Suchergebnisse

The energy transition law passed by the French government has specific implications for renewable energies, in particular for their remuneration mechanism. Until 2015, a purchase obligation contract made it possible to sell electricity from wind power at a fixed rate. From 2015 onwards, some wind farms began to be exempted from the purchase obligation. This is because wind energy is starting to be sold directly on the market by the producers because of the breach of the purchase obligation contracts. Distribution system operators and transmission system operators require or even oblige producers to provide at least a production forecast one day in advance in order to rebalance the market. Over- or underestimation could be subject to penalties. There is, therefore, a huge need for accurate forecasts. It is in this context that this thesis was launched with the aim of proposing a model for predicting wind farms production by machine learning. We have production data and real wind measurements as well as data from meteorological models. We first compared the performances of the GFS and ECMWF models and studied the relationships between these two models through canonical correlation analysis. We then applied machine learning models to validate a first random forest prediction model. We then modeled the spatio-temporal wind dynamics and integrated it into the prediction model, which improved the prediction error by 3%. We also studied the selection of grid points by a variable group importance measure using random forests. Random forest prediction intervals associated with point forecasts of wind farm production are also studied. The forecasting model resulting from this work was developed to enable the ENGIE Group to have its own daily forecasts for all its wind farms. ; La loi de transition énergétique votée par l'Etat français a des implications précises sur les énergies renouvelables, en particulier sur leur mécanisme de rémunération. Jusqu'en 2015, un contrat d'obligation d'achat permettait de vendre ...

The energy transition law passed by the French government has specific implications for renewable energies, in particular for their remuneration mechanism. Until 2015, a purchase obligation contract made it possible to sell electricity from wind power at a fixed rate. From 2015 onwards, some wind farms began to be exempted from the purchase obligation. This is because wind energy is starting to be sold directly on the market by the producers because of the breach of the purchase obligation contracts. Distribution system operators and transmission system operators require or even oblige producers to provide at least a production forecast one day in advance in order to rebalance the market. Over- or underestimation could be subject to penalties. There is, therefore, a huge need for accurate forecasts. It is in this context that this thesis was launched with the aim of proposing a model for predicting wind farms production by machine learning. We have production data and real wind measurements as well as data from meteorological models. We first compared the performances of the GFS and ECMWF models and studied the relationships between these two models through canonical correlation analysis. We then applied machine learning models to validate a first random forest prediction model. We then modeled the spatio-temporal wind dynamics and integrated it into the prediction model, which improved the prediction error by 3%. We also studied the selection of grid points by a variable group importance measure using random forests. Random forest prediction intervals associated with point forecasts of wind farm production are also studied. The forecasting model resulting from this work was developed to enable the ENGIE Group to have its own daily forecasts for all its wind farms. ; La loi de transition énergétique votée par l'Etat français a des implications précises sur les énergies renouvelables, en particulier sur leur mécanisme de rémunération. Jusqu'en 2015, un contrat d'obligation d'achat permettait de vendre ...

The energy transition law passed by the French government has specific implications for renewable energies, in particular for their remuneration mechanism. Until 2015, a purchase obligation contract made it possible to sell electricity from wind power at a fixed rate. From 2015 onwards, some wind farms began to be exempted from the purchase obligation. This is because wind energy is starting to be sold directly on the market by the producers because of the breach of the purchase obligation contracts. Distribution system operators and transmission system operators require or even oblige producers to provide at least a production forecast one day in advance in order to rebalance the market. Over- or underestimation could be subject to penalties. There is, therefore, a huge need for accurate forecasts. It is in this context that this thesis was launched with the aim of proposing a model for predicting wind farms production by machine learning. We have production data and real wind measurements as well as data from meteorological models. We first compared the performances of the GFS and ECMWF models and studied the relationships between these two models through canonical correlation analysis. We then applied machine learning models to validate a first random forest prediction model. We then modeled the spatio-temporal wind dynamics and integrated it into the prediction model, which improved the prediction error by 3%. We also studied the selection of grid points by a variable group importance measure using random forests. Random forest prediction intervals associated with point forecasts of wind farm production are also studied. The forecasting model resulting from this work was developed to enable the ENGIE Group to have its own daily forecasts for all its wind farms. ; La loi de transition énergétique votée par l'Etat français a des implications précises sur les énergies renouvelables, en particulier sur leur mécanisme de rémunération. Jusqu'en 2015, un contrat d'obligation d'achat permettait de vendre ...

The energy transition law passed by the French government has specific implications for renewable energies, in particular for their remuneration mechanism. Until 2015, a purchase obligation contract made it possible to sell electricity from wind power at a fixed rate. From 2015 onwards, some wind farms began to be exempted from the purchase obligation. This is because wind energy is starting to be sold directly on the market by the producers because of the breach of the purchase obligation contracts. Distribution system operators and transmission system operators require or even oblige producers to provide at least a production forecast one day in advance in order to rebalance the market. Over- or underestimation could be subject to penalties. There is, therefore, a huge need for accurate forecasts. It is in this context that this thesis was launched with the aim of proposing a model for predicting wind farms production by machine learning. We have production data and real wind measurements as well as data from meteorological models. We first compared the performances of the GFS and ECMWF models and studied the relationships between these two models through canonical correlation analysis. We then applied machine learning models to validate a first random forest prediction model. We then modeled the spatio-temporal wind dynamics and integrated it into the prediction model, which improved the prediction error by 3%. We also studied the selection of grid points by a variable group importance measure using random forests. Random forest prediction intervals associated with point forecasts of wind farm production are also studied. The forecasting model resulting from this work was developed to enable the ENGIE Group to have its own daily forecasts for all its wind farms. ; La loi de transition énergétique votée par l'Etat français a des implications précises sur les énergies renouvelables, en particulier sur leur mécanisme de rémunération. Jusqu'en 2015, un contrat d'obligation d'achat permettait de vendre ...

The energy transition law passed by the French government has specific implications for renewable energies, in particular for their remuneration mechanism. Until 2015, a purchase obligation contract made it possible to sell electricity from wind power at a fixed rate. From 2015 onwards, some wind farms began to be exempted from the purchase obligation. This is because wind energy is starting to be sold directly on the market by the producers because of the breach of the purchase obligation contracts. Distribution system operators and transmission system operators require or even oblige producers to provide at least a production forecast one day in advance in order to rebalance the market. Over- or underestimation could be subject to penalties. There is, therefore, a huge need for accurate forecasts. It is in this context that this thesis was launched with the aim of proposing a model for predicting wind farms production by machine learning. We have production data and real wind measurements as well as data from meteorological models. We first compared the performances of the GFS and ECMWF models and studied the relationships between these two models through canonical correlation analysis. We then applied machine learning models to validate a first random forest prediction model. We then modeled the spatio-temporal wind dynamics and integrated it into the prediction model, which improved the prediction error by 3%. We also studied the selection of grid points by a variable group importance measure using random forests. Random forest prediction intervals associated with point forecasts of wind farm production are also studied. The forecasting model resulting from this work was developed to enable the ENGIE Group to have its own daily forecasts for all its wind farms. ; La loi de transition énergétique votée par l'Etat français a des implications précises sur les énergies renouvelables, en particulier sur leur mécanisme de rémunération. Jusqu'en 2015, un contrat d'obligation d'achat permettait de vendre ...

The purpose of the Phd is to analyze questions raised by short-termism in takevoer bids. As a matter of fact, some shareholders only have short-terme strategies (such as Hedge funds,.) and takeover bids provide some fantastic arbitration opportunities. First, one should clearly identify these actors. Products which might be used in such situation will also have to be studied. Second, one should analyze which defence could provide the target. Third, a study of the opportunity or repealing or amending french legislation on these issues will be done. ; Cette thèse vise à analyser les aspects juridiques du rôle joué par les acteurs ayant une stratégie actionariale de court-terme (hedge funds,.) dans le cadre des offres publiques d'acquisition. Outre l'identification de ces acteurs et la description des méthodes employées, il s'agit aussi de s'interroger sur les moyens à disposition de la société cible pour se défendre et de se demander si des évolutions législatives ne seraient pas nécessaires.

The purpose of the Phd is to analyze questions raised by short-termism in takevoer bids. As a matter of fact, some shareholders only have short-terme strategies (such as Hedge funds,.) and takeover bids provide some fantastic arbitration opportunities. First, one should clearly identify these actors. Products which might be used in such situation will also have to be studied. Second, one should analyze which defence could provide the target. Third, a study of the opportunity or repealing or amending french legislation on these issues will be done. ; Cette thèse vise à analyser les aspects juridiques du rôle joué par les acteurs ayant une stratégie actionariale de court-terme (hedge funds,.) dans le cadre des offres publiques d'acquisition. Outre l'identification de ces acteurs et la description des méthodes employées, il s'agit aussi de s'interroger sur les moyens à disposition de la société cible pour se défendre et de se demander si des évolutions législatives ne seraient pas nécessaires.

The purpose of the Phd is to analyze questions raised by short-termism in takevoer bids. As a matter of fact, some shareholders only have short-terme strategies (such as Hedge funds,.) and takeover bids provide some fantastic arbitration opportunities. First, one should clearly identify these actors. Products which might be used in such situation will also have to be studied. Second, one should analyze which defence could provide the target. Third, a study of the opportunity or repealing or amending french legislation on these issues will be done. ; Cette thèse vise à analyser les aspects juridiques du rôle joué par les acteurs ayant une stratégie actionariale de court-terme (hedge funds,.) dans le cadre des offres publiques d'acquisition. Outre l'identification de ces acteurs et la description des méthodes employées, il s'agit aussi de s'interroger sur les moyens à disposition de la société cible pour se défendre et de se demander si des évolutions législatives ne seraient pas nécessaires.

Short-term financing is forgotten by theory of corporate finance. However, French medium-sized firms use a lot this source of funding. The objective of this thesis is to analyze the determinants of short-term financing for these firms. The first part aims to establish a literature review of theories to explain the use of short-term financing. The second part empirically checks these theories on two samples, specifically 201 family businesses and 1,453 managerial firms. On the one hand, it is a question of characterizing the unlisted medium-sized enterprises and on the other hand, highlighting the determinants of the use of short-term financing. The primary results indicate that short-term financing is a management tool for the medium-sized enterprise. It can also have two functions, one compensatory and / or one passive cash. Furthermore, it brings out that managerial and family businesses exploit short-term financing differently. ; Le financement à court terme est le parent pauvre de la théorie financière. Pourtant, les moyennes entreprises françaises utilisent fortement ce financement. Ce travail a pour objectif d'analyser les déterminants du financement à court terme pour ces entreprises. La première partie vise à établir une revue de littérature des théories permettant d'expliquer l'utilisation du financement à court terme. La deuxième partie vient tester empiriquement ces théories sur deux échantillons, à savoir 201 entreprises familiales et 1 453 entreprises managériales. Il s'agit, d'une part, de caractériser les moyennes entreprises non cotées et d'autres part, de mettre en évidence les déterminants à l'utilisation de financement à court terme. Les principaux résultats indiquent que le financement à court terme est un outil de gestion au service de la moyenne entreprise. Il peut aussi assumer deux rôles, un compensatoire et/ou un de trésorerie passive. Par ailleurs, on met en évidence que les entreprises managériales et familiales exploitent différemment le financement à court terme.

The aviation industry has for many years pursued the objective of an optimum level of safetyin the air transport sector. With regard to military aviation, more precisely tactical, thispriority is coupled with an increasingly high and polymorphic search for performance. Whatcharacterize this type of aviation is the relationship between the performance pursued and theaccepted risks. It depends essentially on the context and the stakes of the missions to becarried out.The human factor approach is a major leverage for achieving this challenge. Thus, within theconstrained domain of aeronautics, the design and development of tools to assist crewcognition remains a prospect for the future, even if pilot training also becomes a majorchallenge for the coming years. In this context, the management of cognitive resources, and inparticular the specific management strategies put in place by the pilots, are central to thedecision-making process under constraints.In a research and engineering approach in cognition, we undertook a study involving pilotsand allowing the understanding of these mechanisms as well as the production ofrecommendations for the design of tools to help manage their cognitive resources. On thebasis of the analysis of feedback, and results of a preliminary experimental approach, we havebuilt a protocol to highlight the strategies implemented by the pilots in the context of anactivity during the descent and the final approach on the Clermont-Ferrand airport with acritical breakdown. The experimental results reconciled with our understanding hypotheseson the management of cognitive resources and management strategies, complete our analysisand recommendations for a tool to help manage the resources of the pilots. ; L'industrie aéronautique poursuit depuis de nombreuses années l'objectif d'un niveau optimal de sécurité dans le cadre du transport aérien. En ce qui concerne l'aviation militaire, plus exactement tactique, cette priorité se double d'une recherche de performance de plus en plus élevée et ...

Depuis son élection, Donald Trump a été à l'origine de mesures importantes qui ont porté atteinte aux doctrines de droit administratif relatives aux procédures décisionnelles au point de modifier profondément l'élaboration des politiques publiques. Ces mesures de libéralisation, prises par le biais d'ordonnances ou de nominations présidentielles, ont de plus en plus réduit l'expertise technocratique nécessaire à la mise en œuvre des politiques publiques. Elles pourraient avoir un impact profond sur l'administration fédérale. Le pouvoir législatif est aussi impliqué dans ces changements. Avant que les élections de 2018 ne mettent fin à la mainmise républicaine sur le Congrès, la Chambre des représentants adopta deux initiatives – le règlement sur la surveillance de l'exécutif (Executive in Need of Scrutiny [REINS]) et la loi sur la redevabilité réglementaire (Regulatory Accountability Act [RAA]) – qui auraient eu des conséquences similaires si elles avaient été transformées en lois. Le présent article évalue les conséquences à court et à long terme en matière de transparence et d'équilibre démocratique/constitutionnel de cette évolution.

We introduce the concept of carbon footprint into an aggregate demand and supply model with imperfectly competitive price and wage formation. We analyse the properties of the short-term macroeconomic equilibrium in the presence of a climate policy, which may take the form either of a carbon tax or of quotas of pollution permits. We show that in the short run climate policy (or its strengthening) is simultaneously a negative aggregate supply shock and a positive aggregate demand shock. It is thus inflationary but it has an ambiguous impact on aggregate economic activity and employment: it will only stimulate output in an economy where nominal wages are rigid enough. In all cases, climate policy will depress real wages. We also analyse the interactions between climate policy and the usual macroeconomic policies of demand (fiscal and monetary stimuli) and supply (labour tax cut). The multiplier effects of these demand and supply policies depend on the instrument chosen for implementing the climate policy (carbon tax or pollution permits). We finally establish the conditions under which a reform combining a climate policy strengthening and a labour tax cut can reach the double objective of a lower carbon footprint and a lower unemployment rate, without reducing workers' real wages. Such a policy reform has however an ambiguous impact on the government surplus (or deficit).

We introduce the concept of carbon footprint in a global mod and global demand with imperfect competitive formation of prices and wages and examine the properties of equilibrium in the presence of a climate policy. We are exploring two possible instruments of this policy, a carbon tax or a pollution permit quota. We show that in the short term climate policy (or its tightening) is both a negative overall shock and a positive global demand shock. It therefore causes inflationary effects but has an ambiguous impact on economic activity, employment and unemployment. It is only in an economy with sufficient nominal wage rigidities that climate policy will — under certain conditions — stimulate short-term activity. In all cases, it will be negative on real wages. We are still studying the interactions between climate policy and traditional macro economic policies of demand (budgetary or monetary stimulus) and off (reduction in social security contributions). The multipliers of these policies are influenced by the existence of a climate policy and divide according to the instrument chosen (tax or permit). We show the conditions under which a reform combining tighter climate policy and lower social contributions on labour can lead to a double dividend (reduction of the carbon footprint, reduction of unemployment), without penalising workers' actual wages. However, such a policy has uncertain effects on the government balance. ; Nous introduisons le concept d'empreinte carbone dans un mod èle o ffre globale et demande globale avec formation imparfaitement concurrentielle des prix et salaires et en examinons les propriétés de l' équilibre en présence d'une politique climatique. Nous étudions deux instruments possibles de cette politique, une taxe carbone ou un quota de permis de pollution. Nous montrons qu' a court terme la politique climatique (ou son durcissement) constitue à la fois un choc d'off re globale négatif et un choc de demande globale positif. Elle provoque donc des effets inflationnistes mais a un impact ...

The increasingly contribution of local communities to fund new high speed railway infrastructures generates expectations about immediate results of their investment in the form of economic benefits for their territories. In this thesis, we offer an empirical evaluation of local economic benefits in the short and medium term of major transport infrastructures constructions based on the South Europe Atlantic high-speed rail line case study. Based on original data and regional growth theory, we model the short term economic impact of the rail line construction on Aquitaine, Centre and Poitou-Charentes regions. We complete this short-term approach by analysing the future of constructor's former employees and the path of local suppliers and subcontractors. We show that during a period of high unemployment and low business activity, major transport infrastructures constructions have mainly short-term economic impact. The individual's risk of unemployment after the construction is high for former employees even if local policies are implemented. With regard to local business, the end of the construction leads to the return to a normal level of activity, below their productive capacities. ; De plus en plus mises à contribution pour financer les nouvelles infrastructures ferroviaires à grande vitesse, les collectivités locales françaises attendent des effets immédiats de leur investissement sous la forme de retombées économiques de la construction pour les territoires qu'elles administrent. Dans cette thèse, nous proposons une démarche empirique d'évaluation des retombées économiques locales de court terme et de moyen terme des grands chantiers d'infrastructures de transport à partir du cas de la Ligne à Grande Vitesse Sud Europe Atlantique (LGV SEA). A partir de données originales et de la théorie de la croissance régionale, nous modélisons l'impact économique de court terme de la construction de la ligne sur les régions Aquitaine, Centre et Poitou-Charentes. Nous complétons cette approche court-termiste en étudiant le devenir des ex-personnels locaux du constructeur et la trajectoire des sous-traitants et fournisseurs locaux. Nous montrons qu'en période de fort taux de chômage et de faible activité des entreprises, les grands chantiers d'infrastructure de transport ont un impact économique essentiellement court-termiste. Les individus ont alors une forte probabilité de se retrouver à nouveau au chômage après leur mission, quand bien même des politiques d'accompagnement sont mises en œuvre. Pour les entreprises locales, la fin du chantier marque le retour à un niveau d'activité conforme à la dynamique nationale, soit en-deçà bien souvent de leurs capacités productives.

Abstract: This thesis deals with the practices of assigning detainees inside short-term prisons. Our findings are based on an ethnographic survey in men's prisons. We examine the ways in which order is produced through observing prison warders' practices – ways in which prisoners are classified, categorized, assigned and monitored. The analysis takes also into account the observed practices from the inmates' perspective. By combining the study of the modes of identifying inmates with how the detention sectors are organized, this study wants to show that space management also shapes individual "careers" within the institution.To this end, it analyses the ways in which the prison order is produced in relation to its external environment, and in particular the prisoners' territories of origin.Three approaches are put to the test: one focuses on the study of the arrivals' quarters; another one revolves around the assignment practices as they are implemented and perceived; the third one eventually looks at the implementation of prison intelligence. These entry points make it possible to grasp the way in which prison practices and categories filter, i.e. select, information on the external environment of the institution but also on the trajectory of prisoners. The reconfiguration of surveillance practices in the light of contemporary reforms of penal confinement will therefore be examined from this perspective. The material used in this study is the result of a nine-month ethnographic survey in two short-term prisons in different French regions. It combines the observation of professional practices in detention and the role of professionals in assignment commissions. It is also based on semi-directive interviews conducted with detainees, supervisory and management staff. ; Résumé : Cette thèse porte sur les pratiques d'affectation des détenus à l'intérieur des maisons d'arrêt. À partir d'une enquête ethnographique dans deux établissements pour hommes, elle interroge les modalités de production de l'ordre à l'appui de ...