Transmission pricing and congestion management are two important aspects of modern power sectors working under a deregulated environment or moving towards a deregulated system (open access) from a regulated environment. The transformation of power sector for open access environment with the participation of private sector and potential power suppliers under the regime of trading electricity as a commodity is aimed at overcoming some of the limitations faced by the vertically integrated system. It is believed that this transformation will bring in new technologies, efficient and alternative sources of power which are greener, self sustainable and competitive. There is ever increasing demand for electrical power due to the changing life style of human beings fueled by modernization and growth. Augmentation of existing capacity, siting of new power plants, and a search for alternate viable sources of energy that have lesser impact on environment are being taken up. With the integration of power plants into the grid depending upon the type, loca- tion and technology used, the cost of energy production also differs. In interconnected networks, power can flow from one point to other point in infinite number of possible paths which is decided by the circuit parameters, operating conditions, topology of network and the connected loads. The transmission facility provided for power transfer has to recover the charges from the entities present in the network based on the extent of utilization. Since power transmission losses account for nearly 4 to 8% of the total generation, this has to be accounted for and shared properly among the entities depending upon the connected generation/load. In this context, this thesis aims to evaluate the shortcomings of existing tracing methods and proposes a tracing method based upon the actual operating conditions of the network taking into account the network parameters, voltage gradient among the connected buses and topology of the network as obtained by the online state estimator/load flow studies. The concept proposed is relatively simple and easy to implement in a given transactional period. The proposed method is compared against one of the existing tracing technique available in literature. Both active and reactive power tracing is handled at one go. The summation of partial contributions from all the sources in any given line of the system always matches with that of the respective base case ow. The AC power flow equations themselves are nonlinear in nature. Since the sum of respective partial flows in a given branch is always equal to the original ow, these are termed as virtual flows and the effect of nonlinearity is still unknown. The virtual flows in a given line are complex in nature and their complex sum is equal to the original complex power flows as in the base case. It is required to determine whether these are the true partial flows. To answer this, a DC equivalent of the original AC network is proposed and is called as the R - P equivalent model. This model consists of only the resistances as that of original network (the resistances of transformers and lines neglecting the series reactance and the shunt charging) only. The real power injections in a AC network i.e. sources into respective buses and loads (negative real power injections) are taken as injection measurements of this R P model and the bus voltages (purely real quantities) are estimated using the method of least squares. Complex quantities are absent in this model and only real terms which are either sums or differences are present. For this model, virtual flows are evaluated and it has been verified that the virtual real power contributions from sources are in near agreement with the original AC network. This implies that the virtual flows determined for the original network can be applied for day-to-day applications. An important feature of the virtual flows is that it is possible to identify counter ow components. Counter flow components are the transactions taking place in opposite direction to the net flow in that branch. If a particular source is produces counter flow in a given line, then it is in effect reducing congestion to that extent. This information is lacking in most of the existing techniques. Counter flows are useful in managing congestion. HVDC links are integrated with HVAC systems in order to transfer bulk power and for the additional advantages they offer. The incremental cost of a DC link is zero due to the closed loop control techniques implemented to maintain constant power transfer (excluding constant voltage or constant current control). Consequently, cost allocation to HVDC is still a problem. The proposed virtual power flow tracing method is extended to HVAC systems integrated with HVDC in order to determine the extent of utilization of a given link by the sources. Before evaluating the virtual contributions to the HVDC links, the steady state operating condition of the combined system is obtained by per-forming a sequential load flow. Congestion is one of the main aspects of a deregulated system, and is a result of several transactions taking place simultaneously through a given transmission facility. If congestion is managed by providing pricing signals for the transmission usage by the parties involved. It can also be due to the non-availability of transmission paths due to line outages as a result of contingencies. In such a case, generation active power redispatch is considered as a viable option in addition to other available controls such as phase shifters and UPFCs to streamline the transactions within the available corridors. The virtual power flow tracing technique proposed in the thesis is used as a guiding factor for managing congestions occurring due to transactions/contingencies to the possible extent. The utilization of a given line by the sources present in the network in terms of real power flow is thus obtained. These line utilization factors are called as T-coefficients and these are approximately constant for moderate increments in active power change from the sources. A simple fuzzy logic based decision system is proposed in order to obtain active power rescheduling from the sources for managing network congestions. In order to enhance the system stability after rescheduling, reactive power optimization has life systems to illustrate the proposed approaches. For secure operation of the network, the ideal proportion of active power schedule from the sources present in the network for a given load pattern is found from network [FLG] matrix. The elements of this matrix are used in the computation of static voltage stability index (L-index). This [FLG] matrix is obtained from the partitioned network YBUS matrix and gives the Relative Electrical Distance (RED) of each of the loads with respect to the sources present in the network. From this RED, the ideal proportion of real power to be drawn by a given load from different sources can be determined. This proportion of active power scheduling from sources is termed as Desired Proportion of Generation (DPG). If the generations are scheduled accordingly, the network operates with less angular separation among system buses (improved angular stability), improved voltage profiles and better voltage stability. Further, the partitioned K[GL] matrix reveals information about the relative proportion in which the loads should draw active power from the sources as per DPG which is irrespective of the present scheduling. Other partitioned [Y ′ GG] matrix is useful in finding the deviation of the present active power output from the sources with respect to the ideal schedule. Many regional power systems are interconnected to form large integrated grids for both technical and economic benefits. In such situations, Generation Expansion Planning (GEP) has to be undertaken along with augmentation of existing transmission facilities. Generation expansion at certain locations need new transmission networks which involves serious problems such as getting right-of-way and environmental clearance. An approach to find suitable generation expansion locations in different zones with least requirements of transmission network expansion has been attempted using the concept of RED. For the anticipated load growth, the capacity and siting generation facilities are identified on zonal basis. Using sample systems and real life systems, the validity of the proposed approach is demonstrated using performance criteria such as voltage stability, effect on line MVA loadings and real power losses.

[pt] O planejamento da expansão da transmissão tem por objetivo identificar o conjunto de novas linhas de transmissão que serão instaladas na rede elétrica, a fim de garantir a segurança e a qualidade do sistema, atendendo ao crescimento da demanda. No Brasil, o primeiro estágio do planejamento consiste em definir e avaliar o corredor para locação das linhas candidatas. Nesta etapa são definidas informações como cabo escolhido, preços médios, tempo de comissionamento, impactos socioambientais e informações sobre a região. No estágio seguinte ocorre o leilão de transmissão em que vários investidores competem pelos lotes de transmissão. No último estágio, o ganhador do leilão é o responsável pela instalação e comissionamento da linha de transmissão. Apesar do levantamento feito no estágio inicial, os projetos de linha de transmissão podem sofrer atrasos e aumentos no custo final, principalmente, por questões de licenciamentos ambientais, desvios do traçado devido a travessias e interferências com áreas protegidas. A presente dissertação propõe metodologia para dimensionamento e precificação da linha de transmissão, ambos de acordo com os critérios e banco de dados da ANEEL, de forma a acelerar e facilitar o processo de planejamento. Com o intuito de evitar atrasos e prever interferências socioambientais, a segunda parte do trabalho apresenta uma metodologia que consiste em localizar e identificar cruzamentos e interferências com áreas protegidas de caráter ambiental e/ou infraestrutural no território brasileiro, a partir das coordenadas do traçado da linha de transmissão em análise. A terceira parte do trabalho verifica, a partir dos resultados anteriores, o impacto no planejamento da expansão da transmissão através de um modelo de programação linear inteira mista considerando fluxo de potência CC, despacho econômico e critério N-1. / [en] The transmission expansion planning aims at identifying a set of new power lines to be installed on the grid, in order to guarantee the reliability and quality of the system, meeting the demand growth. In Brazil, the first stage of planning consists of defining e survey the corridor for the transmission line siting. At this stage it is defined data such as conductor chosen, average prices, commissioning time, socioenvironmental impacts and information about the region. In the following stage, occurs the auction which several investors compete for the transmission lots. In the last stage, the winner of the auction becomes responsible for the installation and commissioning. Despite the survey of the initial stage, the transmission lines undergo delays and additional costs, mainly, due to environmental licensing, changes of the defined route due to crossing and interferences with protected areas. The present dissertation proposes a methodology to design and price the transmission line, both accordingly to the ANEEL database and criteria, in order to accelerate and facilitate the planning process. Aiming to avoid delays and foreseeing socioenvironmental impacts, the second part of the dissertation presents a methodology that consists of locating and identifying crossings and interferences with protected areas of environmental and/or infrastructural aspect on the Brazilian territory, from the coordinates of the transmission line route in analysis. The third part verifies, from the previous results, the impact on the transmission expansion planning through a model based on a mixed-integer linear programming, considering a DC power flow, unit commitment and N-1 criteria

[pt] A solução do problema de planejamento da expansão da transmissão (PET) tem por objetivo geral identificar reforços a serem construídos na rede de forma a garantir a adequada interligação entre carga e geração, previstos para um determinado horizonte de estudo. No processo de solução desse problema, busca-se manter o equilíbrio ótimo entre os custos envolvidos (investimento e operação) e os níveis de qualidade e desempenho na operação do sistema reforçado. Nesse sentido, é proposta nesta dissertação de mestrado uma ferramenta de otimização especializada para solução do problema PET, a qual é baseada na técnica metaheurística Algoritmo Genético. A ferramenta proposta, denominada Algoritmo Genético Especializado (AGE-PET), faz uso de informações heurísticas fundamentadas em análises atualizadas de fluxo de potência da rede realizadas durante o processo evolutivo de solução do problema. Essas informações heurísticas são traduzidas por meio de índices de sensibilidade, os quais são integrados aos operadores genéticos inerentes à ferramenta, conduzindo a solução do problema na direção de planos de expansão de boa qualidade. Para análise e validação da metodologia proposta, é solucionado o problema PET estático de longo prazo, considerando o modelo linearizado DC com perdas ôhmicas e atendimento do critério de segurança N-1 para a rede de transmissão. Sistemas elétricos de transmissão com diferentes características e dimensões, incluindo um subsistema atual da rede interligada brasileira, são empregados nos estudos realizados. / [en] The main goal in the solution of the transmission expansion planning (TEP) is to identify reinforcements to be built in the network in order to guarantee the adequate interconnection between load and electric power generation, both foreseen for a given future planning horizon. In the process of solving this problem, the aim is to maintain the optimal balance between the costs involved (investment and operation) and the levels of quality and performance in the operation of the reinforced system. Thus, it is proposed in this dissertation a specialized optimization tool for solving the TEP problem, which is based on the metaheuristic Genetic Algorithm technique. The proposed tool, called Specialized Genetic Algorithm (SGA-TEP), makes use of heuristic information based on updated network power flow analyses carried out during the evolutionary process of solving the problem. This heuristic information is translated by means of sensitivity indices, which are integrated with the genetic operators inherent to the tool, leading to the solution of the problem in the direction of good quality expansion plans. For analysis and validation of the proposed methodology, the long-term static TEP problem is solved, considering the linearized DC model with ohmic losses and the compliance of the N-1 security criterion for the transmission network. Electric transmission systems with different characteristics and dimensions, including a recent subsystem of the Brazilian interconnected grid, are used in the case studies.

[pt] Este trabalho explora a estrutura de decomposição de um problema de planejamento da expansão da geração hidrotérmica, utilizando uma integração entre uma Decomposição de Benders modificada e um Progressive Hedging. Consideramos uma representação detalhada das restrições cronológicas de curto prazo, com resolução horária, baseando-se em dias típicos para cada etapa. Além disso, representamos a natureza estocástica de uma política operacional hidrotérmica multiestágio por meio de uma Regra de Decisão Linear otimizada, garantindo decisões de investimento compatíveis com uma política operacional não antecipativa. Para resolver este problema de otimização em grande escala, propomos um método de decomposição de Benders aprimorado com várias instâncias do problema mestre, onde cada uma delas é reforçada por cortes primários além dos cortes de Benders gerados a cada candidato a solução do mestre. Nossa nova abordagem permite o uso de termos de penalização de Progressive Hedging para fins de regularização. Mostramos que o algoritmo proposto é 60 porcento mais rápido que os tradicionais e que a consideração de uma política operacional não antecipativa pode economizar, em média, 8.27porcento do custo total em testes fora da amostra. / [en] This paper exploits the decomposition structure of the hydrothermal generation expansion planning problem with an integrated modified Benders Decomposition and Progressive Hedging approach. We consider a detailed representation of hourly chronological short-term constraints based on typical days per month and year. Also, we represent the multistage stochastic nature of the hydrothermal operational policy through an optimized linear decision rule, thereby ensuring investment decisions compatible with a nonanticipative implementable operational policy. To solve the resulting large-scale optimization problem, we propose an improved Benders Decomposition method with multiple instances of the master problem, each of which strengthened by primal cuts and new Benders cuts generated by each master s trial solution. Additionally, our new approach allows using Progressive Hedging penalization terms for regularization purposes. We show that our method is 60 percent faster than the traditional ones and also that the consideration of a nonanticipative operational policy can save, on average, 8.27 percent of the total cost in out-of-sample tests.

Svenska kraftnät (Swedish National Grid) is the transmission system operator in Sweden and is responsible for maintaining and developing the Swedish transmission grid. One of the tasks included in this responsibility is transmission expansion planning, which means analyzing and planning the capacity in the future transmission grid for the requested load and generation. Historically, the N-1-criterion has been used to evaluate the reliability in transmission grid expansion planning. This criterion is deterministic, which means that all failures in the grid are considered equally, regardless of the differences in probability. In a system with an increased share of intermittent energy sources and load, it is increasingly demanding to plan and build a system that is N-1-secure in all situations. Probabilistic Risk Assessment (PRA) is a complementing method that takes the probability and consequence of different faults into consideration. The possible benefits of using PRA are higher utilization of the power grid, greater system operating flexibility, better support for system planning, and an overall optimization of socio-economic benefits. In this master thesis project, a method for PRA in transmission expansion planning at Svenska kraftnät is proposed. The method consists of three steps: generation of operating states, contingency analysis, and reliability assessment. Historical frequency and duration of faults in the transmission grid are used to estimate the probability of different contingencies. The method results in three reliability measures for the system: expected energy not supplied (MWh/year), expected duration of outages (h/year), and expected duration of overloads (h/year). The three reliability measures are combined into a composite comparison index, which can be used to compare different alternatives in transmission expansion planning. The proposed method is tested on a PSS/E model of the Swedish transmission grid and 14 different operating states. Four different investment alternatives are analyzed, including changes in load and generation, and grid reinforcements. The conclusion is that the proposed method is a useful tool for power system analysis at Svenska kraftnät and that the process for generating the operating states must be further developed. / Historiskt har det deterministiska N-1-kriteriet använts för att bedöma transmissionsnätets tillförlitlighet vid långsiktig nätplanering. Detta innebär att systemet ska dimensioneras för att klara ett bortfall av någon systemkomponent under värsta tänkbara driftfall, exempelvis topplasttimmen. I ett elsystem med alltmer intermittent förbrukning och produktion kan det dels vara svårt att veta vad som är det värsta tänkbara fallet, och dels kan det bli mycket kostsamt att dimensionera ett system som är N-1-säkert i alla lägen. Därför är det intressant att införa kompletterande probabilistiska verktyg. I detta examensjobb föreslås en metod för att beräkna och använda probabilistiska mått för att bedöma transmissionsnätets tillförlitlighet. Metoden använder flera tänkbara driftfall med varierande sannolikhet och värden på hur sannolika olika typer av fel i systemet är. Tänkbara fel analyseras och resulterar i mått på systemets förväntade överlaster och avbrott, uttryckt i timmar per år och energi per år. Dessa nyckeltal kombineras till ett sammanvägt mått, som kan användas för att jämföra olika nätanslutningar och investeringsalternativ.

Modern power systems are at the forefront of addressing the transition towards a decarbonized energy system, with increased integration of renewable energy sources becoming the key means to achieve the same. In this context, an expansion planning problem provides a decision support framework for investments in new generation and transmission assets over a long time-frame, addressing a wide range of technical and economic criteria aligned with national policies. It is thus an important but complex problem to solve, involving a number of modelling challenges and uncertainties to be considered. These include the treatment of operational variability due to the intermittent nature of renewable sources like wind or solar, while also considering uncertainties such as demand growth, technological developments impacting future investment costs among others, that define the long-term dynamics in the expansion. In this regard, one of the goals of the EU Project Spine is to create open source models to study investment scenarios for the expansion of power systems. This thesis work aims to offer insights for the Spine project, by identifying and exploring various requirements pertinent to a planning problem, along with method development. The primary objective of this thesis is to develop an expansion planning model, that determines the optimal location, size or capacity and time of investment for different candidates in generation and transmission assets, including short-term energy storage. A Mixed-Integer Linear Programming (MILP) optimization problem is formulated for the same, with both investment and operational sub-problems solved together. Operational variability has been modelled in a reduced form using profiles of representative days, while also incorporating contemporary requirements in the planning problem such as penetration targets for renewable generation. The developed model has been evaluated using a case study done on a small test network, in which different expansion scenarios involving varying demand growth and phase-out of conventional generators are investigated. Also, a two-stage stochastic optimization is performed to consider long-term uncertainties in demand growth and the quality of the stochastic solution is analyzed. It is inferred from the results that the expansion solution is indeed different for different scenarios, and stochastic optimization proves to be important in addressing long-term uncertainties, as reflected by a high value of stochastic solution (VSS). / Moderna kraftsystem ligger i framkant när det kommer till omställningen till ett fossilfritt energisystem. Ökad integrering av förnybara energikällor är den främsta lösningen för att uppnå detta. I samband med omställningen kan ett utbyggnadsplanering problem bidra till ramverk för investeringsbeslut för genererings- och transmissionstillgångar över ett långt tidsspann, vilket tar hänsyn till en bredd av tekniska och ekonomiska kriterier i linje med nationella policyer. Detta är ett viktigt, men ett komplext problem som inkluderar ett stort antal modelleringsutmaningar och osäkerheter som måste beaktas. Bland annat inkluderas hur drift varierar på grund av de förnybara energikällornas intermittenta karaktär såsom vind och sol, medan osäkerheter kring hur efterfrågan utvecklas, tekniska framsteg som påverkar framtida investeringar m.m., också behöver vägas in. Med hänsyn till detta är ett av målen för EU Project Spine att skapa en open source för modeller med syftet att studera investeringsscenarier när kraftsystemet expanderar. Syftet med detta examensarbete är att ge insikt i Spine-projektet genom att identifiera och utforska olika relevanta krav för ett planneringsproblem samt att utveckla metoder. Det huvudsakliga målet för detta examensarbete är att utveckla en expanderad planeringsmodell som bestämmer optimal placering, storlek, kapacitet och tidpunkt för investering för olika typer av genererings- och transmissionstillgångar samt kortvarig energilagring. Ett mixed-integer linjär programmering (MILP) optimeringsproblem har formulerats, där både investerings- och drifts-subproblem beräknas tillsammans. Variabel drift av kraftsystemet har modellerats på reducerad form genom att använda profiler för representativa dagar, därtill inkluderas samtida krav i planeringen såsom mål för penetreringsnivå av förnybara energikällor. Den utvecklade modellen har utvärderats i en fallstudie på en liten nätmodell där olika scenarier har utforskats. I scenarierna varieras tillväxten på efterfrågan och när utfasningen av konventionella generatorer sker. Därtill, sker en två-stegs stokastisk optimering för att ta hänsyn till långsiktiga osäkerheter kring tillväxten på efterfrågan och kvalitén av den stokastiska lösningen har analyserats. Resultaten visar att den expanderade lösningen är olika för olika scenarier, och att den stokastiska optimeringen är viktig när långsiktiga osäkerheter måste beaktas som visas genom ett högt värde för den stokastiska lösningen (VSS).

Orientador: Rubén Augusto Romero Lázaro / Resumo: A análise de sistemas altamente complexos quando e analizado o problema de planejamento de expansão de redes de transmissão de longo prazo, é o foco principal deste trabalho. Os modelos e metodos propostos são aplicados ao problema de planejamento estático tradicional, que é um problema de otimização matemática classificado como NP-completo, não-linear inteiro misto. O qual envolve no investimento, variáveis operacionais contínuas e variáveis inteiras. O comportamento normal de cada sistema pode conter informação essencial para a criação de novos métodos, como os planos de corte baseados em cortes de diferença de ângulos para problemas de grande escala, o que é a base é o ponto de partida deste trabalho, derivando em desigualdades válidas é ciclos críticos. Os cortes angulares básicos reduzem o espaço de busca do problema e o tempo total de cálculo deste problema, enquanto ao método de inequações válidas que pode ser usado para fornecer limites inferiores sólidos no investimento ótimo do planejamento de transmissão, já que a diferença entre o modelo DC (modelo exato) e o modelo de transporte (modelo mais relaxado) são as restrições angulares. Os ciclos críticos têm sido desenvolvidos para melhoraralguns dos modelos tradicionais do problemas de planejamento da expansão da rede de transmissão de longo prazo. A razão por trás disso é a ausência da segunda lei de Kirchhoff, que completa a representação do sistema, mas aumenta a complexidade. Para resolver os problemas resultantes... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The analysis of highly complex systems when solving the long-term transmission network expansion planning problem is the main focus of this work. The proposed improved models and methodology are applied to the traditionalstatic planning problem, which is a mathematical optimization problem classified as NP-complete and mixed-integer nonlinear problem. It involves continuousoperating variables and integer investment variables. The normal behavior of each system can be shown essential information to the creation of new methods, as the cutting-planes based in bus-angle difference cuts for large-scale problems which were the starting point of this work, deriving in valid inequalities and critic cycles. The angular cuts aim to reduce the search space of the problem and the total computation time of this NP-hard problem as for the valid inequalities methodthat can be used to provide strong lower bounds on the optimal investment of the transmissionplanning, since the difference between the DC model (exact model) and the transport model (more relaxed model) are the angular constraints. Critic cycles has been develop in order to improve some of the traditional long-term transmission network expansion planning problem models. The reason behind it is the absence of second Kirchhoff’s law which completes the representationof the system, but increase the complexity. In order to solve the resulting problems, this work uses the modeling language AMPL with the solver CPLEX. In test systems w... (Complete abstract click electronic access below) / Doutor

Orientador: Rubén Augusto Romero Lázaro / Resumo: Neste trabalho, consideram-se a análise teórica e a implementação computacional dos algoritmos Primal Simplex Canalizado (PSC) e Dual Simplex Canalizado (DSC) especializados. Esses algoritmos foram incorporados em um algoritmo Branch and Bound (B&B) de modo a resolver o problema de Planejamento da Expansão de Sistemas de Transmissão (PEST). Neste caso, o problema PEST foi modelado usando os chamados modelo de Transportes e modelo Linear Disjuntivo (LD), o que produz um problema de Programação Linear Inteiro Misto (PLIM). O algoritmo PSC é utilizado na resolução do problema de Programação Linear (PL) inicial após desconsiderar a restrição de integralidade do problema PLIM original. Juntamente com o algoritmo PSC, foi implementada uma estratégia para reduzir o número de variáveis artificiais adicionadas ao PL, consequentemente reduzindo o número de iterações do algoritmo PSC. O algoritmo DSC é utilizado na reotimização eficiente dos subproblemas gerados pelo algoritmo B&B, através do quadro ótimo do PL inicial, excluindo, assim, a necessidade da resolução completa de cada subproblema e, consequentemente, reduzindo o consumo de processamento e memória. Nesta pesquisa, é apresentada uma nova proposta de otimização, e, consequentemente, a implementação computacional usando a linguagem de programação FORTRAN que opera independentemente de qualquer solver. / Doutor

Submitted by JEFERSON BACK VANDERLINDE null (jefersonbv@yahoo.com.br) on 2017-11-01T16:38:25Z No. of bitstreams: 1 jeferson_tese_final_20171101.pdf: 4860852 bytes, checksum: 2f99c37969be3815f82b1b4455a40230 (MD5) / Approved for entry into archive by LUIZA DE MENEZES ROMANETTO (luizamenezes@reitoria.unesp.br) on 2017-11-13T15:38:34Z (GMT) No. of bitstreams: 1 vanderlinde_jb_dr_ilha.pdf: 4860852 bytes, checksum: 2f99c37969be3815f82b1b4455a40230 (MD5) / Made available in DSpace on 2017-11-13T15:38:34Z (GMT). No. of bitstreams: 1 vanderlinde_jb_dr_ilha.pdf: 4860852 bytes, checksum: 2f99c37969be3815f82b1b4455a40230 (MD5) Previous issue date: 2017-09-06 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Neste trabalho, consideram-se a análise teórica e a implementação computacional dos algoritmos Primal Simplex Canalizado (PSC) e Dual Simplex Canalizado (DSC) especializados. Esses algoritmos foram incorporados em um algoritmo Branch and Bound (B&B) de modo a resolver o problema de Planejamento da Expansão de Sistemas de Transmissão (PEST). Neste caso, o problema PEST foi modelado usando os chamados modelo de Transportes e modelo Linear Disjuntivo (LD), o que produz um problema de Programação Linear Inteiro Misto (PLIM). O algoritmo PSC é utilizado na resolução do problema de Programação Linear (PL) inicial após desconsiderar a restrição de integralidade do problema PLIM original. Juntamente com o algoritmo PSC, foi implementada uma estratégia para reduzir o número de variáveis artificiais adicionadas ao PL, consequentemente reduzindo o número de iterações do algoritmo PSC. O algoritmo DSC é utilizado na reotimização eficiente dos subproblemas gerados pelo algoritmo B&B, através do quadro ótimo do PL inicial, excluindo, assim, a necessidade da resolução completa de cada subproblema e, consequentemente, reduzindo o consumo de processamento e memória. Nesta pesquisa, é apresentada uma nova proposta de otimização, e, consequentemente, a implementação computacional usando a linguagem de programação FORTRAN que opera independentemente de qualquer solver. / In this research, the theoretical analysis and computational implementation of the specialized dual simplex algorithm (DSA) and primal simplex algorithm (PSA) for bounded variables is considered. These algorithms have been incorporated in a Branch and Bound (B&B) algorithm to solve the Transmission Network Expansion Planning (TNEP) problem. In this case, the TNEP problem is modeled using transportation model and linear disjunctive model (DM), which produces a mixed-integer linear programming (MILP) problem. After relaxing the integrality of investment variables of the original MILP problem, the PSA is used to solve the initial linear programming (LP) problem. Also, it has been implemented a strategy in PSA to reduce the number of artificial variables which are added into the LP problem, and consequently reduces the number of iterations of PSA. Through optimal solution of the initial LP, the DSA is used in efficient reoptimization of subproblems, resulting from the B&B algorithm, thus excludes the need for complete resolution of each subproblems, which results reducing the CPU time and memory consumption. This research presents the implementation of the proposed approach using the FORTRAN programming language which operates independently and does not use any commercial solver.

[pt] Esta dissertação está estruturada como uma coleção de cinco artigos formatados em capítulos. Os quatro primeiros artigos apresentam contribuições em modelagem e metodológicas para problemas de operação ou investimento em sistemas de potência usando arcabouço de otimização robusta adaptativa e modificações no algoritmo de geração de linhas e colunas (CCGA). O primeiro artigo aborda a programação de curto prazo com restrição de segurança, onde a resposta automática de geradores é considerada. Um modelo robusto de dois estágios é adotado, resultando em complexas instâncias de programação inteira mista, que apresentam variáveis binárias associadas às decisões de primeiro e segundo estágios. Um novo CCGA que explora a estrutura do problema é desenvolvido. O segundo artigo usa redes neurais profundas para aprender o mapeamento das demandas nodais aos pontos de ajuste dos geradores para o problema do primeiro artigo. O CCGA é usados para garantir a viabilidade da solução. Este método resulta em importantes ganhos computacionais em relação ao primeiro artigo. O terceiro artigo propõe uma abordagem adaptativa em dois estágios para um modelo robusto de programação diária no qual o conjunto de incerteza poliedral é caracterizado diretamente a partir dos dados de geração não despachável observados. O problema resultante é afeito ao CCGA. O quarto artigo propõe um modelo de dois estágios adaptativo, robusto em distribuição para expansão de transmissão, incorporando incertezas a longo e curto prazo. Um novo CCGA é desenvolvido para lidar com os subproblemas. Finalmente, sob uma perspectiva diferente e generalista, o quinto artigo investiga a adequação de prêmios de incentivo para promover inovações em aspectos teóricos e computacionais para os desafios de sistemas de potência modernos. / [en] This dissertation is structured as a collection of five papers formatted as chapters. The first four papers provide modeling and methodological contributions in scheduling or investment problems in power systems using the adaptive robust optimization framework and modifications to the column-and-constraint-generation algorithm (CCGA). The first paper addresses the security-constrained short-term scheduling problem where automatic primary response is considered. A two-stage robust model is adopted, resulting in complex mixed-integer linear instances featuring binary variables associated with first- and second-stage decisions. A new tailored CCGA which explores the structure of the problem is devised. The second paper uses deep neural networks for learning the mapping of nodal demands onto generators set point for the first paper s model. Robust-based modeling approaches and the CCGA are used to enforce feasibility for the solution. This method results in important computational gains as compared to results of the first paper. The third paper proposes an adaptive data-driven approach for a two-stage robust unit commitment model, where the polyhedral uncertainty set is characterized directly from data, through the convex hull of a set of previously observed non-dispatchable generation profiles. The resulting problem is suitable for the exact CCGA. The fourth paper proposes an adaptive two-stage distributionally robust transmission expansion model incorporating long- and short-term uncertainties. A novel extended CCGA is devised to tackle distributionally robust subproblems. Finally, under a different and higher-level perspective, the fifth paper investigates the adequacy of systematic inducement prizes for fostering innovations in theoretical and computational aspects for various modern power systems challenges.