Abstract
In order to develop a flexible simulator, a variety of models for Ancillary Services (AS) negotiation has been implemented in MASCEM a multi-agent system competitive electricity markets simulator. In some of these models, the energy and the AS are addressed simultaneously while in other models they are addressed separately. This paper presents an energy and ancillary services joint market simulation. This paper proposes a deterministic approach for solving the energy and ancillary services joint market. A case study based on the dispatch of Regulation Down, Regulation Up, Spinning Reserve, and Non-Spinning Reserve services is used to demonstrate that the use of the developed methodology is suitable for solving this kind of optimization problem. The presented case study is based on CAISO real AS market data considers fifteen bids. © 2011 IEEE.

Abstract
This paper presents a multistage transmission expansion planning (TEP) which alleviates the level of transmission congestion during the planning horizon. Due to the combinatorial nature of the proposed TEP model, a Benders decomposition approach intertwined with a manipulated disjunctive model is applied to decompose the original TEP problem into a master problem and two sub-problems standing for system security and optimal operation. The security sub-problem applying the N-1 contingency criterion to assess the transmission system security. Besides, the optimal operation sub-problem makes it possible for the proposed TEP model to fulfill the optimal operation as well as to calculate the difference between system lacational marginal prices (LMPs) for all buses. Also, this model appends a specific term into the TEP objective function as the congestion level (CL) reflecting the degree of market competitiveness. Therefore, the proposed TEP model minimizes the total costs comprising the investment cost of candidate transmission lines as well as the level of transmission congestion. The proposed approach is applied to the northeastern area of the Iranian power grid. © 2011 IEEE.

Abstract
Several types of market equilibria approaches, such as Cournot, Conjectural Variation (CVE). Supply Function (SFE) or Conjectured Supply Function (CSFE) have been used to model electricity markets for the medium and long term. Among them, CSFE has been proposed as a generalization of the classic Cournot. It computes the equilibrium considering the reaction of the competitors against changes in their strategy, combining several characteristics of both CVE and SFE. Unlike linear SFE approaches, strategies are linearized only at the equilibrium point, using their first-order Taylor approximation. But to solve CSFE, the slope or the intercept of the linear approximations must be given, which has been proved to be very restrictive. This paper proposes a new algorithm to compute CSFE. Unlike previous approaches, the main contribution is that the competitors' strategies for each generator are initially unknown (both slope and intercept) and endogenously computed by this new iterative algorithm. To show the applicability of the proposed approach, it has been applied to several case examples where its qualitative behavior has been analyzed in detail.

Abstract
This paper presents a new two-step algorithm to compute a conjectured supply function electricity market equilibrium with DC transmission network constraints. This approach generalizes a previous authors' model developed for the single-bus case. Unlike other approaches, its main contribution is that the parameters of the first order approximation of the conjectured supply functions (intercept and slope) are endogenously determined, coherently with the network lines status. Nodal prices are used to split the market into single prices areas. Each area is treated as a single-bus market from the transmission constraints point of view, and the authors' single-bus algorithm is applied to compute the generators supply functions for each area. These new generators strategies are then cleared to determine new nodal prices and areas for the next iteration. Convergence is achieved when the network lines status and strategies of the generators do not change significantly in two consecutive iterations. The algorithm has been tested with some illustrative case examples, and with a simplified version of the MIBEL market (Spain-Portugal). © 2011 IEEE.

Abstract
Long term electricity markets models tend to use simplified representations of both the demand and the generation units, to reduce the amount of input data and decision variables used, and also to decrease their execution times. On the one hand, hourly demand curves are usually simplified into a reduced set of non-chronological demand levels, each one representing hours with similar demand values. On the other hand, individual generation units are condensed into technologies grouping their costs curves by similarity in different appropriated technological cost mappings. This paper proposes several novel Mixed Integer Programming models to solve these two curve-fitting problems when the approximating function is a Piece-Wise Linear Function. By means of two real cases study it shows that the approximation approach has real applicability since it does not significantly compromise the traditional system representation. © 2011 IEEE.

Abstract
The increasing penetration of interruptible sources of energy is making security of supply a key aspect of present and future networks management, and reserves markets are gaining significant relevance. Demand representation used in traditional long term market models normally consists in a set of non chronological demand levels corresponding to hours with similar demand values. However, reserve issues are closely related with short term constraints (such as ramps), and this lack of chronological coupling does not allow for an appropriate representation of these technical constraints. This paper presents a joint energy and reserve conjectural equilibrium model that provides signal prices for both commodities and computes productions accordingly by satisfying system demand and reserve requirements. Generation is represented at a technological level, and water contributes to energy and reserve requirements with daily constraints. To reduce the feasible region, clustering is used to simplify hourly demand series into only a few daily patterns. In addition, keeping the link between hours and demand levels allows the model to combine short term technical constraints with traditional long term strategic planning constraints. © 2011 IEEE.