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.

Abstract
Despite the large number of studies on the phenomenon of imposex, the mechanism underlying the abnormal growth of male sexual characters onto females in numerous gastropod species is yet to be fully elucidated. Although several hypotheses have been raised over the years, a convincing body of evidence indicates that tributyltin-induced imposex involves the abnormal modulation of the retinoid X receptor (RXR). Here, we investigate the RXR gene transcription at different timings and tissues upon exposure to environmentally relevant concentrations of tributyltin (TOT) (100 ng Sn/L TBT) in both genders of the imposex susceptible gastropod Nucella lapillus. RXR gene transcription was determined at two time-points (i.e., before and after imposex initiation) by quantitative Real Time PCR in potential target tissues: the central nervous system (CNS), penis/penis forming area (PFA), gonads and digestive gland. TBT-exposure altered transcription of RXR gene in a tissue and sex specific manner. In the CNS, a significant down-regulation was observed in females both before and after imposex initiation (P <= 0.01 and P <= 0.05, respectively). A similar trend was observed in male CNS at the first time-point, although differences between control and the TBT-exposed group were just above significance (P=0.059). The penis/PFA showed no differences in transcription of RXR gene between control and TBT exposed female snails before imposex induction, or before and after imposex initiation for males. However, male penis showed higher transcription of RXR gene in comparison to the PFA of females. After imposex has been induced, a significant (P <= 0.001) increase in transcription of RXR gene was observed in penis of females with vas deference sequence index (VDS) levels of 3-4 in comparison with the PFA of both control and imposex females with VDS 1-2. At advanced stages of imposex, females displayed RXR transcription patterns in penis identical to those of males, which points to a functional role of RXR in the penis of both genders. In the other tissues, gonads and digestive gland. RXR gene transcription was not affected by TBT, at any of the analysed time-points. These patterns of RXR gene transcription upon TOT exposure highlight the pivotal involvement of the CNS in the mechanism of imposex induction. We integrate the results in a conceptual model, and discuss the central role of RXR and the retinoic acid signalling pathways in imposex and male genitalia formation in gastropods.

Abstract
Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts. © 2010 Elsevier Inc.

Abstract
This paper discusses risk management, contracting, and bidding for a wind power producer. A majority of the wind power in the United States is sold on long-term power purchase agreements, which hedge the wind power producer against future price risks. However, a significant amount is sold as merchant power and therefore is exposed to fluctuations in future electricity prices (day-ahead and real-time) and potential imbalance penalties. Wind power forecasting can serve as a tool to increase the profit and reduce the risk from participating in the wholesale electricity market. We propose a methodology to derive optimal day-ahead bids for a wind power producer under uncertainty in realized wind power and market prices. We also present an initial illustrative case study from a hypothetical wind site in the United States, where we compare the results of different day-ahead bidding strategies. The results show that the optimal day-ahead bid is highly dependent on the expected day-ahead and real-time prices, and also on the risk preferences of the wind power producer. A deviation penalty between day-ahead bid and real-time delivery tends to drive the bids closer to the expected generation for the next day.