Leonardo W. de Oliveira

Power system stabilizers tuning using bio-inspired algorithm

This paper presents a methodology for coordinated tuning of power system stabilizers taking into account a set of pre-specified operating conditions. The tuning procedure is formulated as an optimization problem which aims to maximize the system damping ratio. The proposed methodology is based on the bio-inspired Modified Cuckoo Search method. The methodology is applied for coordinated stabilizer tuning to New England test system. The results obtained are compared with a genetic algorithm approach.

Influência da variação da produtividade das usinas hidroelétricas no cálculo da energia firme

In the present work, the problem associated to the firm energy evaluation is treated as a non linear optimization model, which allows the representation of the productivity variation of the hydro plants. The proposed model takes into account the individualized representation of the plants and the historical series of flows since the month of January of 1931. The proposed optimization problem will be solved using the Primal-Dual Interior Point Method. A case study will be presented including the Brazilian Interconnected National System. The results obtained show that the proposed methodology is promising, since it presents an energy market value more realistic when compared with existing methodologies.

Non-convex Economic Dispatch using Trelea Particle Swarm Optimization

Based in the importance of the Economic Dispatch for operation and planning of power systems, this paper presents the Trelea Particle Swarm Optimization method (Trelea-PSO) applied to this issue. In this paper the ED problem is modeled considering the valve-point effects and multiple fuels, though a non-convex function. Study cases composed of two 10 thermal generators systems are presented to validate the proposed methodology. The results obtained was compared to others presented in literature.

Application of Robust Optimization Technique to the Energy Planning Problem

The present work proposes an approach based on the application of the robust optimization technique named column-and-constraint generation (C&CG), for solving the problem of energy planning comprising the minimization of the thermoelectric dispatch cost during a daily operation of a system with wind and hydraulic generation. In order to define the hourly dispatch of thermoelectric generation, the approach considers a history of flow for the hydraulic generation, as well as uncertainties over the wind behavior in the wind power plant. Thus, the short-term energy planning is defined by taking into account the wind stochastic through the concept of uncertainties. As solving proposal, linear programming with a robust optimization (RO) mathematical technique through the C&CG algorithm is used. This method is applied to divide the global problem into wind speed uncertainties scenarios.

Real Time simulation of PV System integration to the distribution grid using dynamic load model

Nowadays, the insertion of Distributed Generation (DG) on electrical distribution systems has been motivated due to environmental, technical and economical issues. Sources of DG allow an offer of energy generation next to consumers through the conversion of low carbon energy sources. Although DG may collaborate on the reduction of technical losses in the system, the insertion of renewables to the electrical grid can affect the protection and also stability of the grid. Therefore, the development of computational tools to evaluate and analyze positives and negatives impacts of renewables in the distribution system is very important. In this context, the following paper suggests an analysis of DG impacts using Real Time Digital Simulation (RTDS) equipment. A simulation using an IEEE 13 node test feeder has been implemented, and tested with the presence of two photovoltaic arrays acting as mini generation. Residential, commercial and industrial load profiles as well as irradiation curves have been modeled according to real data parameters. Results show the effect of the power injected into the grid in all three load-type situations.

Collision Avoidance for Multi-robot Systems with Coincident Paths Based on Fictitious Collision Points Using Nonlinear Formulation

This paper addresses the problem of collision avoidance along specified paths in multiple mobile robot systems. These collisions can be represented by points of intersection or coincident segments between paths. The proposal of the work is to model these segments where the collision is possible through fictitious points. In addition, the advantages of the nonlinear versus mixed integer linear formulation, widely used in the literature, are verified. Comparisons were made and it’s proved the superiority of the proposed method with respect to complexity, computational time and inclusion of nonlinear constraints. Moreover, the simulations performed using this technique indicate that the method is promissory for applications in real systems.

Distribution Systems Reconfiguration for Voltage Stability Maximization by using Artificial Immune Systems

This paper proposes a methodology for reconfiguration of Electrical Distribution Systems EDS to maximize the system voltage stability. The proposed approach is based on the metaheuristic and bioinspired optimization technique called Artificial Immune System AIS and stability indexes. The optimization problem presents operational and network constraints, as well as the radial and connected operation and the nodal voltage limits. Comparisons between two indexes are made for evaluate their impact on the reconfiguration problem. Three case studies are presented to assess the proposed approach and the stability indexes.

Optimal restoration of power distribution system through particle swarm optimization

This paper proposes an approach for optimal restoration of radial power distribution networks after an incident. This complex problem requires a decision-making process whose combinatorial nature can avoid the assessment of all possible solutions. Thus, the proposed approach is based on a binary coding particle swarm optimization (PSO) tool for handling the discrete variables associated with the switching decisions. The restoration process involves a multi-objective reconfiguration model whose objectives are maximizing the supplied loads and the voltage regulation, with minimal power loss and switching maneuvers. Two case studies are introduced.

Power distribution systems planning with distributed thermal and wind generation

This paper presents a new approach for distribution systems planning with thermal and wind distributed generation (DG). This approach determines the optimal placement of biomass-based thermal and wind distributed generation aiming at minimizing the energy loss, emissions and the total investment and operation costs, as well as improving the voltage regulation. The costs for the purchased energy from grid and thermal generation based on biomass resource are considered. The wind power is given by pre-established nominal power and capacity factor. To solve the mixed integer nonlinear problem, a genetic algorithm (GA) with embedded optimal power flow (OPF) tool is proposed. The OPF is used to determine the size of the thermal generators. Results are presented for well-known systems from literature.

Inclusão de restrições dinâmicas no problema de planejamento de potência reativa

This paper presents a new methodology for power systems operation planning in which dynamic constraints related to the rotor shaft impacts are incorporated into the optimal power flow problem. In this new model the transients at the instant of the contingency is incorporated to the OPF problem, as an additional constraint, in order to keep the rotor shaft torques within limits, which are recommended by the National System Operator (ONS). Then the traditional problem of reactive power planning in electrical power systems includes the generator rotor shaft impact effects when a contingency is present. The problem is formulated using the primal-dual interior point technique associated to the mathematical Benders decomposition. Case studies using the IEEE-14 and IEEE-118 bus test systems are presented to show the effectiveness of the proposed methodology.