ranges the bidding genset blocks in order of increasing price to The bid variable price b((: describes the V< form a merit order list for each ADP half hour to the ceM as a function of mw provided. The price of the most expensive genset dispatched in any half that the bid variable price is a p hour t is designated as the System Marginal Price(SMP.)[3], e into R, the set of real for that half hour as is shown in Figure 2. Each genset that here pin(pi)is the minimum(maximum)output of ates during half hour t receives a payment that includes bidder is unit MPt for each MWh of energy generated during that time The bid start-up price b(: describes the cost incurred ( Hence every genset is paid more than or equal to the price by the CPP whenever unit i is started up. We assume specified in the offer file. Generators also receive the submitted that the start-u is a function of the down time start-up price each time the unit is started up the unit with 62:[0,∞)→R The bid ofered capacity gi=[ai, 1, ai, 2. by bidder i to the CPP dispatcher for use We assume that the bidder submi correct operational data for the unit lest a schedule be infeasible. These consist of pin, spinning reserve capability of unit Ti and d the unit minimum up and down times, respectively. The generator not obliged to reveal any information concerning true costs. The bid variable price, bid start-up price and bid offered ca- pacity are strategic decision variables that the bidde er selec maximize profits. he define a bid of bidder i to be the triple Bi=( 4(), Figure 2: Determination of the system marginal pric 620, gi). A bid p: is admissible if b! ()ccp?im, p7 a],b EC[0, oo)and ga 20cR, where C[a, bl(C(a, b1)denotes the set of continuous(piece-wise linear)functions on the interval [a, b] We construct a framework that embodies the salient charac- We state the CEM operator problem using the nota teristics of the EWPP. The bidder, thus, submits a bid for the tion of Table 1 and the definition of the T-dimensione right to serve load Under competitive conditions, the bidder vectors D= [D1, D2,, Dr], R=[Ri, Ra,Rr ui= [ui lect the unit to be included in the commitment list. Since the ],g2=四p,i,…;r]and al vectors bidder receives a payment which is greater or equal to its bi der to maximise profits. Given the large-scale and nonlinear li,r,IMl The cem operator problem determine nature of the problem, the auction theory literature (4). (5). (6 most economic dispatch that satisfies the forecasted demands and exploits well the structural characteristics of the analyti- constraints. This is denoted by cal based on decision analysis CEM framework. The strength of the results lies in the explicit representation of the variou constraints and considerations under which power systems op ) crate. The analytical development not only allows the optimal bidding strategy formulation but also is useful in providing es- d analytical 区+ ing the performance of generating units. Extensive numerical (1) results illustrate the robustness and superiority of the analyti- ally developed optimal bidding strategies subject to D4-∑A1Pi;tui;=0 The Framework Rt-∑1r;tw;t≤0 We develop a general competitive electricity (CEM) framework which we use to formulate and anal pn≤p,t≤p The commitment and dispatch of units in the CEM are based 0≤pi;≤ai;t on a competitive auction procedure. The market sellers, typi- 0≤rt≤min{r,pa-p; =1,2,…,M cally generators, submit a sealed bid stating the price at which they are willing to sell power. The CEM operator, the en tity responsible for coordinating all energy transactions with Tie satisfies the t and i constraints the Cem, selects the set of least expensive units to meet the We formulate roblems by considering he bids received from the set of M bidders. Each bid B: has we refer to equations( 1)-(3)as the primal form of the CEm ator problem(CEMP). The triple 2=uip r], is 310