A MPCC approach on a Stackelberg game in an electric power market : changing the leadership

An electric power market is studied as a Stackelberg game where two firms, A and B, produce energy. It is analyzed two distinct situations, according to the firm who plays the leader role: the first one, when the firm A is the leader and the other firm is the follower, and the second that is the reverse of the players roles. The main goal is to understand the behavior of the various agents that compose the electric power network, such as transmissions capacity, quantities of power generated and demanded, when changing leadership. The problem is formulated as a Mathematical Program with Complementarity Constraints (MPCC) and reformulated into a Nonlinear Program (NLP), allowing the use of robust NLP solvers. Numerical results are presented and some final considerations are carried out.Universidade do Minho. Centro AlgoritmiFundação para a Ciência e a Tecnologia (FCT

Value of risk scores in the decision to palliate patients with ruptured abdominal aortic aneurysm

Background: The aim of this study was to develop a 48-h mortality risk score, which included morphology data, for patients with ruptured abdominal aortic aneurysm presenting to an emergency department, and to assess its predictive accuracy and clinical effectiveness in triaging patients to immediate aneurysm repair, transfer or palliative care. Methods: Data from patients in the IMPROVE (Immediate Management of the Patient With Ruptured Aneurysm: Open Versus Endovascular Repair) randomized trial were used to develop the risk score. Variables considered included age, sex, haemodynamic markers and aortic morphology. Backwards selection was used to identify relevant predictors. Predictive performance was assessed using calibration plots and the C-statistic. Validation of the newly developed and other previously published scores was conducted in four external populations. The net benefit of treating patients based on a risk threshold compared with treating none was quantified. Results: Data from 536 patients in the IMPROVE trial were included. The final variables retained were age, sex, haemoglobin level, serum creatinine level, systolic BP, aortic neck length and angle, and acute myocardial ischaemia. The discrimination of the score for 48-h mortality in the IMPROVE data was reasonable (C-statistic 0·710, 95 per cent c.i. 0·659 to 0·760), but varied in external populations (from 0·652 to 0·761). The new score outperformed other published risk scores in some, but not all, populations. An 8 (95 per cent c.i. 5 to 11) per cent improvement in the C-statistic was estimated compared with using age alone. Conclusion: The assessed risk scores did not have sufficient accuracy to enable potentially life-saving decisions to be made regarding intervention. Focus should therefore shift to offering repair to more patients and reducing non-intervention rates, while respecting the wishes of the patient and family

SECURITY ANALYSIS AND OPTIMIZATION

75121623164

Generalized state estimation

Power system state estimation derives a real-time network model by extracting information from a redundant data set consisting of telemetered, predicted and static data items. This paper describes a generalized, fully developed, estimation approach that fundamentally improves the information extraction process. Its main contribution is the successful inclusion of topology and parameters in the estimation and bad data analysis processes. This is valuable both in the initial commissioning of a state estimator, and in its routine real-time and study mode application. The approach involves a variety of novel concepts and methods. It is usable in Weighted Least Squares (WLS) and other estimation approaches.1331069107

STUDIES ON POWER SYSTEM LOAD FLOW EQUIVALENCING

9962301231

An MPCC approach on a Stackelberg game in an electric power market: changing the leadership

An electric power market is formulated as a Stackelberg game where two firms, A and B, produce energy. Two distinct situations, according to the firm who plays the leader role, are analysed. In the first one, the firmA is the leader and the firm B is the follower, and in the second situation the players reverse their roles. In order to select the optimal strategy, the leader uses as knowledge his own perception of the market and anticipates the reactions of the other followers. The main goal of this paper is to understand the behaviour of the various agents that compose the electric power network, such as transmissions capacity, quantities of power generated and demanded, when the leadership changes. The problem is formulated as a mathematical program with complementarity constraints (MPCC) and reformulated into a nonlinear program (NLP), allowing the use of robust NLP solvers. Computational results using Lancelot, Loqo and Snopt solvers are performed. The numerical experiments show that the firm profit is conditioned by the available information