characteristics of CV. The CV method is broadly applied in transportation decision, investment decision and other economic environments [13] and [14]. In power systems, the conjectural supply function is proposed to simulate the electricity market of Spain effectively [7], and in [8] it is applied to simulate the E&W market using linear dc network. However, the previous work on CV is still remaining in a static framework and requiring cost functions to estimate the conjectural parameters [8], which might make the conjecture of each firm different from the actual response of its rivals and therefore lead to less firm profits. In this paper, the concept of CV and its applications in electricity spot markets are introduced. The conjecture of a firm is defined as its belief or expectation of how its rivals will react to the change of its output. CV based bidding strategy (CVBS) method can help generation firms to improve their strategic bidding and maximize their profits in actual electricity spot markets with imperfect information. In real markets with multiple players, a firm using CVBS will integrate its rivals’ responses into one pseudo-competitor's response and use only available imperfect information announced in the market to make optimal decision accordingly. It is shown that classical game theoretical bidding strategies (GTBS) are special cases of CVBS families, and the system equilibrium reached via CVBS is a Nash equilibrium. Computer test results support the analytic conclusions very well. The paper is arranged as follows. Section 2 presents math model of CV based bidding. Section 3 gives the application of CV based bidding strategy in real N-player power markets. Comparison of CVBS with classical GTBS approaches is presented in Section 4, together with the proof that if CVBS approach converges, it will converge to a Nash equilibrium. Section 5 is a computer test with conclusions drawn in Section 6.

نتیجه گیری انگلیسی

This paper presents the concept of conjectural variation and its applications to strategic bidding of generation firms in the electricity spot market. It is shown that the conjectural variation based bidding strategy can help Gencos to maximize their profits based on available imperfect information; classical market structures and game theoretical bidding strategies, such as perfect competition, Cournot, Stackelberg and monopoly (collusion), are special cases in the CVBS solution family; using CVBS, a Nash equilibrium can be reached in the repeated electricity market, which corresponds to a special set of CVs held by individual generation firms. Computer test results support the analytic conclusions very well.

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