Carlos F. M. Almeida

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.

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.

Harmonic coupled norton equivalent model for modeling harmonic-producing loads

This paper verifies the importance of load modeling for the harmonic assessment of power systems. Three different models are discussed, and the impact of each approach on the harmonic evaluation of power networks is highlighted.

Genetic algorithms applied for the optimal allocation of power quality monitors in distribution networks

This paper presents a methodology which determines the optimal allocation of power quality monitors, in order to monitor the occurrence of voltage sags and swells in distribution networks. Initially, the methodology characterizes the system under analysis regarding the occurrence of voltage sag and swells. This characterization is performed through the simulation of several short-circuits at different points of the system being studied and taking in to consideration several conditions (fault impedance, fault type, etc.). For this purpose, a new method that defines the most relevant short-circuit conditions is proposed. After the systems characterization, the methodology makes use of Genetic Algorithms (GA) to define the minimum number of monitors required to monitor the whole system, and also the places where these monitors should be installed in the power network.

Evaluation of distributed generation impacts on distribution networks under different penetration scenarios

This paper presents a methodology and a computational tool developed for the assessment of the impacts caused by photovoltaic and wind generators, up to 100 kW, connected to the distribution networks, and aims at a real network application. The impact on the power distribution systems planning derive from the new network configuration caused by the installation of distributed generators and the demand growth. The curves associated with the distributed generators (DG) are modelled based on the average behavior of the inputs, such as irradiation and wind, and the technologies available. Their locations are defined by a DG probabilistic allocation algorithm based on attractiveness measures, as a function of economic variables. The network impacts consider prospective scenarios, and are determined by the diagnosis of network elements, by monitoring the loading of feeders and secondary networks, as well as the analysis of voltage profiles, losses, and protection effectiveness.

Algorithm for decentralized Volt/VAr control in distribution networks

Power utilities currently face challenges to provide energy considering minimum requirements for power quality and reliability. Control and monitoring of aging assets to meet a growing demand are reasons for such difficulties. Voltage control and reactive power management (Volt/VAr) are automation techniques that can be effectively used in distribution systems. These practices lead to benefits such as improvement in reliability and efficiency, minimization of operation and maintenance costs, among others. In the present study a methodology of decentralized Volt/VAr control (VVC) was developed through an optimization problem in which Genetic Algorithms (GA) are used to find an optimum solution, through the coordination and control of on load tap changers (OLTCs) in power transformers, capacitors banks and voltage regulators placed along the feeders. The proposed algorithms are implemented on a 22 bus power distribution test system.

Integrated subsea production system: An overview on energy distribution and remote control

In 2012, Brasil had a proved reserve of 15.3 billions of BOE (barrel of oil equivalent). The offshore reserve corresponds to more 94% of this amount. Petrobras, the Brasilian E&P company, leads the offshore production in ultra-deep water (deeper than 1500 m of water depth) worldwide. The current offshore production in ultra-deep waters deploys a Floating Production Unit (FPU), and some subsea equipments, such as, wet Christmas trees, manifolds, separation & booster systems, risers and pipelines. However, on board of the FPU, there are several other systems, namely, power generators, separators, gas treatment system, water treatment system, artificial lift system, injection system, etc. A future paradigm shift in the offshore petroleum production shall be the installation of all necessary systems on the sea floor. This article addresses to two challenges that raise with this new integrated operations with subsea oilfield production: the “remote operation and monitoring”, and the “power generation and distribution”. Remote operation and monitoring come from the need to transfer the process operators to shore and optimize the number of operators, to improve the processes availability by reducing the operator response time to a specific task, to provide continuous and predictive monitoring of vital processes, among other factors. Within the context of integrated operations, a remote operating center provides a broad and integrated overview of several processes in the asset, by using modern supervisory software (3D and 4D), database, remote sensoring, among others technologies. Part of this article also provides a comparative discussion between some technologies used in the implementation of remote operation and monitoring. Due to the substantial amount of electrical power required by subsea process units and their relatively long life cycle, typical aspects related to power generation and distribution have been changing. Alternatives, which were not cost effective before, are considered as new trends in the development of new process units due to political aspects and advances in the technology involved. Subsea high-voltage power distribution systems have become an alternative to supply the total load of subsea process units. According to this approach, electrical power distribution is located near the load center, as on shore installations. Normally, such installations are supplied from shore through long power umbilicals, as the supply of individual loads is not economically interesting. The advances in the use of renewable sources have also promoted new alternatives in power generation. These approaches become more interesting due to the possibility of installing large power generation plants using renewable sources on shallow water and transmitting the power to a set of subsea process units. Thus, new alternatives arise, such as the possibility of power transmission in high voltage direct current systems (HVDC), avoiding common problems faced in power transfer capacity using high voltage alternate current systems (HVAC), as large amount of reactive power needed to compensate cables capacitance. This paper discusses these issues aroused due to power supply of subsea process units.

Determining frequency dependent equivalents through evolutionary algorithms

The aim of this paper is to present an alternative methodology for obtaining frequency dependent equivalents from power networks. The methodology focus on determining rational functions that suitably approximate the frequency response of admittance present in networks equivalents. Through this methodology, part of the system under analysis can be replaced by a Frequency Dependent Network Equivalent (FDNE), which simplifies system representation and makes possible the accurate evaluation of large power networks. The methodology is based on Evolutionary Algorithms (EAs). Basically, different set of values for the rational function parameters are simultaneously assessed. The EA suitably changes the values for the function parameters, decreasing the RMS error between the systems original frequency response and the response provided by the rational function. The results obtained through the proposed methodology are compared with the ones obtained through the Vector Fitting methodology, which is the common approach used for solving similar problems.

Protection System Considerations in Networks with Distributed Generation

This chapter presents methodologies to assess the impact of distribution generation on electric distribution network protection systems for an integrated network planning. The distributed generation (DG) alternative is seen as a shift in the paradigm of energy generation in the world. The adoption of renewable sources of energy for residential or commercial production brings not only environmental benefits, but also an opportunity to ease the supplying difficulties found in many countries. Despite solving some of the energy suppling problems, this paradigm change caused by the insertion of DG in electric distribution networks can bring some undesired technical impacts. The typical impacts assessed in the electric distribution networks planning involve the expansion of the network, such as losses, power factor, line loading, and voltage profiles, among others. However, a massive insertion of DG may also cause significant problems to the network protection, which involves the protection planning. In this way, it is necessary to identify potential protection issues and design means to model, diagnose and mitigate such issues. This chapter aims at describing the importance of predicting the potential impacts of high penetration of renewable sources on the protection system from electric distribution networks, in order to achieve an integrated network planning. Thus, in the beginning of this chapter it is discussed the main protection system issues that may arise from the high penetration of distributed generation, such as loss of protection coordination, overvoltage, loss of protection sensitivity, directional false tripping, unwanted fuse blowing, beside others. The chapter than demonstrates possible models utilized to assess those impacts, such as network modeling and renewable sources modeling, possible approaches such as the probabilistic and deterministic perspectives, regarding DG allocation algorithms and the possible methodologies for assessment such as scenarios or sensitivity analysis. The methodologies evaluate the protection impacts and are based on several short circuit calculations and for the probabilistic approach, the Monte Carlo Method. The results shown in the chapter may represent the calculation of such impacts for electric distribution networks. Those may contain loss of sensitivity, directional false tripping and unwanted fuse blowing impact calculations for some networks to illustrate the methodologies. To conclude the chapter, there will be more discussions regarding the results presented and the potential benefits of including this analysis on the integrated distribution network planning. In the end, the chapter illustrates the application of the presented methodologies with a case study using a real distribution network.