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This work describes a method for optimization criteria weighing in a dynamic optimal power flow that determines the following types of hydrothermal dispatch: monthly and weekly discretized by load levels and daily discretized by hours. This dynamic optimal power flow is used along with a formulation that determines medium-, short- and very short-term hydrothermal dispatch. It adopts a detailed representation of all hydroelectric and thermoelectric plants and includes electrical restrictions for the Brazilian interconnected system. The optimization criteria considered are as follows: minimization of the thermal operation cost, the deficit cost, the electrical losses, minimization of the power flow through the interchange lines and the deviation of thermal power concerning the targets provided by an energetic problem. These targets are previously computed and aim at attending to the energy demand, minimizing the fuel and deficit costs. Concomitant consideration of these optimization criteria requires analysis of the best combination of weights associated with each portion of the objective function. The applied method uses an effort versus impact matrix to assist a combination of weights that meet pre-established criteria, as well as to normalize the results of each portion to better characterize the performance of each of them in solving the problem. The use of this method is part of an ANEEL R&D project, proposed by COPEL, PD-06491-0307-2013, which provides for large-scale optimization applied to the Brazilian hydrothermal dispatch. The weighing process described was tested for the PAR-ONS case for the year 2020 (winter), which has 6812 buses and 9921 lines.

Distribution networks are suffering a transformation process with the insertion of distributed energy resources, changing from a passive part of the power grid into an active system. Aiming to reduce the challenges for the distribution system operators to keep the power grid operating inside of the quality levels it is possible to propose some ancillary services. Optimum Power flow is an optimization method used to plan the distribution grid operation. Additionally, the distributed energy resources can be modeled on it and ancillary services provisioning can be considered, as proposed in this work. In this way, the objective of the present work is to formulate a Multiperiod Optimum Power Flow (MPOPF) with the insertion of distributed generation, energy storage systems, microgrids, and electric vehicles at the distribution grid. This MPOPF considers the provisioning of ancillary services by the inverters associated with the equipment connected to the main grid. In the formulation, the entire grid is modeled, considering the placement of classic equipment as a voltage regulator and capacitor banks, in addition to modern technologies as DFACTS (Distribution - Flexible AC Transmission System) and four-quadrant inverters. The MPOPF was simulated for several scenarios considering a 90-bus test feeder and a real distribution grid from Curitiba – Brazil. From the results, the MPOPF proved to be highly robust, being able to simulate the grid with all the equipment connected simultaneously, performing the optimal dispatch of active and reactive power, as well as allowing the operation of ancillary services such as voltage support, peak-shaving, and demand-side management.

Dentre os estudos realizados na fase de planejamento da operação de sistemas elétricos, tem os que visam aplicar adequadamente equipamentos que promovam a qualidade da energia elétrica entregue aos consumidores. No conjunto dos diversos equipamentos disponíveis, este trabalho aponta para a alocação ótima de religadores automáticos simplificados (RASs) em redes de distribuição. Para tanto, formula um problema de otimização (resolvido via Algoritmos Genéticos) que visa otimizar vários índices de qualidade da energia elétrica ao menor custo de investimento. Assim, a função multiobjetivo maximiza os custos evitados por multas aplicadas pelo regulador, minimiza o custo de instalação, manutenção e operação dos RASs, maximiza a priorização na instalação em locais com índices de falha elevado e minimiza o tempo do retorno de investimento. Os resultados obtidos foram simulados utilizando o sistema IEEE-123 barras.

Este trabalho descreve uma metodologia aplicada para ponderação de critérios de otimização que compõem um Fluxo de Potência Ótimo Dinâmico (FPOD) que determina despacho hidrotérmico mensal discretizado por patamares de carga. Esse FPOD é utilizado em formulação que determina despacho hidrotérmico de médio prazo não linear, com modelagem estocástica e que adota representação detalhada de todas as usinas hidroelétricas e termoelétricas e inclui restrições elétricas do sistema interligado brasileiro. Os critérios de otimização considerados no FPOD são os seguintes: minimização do custo de geração das usinas térmicas, do custo de déficit, das perdas elétricas, minimização de fluxo de potência nas linhas de intercâmbio e do desvio de potência térmica em relação ao fornecido pelo problema energético. A consideração concomitante desses critérios de otimização requer análises quanto a busca da melhor combinação dos pesos associados a cada parcela da função objetivo. A metodologia aplicada utiliza matriz de esforço versus impacto para auxiliar na obtenção da melhor combinação de pesos que atendem critérios pré-estabelecidos, como também normaliza resultados de cada parcela a fim de melhor caracterizar a atuação de cada uma delas na solução do problema. A utilização dessa metodologia faz parte de um projeto de P&D ANEEL, proposto pela COPEL, PD-6491-0307/2013, que prevê otimização em larga escala aplicada ao despacho hidrotérmico brasileiro. O processo de ponderação descrito foi testado para o caso PAR-ONS referente ao ano de 2017 (inverno) que possui 6352 barras e 9269 linhas para cada patamar de carga.

This study describes a methodology to solve the multi-period distribution expansion planning problem considering reliability, distributed generation (DG), capacitor and switch placement in the context of smart grids. The developed computational model is formulated as a mixed integer nonlinear optimisation problem and solved through the combination of meta-heuristics, stochastic simulation methods (Monte-Carlo simulation), and application of optimal power flow. The main objectives of this optimisation problem are defining the best choice to install power system components and determining the installation period and size of components to minimise investment cost while maximising system reliability. The proposed method was implemented in a modified version of the IEEE-RBTS bus 2 and in a 90-bus test system. The obtained results show a reduction of >20% of the operating cost and >70% of the average interruption time. In addition, it was performed scenarios not including DG, self-healing, and reliability analysis, individually. The analyses show the impact in the results by including a new variable in the expansion planning, increasing up to 40% in the fitness function value. Furthermore, it is presented with a discussion of the impact of the method to estimate the reliability indexes on the optimisation process.

The development of electricity distribution networks has affected their planning and operation, requiring more specialized studies such as three-phase analyses that allow the inclusion of unbalanced loads and the mutual impedances of power cables. These more detailed modeling approaches allow a better understanding and control of the factors related to power quality such as losses and maintenance of the voltage profile and power factor. These quality issues can often be addressed using the appropriate allocation of capacitor banks and voltage regulators. This paper proposes an optimization approach for allocating these devices using a metaheuristic technique to improve the quality of the power supply in the context of unbalanced three-phase power grids. The optimization problem is solved via binary particle swarm optimization. The load flow analysis is carried out using OpenDSS software, which allows the modeling of unbalanced three-phase topologies. The mathematical formulation proposed is tested using an IEEE-34 and IEEE-123 system bus.

The world energy matrix has diversified and has become a mix of hydroelectric, thermoelectric and renewable sources, such as wind energy. However, wind power is uncertain and variable, and its random intermittence leads to great challenges in coordinating it with a large hydrothermal system, for example. These questions require increased availability of spinning reserve as a solution to reduce the risk of deficit in moments when there is no wind power generation. This spinning reserve must be appropriately allocated between the hydraulic and thermal generating units so that, when necessary, they will be available and operational. To carry out this adequate allocation, besides considering the conventional operational limits of a problem of generation dispatch, it is also necessary to take into consideration the limits of the interchange lines that connect the subsystems that compose the electric network. So, in cases of congestion of these transmission lines, the subsystem itself can supply its spinning reserve under different hydrological conditions. Thus, this work proposes a mathematical formulation to dispatch power generation and allocate spinning reserve simultaneously, considering different hydrological day-ahead conditions. To do this, a nonlinear and dynamic optimal power flow is modeled, which, in addition to performing the active and reactive power dispatch of a hydrothermal system (including electrical and energy restrictions) for a day-ahead horizon, is also capable of carrying out an optimal allocation of the spinning reserve (hydraulic and thermal). The model is tested using a system of 33 buses to represent the system of the southern region of Brazil.

The growth of photovoltaic systems (PV) and battery energy storage systems (BESS) will become a challenge for distribution players. In this way it is important to understand how these systems can impact on the distribution grid operation. For this, a study was developed considering the insertion of PV on IEEE 13 buses test feeder, based on different penetration levels. These levels were calculated contemplating two different parameters: the one most used in Brazil, and the parameter that consists in an extended criterion used worldwide. Considering these possibilities, different penetration levels of photovoltaic were defined. In conjunction with photovoltaic generation, a BESS was inserted in the same feeder, in order to evaluate the impacts of this system. From the simulations was possible to evaluate the tap changes, the voltage profile, power losses and the total energy, including if there was reverse power flow at any moment during one day.

This paper proposes an expeditious methodology that provides hourly assessments of the effect of intermittent wind and solar power generation on the electrical quantities characterizing power systems. Currents are measured via circuit breakers to confirm the correct sizing of devices based on their rated currents. Nodal voltage magnitudes are assessed for compliance with limits imposed by regulatory authorities, whereas the active power produced by hydroelectrical generators is assessed for reserve energy. The proposed methodology leverages a fuzzy extended deterministic optimal power flow that uses in power balance equations the average hourly values of active power generated by wind and solar sources as well as hourly energy load. The power grid is modeled at the substation level to directly obtain power flow through circuit breakers. Uncertainties in power system electrical quantities are assessed for an optimal solution using a Taylor series associated with deviations from the average values of the active power produced by the wind and solar sources. These deviations are represented using a fuzzy triangular model reflecting the approximations of the probability density functions of these powers. The methodology takes into account a subjective investigation that focuses on the qualitative characteristic of these energy sources&rsquo, behaviors.

This paper models a three-phase optimal power flow applied to distribution networks. The objective function is to minimize electrical losses, the restrictions of which are the maximum and minimum levels of active and reactive power supplied the voltage magnitudes, and taps of voltage regulators with consideration of the mutual impedances of cables. In order to gain numerical stability, the voltage phasor is represented by the rectangular form. The optimization problem is solved by the Interior Points Method version Primal–Dual, whose importance to the planning of distribution networks is tested using the IEEE-123 system bus.

The operation planning of the Brazilian power system is a great challenge due to its size of continental dimensions, large seasonal variations, and predominantly hydroelectric nature. Its operation requires careful planning to reconcile conflicting goals such as spill minimization during the rainy season, and minimization of generation deficits during the dry season, i.e., operation risk minimization. The optimization models for hydrothermal systems currently used to operate large systems do not include the electric network when determining the energy goals. This work aims at modeling a hydrothermal dispatch problem by means of genetic algorithms. The electrical constraints are included by an optimal power flow, which is solved monthly over the planning horizon. The fitness function is composed of criteria that look for using the reservoirs as much as possible during the rainy season, thus, minimizing spills and production costs and, at the same time, catering for the load and limits of energy exchange between the subsystems. The methodology was tested using the 33-bus system.

O constante crescimento do parque gerador exige analise continua dos niveis de corrente de curto-circuito que circulam pelos disjuntores instalados nas subestacoes a fim de sinalizar os que estao superados. Os metodos existentes para calculo das correntes de curto-circuito utilizam o convencional modelo barra-ramo, que nao fornece diretamente os valores de corrente de curto-circuito que circulam internamente pelos disjuntores que compoem as subestacoes. Ja o metodo no nivel de secao de barra modela a configuracao dos disjuntores nas subestacoes e permite a analise direta dos mesmos. Assim, este artigo tem como objetivo analisar e comparar a influencia da representacao no nivel de secao de barras com a tradicional representacao barra-ramo em estudos de superacao de disjuntores, utilizando para tanto as normas do Operador Nacional do Sistema referentes a superacao de disjuntores. Os sistemas analisados sao de 5 e 291 barras.

This paper proposes an extension of the traditional mathematical formulation of short-circuit analysis in order to make it able to process networks modeled at bus-section level. Differently from the existing methodology for calculating short-circuit currents, which is based on the conventional bus-branch network model, the proposed approach processes networks modeled at the physical level, allowing the direct determination of short-circuit currents through closed-circuit breakers. For this purpose, the current through circuit breakers is included in the problem as a new state variable. Besides, information regarding the closed status position of circuit breakers is taken into account as additional linear equations, producing a non-redundant set of algebraic equations. The proposed approach provides an efficient tool for directly determining the short-circuit current flowing through circuit breakers into a selected substation of the network, avoiding unreliable artifices and tedious post-processing procedures required by the existing methodology, which is based on the bus/branch model. Simulations conducted on a five-bus test system and a 291-bus test system are used to illustrate the proposed methodology.

Overhead transmission lines are exposed to several risks associated with its surroundings, changes in design characteristics and climatic variations. Many times, these risks can lead to serious damages, incurring in drop towers. So, this work has the objective of evaluation of the susceptibility of the structures to suffer mechanical efforts above the projected, which can lead to their falls. It is made taking the database of the structures and information about the ones that had suffered damages and using the Rough Sets Theory and the Regression Logistic Method to extract knowledge about what parameters and variables influence the mechanic behavior of the operation lines and can be applied to diagnose possible dropped towers. The results are obtained using the history of two thousand steel structures currently operating in the state of Parana, from which rules are generated to identify the susceptibility of fall.

One of the alternatives to reduce costs in a power system is the application of distributed generation (DG). Although inherent flexibilities of DG, the point of connection must be carefully chosen in order to avoid any hazardous impact. Normally, this choice is based on loss minimization, improvement of the voltage profile and reduction of the power flows through the lines. The search field of this problem is vast. In order to diminish it, this article assumes that only some buses of the network are candidates to the connection. Thus, one of the main objectives of this work is the proposition of a sensitivity analysis that indicates the best buses to realize the connection. Due to peculiarities of this proposed analysis, the voltage phasor is represented by the rectangular form. To test it, a conventional allocation’s methodology is implemented and solved using genetic algorithms (GA) together with an optimal power flow (OPF). A purely radial feeder of one distribution company in Brazil, with 2678 buses and a typical network of 70 buses are chosen to present the results of the methodology.

Banks of capacitors (BCs) at distribution systems are used to compensate the reactive energy of the network, reduce electric losses and improve the voltage profile. The planning and operation of BCs includes the determination of ideal allocation of them at the distribution network, defining its type, size and adjustments. Considering that the loads undergo variations during the operation time, fixed decision of input/output of the BCs may not be enough to provide the necessary reactive compensation. Therefore, the main objective of this work is to develop a heuristic to adjust the switching of the automatic BCs. This heuristic uses the results of a Parametric Optimal Power Flow that minimizes the electric losses and controls voltage profile along the feeders of the distribution network. The results are presented using a system of 70 buses.

The high reactive power level demanded by the distribution systems, the loads growth and consequent increase of system losses introduce variations at the buses voltage magnitudes, which compromise the quality of the supplied electric energy. To assure high quality, some devices such as voltage regulators – VRs and capacitors banks – CBs, are installed to allow effective control of voltage magnitude, reactive power and power factor. The present work proposes a methodology to allocate simultaneously these devices using both Genetic Algorithms – GAs and Optimal Power Flow – OPF. The strategy proposed involves the adoption of GA for the allocation of CBs with specification for the type of bank (fixed or automatic) and the reactive power (kvar), as well as the allocation of VRs with adjustment of their secondary voltage. The OPF is responsible for the solution of the power balance equations, tap adjustments of the VRs that assure the voltage level at their exits according to the voltage level specified by the GA for the diverse load curve and for the attainment of the nominal current of the VRs allocated.

This work presents an optimization model to allocate TCPST at congested transmission systems. The problem was resolved by the Genetic Algorithms (GA) together with an optimal power flow (OPF). The proposed strategy used the GA to make the allocation of the TCPST and the OPF to obtain the load flow solution and optimal adjustments of the phase shifter’s taps. The mathematical formulation of the methodology is based on installation’s costs of the equipment and total system overload minimization. In order to diminish the search field a methodology to elect the most favorable substations to the devices allocation was considered. This methodology was tested at a 291 bus system that is equivalent, in heavy load, to the electric network of the State of Parana in Brazil.

This paper presents a non-linear model that characterizes the steady state behavior of a system through power balance equations derived for network users. In the formulation, a network user may be a particular generator or load, a power company, a bilateral or multilateral transaction or the pool. By means of a parameter variation, different models are employed to represent network users, starting with ideal current sources and evolving to ideal voltage sources. Currents and voltages allocated to every user vary according to the user modeling and are tracked throughout the parameter variation, providing means to determine the best representation for network users. Results for a 2-bus example and an equivalent of the Brazilian Southern Region system are presented and validated.

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.

This work proposes an optimization model for the power dispatch under a pool-bilateral market. In it, all transactions and also the power traded in the spot market are separated into different networks according to the corresponding current injections. Using the superposition principle (SP), a set of network equations is assigned to every transaction and also to the power injections related to the pool (spot market). The model comprises all network equations and also inequalities representing operational limits. A primal-dual interior-point method is used for the resolution of the optimization problem. The line currents, complex voltages, and power generation associated with every transaction and with the spot market are obtained. Results are presented for a 5 bus and the IEEE 118 bus systems.

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.

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.

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.

Este artigo apresenta a formulação matemática de um problema de pré-despacho de geração de potência ativa e reativa no qual a função objetivo engloba minimização dos custos de usinas térmicas e minimização das perdas elétricas na transmissão. A representação do fasor tensão é feita em coordenadas retangulares, consideram-se os limites de transmissão utilizando a formulação linearizada e o problema de otimização é resolvido pelo Método de Pontos Interiores versão Primal-Dual. A eficiência da formulação é testada utilizando-se o sistema de 5 barras e o sistema de 291 barras que representa o sistema elétrico reduzido do estado do Paraná. 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 Paraná system composed of 291 buses.