Cette thèse porte sur l'étude des apports de la flexibilité dans les réseaux Smart Grids Basse Tension. Ces derniers étant fondamentalement différents des réseaux Moyennes et Hautes Tensions, la gestion des flexibilités BT ne peut être calquée sur celle des réseaux MT et HT. De nouveaux moyens de contrôle doivent donc être développés. L'apport de ces flexibilité est analysé selon deux principaux bénéfices: la gestion opérationnelle la réduction de la pointe. Le premier apport porte donc sur le maintien des variables critiques à l'interieur des contraintes admissibles. Le but est de pouvoir gérer le réseau au plus près de ses limites, et donc d'éviter d'avoir à le renouveler, nottament en cas d'insertion importante de production décentralisée ou de véhicules électriques. La flexibilité utilisée est la gestion coordonnée des production décentralisées (puissances actives, réactives et phase de connection) et d'un régleur en charge. Le second porte sur la réduction de la pointe de consommation, soit au niveau du transformateur, soit au niveau national. La flexibilité utilisée est le délestage du chauffage électrique pendant une courte durée, suivie d'un rebond de puissance lorsque le chauffage est rallumé. / This thesis investigates the potential contributions of flexibilities in Low Voltage Smart Grids. These networks are intrinsically different than Medium and High Voltages networks, so that the control of LV flexibilities cannot be directly taken from MV and HV networks, and new methods should be developed. The contribution of these flexibilities is studied through two main benefits: improved network operation and peak shaving. The first benefit focuses on maintaining the critical variables within the admissible constraints. The objective is to manage the network closer to its limits, reducing the need for margins, and therefore the need for upscaling. This is especially true in case of significant insertion of distributed generations or electric vehicles. The studied flexibility is the coordinated management of decentralized generation (active and reactive powers, phase switch) and a tap changer. The second benefit concerns the reduction of the peak consumption, either at the transformer, either at the national level. The studied flexibility is the shedding of electric heating for a short time, followed by a rebound when the heating is turned back on.

The growing uptake of wind and photovoltaic technologies requires further sources of system-level flexibility to avoid or defer significant investments. The ability to control, to some extent, customer demand (load management, LM) is one of these sources of flexibility. However, the direct involvement of a large number of customers makes the scalability of such approach a major challenge. A mostly unexplored solution to overcome the challenges of managing thousands or millions of customers is to leverage the positive correlation between voltage and demand. More precisely, Distribution Network Operators (DNOs) can control existing regulation devices to reduce customer voltages and so triggering a reduction in demand. This scheme, hereafter called voltage-led LM, avoids the direct involvement of customers overcoming one of the major barriers of traditional LM solutions. To understand whether this approach can be of any significance, a methodology able to quantify such reduction in demand need to be developed. However, the few methodologies available in the literature neglect the interactions across voltage levels and their influence on the benefits of the scheme. Moreover, time-varying demand profiles and load models are not always considered. Finally, the impact that the widespread adoption of distributed energy resources might have, is also neglected. This thesis addressed these gaps by developing a four-stage approach in which the time-varying volume of demand reduction that the scheme can unlock is quantified considering for the first time the influences among all voltage levels in distribution network. To reduce the complexity each voltage level is analysed separately whilst maintaining the corresponding dependencies. The methodology, also able to extrapolate the results at national scale, can quantify the impact that the uptake of residential scale PV units might have on the scheme. The methodology is demonstrated with a real UK case study where 10-min resolution time-series daily and seasonal analysis are performed. For the first time real network models across the whole distribution network, from 132 kV to 400 V, have been adopted. The interactions across voltage levels, the adoption of realistic load models, the variety of network models and the use of a time-varying approach, all aspects simultaneously considered for the first time in a case study, have shown to play a key role in the quantification. In Great Britain the scheme is expected to provide a significant volume of flexibility of around 1.8GW (60 GW of peak demand). The presence of PV, at least in the short term, has shown to have only a marginally effect on the benefits unlocked by the voltage-led LM scheme, making such scheme promising even in a low carbon future.

Recent technological developments are bringing about substantial changes that are converting traditional distribution networks into "smart" distribution networks. In particular, it is possible to observe seamless integration of Information and Communication Technologies (ICTs), including the widespread installation of automatic equipment, smart meters, etc. The increased automation facilitates active network management, interaction between market actors and demand side participation. If we also consider the increasing penetration of distributed generation, renewables and various emerging technologies such as storage and dynamic rating, it can be argued that the capacity of distribution networks should not only depend on conventional asset. In this context, taking into account uncertain load growth and ageing infrastructure, which trigger network investments, the above-mentioned advancements could alter and be used to improve the network design philosophy adopted so far. Hitherto, in fact, networks have been planned according to deterministic and conservative standards, being typically underutilised, in order for capacity to be available during emergencies. This practice could be replaced by a corrective philosophy, where existing infrastructure could be fully unlocked for normal conditions and distributed energy resources could be used for post fault capacity services. Nonetheless, to thoroughly evaluate the contribution of the resources and also to properly model emergency conditions, a probabilistic analysis should be carried out, which captures the stochasticity of some technologies, the randomness of faults and, thus, the risk profile of smart distribution networks. The research work in this thesis proposes a variety of post fault capacity services to increase distribution network utilisation but also to provide reliability support during emergency conditions. In particular, a demand response (DR) scheme is proposed where DR customers are optimally disconnected during contingencies from the operator depending on their cost of interruption. Additionally, time-limited thermal ratings have been used to increase network utilisation and support higher loading levels. Besides that, a collaborative operation of wind farms and electrical energy storage is proposed and evaluated, and their capacity contribution is calculated through the effective load carrying capability. Furthermore, the microgrid concept is examined, where multi-generation technologies collaborate to provide capacity services to internal customers but also to the remaining network. Finally, a distributed software infrastructure is examined which could be effectively used to support services in smart grids. The underlying framework for the reliability analysis is based on Sequential Monte Carlo Simulations, capturing inter-temporal constraints of the resources (payback effects, dynamic rating, DR profile, storage remaining available capacity) and the stochasticity of electrical and ICT equipment. The comprehensive distribution network reliability analysis includes network reconfiguration, restoration process, and ac power flow calculations, supporting a full risk analysis and building the risk profile for the arising smart distribution networks. Real case studies from ongoing project in England North West demonstrate the concepts and tools developed and provide noteworthy conclusions to network planners, including to inform design of DR contracts.

We have proposed a method by which the topology of a network might be discovered through an algorithm like the distributed Bellman-Ford algorithm. We have explored the inner workings of two methods to automate power distribution network reconfiguration, the ILP Solver and the Heuristic Solver. We have seen how networks of different shapes can be translated into a flattened topology, which is necessary preprocessing to find a power assignment solution for a network. We have also seen some experimental results comparing the performance of the ILP Solver and the Heuristic Solver. The Heuristic Solver is a very fast, efficient algorithm to reconfigure power distribution, which is important in the case of an emergency. It performs consistently with near perfect results at a speed that is orders of magnitude quicker than the ILP Solver in almost all cases. In an application where a network is small and time is not an important constraint, the ILP Solver could possibly be preferable, but in any context where time is sensitive and near-perfect results are as acceptable as perfect results, the Heuristic Solver is much preferable. There is always room for improvement. Future tests should perhaps allow for non-integer capacity units, or loads that require other values than unit capacity. Optimizing each algorithm by rewriting them in C could give more optimized tests, though this may not be necessary to make judgments about implementing one or the other. There may be some ways to improve the Heuristic Solver, such as arranging the ordered_links in some way that could be more optimal. The algorithm could also be improved by taking advantage of the fact that once there are no more sources with capacity to provide any loads, the process of trying to assign loads to them for power supply can cease. Perhaps this method could be combined with other methods that do not presently account for load priorities or place as much value on fast execution.

abstract: The energy consumption by public drinking water and wastewater utilities represent up to 30%-40% of a municipality energy bill. The largest energy consumption is used to operate motors for pumping. As a result, the engineering and control community develop the Variable Speed Pumps (VSPs) which allow for regulating valves in the network instead of the traditional binary ON/OFF pumps. Potentially, VSPs save up to 90% of annual energy cost compared to the binary pump. The control problem has been tackled in the literature as “Pump Scheduling Optimization” (PSO) with a main focus on the cost minimization. Nonetheless, engineering literature is mostly concerned with the problem of understanding “healthy working conditions” (e.g., leakages, breakages) for a water infrastructure rather than the costs. This is very critical because if we operate a network under stress, it may satisfy the demand at present but will likely hinder network functionality in the future. This research addresses the problem of analyzing working conditions of large water systems by means of a detailed hydraulic simulation model (e.g., EPANet) to gain insights into feasibility with respect to pressure, tank level, etc. This work presents a new framework called Feasible Set Approximation – Probabilistic Branch and Bound (FSA-PBnB) for the definition and determination of feasible solutions in terms of pumps regulation. We propose the concept of feasibility distance, which is measured as the distance of the current solution from the feasibility frontier to estimate the distribution of the feasibility values across the solution space. Based on this estimate, pruning the infeasible regions and maintaining the feasible regions are proposed to identify the desired feasible solutions. We test the proposed algorithm with both theoretical and real water networks. The results demonstrate that FSA-PBnB has the capability to identify the feasibility profile in an efficient way. Additionally, with the feasibility distance, we can understand the quality of sub-region in terms of feasibility. The present work provides a basic feasibility determination framework on the low dimension problems. When FSA-PBnB extends to large scale constraint optimization problems, a more intelligent sampling method may be developed to further reduce the computational effort. / Dissertation/Thesis / Masters Thesis Industrial Engineering 2018

Made available in DSpace on 2015-05-14T12:09:32Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 4820663 bytes, checksum: cc588b07b38e446793574dcf4b7b7b0c (MD5) Previous issue date: 2014-06-09 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / The present study aims dissertative modeling and calibration of a real distribution system water, with emphasis on the identification of water losses. The case study was the supply system of Juatama community in Quixadá, located in the central region of the state of Ceará. The distribution network under study was recently installed and is operating with stability, which enabled the development of a model that successfully describes the real system. The calibration process was carried out through LenhsCalibra application, which uses an optimization algorithm based on the technique of genetic algorithms. The program allowed multivariate calibration, including how to search the demand variables and the roughness of pipes, whose values were adjusted using simulations from the actual flow levels and pressures. The calibrated model system showed satisfactory results, and identify the record of discharges used for cleaning of the network and network points higher than those with demands effectively, are consumed by customers. / O presente estudo dissertativo tem por objetivo a modelagem e calibração de um sistema de distribuição de água real, com ênfase na identificação das perdas de água. O estudo de caso foi o sistema de abastecimento da comunidade de Juatama, em Quixadá, localizada na região central do Estado do Ceará. A rede de distribuição em estudo foi instalada recentemente e vem operando com estabilidade, o que possibilitou o desenvolvimento de um modelo que descreve satisfatoriamente o sistema real. O processo de calibração foi realizado por meio do aplicativo LenhsCalibra, que utiliza um algoritmo de otimização baseado na técnica de algoritmos genéticos. O programa possibilitou a calibração multivariada, incluindo como variáveis de busca a demanda e a rugosidade das tubulações, cujos valores foram ajustados através de simulações a partir dos níveis de vazão e pressões reais. O modelo calibrado do sistema apresentou resultados satisfatórios, além de identificar o registro de descargas utilizadas para limpeza da rede e pontos na rede com demandas superiores às que, efetivamente, são consumidas pelos clientes.

Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / Este trabalho apresenta um sistema multiagente para recomposiÃÃo au-tomÃtica de redes de distribuiÃÃo de energia elÃtrica. O sistema proposto à formado por trÃs tipos de agentes: agente dispositivo, agente alimentador e agente subesta-ÃÃo. Os agentes dispositivos estÃo associados aos equipamentos do sistema e sÃo responsÃveis pela coleta de informaÃÃes da rede; os agentes alimentadores sÃo responsÃveis pelo gerenciamento dos alimentadores do sistema; e, os agentes su-bestaÃÃes sÃo responsÃveis pelo gerenciamento da capacidade de suprimento da rede. SÃo apresentados os comportamentos e interaÃÃes dos agentes do sistema durante o processo de recomposiÃÃo, visando restabelecer a energia elÃtrica dos trechos desenergizados e nÃo defeituosos, afetados por falta no alimentador ou falta no transformador da subestaÃÃo. SÃo apresentados oito estudos de casos que testam diferentes situaÃÃes possÃveis de ser encontrada nos sistemas de distribuiÃÃo, como recomposiÃÃo mediante descoordenaÃÃo da proteÃÃo, recomposiÃÃo parcial do sistema devido as restriÃÃes operacionais do sistema e recomposiÃÃes para falta no transformador da subestaÃÃo. Para validaÃÃo dos casos testes foi desenvolvido um simulador que possibilita a simulaÃÃo de faltas em diferentes locais do sistema elÃtrico em estudo. AtravÃs do ambiente visual do simulador, onde à disponibilizado o diagrama unifilar do sistema com os estados dos equipamentos e a ferramenta de captura de mensagem do JADE, à possÃvel simular diversos cenÃrios e observar interaÃÃo dos agentes em busca da recomposiÃÃo do sistema. O sistema proposto à capaz de localizar a falta, isolar o trecho defeituoso e restaurar o sistema, considerando restriÃÃes operacionais e descoordenaÃÃo do sistema de proteÃÃo. / This work presents a multi-agent system for automatic restoration of power distribution networks. The proposed system consists of three types of agents: device agent, feeder agent and substation agent. Device agents are associated with system equipment and are responsible for information acquisition of the network; the feeder agents are responsible to manage the feeders; and the substations agents are accountable of manage the network supply capability. The behaviors and interactions of the system agents during the restoration process, aiming to restore the feeder sectors affected by but not in fault, are presented. Eight case studies are presented, which test different possible situations likely to be found in the distribution systems, such as restoration by uncoordinated protection, partial recovery of the system because of operating system restrictions and recomposition for faults in the transformer substation. To validate the test cases a simulator was developed, which allows the simulation of faults in different locations of the power system under study. Through the simulator, where there are the single line diagram of the system with the state of the equipment and the tool to capture message in JADE, is possible to simulate different scenarios and observe the interaction of agents in search of system restoration. The proposed system is able to locate and isolate the fault, and restore suitably the system, considering operating limits and uncoordinated system protection.

Esta dissertação apresenta uma metodologia de otimização do fluxo de potência em sistemas elétricos de subtransmissão utilizando duas técnicas da Computação Evolutiva, os Algoritmos Genéticos e as Estratégias Evolutivas. A metodologia decompõe o problema em duas partes e o trata seqüencialmente. A primeira parte procede com a otimização do fluxo de potência ativa e a segunda com a otimização do fluxo de potência reativa. São apresentadas as características e estruturas básicas dos Algoritmos Genéticos e das Estratégias Evolutivas. A técnica dos Algoritmos Genéticos é implementada no modelo de otimização do fluxo de potência ativa e a técnica das Estratégias Evolutivas no modelo de otimização do fluxo de potência reativa. As variáveis de controle dos modelos desenvolvidos são, respectivamente, os estados dos dispositivos de seccionamento e os níveis de tensão dos barramentos dos pontos de fronteira, associadas ao sistema analisado. Analisam-se os sistemas elétricos de subtransmissão que contêm múltiplos pontos de fronteira (conexão) com a Rede Básica e diversas possibilidades de configuração operativa. A metodologia proposta é aplicada a um sistema elétrico de subtransmissão real a fim de minimizar o custo dos encargos de uso dos sistemas de transmissão. Os resultados obtidos mostram a eficácia dos algoritmos desenvolvidos na busca das soluções desejadas. / This dissertation presents a power flow optimization methodology on subtransmission electric systems using two techniques of Evolutionary Computation, namely the Genetic Algorithms and the Evolution Strategies. The methodology splits the problem into two parts and treats it separately. On the first step it proceeds to optimize the active power flow and on the second step to optimize the reactive power flow. Characteristics and basic structures of the Genetic Algorithms and the Evolution Strategies are shown. The Genetic Algorithms technique is implemented on the active power flow optimization model and the Evolution Strategies technique on the reactive power flow optimization model. The control variables of developed models are, respectively, the switch states and the border point bar voltage levels, associated to the analyzed system. The subtransmission electric systems that have multiple border (connection) points to the Basic Network and many operative configuration possibilities are analyzed. The proposed methodology is applied to a real subtransmission electric system in order to minimizes the transmission system use duty costs. The obtained results show the efficacy of the developed algorithms in the search of desired solutions.

Submitted by Geandra Rodrigues (geandrar@gmail.com) on 2018-05-23T17:48:25Z No. of bitstreams: 1 andrelopesmarinhodossantos.pdf: 2400435 bytes, checksum: 2f58d7bcbbafebad1c3f9814b3568a23 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2018-05-24T17:37:03Z (GMT) No. of bitstreams: 1 andrelopesmarinhodossantos.pdf: 2400435 bytes, checksum: 2f58d7bcbbafebad1c3f9814b3568a23 (MD5) / Made available in DSpace on 2018-05-24T17:37:03Z (GMT). No. of bitstreams: 1 andrelopesmarinhodossantos.pdf: 2400435 bytes, checksum: 2f58d7bcbbafebad1c3f9814b3568a23 (MD5) Previous issue date: 2018-02-26 / O presente trabalho apresenta uma metodologia para o planejamento da operação de bancos de baterias em redes de distribuição, as quais contém a presença de geração distribuida proveniente de fontes renováveis de energia. Para tanto, o problema do fluxo ótimo de potência é solucionado com a inclusão da potência injetada ou absorvida pelas baterias como variável de otimização no modelo proposto. O objetivo é que a inserção de baterias impacte de forma a reduzir os custos de energia e os custos de confiabilidade da rede, e, consequentemente provocando a diminuição dos custos totais de operação do SDE em um horizonte de planejamento de longo prazo. A utilização da meta-heurística denominada SIA se deve a sua aplicabilidade em sistemas de grande porte, visto que, nestes casos, a busca exaustiva pela melhor solução torna-se inviável. Análises utilizando cinco tipos de baterias e sua inserção em quatro sistemas de distribuição conhecidos da literatura são realizados para a validação da metodologia proposta. Resultados apresentados demonstram a aplicabilidade da metodologia proposta, assim como a viabilidade de utilização de bancos de baterias em redes de distribuição de energia. / This work presents an application for the operation planning of battery storage systems in electricity distribution networks with penetration of distributed generation from renewable sources of energy. For this, the an optimal power flow algorithm is applied with the inclusion of the power supplied or absorbed by battery banks as an optimization variable in the developed model. The objective is that the battery banks insertion impacts on the reduction of energy and reliability costs of the network, and, as a consequence, to lead in the reduction of the total costs of the distribution network in a long term operation period. The choice for a meta-heuristic called SIA is due their ability to deal with large scale problems, in which an exhaustive search would not be feasible. Analysis using five battery types applied to four well known systems in literature are performed to validate the proposed methodology. Results presented demonstrate the applicability of the proposed methodology, as well as the feasibility of using battery banks in energy distribution networks.

Le raccordement des énergies renouvelables (ENR) aux réseaux de distribution peuvent nécessiter des travaux de renforcement coûteux et long à mettre en œuvre. Différentes solutions alternatives peuvent dans certains cas limiter l'ampleur des travaux à réaliser et donc leur montant et/ou leur durée. L’utilisation de telles solutions nécessite au préalable de réviser les méthodes de planification du réseau pour qu’elles puissent analyser leurs impacts technico-économiques. Cette thèse a pour objet d’apporter un cadre adapté à l’étude des leviers d’intégration des ENR à l’aide de nouvelles méthodes pour la planification pluriannuelle des réseaux de distribution. Comparée à l’état de l’art, l’approche adoptée présente l’avantage d’estimer les performances de ces leviers à moyen/long terme en considérant : 1) le comportement du gestionnaire de réseau de distribution, modélisé sous la forme d’une stratégie de planification multi-variables, 2) les interactions entre les réseaux de moyenne et basse tension, et 3) les incertitudes sur l’arrivée des ENR. Ces trois axes d’amélioration ont pu être abordés grâce à des méthodes de maîtrise du temps de calcul appliquées à l’estimation pluriannuelle de l’état électrique du réseau. Le potentiel de l’approche proposée est illustré via l’analyse technico-économique de plusieurs stratégies de planification incluant des leviers traditionnels et/ou des leviers d’effacement de production. Les travaux se concluent sur une première contribution sur l’optimisation des stratégies de planification compte tenu des incertitudes sur l’arrivée des ENR / The integration of Renewable Energy Sources (RES) into the distribution networks may require network reinforcements that can be expensive and take time. Different alternative solutions can limit the amount of work to be carried out and thus reduce their cost and/or duration. The use of such solutions requires modifying the network planning methods so as to analyze their techno-economic impacts. This research aims to provide a suitable framework for the study of RES-integration solutions using novel methods for the multi-year planning of distribution networks. Compared to the state of the art, the proposed approach provides the advantage of assessing the performance of these solutions in the medium/long run by considering: 1) the behavior of the distribution system operator, which is modeled as a multi-variable planning strategy, 2) the interactions between medium- and low-voltage networks, and 3) the uncertainties on the arrival of new RES. These three points could have been addressed by applying methods of reducing computation time to the multi-year estimation of the electrical network state. The potential of the proposed approach is illustrated through the techno-economic analysis of several planning strategies including traditional solutions and/or generation curtailment. The research concludes with a first contribution to the planning strategy optimization by taking into account the uncertainties on the arrival of new RES.