Sensitivity analysis for the outages of nuclear power plants

International audienceNuclear power plants must be regularly shut down in order to perform refueling and maintenance operations. The scheduling of the outages is the first problem to be solved in electricity production management. It is a hard combinatorial problem for which an exact solving is impossible. Our approach consists in modelling the problem by a two-level problem. First, we fix a feasible schedule of the dates of the outages. Then, we solve a low-level problem of optimization of elecricity production, by respecting the initial planning. In our model, the low-level problem is a deterministic convex optimal control problem. Given the set of solutions and Lagrange multipliers of the low-level problem, we can perform a sensitivity analysis with respect to dates of the outages. The approximation of the value function which is obtained could be used for the optimization of the schedule with a local search algorithm.Les centrales nucléaires doivent être régulièrement arrêtées afin de réaliser des opérations de maintenance et de rechargement en combustible nucléaire. La planification de ces arrêts constitue le premier problème à résoudre en gestion de la production d'électricité. C'est un problème combinatoire difficile qui ne peut être résolu exactement. Notre approche consiste à modéliser ce problème par un problème à deux niveaux. Tout d'abord, nous fixons un calendrier admissible des dates des arrêts des centrales. Puis, nous résolvons un sous-problème de production d'électricité, en respectant le calendrier initial. Dans notre modèle, ce sous-problème est un problème de contrôle optimal déterministe et convexe. Etant donnés les solutions et multiplicateurs de Lagrange du sous-problème, nous pouvons réaliser une analyse de sensibilité par rapport aux dates des arrêts. L'approximation de la fonction valeur que nous obtenons devrait permettre de mettre en place un algorithme de recherche locale pour l'optimisation de ces dates d'arrêts

Semidefinite Programming. methods and algorithms for energy management

La présente thèse a pour objet d explorer les potentialités d une méthode prometteuse de l optimisation conique, la programmation semi-définie positive (SDP), pour les problèmes de management d énergie, à savoir relatifs à la satisfaction des équilibres offre-demande électrique et gazier.Nos travaux se déclinent selon deux axes. Tout d abord nous nous intéressons à l utilisation de la SDP pour produire des relaxations de problèmes combinatoires et quadratiques. Si une relaxation SDP dite standard peut être élaborée très simplement, il est généralement souhaitable de la renforcer par des coupes, pouvant être déterminées par l'étude de la structure du problème ou à l'aide de méthodes plus systématiques. Nous mettons en œuvre ces deux approches sur différentes modélisations du problème de planification des arrêts nucléaires, réputé pour sa difficulté combinatoire. Nous terminons sur ce sujet par une expérimentation de la hiérarchie de Lasserre, donnant lieu à une suite de SDP dont la valeur optimale tend vers la solution du problème initial.Le second axe de la thèse porte sur l'application de la SDP à la prise en compte de l'incertitude. Nous mettons en œuvre une approche originale dénommée optimisation distributionnellement robuste , pouvant être vue comme un compromis entre optimisation stochastique et optimisation robuste et menant à des approximations sous forme de SDP. Nous nous appliquons à estimer l'apport de cette approche sur un problème d'équilibre offre-demande avec incertitude. Puis, nous présentons une relaxation SDP pour les problèmes MISOCP. Cette relaxation se révèle être de très bonne qualité, tout en ne nécessitant qu un temps de calcul raisonnable. La SDP se confirme donc être une méthode d optimisation prometteuse qui offre de nombreuses opportunités d'innovation en management d énergie.The present thesis aims at exploring the potentialities of a powerful optimization technique, namely Semidefinite Programming, for addressing some difficult problems of energy management. We pursue two main objectives. The first one consists of using SDP to provide tight relaxations of combinatorial and quadratic problems. A first relaxation, called standard can be derived in a generic way but it is generally desirable to reinforce them, by means of tailor-made tools or in a systematic fashion. These two approaches are implemented on different models of the Nuclear Outages Scheduling Problem, a famous combinatorial problem. We conclude this topic by experimenting the Lasserre's hierarchy on this problem, leading to a sequence of semidefinite relaxations whose optimal values tends to the optimal value of the initial problem.The second objective deals with the use of SDP for the treatment of uncertainty. We investigate an original approach called distributionnally robust optimization , that can be seen as a compromise between stochastic and robust optimization and admits approximations under the form of a SDP. We compare the benefits of this method w.r.t classical approaches on a demand/supply equilibrium problem. Finally, we propose a scheme for deriving SDP relaxations of MISOCP and we report promising computational results indicating that the semidefinite relaxation improves significantly the continuous relaxation, while requiring a reasonable computational effort.SDP therefore proves to be a promising optimization method that offers great opportunities for innovation in energy management.PARIS11-SCD-Bib. électronique (914719901) / SudocSudocFranceF

Optimization Methods Applied to Power Systems Ⅱ

Electrical power systems are complex networks that include a set of electrical components that allow distributing the electricity generated in the conventional and renewable power plants to distribution systems so it can be received by final consumers (businesses and homes). In practice, power system management requires solving different design, operation, and control problems. Bearing in mind that computers are used to solve these complex optimization problems, this book includes some recent contributions to this field that cover a large variety of problems. More specifically, the book includes contributions about topics such as controllers for the frequency response of microgrids, post-contingency overflow analysis, line overloads after line and generation contingences, power quality disturbances, earthing system touch voltages, security-constrained optimal power flow, voltage regulation planning, intermittent generation in power systems, location of partial discharge source in gas-insulated switchgear, electric vehicle charging stations, optimal power flow with photovoltaic generation, hydroelectric plant location selection, cold-thermal-electric integrated energy systems, high-efficiency resonant devices for microwave power generation, security-constrained unit commitment, and economic dispatch problems

Integrating Renewable Energy in Pacific Island Countries

The purpose of this thesis is to investigate the entry of renewable energy technologies into Pacific Islands' electricity markets, with particular focus on a new technology: the Pelamis, a wave energy converter. Pacific Islands are endowed with various types of renewable energy resources, yet they remain highly dependent on expensive fuel imports for their energy requirements, using little renewable energy. This paradox is investigated by studying the characteristics of Pacific Islands' electricity markets, including a case study on the entry of a new renewable energy technology, the Pelamis, into the electricity market of Hawaii. The integration of renewable energy technologies into Pacific Islands' electricity systems is then analysed from the point of view of an energy planner. The recent application of portfolio analysis to energy planning has provided a new framework to evaluate the different electricity generating options available to energy planners. Taking both the generating cost and financial risk of each technology into account, portfolio theory has been applied to various European countries, by comparing actual generation portfolios to an efficient frontier showing the trade-off between energy security and the cost of electricity generation. This framework has clear relevance to Pacific Island Countries. However, the characteristics inherent to Pacific Island Countries have important implications on the operation of their electricity systems, which are not necessarily taken into account in portfolio analysis. In particular, geographical isolation inhibits these countries from connecting to larger intercontinental grids, which emphasizes the importance of reliability of supply. This thesis presents a mathematical model which establishes a method for computing an optimal intertemporal path for introducing renewable energy into a pre-existing electricity system. The model explicitly allows for the cost of maintaining reliability of supply as intermittent generators are integrated. The framework also incorporates concepts from Integrated Resource Planning and portfolio analysis. Finally, policies for accelerating renewable energy development are reviewed, and a discussion is provided on the policies which are likely to be most suitable to Pacific Islands. One of the main conclusions of this thesis is that the amount of backup capacity for renewable energy can be optimally minimized by diversifying the mix of renewable energy resources in each island. In practice, this would require studying the complementarities and loading curves of the various renewable resources available, and comparing their total potential production, and the variability of this production, to electricity demand. This would allow energy planners to model the inclusion of a maximum amount of renewable energy using a minimum of backup capacity to maintain system reliability, potentially leading to a more efficient implementation and formulation of policies aimed at developing renewable energy generation in Pacific Islands

Intelligent energy management system - techniques and methods

ABSTRACT Our environment is an asset to be managed carefully and is not an expendable resource to be taken for granted. The main original contribution of this thesis is in formulating intelligent techniques and simulating case studies to demonstrate the significance of the present approach for achieving a low carbon economy. Energy boosts crop production, drives industry and increases employment. Wise energy use is the first step to ensuring sustainable energy for present and future generations. Energy services are essential for meeting internationally agreed development goals. Energy management system lies at the heart of all infrastructures from communications, economy, and society’s transportation to the society. This has made the system more complex and more interdependent. The increasing number of disturbances occurring in the system has raised the priority of energy management system infrastructure which has been improved with the aid of technology and investment; suitable methods have been presented to optimize the system in this thesis. Since the current system is facing various problems from increasing disturbances, the system is operating on the limit, aging equipments, load change etc, therefore an improvement is essential to minimize these problems. To enhance the current system and resolve the issues that it is facing, smart grid has been proposed as a solution to resolve power problems and to prevent future failures. This thesis argues that smart grid consists of computational intelligence and smart meters to improve the reliability, stability and security of power. In comparison with the current system, it is more intelligent, reliable, stable and secure, and will reduce the number of blackouts and other failures that occur on the power grid system. Also, the thesis has reported that smart metering is technically feasible to improve energy efficiency. In the thesis, a new technique using wavelet transforms, floating point genetic algorithm and artificial neural network based hybrid model for gaining accurate prediction of short-term load forecast has been developed. Adopting the new model is more accuracy than radial basis function network. Actual data has been used to test the proposed new method and it has been demonstrated that this integrated intelligent technique is very effective for the load forecast. Choosing the appropriate algorithm is important to implement the optimization during the daily task in the power system. The potential for application of swarm intelligence to Optimal Reactive Power Dispatch (ORPD) has been shown in this thesis. After making the comparison of the results derived from swarm intelligence, improved genetic algorithm and a conventional gradient-based optimization method, it was concluded that swam intelligence is better in terms of performance and precision in solving optimal reactive power dispatch problems

Intelligent energy management system : techniques and methods

ABSTRACT Our environment is an asset to be managed carefully and is not an expendable resource to be taken for granted. The main original contribution of this thesis is in formulating intelligent techniques and simulating case studies to demonstrate the significance of the present approach for achieving a low carbon economy. Energy boosts crop production, drives industry and increases employment. Wise energy use is the first step to ensuring sustainable energy for present and future generations. Energy services are essential for meeting internationally agreed development goals. Energy management system lies at the heart of all infrastructures from communications, economy, and society’s transportation to the society. This has made the system more complex and more interdependent. The increasing number of disturbances occurring in the system has raised the priority of energy management system infrastructure which has been improved with the aid of technology and investment; suitable methods have been presented to optimize the system in this thesis. Since the current system is facing various problems from increasing disturbances, the system is operating on the limit, aging equipments, load change etc, therefore an improvement is essential to minimize these problems. To enhance the current system and resolve the issues that it is facing, smart grid has been proposed as a solution to resolve power problems and to prevent future failures. This thesis argues that smart grid consists of computational intelligence and smart meters to improve the reliability, stability and security of power. In comparison with the current system, it is more intelligent, reliable, stable and secure, and will reduce the number of blackouts and other failures that occur on the power grid system. Also, the thesis has reported that smart metering is technically feasible to improve energy efficiency. In the thesis, a new technique using wavelet transforms, floating point genetic algorithm and artificial neural network based hybrid model for gaining accurate prediction of short-term load forecast has been developed. Adopting the new model is more accuracy than radial basis function network. Actual data has been used to test the proposed new method and it has been demonstrated that this integrated intelligent technique is very effective for the load forecast. Choosing the appropriate algorithm is important to implement the optimization during the daily task in the power system. The potential for application of swarm intelligence to Optimal Reactive Power Dispatch (ORPD) has been shown in this thesis. After making the comparison of the results derived from swarm intelligence, improved genetic algorithm and a conventional gradient-based optimization method, it was concluded that swam intelligence is better in terms of performance and precision in solving optimal reactive power dispatch problems.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Three essays on the economics of renewable energy in small island economies

In chapter 1, we introduce mechanism and present results of an integrated investment appraisal of an onshore wind farm for electricity generation in Cape-Verde that is owned and operated by a private investor. From the perspective of the electric utility and the economy, the results of such an ex-ante financial and economic appraisal of wind electricity generation depends critically on one’s view of the expected long-term level of future fossil fuel prices, negotiations of the power purchase agreement (PPA) price and wind capacity factor. In Chapter 2, we investigate the impacts of wind and solar renewable power sources on both electricity generation and planning by employing and applying a cost minimization model in Cyprus. The cost minimization model demonstrates that the use of wind alone and mix of wind and solar power in an electricity generation mix reduces the overall cost of the system. Due to high cost of electricity generation from fuel oil in Cyprus, we conclude that shift toward wind and solar mix of energy sources in Cyprus will have significant impact by means of cost reduction. Therefore, integrating these renewables will essentially contribute to the welfare of Cypriot consumers alongside its environmental and health benefits associated in them. In Chapter 3, we study the impacts of implementing real-time electricity pricing (RTP) in the Cypriot electricity market with and without wind/solar capacities. We use a merit order stack approach to generation investment and operation decisions. Empirical results show that dynamic pricing will increase generation capacity utilization by means of reduction in equilibrium installed capacity reduction and increase in load factors of off-peak plants. These savings are larger at higher demand elasticities. The emissions from electricity generation will potentially increase resulting from increased energy consumption, however. Because wind (solar) availability comes mostly during low (high) demand hours when relatively cleaner (dirtier) plants operate in the system, we find that there is considerable potential for capital cost savings and emission savings from smart metering even with only a small consumer response and at moderate participation in the programme. At the current costs of solar, investing in wind alone will however yield higher bill savings

Portuguese transmission grid incidents risk assessment

Documento confidencial. Não pode ser disponibilizado para consultaTese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201