This paper proposes a vector-controlled distributed generator (DG) model for a power flow based on a three-phase current injection method (TCIM). In order to represent the DG models in the power flow, steady-state phase current output equations are formulated. Using these equations, the TCIM power flow formulation is modified to include the DG models. In the proposed power flow, a DG-connected ...

In this paper an optimal placement of photovoltaic systems (PV) as a source of active and reactive power in radial distribution networks is considered. The objective function of this problem is minimizing system losses and improving voltage profile. Genetic Algorithm (GA) implemented for this purpose. Photovoltaic solar systems can be used as STATCOM for voltage regulation and power factor corr...

This paper presents an application of elitist non-dominated sorting genetic algorithm (NSGA-II) for solving a multi-objective reactive power market clearing (MO-RPMC) model. In this MO-RPMC model, two objective functions such as total payment function (TPF) for reactive power support from generators/synchronous condensers and voltage stability enhancement index (VSEI) are optimized simultaneous...

This paper proposes, an efficient variant of particle swarm optimization (PSO) to solve the multi-objective optimal reactive power flow (ORPF) based flexible AC transmission system (FACTS) using multi STATCOM Controllers by adjusting dynamically their parameters setting. Two objectives function are considered (power loss and voltage deviation) to validate the robustness of the proposed approach...

In this paper, the reconfiguration of distribution networks in order to optimize several aspects of its operation is presented. The proposed methodology based on genetic algorithms finds the optimal reconfiguration for networks which have a radial topology, taking in consideration the expected occurrence of voltage sags reduction and also the real power losses. The developed functions of the ge...

In this paper, Integer Programming based methodology is presented for the optimal placement of Phasor Measurement Unit (PMU) that minimizes the cost of installation and provide the entire power system observability. The concepts of zero injection buses are used in this paper for further reduction in number of PMUs. Integer Programming may produce multiple results if neighboring buses to zero in...

In this paper an artificial neural network (ANN) based methodology is proposed for determining external equivalent. The modified Newton-Raphson method with constant interchange of total active power between internal and system used solving the load flow problem. A multilayer perceptron (MLP) backpropagation training algorithm applied determination. was tested IEEE 24-bus test simulation results...

Received Jan 9, 2018 Revised Mar 2, 2018 Accepted Mar 18, 2018 The objective of this paper is to predict the secure or the insecure state of the power system network using a hybrid technique which is a combination of Artificial Neural Network (ANN) and voltage stability indexes. Voltage collapse or an uncontrollable drop in voltage occurs in a system when there is a change in the condition of t...

This paper proposes a refined genetic algorithm (RGA) for solving optimal measurement placement with single measurement pair loss contingency for power system state estimation. Even though the global minimum measurement pair number is , their proper positions are required to make the system observable. The observability is checked by the topological analysis method and triangular factorization ...

In this paper, a new reactive power market clearing (RPMC) mechanism for day-ahead competitive electricity market is developed based on multi-objective optimization approach. In proposed mechanism, three objective functions such as total payment function (TPF) for reactive power support from generators and synchronous condensers, total real transmission loss (TRTL) and voltage stability enhance...