Since the last United Nations Climate Change Conference in 2015 in Paris (the COP 21), world leaders acknowledged climate change. There is no need any more to justify the switch from fossil fuel-based to renewable energy sources. Nevertheless, this transition is far from being straightforward. Besides technologies that are not yet mature -- or at least not always financially viable in today's economy -- the power grid is currently not ready for a rapid and massive integration of renewable energy sources. A main challenge for the power grid is the inadequacy between electric production and consumption that will rise along with the integration of such sources. Indeed, due to their dependence on weather, renewable energy sources are intermittent and difficult to forecast with today's tools. As a commodity, electricity is a quite distinct good for which there must be perfect adequacy of production and consumption at all time and characterized by a very inelastic demand. High shares of renewable energy sources lead to high price volatility and a higher risk to jeopardize the security of supply. Additionally, the switch to renewable energy sources will lead to an electrification of loads and transportation, and thus the emergence of new higher-consumption loads such as electric vehicles and heat pumps. These new and higher-consumption loads, combined with the population growth, will cause over-rated power load increases with less predictable load patterns in the future.This work focuses on issues specific to the distribution power grid in the context of the current energy transition. Traditional low-voltage grids are perhaps the most passive circuits in power grids. Indeed, they are designed primarily using a fit and forget approach where power flows go from the distribution transformer to the consumers and no element has to be operated or regularly managed. In fact, low-voltage networks completely lack observability due to very low monitoring. The distribution grid will especially undergo drastic changes from this energy transition. Distributed sources and new high-consumption -- and uncoordinated -- loads result in new power flow patterns, as well as exacerbated evening peaks for which it is not designed. The consequences are power overloads and voltage imbalances that deteriorate grid components, such as a main asset like the medium-to-low voltage transformer. Additionally, the distribution grid is characterized by end-users that pay a price for electricity that does not reflect the grid situation -- that is, mostly constant over a year -- and allow little to no actions on their consumption.These issues have motivated authorities to propose a global approach to ensure security of electricity supply at short and medium-term. The latter requires, among others, the development of demand response programs that encourage users to take advantage of load flexibility. First, we propose adequate electricity pricing structures that will allow users to unlock the potential of such demand response programs; namely, dynamic pricings combined with a prosumer structure. Second, we propose a fast and robust two-level optimization, formulated as a mixed-integer linear program, that coordinates flexible loads. We focus on two types of loads; electric vehicles and heat pumps, in an environment with solar PV panels. The lower level aims at minimizing individual electricity bills while, at the second level, we optimize the power load curve, either to maximize self-consumption, or to smoothen the total power load of the transformer. We propose a parametric study on the trade-off between only minimizing the individual bills versus only optimizing power load curves, which have proven to be antagonist objectives. Additionally, we assess the impact of the rising share of flexible loads and renewable energy sources for scenarios from today until 2050. A macro-analysis of the results allows us to assess the benefits of load flexibility for every actor of the distribution grid, and depending on the choice of a pricing structure. Our optimization has proved to prevent evening peaks, which increases the lifetime of the distribution transformer by up to 200%, while individual earnings up to 25% can be made using adequate pricings. Consequently, the optimization significantly increases the power demand elasticity and increases the overall welfare by 10%, allowing the high shares of renewable energy sources that are foreseen. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

Les défis environnementaux et l’augmentation de la population viennent en preuve de l’importance de réfléchir à d’autres moyens de production tout en maintenant la sécurité et la fiabilité du système électrique. La sûreté du système électrique exige à tout moment que la production soit égale à la demande des consommateurs, pour ça, différentes solutions sont déjà mises en place, ces solutions consistent à mettre en marche des moyens de pointes couteux et polluants pendant les périodes de pointes, mais comme les moyens de production son insuffisants et vue la difficulté d’exploitation de nouveaux moyens de production, une nouvelle réflexion sur la gestion de la demande est apparue; celle-ci se base sur la possibilité à gérer la demande du consommateur final au lieu de la satisfaire.L’objectif de la thèse est d’étudier la possibilité à rendre des services au système électrique en appliquant des actions de contrôle dites de DR (Demand Response), sur différents types de charges électriques. Ces actions de DR représentent des interruptions partielles appliquées sur les charges électriques de type thermique. Notre choix s’est basé sur ces types de charges parce que celles-ci emmagasinent de la chaleur respectivement dans l’air et dans l’eau; qui peut être restituée pendant la période de contrôle ou d’interruption. Néanmoins, il existe un effet négatif qui suit le contrôle de ces charges car l’énergie effacée de ces charges est reportée à l’instant de reconnexion de celles-ci; ce report prend la forme d’un pic de consommation nommé CLPU (Cold Load Pick-Up) et qui apparait au moment de la reconnexion. Le CLPU représente un problème qui doit être géré, et sa magnitude dépend des types d’actions de contrôle qu’on veut implanter et aussi des conditions du système électrique (contingence, défaillance d’une unité de production ou besoin de réserve de puissance). Pendant la thèse, le CLPU est contrôlé et optimisé ainsi que la puissance effacée. Un cas d’étude est présenté sur la contribution des actions de gestion de la demande à l‘ajustement entre la demande et la production et l’effet généré sur le réglage secondaire de fréquence. / Environmental challenges and the increasing in electric demand show the importance of considering other form of production while maintaining the safety and reliability of the electrical system. The electrical power systems stability lays on a fundamental constraint: supply and demand must be equal at each instant, so, different solutions are already in place, these solutions include controlling generators’ production during peak periods. But, power units (mainly nuclear, thermal, hydro) capacities are not always sufficient and flexible to follow the demand variations during these periods; an alternative solution to this insufficiency is to make the demand following the electrical power generation by providing bulks of electrical power to the power system by curtailing consumer’s electric load consumption. Such a solution that represents a new organization in the power system industry can be done by Demand Side Management (DSM) actions. The aim of the thesis is to study the possibility to offer services to the electrical system by applying control actions called DR (Demand Response) on different types of electric loads. These DR actions represent partial interruptions of electrical loads’ consumption and especially thermal loads’ consumption.Our choice was based on the thermal electric loads because they store heat respectively in air and water, which can be restored during the control period or interruption. However, there is a negative effect that follows the control of these type of loads because the reduced energy during curtailment period is deferred at the time of reconnection, this deferred power takes the form of a power peak named CLPU (Cold Load Pick-Up), which appears at the time of reconnection. The CLPU is a problem that must be managed, and its magnitude depends on the type of control actions and on the electric system conditions (ie: contingency or failure of a generating unit). In the thesis, the CLPU is controlled and optimized as well as the load reduction during curtailment period. The contribution of control actions in balancing mechanisms and the effect produced on the secondary control of frequency are analyzed.

Made available in DSpace on 2017-07-10T17:11:46Z (GMT). No. of bitstreams: 1 DISSERTACAO ARTUR CARRIJO2.pdf: 2100488 bytes, checksum: 46e631e94e2bb6d4c69d8d2891f6e200 (MD5) Previous issue date: 2013-12-18 / The electricity market has many participants performing various roles. In the context of Smart Grids, it expands the number of participating agents and, consequently, the number, the competition and complexity of the interactions between them. The competition allows consumersto discover and explore energy sources of low cost but requires the consumer other interactions beyond the traditional relationship with the distribution company (distco). With the redefinition of the role of the consumer as a result of his active participation in the balance between supply and demand of energy, it becomes necessary to identify their interactions with the other participants, tasks, systems, subsystems and functions important to actively contribute to this balance. These interactions, called interfaces, are characterized by information that actors communicate itself to perform its functions of information collection and control tasks related to market equilibrium. The determination of these interfaces is not a trivial task because of the various alternatives for integration of the demand side. Different types and combinations of interactions between the supplier and its customers are possible. In this work will be used as a basis for discussion a concept of balance between generation and demand called homeostatic control, initially designed for a scenario of a vertically integrated monopoly. It will be studied the interactions of the consumer using the concept of homeostatic control expanded to consider the functions of demand control and integration of distributed generation and a market model that allows for consumer empowerment and within the paradigm of smart grids. / O mercado de energia elétrica possui diversos participantes exercendo vários papéis. No contexto das redes elétricas inteligentes, amplia-se o número de agentes participantes e, consequentemente, o número, a competição e a complexidade das interações entre eles. A competição permite aos consumidores descobrir e explorar fontes de baixo custo, mas requer do consumidor outras interações além da tradicional relação com a empresa distribuidora. Com a redefinição do papel do consumidor, resultado da participação ativa no processo de equilíbrio entre suprimento e demanda de energia, torna-se necessário identificar suas interações com os demais participantes, tarefas, sistemas, subsistemas e funções, importantes para que contribua ativamente com esse equilíbrio. Estas interações, denominadas interfaces, são caracterizadas pelas informações que os atores comunicam em si para executar suas funções de coleta de informações e tarefas de controle relacionadas ao equilíbrio do mercado. A determinação destas interfaces não é uma tarefa trivial em razão das diversas alternativas de integração do lado da demanda. São possíveis diferentes tipos e combinações de interações entre o fornecedor e seus clientes. Neste trabalho será utilizado como base de discussão um conceito de equilíbrio entre geração e demanda denominado controle homeostático, desenhado inicialmente para um cenário de monopólio verticalmente integrado. Serão estudadas as interações do consumidor utilizando o conceito de controle homeostático ampliado para considerar as funções de controle da demanda e a integração da geração distribuída em um modelo de mercado que permite o empoderamento do consumidor dentro do paradigma das redes elétricas inteligentes.

<p>Sve češćom upotrebom cloud okruženja dolazi do potrebe da se postojeća softverska rešenja migriraju. Metodologija za migraciju na cloud postoji više, gde se u finalnim fazama planiraju modifikacije nad arhitekturom softvera tako da se iskoriste prednosti cloud sistema. Za ekonomsku efikasnost usled uštede resursa je neophodna višeorganizacijska osobina. Svrha ovog istraživanja je da pojasni višeorganizacijsko svojstvo i da predloži rešenje za migraciju postojećih softvera na višeorganizacijski SaaS ali sa što manje neophodnih modifikacija ciljnog softvera. S toga je predloženo rešenje platforma koja omogućuje lakšu migraciju. Nakon faze istraživanja i sagledavanja domena pametnih elektroenergetskih mreža, kreiran je prototip predloženog rešenja kao i niz eksperimenata u skladu sa definisanim naučnim pitanjima. Eksperimenti su izvršeni u privatnom cloud okruženju. Hipoteze su adresirane kroz viziju primene rešenja na NDMS (Napredni distributivni menadžment sistem) u slučaju šest organizacija, a doneti su sledeći zaključci: višeorganizacijskim modelom se ostvaruju uštede u resursima od 32%, za tri reda veličine veća visoka dostupnost, ali uz usporenja do 20 milisekundi po svakom servisnom zahtevu. Takođe, aplikativni model učesnika modernih PaaS usluga nije primeren gde je sinhronizam zahtevan, niti u slučajevima gde se očekuju odgovori nad skupom učesnika u realnom vremenu. Istraživanje ukazuje na mogućnost primene višeorganizacijskog modela čak i u slučaju kompleksnih rešenja kakva se sreću u domenu pametnih elektroenergetskih mreža, a akademskom validacijom potvrđuju način implementacije važnog finalnog koraka u procesu migracije softvera na cloud bazirani SaaS.</p> / <p>Progressive cloud adoption requires migration of existing software solutions. Today, many cloud adoption methodologies exist. Usually, the final phase in cloud adoption include software architecture modifications to make the most of the benefits of cloud computing, like multi-tenancy which enables economic efficiency. The aim of this research is to explain the multi-tenancy and to provide a solution for migration of existing software to multi-tenant SaaS while modifying the target software as little as possible. Therefore, the research proposes a platform that enables easier cloud adoption. After the research phase focused on a smart grid domain, the prototype was created with experiments targeting formulated research questions. The experiments were conducted in a private cloud environment. Research hypotheses were analyzed using hypothetical multi-tenant ADMS (Advanced Distribution Management System) in case of six tenants, with the following conclusions: multi-tenancy saves 32% of resources, it provides three orders of magnitude higher availability, but affects performances by introducing a delay of up to 20 milliseconds per service request. Also, reliable actors programing model used in modern PaaS services is not suitable in use cases with needs for synchronous behavior, nor in in use cases where querying a set of actors is needed in real time. The research demonstrates feasibility of applying multi-tenancy even in cases of complex software solutions like the ones in the smart grid domain. The proposed solution is academically validated and it can be used as a final important step in migration of existing software to cloud based multi-tenant SaaS.</p>

Abstract The global energy system is undergoing a slow but massive change, initiated by environmental concerns but it is increasingly driven also by the zero-marginal cost of renewable energy. This change includes an increase in the effort to make the electric power system the main transport path for energy in the future. A massive research and development effort has henceforth been put into modernizing the electricity grid towards a so-called Smart Grid, by combining the power grid with communication networks and automation, as well as modernized market systems and structures. This work contributes to this process by introducing two unique models. The first provides a tool for better understanding the impact of combined infrastructure networks with a simple yet complex model of a combined energy, communication and decision model. The second model provides a detailed agent-based environment of an electricity market, supporting various independent entities inside the market, as well as a high time resolution and the often-neglected aspect of coupled market stages. That is, all mis-predictions of the first market stage (day-ahead) have to be settled at the second (balancing) stage. Both models are then used to assess the problem of demand side management, in which the traditional practice of power production being adjusted to the demand is at least partially dropped and flexibility in the demand is used to match the supply – as such technologies are deemed crucial to integrate the unsteady supply from renewable resources, like wind and solar power. We find that complicated scaling effects can be found even in the simplified model, hinting at insufficient consideration of the complexities involved in the real world. We then go to show such unfavorable scaling effects also exist in the current market environment as modeled in our second model. Finally, we show how to circumvent these problems within the current environment as well as introduce a framework to analyze cyber-physical systems and better handle their complexity. / Tiivistelmä Globaali energiajärjestelmä on hitaan, mutta massiivisen muutoksen edessä. Tämän muutostarpeen on käynnistänyt ympäristöämme koskevat huolet, mutta lisääntyvässä määrin tähän vaikuttaa nykyään uusiutuvan energian marginaalikustannusten nollataso. Tähän muutokseen liittyy selkeä sähköverkkojen roolin korostuminen, ja pyrkimyksenä näyttää olevan muutos, jossa sähköverkot siirtävät suurimman osan käyttämästämme energiasta. Tämän seurauksena on käynnistetty merkittäviä tutkimus-ja tuotekehityspanostuksia, joiden tavoitteena on nykyaikaistaa sähköverkot älysähköverkoiksi. Älysähköverkoissa yhdistyvät sähköverkkoon integroidut tietoliikenneverkot ja automaatio sekä modernit sähkömarkkinajärjestelmät ja -rakenteet. Tämä työ tuottaa lisää ymmärrystä uudistumisprosessiin tuottamalla kaksi uutta malliratkaisua. Ensimmäisessä mallissa kehitetään työkalu, jonka avulla pystytään paremmin ymmärtämään toisiinsa yhdistettyjen infrastruktuuriverkkojen toimintaa yksinkertaisella, mutta kompleksisella mallilla, jossa energia- ja tietoliikenneverkot sekä tarvittava päätöksenteko yhdistetään. Toinen malli tuottaa yksityiskohtaisen agenttipohjaisen ympäristön sähkömarkkinasta. Malli tukee erilaisten itsenäisten sähkömarkkinaosapuolten mallintamista korkealla aikaresoluutiolla ja erityisesti usein huomiotta jätettyjen toisiinsa kytkeytyvien eri markkinavaiheiden mallintamista. Malli antaa eväitä vastata kysymykseen, miten ensimmäisessä markkinavaiheessa (vuorokausimarkkina) syntyvä ero tuotannon ja kulutuksen välillä tasapainotetaan toisessa markkinavaiheessa (tasapainotusmarkkina). Kumpaakin luotua mallia hyödynnetään arvioitaessa kulutushallintaa, jossa sähköverkkojen perinteisestä tuotannon ja kulutuksen tasapainosta ainakin osittain luovutaan ja kysyntä- eli kulutusjoustoa käytetään tasaamaan kulutus tuotannon suuruiseksi. Tämänkaltaiset mekanismit ovat oleellisia ja kriittisiä, kun sähköverkkoon liitetään suuria määriä vaihtelevatuottoista uusiutuvaa energiaa, kuten aurinko- ja tuulienergiaa. Tutkimuksessa huomasimme merkittäviä ja monimutkaisia skaalautuvuusilmiöitä, jotka kertovat, että sähköverkkojen tutkimuksessa reaalimaailman kompleksisuuden huomioiminen on ollut riittämätöntä. Sähkömarkkinamallia hyödyntämällä huomasimme vastaavia epätoivottuja skaalausilmiöitä esiintyvän myös nykyisessä sähkömarkkinassa. Erityisesti loimme keinoja, joilla skaalausilmiöistä on mahdollista päästä eroon nykyistä sähkömarkkinarakennetta käytettäessä. Tässä työssä luotuja malleja ja niiden viitekehystä hyödyntämällä pystymme paremmin analysoimaan kyberfysikaalisia järjestelmiä ja hallitsemaan niiden kompleksisuutta.

L'accumulation de gaz à effet de serre dans l'atmosphère, produite par des activités anthropiques notamment dans le secteur de l’énergie est une des causes principales du changement climatique. Par conséquent, réaliser une véritable transition énergétique par une décarbonisation des réseaux électriques est devenue un besoin urgent pour atténuer les effets du réchauffement climatique. Dans cette transition, l’introduction des énergies renouvelables a été initiée depuis plusieurs années, principalement en raison de la participation de nouveaux acteurs à ce marché. Aujourd’hui, l’un des grands défis est de maintenir l’équilibre et la sécurité du réseau électrique en tenant compte de la diversité et de la variabilité des ressources énergétiques renouvelables connectées au réseau. L’une des approches permettant de régler ce problème et d’accroître la flexibilité du réseau électrique par ce que l’on désigne comme la Réponse à la Demande (RD). Cette thèse examine précisément ces nouvelles approches et montre l’intérêt de repenser les relations entre les différentes partie-prenantes pour faire émerger des nouveaux modèles d’affaires afin de déployer de nouvelles innovations au service de la transition énergétique. La méthodologie de recherche mise en œuvre de cette thèse consiste en une revue systématique de la littérature et une étude des données empiriques de 15 jeunes entreprises européennes du secteur de l’énergie. En conséquence, la thèse fournit à la communauté de la recherche (1) une méthode de classification pour catégoriser les différents modèles d’affaires de l’énergie (MAEs) et présente une première synthèse des MAE identifiés dans la littérature; (2) un cadre d’analyse des start-ups dans le secteur de l’énergie, complété par l’analyse de 15 start-ups de ce domaine; (3) un outil conceptuel pour l'innovation en matière de RD, appelé Canevas de Modèle d'Affaires de Réponse de Demande (CMARD), qui comprend 12 éléments interreliés. Ce canevas vise à évaluer les activités des offres de RD et à soutenir l'émergence de nouveau modèles d'affaires de RD. Ces résultats permettent de proposer un cadre analytique simplifié des pratiques existantes et peuvent également aider des entrepreneurs ou décideurs à explorer et concevoir de nouvelles offres sur le marché de la réponse à la demande. / The accumulation of greenhouse gases in the atmosphere, produced by human activities in the energy sector is one of the main causes of climate change. Therefore, the decarbonization of power systems has become an urgent need the mitigate to the effects of climate change and achieve the energy transition. The share of renewable energy technologies has been increasing mainly due to the participation of new market players. Today, however, one of the great challenges is to maintain the electricity system’s balance and security despite the large amount of renewable energy resources connected to the grid. One of the approaches to deal with this issue and to increase power system flexibility is the Demand Response (DR). Moreover, scholars argue that business model innovation can act as an energy transition driver. This thesis examines business model innovations in the context of the energy transition by investigating emerging start-up business models. The implemented research methodology in this thesis consists of a systematic literature review and an investigation of empirical data of 15 European energy start-ups. As a result, the thesis provides the research community with (1) a grouping method to classify different Energy Business Models (EBMs) and an initial synthesis of the EBMs identified in the literature; (2) a framework to analyse start-ups in the energy sector, completed with the analysis of 15 energy start-ups; (3) and a conceptual tool for DR innovation, named as the Demand Response Business Model Canvas (DRBMC), which includes 12 interrelated elements. This canvas aims at evaluating DR activities and supporting the emergence of new DR business models. These results can also help entrepreneurs explore new demand response market opportunities, enabling a better understanding and providing a simplified analytic framework of existing business practices.

Cette thèse examine comment répondent des consommateurs aux mécanismes visant à réduire leur consommation d'énergie. Ce besoin de réduction découle de la nécessité d'atteindre les objectifs de réduction d'émissions de gaz à effet de serre, d'augmenter la production d'énergie à partir d'énergie renouvelables et de réaliser des économies d'énergie. Ces objectifs exigent que la demande résidentielle soit plus flexible face à l'évolution de l'offre et que des économies d'énergie soient réalisées par les ménages. Le premier chapitre explore les barrières à l'acceptation et à l'adoption des compteurs intelligents et des incitations qu'ils peuvent fournir. D'importantes barrières existent et les réductions de consommation sont loin d'être réalisées. Le manque de motivation, l'incompréhension de l'information sur la consommation et la rigidité de la vie quotidienne sont les principales barrières qui limitent la réponse des ménages aux incitations fournies par les compteurs intelligents. Le deuxième chapitre analyse les résultats d'expériences de terrain et d'études pilotes portant sur les impacts des différentes incitations sur la consommation résidentielle. Les résultats montrent qu'il existe de grandes variations et qu'en moyenne, une incitation entraînera une réduction de 2% de la consommation d'énergie. Les incitations de feedback en temps réel ainsi que l'information monétaire ont le plus grand effet. Enfin, les études plus robustes font état d'effets de réduction plus faibles. Dans le troisième chapitre, un jeu expérimental de ressources communes est utilisé pour explorer les réponses individuelles aux incitations basées sur le prix et les nudges. Les individus sont encouragés à réduire leur consommation, soit par une augmentation de prix, soit par des smiley évocant leur surconsommation. Le prix est le plus efficace pour encourager le niveau cible de consommation, mais il faut plus de temps pour qu'il fasse effet. Le nudge est compris rapidement mais tend à renforcer les comportements de surconsommation. Le quatrième chapitre examine l'effet du framing sur la disposition à l'effort. Les individus doivent accomplir une tâche simple et répétitive pour laquelle ils reçoivent un paiement à la pièce sous forme d'un gain ou d'une perte. Le framing sous forme de gains et de pertes est combiné à trois structures de paiement différentes : gain fixe, gain faible ou élevé avec une probabilité égale révélée avant ou après la réalisation de l'effort. Les résultats montrent que le framing n'a aucun effet sur la réalisation de l'effort, excepté pour un contexte de gain élevé annoncé avant de fournir l'effort. / This thesis examines how consumers respond to incentives used to encourage a reduction in their energy consumption. This necessary reduction stems from the need to reduce greenhouse gas emissions, increase energy production from renewable energy sources and achieve energy savings. These objectives require that residential demand be more flexible in response to changes in supply and that energy savings be achieved by households. The first chapter explores the barriers to consumer acceptance and adoption of smart meters and the incentives that they provide. Significant barriers exist and consumption reductions are far from being achieved. Limited motivation, lack of understanding of information on consumption and the rigidity of daily life are the main barriers preventing households from acting upon the incentives delivered via smart meters. The second chapter analyses the results of field experiments and pilot studies on the impacts of different incentives on residential consumption. The results show that there are large variations and that, on average, an incentive will result in a 2% reduction in energy consumption. Real-time feedback and monetary information have the greatest effect. Finally, more robust studies report lower reduction effects. In the third chapter, a common pool resource game is used to explore individual responses to price and nudge-based incentives. Individuals are encouraged to reduce their consumption either by price increases or by smilies that reflect their overconsumption. The price is most effective at encouraging the target level of consumption but takes longer to have an effect. The nudge is quickly understood but tends to reinforce overconsumption behaviours. The fourth chapter examines the effect of framing on effort provision. Individuals are asked to complete a simple and repetitive task for which they receive a piece-rate payoff in the form of a gain or loss. Framing in the form of gains and losses is combined with three different payment structures: fixed gain, low gain or high gain with an equal probability revealed before or after the effort is made. The results show that framing has no effect on effort provision, except for a high gain context announced before making the effort.

Avec la convergence de plusieurs tendances profondes du secteur énergétique, lesréseaux électriques intelligents (smart grids) émergent comme le paradigme principal pourla modernisation des réseaux électriques. Les smart grids doivent notamment permettred’intégrer de larges proportions d’énergie renouvelable intermittente, de stockage et devéhicules électriques, ainsi que donner aux consommateurs plus de contrôle sur leur consommationénergétique. L’atteinte de ces objectifs repose sur l’adoption de nombreusestechnologies, et en particulier des technologies de l’information et de la communication.Ces changements transforment les réseaux en des systèmes de plus en plus complexes,nécessitant des outils adaptés pour modéliser, contrôler et simuler leur comportement.Dans cette thèse, l’utilisation des systèmes multi-agents (SMA) permet une approchesystémique de la gestion de l’énergie, ainsi que la définition d’architectures et d’algorithmesbénéficiant des propriétés des SMA. Cette approche permet de prendre en compte lacomplexité d’un tel système cyber-physique, en intégrant de multiples aspects commele réseau en lui-même, les infrastructures de communication, les marchés ou encore lecomportement des utilisateurs. L’approche est mise en valeur à travers deux applications.Dans une première application, un système de gestion de l’énergie pour centrales àturbines à gaz est conçu avec l’objectif de minimiser les coûts de fonctionnement et lesémissions de gaz à effet de serre pour des profils de charge variables. Un modèle de turbineà gaz basé sur des données réelles est proposé et utilisé dans un simulateur spécifiquementdéveloppé. Une métaheuristique optimise dynamiquement le dispatching entre les turbinesen fonction de leurs caractéristiques propres. Les résultats montrent que le systèmeest capable d’atteindre ses objectifs initiaux. Les besoins en puissance de calcul et encommunication sont également évalués.Avec d’autres mesures de gestion de la demande, l’effacement diffus permet de réduiretemporairement la charge électrique, par exemple dans la cas d’une congestion du réseaude transport. Dans cette seconde application, un système d’effacement diffus est proposéet utilise les ressources disponibles chez les particuliers (véhicules électriques, climatisation,chauffe-eau) pour maintenir la demande sous une valeur limite. Des aggrégateursde capacité de réduction de charge servent d’interface entre les opérateurs du réseau etun marché de l’effacement. Un simulateur est également développé pour évaluer la performancedu système. Les résultats de simulations montrent que le système réussit àatteindre ses objectifs sans compromettre la stabilité du réseau de distribution en régimecontinu. / Due to the convergence of several profound trends in the energy sector, smart gridsare emerging as the main paradigm for the modernization of the electric grid. Smartgrids hold many promises, including the ability to integrate large shares of distributedand intermittent renewable energy sources, energy storage and electric vehicles, as wellas the promise to give consumers more control on their energy consumption. Such goalsare expected to be achieved through the use of multiple technologies, and especially ofinformation and communication technologies, supported by intelligent algorithms.These changes are transforming power grids into even more complex systems, thatrequire suitable tools to model, simulate and control their behaviors. In this dissertation,properties of multi-agent systems are used to enable a new systemic approach to energymanagement, and allow for agent-based architectures and algorithms to be defined. Thisnew approach helps tackle the complexity of a cyber-physical system such as the smart gridby enabling the simultaneous consideration of multiple aspects such as power systems, thecommunication infrastructure, energy markets, and consumer behaviors. The approach istested in two applications: a “smart” energy management system for a gas turbine powerplant, and a residential demand response system.An energy management system for gas turbine power plants is designed with the objectiveto minimize operational costs and emissions, in the smart power generation paradigm.A gas turbine model based on actual data is proposed, and used to run simulations witha simulator specifically developed for this problem. A metaheuristic achieves dynamicdispatch among gas turbines according to their individual characteristics. Results showthat the system is capable of operating the system properly while reducing costs and emissions.The computing and communication requirements of the system, resulting from theselected architecture, are also evaluated.With other demand-side management techniques, demand response enables reducingload during a given duration, for example in case of a congestion on the transmissionsystem. A demand response system is proposed and relies on the use of the assets ofresidential customers to curtail and shift local loads (hybrid electric vehicles, air conditioning,and water heaters) so that the total system load remains under a given threshold.Aggregators act as interfaces between grid operators and a demand response market. Asimulator is also developed to evaluate the performance of the proposed system. Resultsshow that the system manages to maintain the total load under a threshold by usingavailable resources, without compromising the steady-state stability of the distributionsystem.

The objective of the proposed research is to analyze automated residential energy management technology using primary energy source utilization. A residential energy management system (REMS) is an amalgamation of hardware and software that performs residential energy usage monitoring, planning, and control. Primary energy source utilization quantifies power system levels impacts on power generation cost, fuel utilization, and environmental air pollution; based on power system generating constraints and electric load. Automated residential energy management technology performance is quantified through a physically-based REMS simulation. This simulation includes individual appliance operation and accounts for consumer behavior by stochastically varying appliance usage and repeating multiple simulation iterations for each simulated scenario. The effect of the automated REMS under varying levels of control will be considered. Aggregate REMS power system impacts are quantified using primary energy source utilization. This analysis uses a probabilistic economic dispatch algorithm. The economic dispatch algorithm quantifies: fuel usage and subsequent environmental air pollution (EAP) generated; based on power system generating constraints and electric load (no transmission constraints are considered). The analysis will comprehensively explore multiple residential energy management options to achieve demand response. The physically-based REMS simulation will consider the following control options: programmable thermostat, direct load control, smart appliance scheduling, and smart appliance scheduling with a stationary battery. The ability to compare multiple automated residential energy management technology options on an equal basis will guide utility technology investment strategies.

This thesis comprises three papers examining the impact of competitive pricing or competition on participants in energy markets. The scope of each paper is narrow but focused, dealing with one particular aspect of competition in each market under study. It is hoped that results from these three studies could provide valuable policy lessons to public policy makers in their task to create or maintain competition in different energy markets, so as to improve efficiencies in these markets. The first and second papers examine the load shifting behavior of industrial customers in Ontario under real time pricing (RTP). Using Hourly Ontario Energy Price (HOEP) data from 2005 to 2008 and industry-level consumption data from all industrial customers directly connected to the transmission grid, the first paper adopts a Generalized Leontief specification to obtain elasticities of substitution estimates for various industry groups, while the second paper adopts a specification derived from standard consumer theory to obtain price elasticity estimates. The findings of both papers confirm that in some industries, industrial customers who are direct participants of the wholesale market tend to shift consumption from peak to off-peak periods in order to take advantage of lower off-peak prices. Furthermore, in the first paper, a demand model is estimated and there is evidence that the marginal effect of hourly load on hourly price during peak periods is larger than the marginal effect during off-peak periods. An important policy implication from the results of these papers is that while RTP is currently limited to industrial customers, it does have positive spillover effects on all consumers. The third paper uses a unique panel dataset of all retail gasoline stations across five Canadian cities from late-2006 to mid-2007 to examine the effect of local competition on market shares and sales of individual stations. The base empirical specification includes explanatory variables representing the number of same brand stations and the number of different brand stations within a 3km radius to identify brand affiliation effect. It is found that the number of local competitors is negatively correlated with market share and sales. More interestingly, a same brand competitor has a larger marginal impact on market share and sales than a competitor of a different brand. These findings suggest that additional local competition leads to cannibalization of market share among existing stations, rather than create new demand. Another implication is that relying only on the number of different brands operating within a geographic market could understate the competition intensity in the local market.