Nelson Kagan

Allocation of Power Quality Monitors by Genetic Algorithms and Fuzzy Sets Theory

The aim of this article is to present the application of Genetic Algorithms (GAs) and Fuzzy Mathematical Programming in the design of Voltage Sag and Swell monitoring systems for power transmission networks. The proposed methodology uses the simulations of different types of short-circuit in many different points of the power system, in order to characterize the system behavior towards the occurrence of voltage sags and swells. Then, different configurations for the monitoring system (number of monitors and buses where they are supposed to be installed) are assessed through GAs. Two different GA modeling are presented, namely one based on binary vectors, for the decision over the installation of a monitor in a specific bus of the power system and another based on integer vectors, in order to indicate in which buses the monitors should be installed. The evaluation of the methodology performance for the IEEE 30- buses network is presented, and a comparison between the results achieved and the results from a similar work in the same field is carried out.

A Power-Quality Index to Assess the Impact of Voltage Harmonic Distortions and Unbalance to Three-Phase Induction Motors

This paper discusses the need to simultaneously monitor voltage unbalance and harmonic distortions in addition to root-mean-square voltage values. An alternative way to obtain the parameters related to voltage unbalance at fundamental frequency as well as voltage harmonic distortions is here proposed, which is based on the representation of instantaneous values at the dq axes and at the instantaneous Euclidean norm. A new power-quality (PQ) index is then proposed to combine the effects of voltage unbalance and harmonic distortions. This new index is easily implemented into existing electronic power meters. This PQ index is determined from the analysis of temperature rise in induction motor windings, which were tested for long periods of time. This paper also shows that these voltage disturbances, which are harmful to the lifetime expectancy of motors, can be measured by alternative ways in relation to conventional methods. Although this paper deals with induction motors only, the results show the relevance for further studies on other pieces of equipment.

Influence of RMS variation measurement protocols on electrical system performance indices for voltage sags and swells

This paper presents an evaluation study for measurement protocols of characteristic parameters related to short duration voltage variations (SDVs). The evaluation of possible differences in the magnitude and the duration of SDVs produced by different protocols is of great importance, for the electrical system performance indices related to voltage sags and swells are in practice obtained by measuring instruments. The study made use of a digital simulator that generated voltage conditions resultant of faults in a distribution network. Several measurement protocols for SDVs were applied and an overall comparison was performed.

Using Genetic Algorithms and Fuzzy Programming to Monitor Voltage Sags and Swells

A genetic algorithms and fuzzy programming methodology can help determine the minimum number of meters (and their location) needed to monitor voltage sags and swells in power networks. This paper proposes a methodology that determines the minimal number of power-quality meters needed to monitor a power network and identifies the buses on which those meters should be installed.

Harmonic state estimation through optimal monitoring systems

The present paper describes a methodology based on Evolutionary Algorithms (EAs) that defines the configuration required for a monitoring system, in order to monitor voltage and current state variables from a power network. The methodology defines not only the sites where the meters should be installed, but also how their transducers (PTs and CTs) should be connected. The monitoring systems observability is verified through three different rules based on Kirchhoffs laws. A branch-and-bound algorithm and a modified Genetic Algorithm (GA) are used to solve the optimization problem. The objective is to reduce the cost of the whole monitoring system. It is also shown why intelligent searching methods are required for solving the optimization problem. Three different networks were used to assess the methodologys performance: IEEE 14-bus system, IEEE 30-bus system and a real power distribution feeder. The results were compared with the ones obtained through other methodologies that have already been published before.

Hybrid Method to Assess Sensitive Process Interruption Costs Due to Faults in Electric Power Distribution Networks

This paper shows a new hybrid method for risk assessment regarding interruptions in sensitive processes due to faults in electric power distribution systems. This method determines indices related to long duration interruptions and short duration voltage variations (SDVV), such as voltage sags and swells in each customer supplied by the distribution network. Frequency of such occurrences and their impact on customer processes are determined for each bus and classified according to their corresponding magnitude and duration. The method is based on information regarding network configuration, system parameters and protective devices. It randomly generates a number of fault scenarios in order to assess risk areas regarding long duration interruptions and voltage sags and swells in an especially inventive way, including frequency of events according to their magnitude and duration. Based on sensitivity curves, the method determines frequency indices regarding disruption in customer processes that represent equipment malfunction and possible process interruptions due to voltage sags and swells. Such approach allows for the assessment of the annual costs associated with each one of the evaluated power quality indices.

Harmonic Distortion State Estimation Using an Evolutionary Strategy

This paper presents a new methodology to estimate harmonic distortions in a power system, based on measurements of a limited number of given sites. The algorithm utilizes evolutionary strategies (ES), a development branch of evolutionary algorithms. The main advantage in using such a technique relies upon its modeling facilities as well as its potential to solve fairly complex problems. The problem-solving algorithm herein proposed makes use of data from various power-quality (PQ) meters, which can either be synchronized by high technology global positioning system devices or by using information from a fundamental frequency load flow. This second approach makes the overall PQ monitoring system much less costly. The algorithm is applied to an IEEE test network, for which sensitivity analysis is performed to determine how the parameters of the ES can be selected so that the algorithm performs in an effective way. Case studies show fairly promising results and the robustness of the proposed method.

A model for electricity markets: The impact of regulation on value

In this paper it is proposed a simple, although useful model, intended for electricity markets, which enlightens the analysis of regulatory procedures and their consequences over value creation. Today it is widely recognized that, in regard to public services, the aim of regulation should be to maximize the social wealth added (EWA). This wealth includes consumers surplus (ECA), tributes paid to government (EGA) and investor value added (EVA). Thus, regulation implies both efficiency, regarding the location of resources, and fair price levels. The task is seriously impaired by informational asymmetries, and a second-best optimum is only attained with incentive-compatible contracts. Those problems, among many others, can be treated with the proposed model. In order to clarify some of the issues, an example is developed showing the social wealth added under several instances of market operation: regulates vs. unregulated firm, level of taxation, and optimized vs. non-optimized investment and resources.

A roadmap for the implementation of smart grids in Brazil

The presentation deals with a project that established a roadmap for the implementation of smart grids in Brazil. The project was divided into 7 research blocks, concerning the main aspects in any smart grid implementation, such as smart metering, automation, distributed resources, IT, telecommunication and public policies. A novel methodology that takes into account the Countrys diversity was developed to establish network evolutions towards smarter grids, considering different possible scenarios. Related costs and benefits were then evaluated..

Evaluating the risk of equipment disruption related to voltage sags

This paper presents a methodology for risk analysis applied to voltage sags in distribution networks. The basis of the methodology is presented, as well as the description of its implementation. Two evaluations are performed for a given distribution network: frequency of occurrence of voltage sags and the impact of the voltage sags on customer loads in statistical basis. Fault events are simulated using the Monte Carlo method, in which variables related to faults are determined according to their probability distributions. The magnitude and the duration of voltage sags and occurrence of interruptions are determined in the network points by considering the fault conditions and the line overcurrent protection devices characteristics. The results presented are indices of sag events and equipment breakdown for any desired voltage tolerance curves, which allows mapping the network in respect to risk, associated to sag events. The emphasis of the studies lies upon the practical questions that appear when industries already installed or planning installation are faced with decisions which are influenced by the rate of occurrence of voltage sags.