Paulo Augusto Nepomuceno Garcia

A New Distribution System Reconfiguration Approach Using Optimum Power Flow and Sensitivity Analysis for Loss Reduction

This paper presents a new approach for distribution system reconfiguration (DSR) based on optimum power flow (OPF) in which the branch statuses (open/close) are represented by continuous functions. In the proposed approach, all branches are initially considered closed, and from the OPF results, a heuristic technique is used to determine the next loop to be broken by opening one switch. Then the list of switches that are candidates to be opened is updated, and the above process is repeated until all loops are broken, making the distribution system radial. This paper includes results and comparisons on test systems utilized in three classical papers published in the technical literature, as well as in a previous paper by the authors. Results obtained on a real large-scale distribution system are also presented

Three-Phase Power Flow Based on Four-Conductor Current Injection Method for Unbalanced Distribution Networks

This work presents a new formulation for the power flow problem, with explicit representation of the neutral conductor and grounding. This methodology has been named the four-conductor current injection method (FCIM). The Newton-Raphson method is applied to solve the set of nonlinear current injection equations that are derived using phase coordinates, and the complex variables are written in rectangular form. The proposed algorithm can be used to analyze both balanced and unbalanced systems, meshed or radial, with controls and distributed generation, and is shown to be very efficient and robust for large scale systems.

Improvements in the representation of PV buses on three-phase distribution power flow

This letter describes a new voltage controlled bus (PV bus) representation in connection with the three-phase current injection method-TCIM of power flow analysis. This representation requires an augmented system of linearized equations to incorporate the reactive power as a dependent variable. Tests and comparisons between the former and the new approach are described and the improved stiffness of this new proposition is demonstrated.

A Comparative Study on the Performance of TCIM Full Newton versus Backward-Forward Power Flow Methods for Large Distribution Systems

This panel discussion summarizes performance comparisons between the well-known backward-forward sweep and a Newton load-flow algorithm when applied to large scale three-phase distribution systems. The three-phase current injection method-TCIM, applies the full Newton method to solve the nonlinear current injection equations which are derived using phase coordinates, and the complex variables are written in rectangular form. This summary intends to discuss simulation results obtained using some practical large scale distribution systems

Four wire Newton-Raphson power flow based on the current injection method

This work presents a new formulation of three-phase, four wire power flow Newton-Raphson method based on the current injection method at every node of the power system that can be expressed in terms of series and shunt connections. The proposed technique is advantageous because both neutral wires and earth impedance can be explicitly be represented.

Power Factor Correction on Distribution Networks Including Distributed Generation

This paper describes the mathematical formulation and implementation of a procedure to design power factor correction in unbalanced distribution systems. The methodology is based on the Four-Conductor Current Injection Method - FCIM, that applies the Newton-Raphson method to solve the power flow problem on four-conductor distribution systems. The set of nonlinear current injection equations are derived using phase coordinates, and the complex variables are written in rectangular form. The mathematical formulation can be especially useful in systems having distributed generators such as induction machines, as well as in systems feeding large industrial consumers. Some test systems are used to demonstrate the effectiveness of the method.

A multiple kernel classification approach based on a Quadratic Successive Geometric Segmentation methodology with a fault diagnosis case

This work presents a new approach for solving classification and learning problems. The Successive Geometric Segmentation technique is applied to encapsulate large datasets by using a series of Oriented Bounding Hyper Box (OBHBs). Each OBHB is obtained through linear separation analysis and each one represents a specific region in a patterns solution space. Also, each OBHB can be seen as a data abstraction layer and be considered as an individual Kernel. Thus, it is possible by applying a quadratic discriminant function, to assemble a set of nonlinear surfaces separating each desirable pattern. This approach allows working with large datasets using high speed linear analysis tools and yet providing a very accurate non-linear classifier as final result. The methodology was tested using the UCI Machine Learning repository and a Power Transformer Fault Diagnosis real scenario problem. The results were compared with different approaches provided by literature and, finally, the potential and further applications of the methodology were also discussed.

Distribution system state estimation using phasor measurement units

This paper presents a new methodology to solve for the state estimation problem in radial distribution networks. The state estimation process is formulated as a constrained optimization problem in which the non-monitored loads are represented by a set of bounded inequality constraints. The branch currents in rectangular coordinates are chosen as state variables. The set of measurements considered are currents and voltages from the PMUs as well as the zero current injections at the no-load buses. The objective function to be minimized is defined as the weighted least square measurements errors. The methodology is validated through simulations on some IEEE radial test feeders.

Static load model adjustment using fuzzy logic and differential evolution

This paper discusses the use of a hybrid system in the field of Computational Intelligence in order to refine the measurement dataset used for determination of the parameters for static load models in Electric Power Systems (EPS). The objective is reducing the effects of natural fluctuation observed in measurement dataset resulting from random loading aggregation and disaggregation on the system under study. Specifically, it is used a fuzzy logic system for processing the filtering of measurement data obtained in the field. It is also important to note that the used approach makes the adjustment of the membership functions of a fuzzy linguistic variables using a meta heuristic called differential evolution. As a result, it is possible to get parameters both for ZIP and Exponential models with mean errors lower than those obtained with raw measurement dataset. The validation of this proposal uses measures that have been made at a CEMIG utility substation in Minas Gerais state, Brazil.

Metodologia heurística construtiva para alocação de bancos de capacitores em sistemas de distribuição de energia elétrica

This paper presents a heuristic constructive algorithm to solve the discrete capacitor size and allocation problem in distribution systems. Initially the discrete nature of the capacitor allocation problem is mitigated by using a sigmoid function in the [0,1] interval which is incorporated into the optimum power flow (OPF) through modifications in the power flow equations. The proposed algorithm uses the primal-dual interior point technique to solve the OPF problem. Finally, the sensitivity obtained by sigmoid function which is weighted by the reactive loading of the distribution system, determines step by step the location, size and number of capacitors to be installed in the distribution system. The proposed technique is applied in two distribution systems. The results obtained are compared with the ones obtained using the genetic algorithm.