A modern power system is composed of many individual entities collaborating with each other to operate the entire system in a secure and economic manner. These entities may have different owners and operators with their own operating rules and policies, and it complicates the decision-making process in the system. In this work, a system of systems (SoS) engineering framework is presented for optimally operating the modern power systems. The proposed SoS framework defines each entity as an independent system with its own regulations, and the communication and process of information exchange between the systems are discussed. Since the independent systems are working in an interconnected system, the operating condition of one may impact the operating condition of others. According to the independent systems’ characteristics and connection between them, an optimization problem is formulated for each independent system. In order to solve the optimization problem of each system and to optimally operate the entire SoS-based power system, a decentralized decision-making algorithm is developed. Using this algorithm, only a limited amount of information is exchanged among different systems, and the operators of independent systems do not need to exchange all the information, which may be commercially sensitive, with each other. In addition, applying chance-constrained stochastic programming, the impact of uncertain variables, such as renewable generation and load demands, is modeled in the proposed SoS-based decision-making algorithm. The proposed SoS-based decision-making algorithm is applied to find the optimal and secure operating point of an active distribution grid (ADG). This SoS framework models the distribution company (DISCO) and microgrids (MGs) as independent systems having the right to work based on their own operating rules and policies, and it coordinates the DISCO and MGs operating condition. The proposed decision-making algorithm is also performed to solve the security-constrained unit commitment incorporating distributed generations (DGs) located in ADGs. The independent system operator (ISO) and DISCO are modeled as self-governing systems, and competition and collaboration between them are explained according to the SoS framework.

The research work presented in this thesis discusses various complex issues associated with reactive power management and pricing in the context of new operating paradigms in deregulated power systems, proposing appropriate policy solutions. An integrated two-level framework for reactive power management is set forth, which is both suitable for a competitive market and ensures a secure and reliable operation of the associated power system. The framework is generic in nature and can be adopted for any electricity market structure. The proposed hierarchical reactive power market structure comprises two stages: procurement of reactive power resources on a seasonal basis, and real-time reactive power dispatch. The main objective of the proposed framework is to provide appropriate reactive power support from service providers at least cost, while ensuring a secure operation of the power system. The proposed procurement procedure is based on a two-step optimization model. First, the marginal benefits of reactive power supply from each provider, with respect to system security, are obtained by solving a loadability-maximization problem subject to transmission security constraints imposed by voltage and thermal limits. Second, the selected set of generators is determined by solving an optimal power flow (OPF)-based auction. This auction maximizes a societal advantage function comprising generators' offers and their corresponding marginal benefits with respect to system security, and considering all transmission system constraints. The proposed procedure yields the selected set of generators and zonal price components, which would form the basis for seasonal contracts between the system operator and the selected reactive power service providers. The main objective of the proposed reactive power dispatch model is to minimize the total payment burden on the Independent System Operator (ISO), which is associated with reactive power dispatch. The real power generation is decoupled and assumed to be fixed during the reactive power dispatch procedures; however, the effect of reactive power on real power is considered in the model by calculating the required reduction in real power output of a generator due to an increase in its reactive power supply. In this case, real power generation is allowed to be rescheduled, within given limits, from the already dispatched levels obtained from the energy market clearing process. The proposed dispatch model achieves the main objective of an ISO in a competitive electricity market, which is to provide the required reactive power support from generators at least cost while ensuring a secure operation of the power system. The proposed reactive power procurement and dispatch models capture both the technical and economic aspects of power system operation in competitive electricity markets; however, from an optimization point of view, these models represent non-convex mixed integer non-linear programming (MINLP) problems due to the presence of binary variables associated with the different regions of reactive power operation in a synchronous generator. Such MINLP optimization problems are difficult to solve, especially for an actual power system. A novel Generator Reactive Power Classification (GRPC) algorithm is proposed in this thesis to address this issue, with the advantage of iteratively solving the optimization models as a series of non-linear programming (NLP) sub-problems. The proposed reactive power procurement and dispatch models are implemented and tested on the CIGRE 32-bus system, with several case studies that represent different practical operating scenarios. The developed models are also compared with other approaches for reactive power provision, and the results demonstrate the robustness and effectiveness of the proposed model. The results clearly reveal the main features of the proposed models for optimal provision of reactive power ancillary service, in order to suit the requirements of an ISO under today’s stressed system conditions in a competitive market environment.

The research work presented in this thesis discusses various complex issues associated with reactive power management and pricing in the context of new operating paradigms in deregulated power systems, proposing appropriate policy solutions. An integrated two-level framework for reactive power management is set forth, which is both suitable for a competitive market and ensures a secure and reliable operation of the associated power system. The framework is generic in nature and can be adopted for any electricity market structure. The proposed hierarchical reactive power market structure comprises two stages: procurement of reactive power resources on a seasonal basis, and real-time reactive power dispatch. The main objective of the proposed framework is to provide appropriate reactive power support from service providers at least cost, while ensuring a secure operation of the power system. The proposed procurement procedure is based on a two-step optimization model. First, the marginal benefits of reactive power supply from each provider, with respect to system security, are obtained by solving a loadability-maximization problem subject to transmission security constraints imposed by voltage and thermal limits. Second, the selected set of generators is determined by solving an optimal power flow (OPF)-based auction. This auction maximizes a societal advantage function comprising generators' offers and their corresponding marginal benefits with respect to system security, and considering all transmission system constraints. The proposed procedure yields the selected set of generators and zonal price components, which would form the basis for seasonal contracts between the system operator and the selected reactive power service providers. The main objective of the proposed reactive power dispatch model is to minimize the total payment burden on the Independent System Operator (ISO), which is associated with reactive power dispatch. The real power generation is decoupled and assumed to be fixed during the reactive power dispatch procedures; however, the effect of reactive power on real power is considered in the model by calculating the required reduction in real power output of a generator due to an increase in its reactive power supply. In this case, real power generation is allowed to be rescheduled, within given limits, from the already dispatched levels obtained from the energy market clearing process. The proposed dispatch model achieves the main objective of an ISO in a competitive electricity market, which is to provide the required reactive power support from generators at least cost while ensuring a secure operation of the power system. The proposed reactive power procurement and dispatch models capture both the technical and economic aspects of power system operation in competitive electricity markets; however, from an optimization point of view, these models represent non-convex mixed integer non-linear programming (MINLP) problems due to the presence of binary variables associated with the different regions of reactive power operation in a synchronous generator. Such MINLP optimization problems are difficult to solve, especially for an actual power system. A novel Generator Reactive Power Classification (GRPC) algorithm is proposed in this thesis to address this issue, with the advantage of iteratively solving the optimization models as a series of non-linear programming (NLP) sub-problems. The proposed reactive power procurement and dispatch models are implemented and tested on the CIGRE 32-bus system, with several case studies that represent different practical operating scenarios. The developed models are also compared with other approaches for reactive power provision, and the results demonstrate the robustness and effectiveness of the proposed model. The results clearly reveal the main features of the proposed models for optimal provision of reactive power ancillary service, in order to suit the requirements of an ISO under today’s stressed system conditions in a competitive market environment.

[pt] Atualmente a metodologia correspondente ao estado da arte utilizada para o planejamento de médio-/longo-prazo da operação de sistemas elétricos de potência é a Programação Dual Dinâmica Estocástica (PDDE). No entanto, a tratabilidade computacional proporcionada por este método ainda requer simplificaçõeses consideráveis de detalhes de sistemas reais de maneira a atingir performaces aceitáveis em aplicações práticas. Simplificações feitas no estágio de planejamento em contraste com a implementação das decisões podem induzir políticas temporalmente inconsistentes e, consequentemente, um gap de sub-otimalidade. Inconsisência temporal em planejamento hidrotérmico pode ser induzida, por exemplo, ao assumir um coeficiente de produtividade constante para as hidrelétricas, ao agregar os reservatórios, ao negligenciar a segunda lei de Kirchhoff e neglienciando-se critérios de segurança em modelos de planejamento. As mesmas restrições são posteriormente consideradas na etapa de implementação do sistema. Esse fato pode estar envolvido com esvaziamento não planejado de reservatórios e entregabilidade inadequada de reservas girantes. Ambos podem levar a altos custos operacionais. Além disso, o sistema pode ficar exposto a um risco sistêmico de racionamento e em última instâcia, blackouts. O gap de sub-otimalidade pode também levar a distorções em mercados de energia. Assim, é razoável que as consequências da inconstência temporal em sistemas hidrotérmicos sejam estudadas. Nesse sentido, este trabalho propõe uma extensão de trabalhos já realizados relacionados à inconsistência temporal para medir os efeitos de simplificações de modelagem em modelos de planejamento resolvidos pela PDDE. A abordagem proposta consiste em usar um modelo simplificado para o planejamento do sistema, que é feito pela avaliação da função de recurso, e um modelo detalhado para a sua operação. Estudos de caso envolvendo simplificações em modelagem de linhas de transmissão e critérios de segurança são realizados. No entanto, o foco deste trabalho se dará na segunda fonte, já que a mesma apresenta maior complexidade na caracterização do efeito. No entanto, a incorporação de critérios de segurança é um grande desafio para operadores de sistemas elétricos, pois o tamanho do modelo tende a crescer exponencialmente quando critérios de segurança reforçados são aplicados. Motivado por isso, o principal objetivo deste trabalho é propor uma nova abordagem ao problema que permite que critérios de segurança possam ser incorporados em modelos de planejamento e consequentemente garantir a entregabilidade de reservas em políticas de planejamento. A formulação do problema é uma extensão multiperiodo e estocástica the modelos de Otimização Robusta Ajustável que já foram propostos na literatura para resolver o problema relacionado à dimensionalidade para um período. A metodologia de solução involve um algoritmo híbrido Robusto-PDDE que por meio do compartilhamento de estados de contingência ativos entre os períodos e cenários de afluência é capaz de atingir tratabilidade computacional. Com a nova abordagem proposta, é possível (i) resolver o problema de agendamento ótimo das reservas em sistemas hidrotérmicos garantindo a entregabilidade das reservas em um critério n - K e (ii) calcular o custo e os efeitos negativos de se negligenciar critérios de segurança no planejamento. / [en] The current state of the art method used for medium/long-term planning studies of hydrothermal power system operation is the Stochastic Dual Dynamic Programming (SDDP) algorithm. The computational savings provided by this method notwithstanding, it still relies on major system simplifications to achieve acceptable performances in practical applications. Simplifications in the planning stage in contrast to the actual implementation might induce time inconsistent policies and, consequently, a sub-optimality gap. Time inconsistency in hydrothermal planning might be induced by, for instance, assuming a constant coefficient production for hydro plants, reservoir aggregation, neglecting Kirchhoff s voltage law, and neglecting security criteria in planning models, which are then incorporated in implementating models. Unaccounted for reservoir depletion and inadequate spinning reserve deliverability situations that were observed in the Brazilian power system might be induced by time inconsistency. And this can lead to higher operational costs. Both these consequences are utterly negative since they pose the system to a great systemic risk of energy rationing or ultimately, system blackouts. In addition, the suboptimility gap may also lead to energy markets distortions. Hence, it seems reasonable that further investigations on consequences of time inconsistency in hydrothermal planning should be undertaken. Along these lines, this work proposes an extension to previous work on the subject of time inconsistency to measure the effects of modeling simplifications in the SDDP framework for hydrothermal operation planning. The approach consists of using a simplified model for planning the system, which is done by means of the assessment of the recourse (cost-to-go) function, and a detailed model for its operation (implementation of the policy). Case studies involving simplifications in transmission lines modeling and in security criteria are carried out. Nevertheless, the focus of this work is on the later source as it is more difficult to address due to the complexity involved in the characterization of this effect. However, incorporating security criteria in planning models poses a major challenge to system operators. This is because the size of the model tends to grow exponentially as tighter security criteria are adopted. Motivated by this, the main objective of this work is to propose a new framework that allows security criteria to be incorporated in planning models and consequently ensure reserve deliverability in planning policies. The problem formulation is a multiperiod stochastic extension of Adjustable Robust Optimization (ARO) based models already proposed in literature to successfully address the dimensionality issue regarding the incorporation of security criteria n - K and its variants. The solution methodology involves a hybrid Robust-SDDP algorithm that by means of sharing active contingency states amongst periods and possible inflow scenarios in the SDDP algorithm is capable of achieving computational tractability. Then, with the proposed approach it is possible to (i) address the optimal scheduling of energy and reserve in hydrothermal power systems ensuring reserve deliverability under an n - K security criterion and (ii) assess the cost and side effects of disregarding security criteria in the planning stage.