Thelma S. P. Fernandes

Load Shedding Strategies Using Optimal Load Flow With Relaxation of Restrictions

This paper proposes an optimization model to minimize the load curtailments necessary to restore the equilibrium of operating point with relaxation of restrictions. This model can be used for the operation planning of electrical power systems. The developed methodology minimizes the load cuts, limiting them to their importance and establishing different stages for them through the relaxation of the minimum limits of voltage and maximum limits of active power flows through the transformers. For instance, when an emergency occurs, if some operational limits are violated for a short period, fewer loads can be cut at a first stage than would be necessary if those violations would not be admitted. If the emergency does not cease, the remaining cuts necessary to recover the violations are made as a second stage of the strategy. On the other hand, if the contingency ceases, within this break, the system is recovered, and at this second stage, unnecessary cuts can be avoided, admitting only small breakings of operational restrictions. This methodology was tested at a system of 291 buses that is equivalent, in heavy load, to the electric network of the State of Parana in Brazil.

Centralized and decentralized approaches to demand response using smart plugs

Residential customers demand generally vary during the day, causing overloads in the distribution system and increasing energy costs. This paper investigates the use of centralized and decentralized scheduling algorithms to help customers adjusting their consumption pattern in demand response programs with Time-Of-Use Tariff. Two algorithms are proposed, one with centralized information from several smart plugs communicating with a Home Automation Controller, and another one, decentralized, running local on each smart plug. The simulations, that used real data from smart plug prototypes from a Brazilian home, indicate that the use of such algorithms can effectively help residential customers achieve Demand-Side Management goals.

Load shedding through optimal power flow to support self-healing actions in distribution feeders

One of the main characteristics of the smart grid is the implementation and development of tools that allow the minimization of system vulnerability as well as an increase in security, reliability and power quality in distribution systems. This paper presents the development of a methodology to support self-healing through demand-side management (load shedding). This methodology allows the self-healing system to restore more loads when compared to traditional methods, through the indication of loads to shed in each bus of the distribution system, taken into account power quality constraints. The methodology was implemented using a Binary Particle Swarm Optimization (BPSO) to self-healing switching determination and Optimal Power Flow (OPF) for the load shedding scheme. The methodology proved to be able to restore more load in an optimal way, minimizing losses and assuring power quality.

Pré-despacho hidrotérmico de potência ativa e reativa via método dos Pontos Interiores e coordenadas retangulares

This article presents the mathematical formulation of the active and reactive power generation pre-dispatch problem, whose objective function is the minimization of thermal plant costs and transmission losses. Bus voltages are represented in rectangular coordinates, transmission limits are imposed through linearized constraints and the optimization problem is solved by the Primal Dual Interior Point Method. The efficiency of the formulation is analyzed in a 5 buses example and an equivalent of the Parana system composed of 291 buses.

Optimal operation of distribution networks with synchronous generators via transient stability constrained optimal power flow

A common approach to deal with transient stability constraints in optimization problems is the combination of a numerical discretization method with interior point methods (IPMs) for solving large-scale nonlinear programming (NLP). The numerical discretization is adopted to convert the differential equations that describe the electromechanical transients in power systems in a set of algebraic equations to be included into a conventional optimal power flow (OPF) problem. The resulting transient stability constrained optimal power flow (TSC-OPF) problem, however, suffers with the curse of dimensionality, high computational time and memory consumption to solve it, even for small systems. To relieve this computational burden, this paper proposes an algorithm that aims at solving a TSC-OPF problem via primal-dual IPM with only a few time steps of numerical discretization in post-fault period, which is enough to ensure the rotor angle first swing stability. Once the TSC-OPF problem is solved, a numerical discretization method is applied to calculate the system trajectory from the first rotor angle peak in post-fault period. An important contribution of the proposed algorithm is to provide a proper accuracy on the computation of constant admittance loads. Numerical results are obtained for a 9-bus distribution network with the purpose of providing a proper sizing of DG units based on synchronous generators and an optimal operation to the network.

Case study on distributed generation for electric vehicle and energy storage integration

This paper presents an integrated system of photovoltaic (PV), energy storage and a charging station for an electric vehicle (EV). The operation mode of the integrated system is controlled by an algorithm which is based on a new Brazilian tariff supported on different prices depending on the hour and the day of the week. It will also be presented a panorama of the distributed generation in Brazil, and the challenges faced during the project and construction of this system.

Inclusão de Energia Eólica no Planejamento da Operação de Curto Prazo com Restrição de Transmissão

Resumo: A energia eólica tem experimentado um grande crescimento no Brasil, pois os grandes potenciais hidrelétricos estão diminuindo levando à diversificação da matriz energética, através de mix de geração com forte predominância hidrelétrica, térmicas e renováveis. Assim, é preciso incorporar nos estudos de planejamento da operação hidrotérmica também a energia eólica a fim de bem utilizar as vantagens de cada tipo de geração.Tendo em vista esta tendência, este trabalho objetiva analisar a influência de se incorporar a geração da energia eólica segunda sua sazonalidade ao longo de mês e ano em um problema de otimização da geração de energia elétrica via Algoritmos Genéticos onde as restrições elétricas são inclusas através do Fluxo de Energia Ótimo que é resolvido mês a mês ao longo do período de 1 ano de planejamento. O método proposto foi testado em um sistema de 34 barras.

Proposta de algoritmo para gerenciamento pelo lado demanda em residências através do corte de smart plugs

Com o aumento da demanda de energia a cada ano e consequentes dificuldades no processo de distribuicao da mesma, e necessidade das concessionarias encontrar saidas para conseguir suprir esse aumento, procurando tecnicas alem do aumento da infraestrutura. Uma dessas saidas e o gerenciamento pelo lado da demanda, que engloba diversas tecnicas incluindo o deslocamento de carga, ou seja, acoes para realizar o deslocamento da utilizacao de equipamentos do horario de pico para outro horario, incentivadas atraves de tarifas variaveis no tempo. Para dar suporte ao cliente nessas acoes, visando beneficios para a concessionaria e tambem reducoes de gastos de energia do cliente, ultimamente vem sido bastante discutida a utilizacao de smart plugs como ferramenta de medicao e de corte, auxiliada por algoritmos que possibilitem a automacao e otimizacao das mesmas. O algoritmo desenvolvido no presente trabalho apresentou resultados satisfatorios, indicando os momentos que o consumidor deve evitar o consumo de energia em cada smart plug assim como auxiliar na reducao do desperdicio de energia, atuando no corte do consumo de aparelhos em standby.