Thesis (MScIng)--University of Stellenbosch, 2004. / ENGLISH ABSTRACT: The optimal placement of different types of compensators on electrical networks is a complex
task faced by network planners and operations engineers. The successful placement of these
devices normally involves a large number of power flow studies and relies heavily on the
experience of the engineer. Firstly the operation and application of the different types of
compensators must be clearly understood. Secondly the application of combinations of
different compensators on a specific network must be investigated. Then the dynamics of the
network and interaction between the network and the compensator/s must be studied under a
wide variety of network conditions and load levels. This task is further complicated by the
non-linear nature of the mathematical equations that govern the power flow and voltage
distribution on an electrical network. Yet another complication is the fact that some of the
variables that describe an electrical network can be non smooth or discrete. For instance, the
discrete value of a tap position of a power transformer can only assume an integer value. To
simplify the problem of compensator placement, advanced software tools are available that
are capable of solving power flows of networks containing compensators. To a large degree,
however, these tools still rely on the user to make intelligent decisions as to the configuration
of networks and the placement of compensators. In many cases trial and error is the only way
to find a good solution.
The purpose of this thesis is to show the different techniques available to implement
intelligent algorithms capable of finding optimal solutions specific to the placement of voltage
regulators. State of the art algorithms are implemented in Matlab that can place voltage
regulators on sub transmission, reticulation and low voltage networks. The sub transmission
and reticulation placement algorithm is a combination of an SQP technique and a simple
combinatorial algorithm. The low voltage placement program is based on a simple genetic
algorithm with a few customized features that has been developed to ensure fast convergence.
The programs developed were used to do optimal voltage regulator placement on a number of
networks. As far as possible real world networks were used. Where real world networks
were not available test networks were used that closely resemble real networks, as they exist
on typical networks owned by Eskom Distribution.
It was found that SQP is a very efficient algorithm for optimising large non-linear problems
such as the placement of a Step Voltage Regulator on a large electrical network. This
algorithm however does not handle discrete variables very well and is also limited in handlingany reconfiguration of the network due to the placement of series devices such as voltage
regulators. To cater for reconfiguration, it is necessary to combine the SQP algorithm with a
combinatorial algorithm.
The genetic algorithm used to do optimal placement of multiple Electronic Voltage
Regulators on low voltage networks was found to be very efficient and robust. This can be
attributed to the simplicity of the algorithm as well as the fact that it does not rely on the
availability of derivative and second derivative information to move towards an optimal
solution. Instead, it only uses fitness values obtained from function evaluations to optimise
the placement problem. Another useful feature of using a genetic algorithm is that the
algorithm does not get stuck in sub optimal areas in the solution space. Both the placement
programs developed are relatively simple and do not consider all the factors involved in the
placement of voltage regulators. However, the addition of any number of factors is however
possible with further development of the programs as presented in this thesis. / AFRIKAANSE OPSOMMING: Die optimale plasing van verskillende kompenseerders op elektriese kragstelsels is ´n
moeilike probleem vir beplanners en operasionele personeel. Die plasing van
kompenseerders gaan gewoonlik gepaard met ´n groot hoeveelheid netwerk studies en die
sukses daarvan berus gewoonlik op die ondervinding van die ingenieur. Eerstens moet die
werking en toepassing van elke kompenseerder behoorlik verstaan word. Tweedes moet die
plasing van ´n enkele asook kombinasies van verskillende kompenseerders ondersoek word.
Dan moet die dinamika van die netwerk en interaksie met die kompenseerder/s bestudeer
word vir al die moontlike netwerk konfigurasies en belasting vlakke. Die taak word verder
bemoeilik deur die nie-liniêre vorm van die wiskundige vergelykings wat die netwerk vrag en
spanning verspeiding beskryf. Nog ´n komplikasie is die feit dat van die veranderlikes wat
die probleem beskryf, diskreet is. Byvoorbeeld die tap posisie van ´n transformator kan slegs
´n heel getal aanneem. Om die plasing van kompenseerders te vergemaklik is gevorderde
sagteware beskikbaar wat simulasies kan doen van netwerke wat kompenseerders bevat. Tot
´n groot mate is die sagteware nog steeds afhanklik van intellegente besluitneming deur die
gebruiker. In die algemeen moet ´n groot hoeveelheid studies nog steeds gedoen work om ´n
goeie oplossing te vind.
Die doel van hierdie tesis is om die verskillende tegnieke te wys wat beskikbaar is om
intelligente algoritmes te implementeer wat optimale oplossings kan vind vir spesifiek die
plasing van spanning reguleerders. Moderne algoritmes is in Matlab geimplementeer wat
spanning reguleerders op sub transmissie, retikulasie en laag spanning netwerke kan plaas.
Die sub transmissie en retikulasie plasings algoritme is gebaseer op ´n kombinasie van ´n
sekwensieële kwadratiese programmering metode en ´n eenvoudige kombinatoriese metode.
Die laag spanning plasings program is gebaseer op ´n eenvoudige genetiese algoritme met ´n
paar unieke verstellings om vinnige konvergensie te verseker. Die twee programme wat
ontwikkel is word dan gebruik on spanning reguleerders te plaas op ´n paar netwerke. So ver
moontlik is bestaande netwerke gebruik. Waar bestaande netwerke nie beskikbaar was nie is
toets netwerke saamgestel wat gebaseer is op bestaande Eskom netwerke.
Daar is gevind dat sekwensieële kwadratiese programmering ´n effektiewe algoritme is om
groot nie liniêre optimerings probleme, soos die plasing van spanning reguleerders, op te los.
Hierdie algoritme is egter nie geskik om diskrete veranderlikes te hanteer nie. Dit is verder
ook nie geskik om enige netwerk rekonfigurasie te hanteer tydens die plasing van seriesgeskakelde kompenseerders soos spanning reguleerders nie. Om die rekonfigurasie moontlik
te maak is dit nodig om die sekwensieële kwadratiese programmering te kombineer met ´n
kombinatoriese algoritme. Daar is verder gevind dat die genetiese algoritme wat gebruik is
om elektroniese spanning reguleerders te plaas op laag spanning netwerke baie effektief en
robuust is. Dit is as gevolg van die eenvoudigheid van die algoritme en die feit dat dit nie
afhanklik is van afgeleide en tweede afgeleide informasie om na die optimale oplossing te
beweeg nie. Die algoritme gebruik slegs fiksheid waardes bereken van funksie evaluasies om
die probleem te optimeer. Nog ´n voordeel van genetiese algoritmes is dat dit nie in sub
optimale gebiede van die oplossing ruimte stil staan nie.
Beide die programme wat ontwikkel is, is redelik eenvoudig en neem nie al die faktore in ag
wat gepaard gaan met die plasing van spanning reguleerders nie. Addisionele faktore kan
egter maklik ingesluit word deur verdere ontwikkeling van die bestaande programme.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/16265 |
| Date | 12 1900 |
| Creators | Burger, I. |
| Contributors | Beukes, H. J., University of Stellenbosch. Faculty of Engineering. Dept. of Electrical Engineering. |
| Publisher | Stellenbosch : University of Stellenbosch |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | Unknown |
| Type | Thesis |
| Format | xiii, 160 leaves : ill. |
| Rights | University of Stellenbosch |
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