Development of a genetic algorithm for evaluating the performance of overhead power distribution lines and proposing solutions to improve distribution line safety (original) (raw)
Related papers
Journal of Engineering, 2018
Growing interest in the smart grid, increasing use of distributed generation, and classical distribution system reconfiguration (DSR) and restoration problems have led to the search for efficient distribution automation tools. One such tool, the improved Fast Nondominated Sorting Genetic Algorithm (FNSGA), not only is effective in finding system configurations that are optimal with respect to voltages, currents, and losses, but also considered parametric study to determine minimum values of N and Gen. In this paper, the essential spanning tree concept is expanded to improve the computational efficiency of the algorithm. Results of the study show that for relatively small test systems, optimum system configurations are obtained using values of N and Gen that require very small CPU times. In larger systems, optimum values of N and Gen requiring reasonable CPU times can also be found, provided that certain carefully chosen branches are removed from the pool of possibilities when producing the initial population in the algorithm. By using essential trees, the efficiency of the calculation is improved.
Investigating effects of neutral wire and grounding in distribution systems with faults
2004
In some applications like fault analysis, fault location, power quality studies, safety analysis, loss analysis, etc., knowing the neutral wire and ground currents and voltages could be of particular interest. In order to investigate effects of neutrals and system grounding on the operation of the distribution feeders with faults, in this research a hybrid short circuit algorithm is generalized. In this novel use of the technique, the neutral wire and assumed ground conductor are explicitly represented. Results obtained from several case studies using IEEE 34-node test network are presented and discussed.
Distribution network optimization: Finding the most economic solution by using genetic algorithms
European Journal of Operational Research, 1998
The problem of finding the optimal features in a distribution network is approached from an economic viewpoint. This problem is closely related to drops in pressure within the network, and is a complex mathematical problem with some empirically adjusted formulae that make the problem very difficult to solve analytically. Thus, a method is proposed for finding the optimal network features, based on a well known optimization procedure, genetic algorithms, which have proven to be useful in this type of problems. Furthermore, new problem-specific genetic operators are presented and shown to be intuitively and in practice better than the standard ones.
A Genetic Algorithm-Based Approach for Three-Phase Fault Evaluation in a Distribution Network
International Journal of Computing, 2020
Standard IEC 60909 provides all the basic information that is used in the evaluation of three-phase short circuit faults. However, it uses numerous estimations in its fault evaluation procedures. It estimates voltage factors, resistance to reactance ratios (R/X), resistance to impedance ratios (R/Z) and other scaling factors. These estimates do not cater for every nominal voltage. Users often have to approximate these values. In this paper, adjustments were made to the genetic algorithm (GA) with regards to gene replacements and arrangement of scores and expectation. During fault computation, the GA was used to stochastically determine R/X and R/Z ratios with regards to the parameters of the power system. The GA was tested on a nominal voltage that is properly catered for by Standard IEC. The GA results and the IEC values were within an approximate range. This implies that the developed GA can be further used to determine these ratios for nominal voltages that are not sufficiently a...
Line fault analysis of ungrounded distribution systems
2013 North American Power Symposium (NAPS), 2013
This paper proposes a new method for line fault analysis of ungrounded distribution systems. The fault condition of a line fault is integrated into the nodal admittance matrix of the faulted line to be modeled. The zero-impedance branch is merged into adjacent impedance branches to be taken into account, and one of its terminal buses with zero neutral-to-ground voltage is chosen as a slave bus when it is an ideal transformer or a voltage regulator with ungrounded winding connection. The three-phase jointly regulation of a distributed generation source is embedded into nodal admittance model of its internal impedance branch by combining three phases of its internal bus into one equivalent phase. The distribution system is partitioned into a main network and a set of lateral networks to be solved. The main network is formed by the connected paths between the terminal buses of the faulted line, and generation sources, and solved by a Gauss-Seidel method. A lateral network is formed by one of the buses of main network and all buses and branches downstream to the bus, and solved by a backward and forward sweep method. The numerical examples are provided to prove the effectiveness of proposed method.
Journal of Energy and Power Engineering, 2014
This paper aims at analyzing the impact of the neutral conductor absence at specific sections over the performance of the power distribution lines, and proposing alternative solutions to mitigate the problems caused by the neutral conductor theft. Simulations are made by the software Interplan and show that the absence of neutral conductor at specific sections of power distribution lines may increase the neutral-to-ground voltages, which compromises the system's safety. The solution developed keeps the technical performance of the power distribution system at satisfactory levels, regarding the voltage profile, or, at least, close to the level before the neutral conductor's theft.
Network Reconfiguration for Loss Reduction in Electrical Distribution System Using Genetic Algorithm
2013
Distribution system is critical links between the utility and the nuclear installation. During feeding electricity to that installation there are power losses. The quality of the network depends on the reduction of these losses. Distribution system which feeds the nuclear installation must have a higher quality power. For example, in Inshas site , electrical power is supplied to the nuclear reactor and other nuclear facilities from two incoming feeders (one from new abu–zabal substation and the other from old abu–zabal substation). Each feeder is designed to carry the full load, while the operator preferred to connect with a new abu–zabal substation, which has a good power quality. Bad power quality affects directly the nuclear reactor and has a negative impact on the installed sensitive equipment and instruments of the operation.This paper introduces an optimization technique based on genetic algorithms for distribution network reconfiguration to reduce the network losses to minimu...
Optimal Placement of Fault Passage Indicators in Distribution Networks using Genetic Algorithms
Algerian Journal of Signals and Systems
Fault Passage Indicators (FPIs); also named Faulted Circuit Indicators (FCIs), have been under development for the last 70 years including new capabilities to satisfy the needs of the distribution network operators. In order to improve system stability, these devices can be deployed along the feeder to reduce, or even eliminate, the uncertainty about the fault location. The number and location of FPIs affects the network reliability that can lead to extra charge on the distribution companies as well as the consumers. In this work, the optimal number and location of fault passage indicators in Power Distribution Networks (PDN) are determined. The problem is cast as an optimization task with a special economical combined objective function and solved using the genetic algorithms. The work has been tested on the two case studies, IEEE 9 bus and IEEE 33 bus systems.
American Journal of Electrical Power and Energy Systems
The distribution networks are more and more heavily loaded due to economic growth, industrial development and housing. The operation of these networks under these conditions generates voltage instabilities and excessive power losses. The present work consisted in the optimal integration of multi-GED (Decentralized Energy Generators) (Photovoltaic (PV), Fuel Cell (FC or PAC) and Wind Generator (WG)) and FACTS (SVC) in a Medium Voltage distribution's departure of the Beninese Electrical Energy Company (SBEE), with a view to improve its technical performances. The diagnostic study of the Ouidah 122-nodes test network, before optimization, revealed that the active and reactive losses are 457.34588 kW and 625.41503 kVAr respectively. This network has high voltage instability with a minimum voltage of 0.80455 p.u. and a minimum VSI of 0.41897 p.u. The optimization of the size and positioning of GED and FACTS was based on the Nondominated Sorting Genetic Algoritm II (NSGA II). After optimization with the NSGA II, a comparative study of the different combinations between the three GEDs and the SVC, made it possible to choose that of the placement of a 121 kW Wind Generator at node 75, a PV of 131 kW at node 51, a system of Fuel Cell (FC, PAC in french) of 700 kW at node 34, and an SVC of 2.126 MVAr at node 94 of the network. This positioning enabled a reduction of 65.11% in active losses and 65.12% in reactive losses. The voltage profile and the voltage stability are clearly improved, with a minimum voltage of 0.96993 p.u. and a minimum VSI of 0.88505 p.u. The initial investment for this project is seven hundred and seven million three hundred and fifty-two thousand three hundred and fifty-eight point seven CFA francs (707,352,358.7 CFA francs). The technical and economic evaluation shows that the payback period is approximately 4 years 6 months and 14 days. The relevant results obtained show that the method used is efficient and effective, and can be applied to other MV departures of the SBEE.
Iraqi Journal for Electrical And Electronic Engineering
Development of distribution systems result in higher system losses and poor voltage regulation. Consequently, an efficient and effective distribution system has become more urgent and important. Hence proper selection of conductors in the distribution system is important as it determines the current density and the resistance of the line. This paper examines the use of different evolutionary algorithms, genetic algorithm (GA), to optimal branch conductor selection in planning radial distribution systems with the objective to minimize the overall cost of annual energy losses and depreciation on the cost of conductors and reliability in order to improve productivity. Furthermore, The Backward-Forward sweep iterative method was adopted to solve the radial load flow analysis. Simulations are carried out on 69-bus radial distribution network using GA approach in order to show the accuracy as well as the efficiency of the proposed solution technique.