Investigating probabilistic techniques for calculating the system capacity in the South African transmission network

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dc.contributor.advisorBekker, Bernarden_ZA
dc.contributor.advisorDalton, Amarisen_ZA
dc.contributor.authorDe Bruyn, Johannesen_ZA
dc.contributor.otherStellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.en_ZA
dc.date.accessioned2024-03-05T06:05:30Zen_ZA
dc.date.accessioned2024-04-26T10:48:27Zen_ZA
dc.date.available2024-03-05T06:05:30Zen_ZA
dc.date.available2024-04-26T10:48:27Zen_ZA
dc.date.issued2024-03en_ZA
dc.descriptionThesis (MEng)--Stellenbosch University, 2024.en_ZA
dc.description.abstractENGLISH ABSTRACT: he large-scale introduction of variable renewable energy (VRE) generators to existing power systems, which were predominantly designed for centralised and dispatchable generation, comes with capacity and stability planning challenges. Academic literature suggests that these challenges are not sufficiently addressed using traditional power system analysis and modelling methods. Many research papers therefore call for the adoption of more statistically sophisticated methodologies that can more adequately describe the uncertainties inherent to variable renewable energy resources. Probabilistic load flow techniques especially have been found to provide a more nuanced representation of the capacity of a power system to host additional generation. This study sets out to prove the hypothesis that using a simplified probabilistic load flow methodology for calculating system capacity would more comprehensively clarify the constraints associated with hosting VRE in the South African transmission network. It does this by developing and applying such a methodology to the Northern Cape transmission network based on similar methodologies in literature. The probabilistic methodology is compared against results gained from a deterministic system capacity analysis also applied to the same portion of the transmission network. Two significant concerns regarding probabilistic analyses are the relatively long solution times and extensive data requirements. Literature suggests that simplifying network representations with equivalent circuits could reduce both while maintaining an acceptable level of accuracy. This study included a brief analysis of these claims by reducing the transmission network model to only the Northern Cape using Ward equivalents for the rest of the system and comparing the power flows in the full and simplified system under various conditions. The results showed that equivalent circuits can reduce solution times considerably without introducing significant errors when care is taken in setting up the internal and external networks. This study further showed that deterministic scenario analyses do not consistently, when seasonal variations are introduced, predict the extreme behaviour of power systems unless a large number of scenarios are considered. Probabilistic system capacity analyses on the other hand were consistent in providing the likely and extreme loading states of the Northern Cape. Recommendations for future studies are the expansion of the methodology presented to include calculating the hosting capacity of the South African system probabilistically to determine whether current deterministic methods are overly conservative in their estimations. Another study would be identifying edge-case scenarios for deterministic analyses in the current South African power system.en_ZA
dc.description.abstractAFRIKAANSE OPSOMMING: Om wispelturige hernubare energiebronne (WHE) in hedendaagse kragstelsels, wat grotendeels ontwerp is vir gesentraliseerde, beheerbare generators, in groot hoeveelhede in te werk kom met uitdagings, veral vir stelselkapasiteit en -stabiliteit beplanning. Akademiese literatuur beweer dat die uitdagings nie voldoende aangespreek word deur tradisionele modellerings en analise metodes nie. Baie navorsers doen dus ‘n oproep vir die aanvaarding van verfynde statistiese analise metodes wat die onsekerhede verbonde aan WHE beter uitlig. Hulle maak veral aanspraak op metodologie¨e wat gebruik maak van probabilistiese drywingsvloei tegnieke, wat meer nuanse toon in die vermo¨e van ‘n stelsel om meer generasie te aanvaar. Die studie het die volgende hipotese probeer bewys: ‘n Vereenvoudigde probabilistiese drywingsvloei metodologie om kragstelsel kapasiteit te bereken sal die beperkings aangaande WHE op die Suid-Afrikaanse transmissie network aanvaar, meer volledig uitlig. Die studie het die ondersoek deur ’n metodologie te ontwikkel gebasseer op soortgelyke studies bevind in die literatuur en die toe te pas op ’n gedeelte van die Noord-Kaap transmissie netwerk. Die resultate vanuit die probabilistiese analise was toe vergelyk teen die wat verkry was vanuit ’n determinisitiese stelsel kapasiteit analise wat op dieselfde gedeelte van die Suid-Afrikaanse netwerk toegepas was. Twee groot kwelpunte van probabilistiese analises oor die algemeen is die relatiewe lang berekenings tye en die omvattende data wat vereis word vir akkurate resultate. Die literatuur stel voor dat die probleme bekamp kan word, met ’n minimale byvoeging van foute, deur dele van die netwerk te vervang met vereenvoudigde verteenwoordigende stroombane. Die study het dus ’n oorhoofse analise gevoer om hierdie te ondersoek. Dit was gedoen deur die Suid-Afrikaanse transmissie netwerk te verklein tot net die Noord-Kaap transmissie netwerk deur al die ander dele van die stelsel te vervang met Ward verteenwoordigende stroombane. Die drywingsvloei resultate was toe vergelyk tussen die volledige en verkleinde stelsels. Die resultate het getoon dat verteenwoordigende netwerke simulasie tye beduidend kan verminder sonder om merkwaardige foute tot gevolg te hˆe, alhoewel dit verys dat die interne en eksterne netwerke sorgvuldig gekies moet word. Die studie het verder ook gewys dat deterministiese scenario analise nie die esktreme gedrag van die netwerk konsekwent voorstel nie, tensy ’n groot hoeveelheid scenario’s beskou word. Probabilistiese analises was meer konsikwent in hulle vermo¨e om die waarskynlike en ekstreme belasting toestand van die Noord-Kaap voor te stel. Aanbevelings vir toekomstige navorsing is dat daar ’n studie gedoen word waar die hoeveelheid ekstra generasie wat die stelsel kan aanvaar probabilisties uitgewerk word en die resultate met die deterministiese resultate vergelyk word om te bepaal of die huidige voorspellings te konserwatief is. Nog ‘n belangrike studie sal wees om te bepaal watter scenario’s wel die ekstreme gedrag van die transmissie netwerk voorstel, dat die scenario’s gebruik kan word vir toekomstige deterministiese analises.af_ZA
dc.description.versionMastersen_ZA
dc.format.extent105 pages : illustrations.en_ZA
dc.identifier.urihttps://scholar.sun.ac.za/handle/10019.1/130251en_ZA
dc.language.isoen_ZAen_ZA
dc.language.isoen_ZAen_ZA
dc.publisherStellenbosch : Stellenbosch Universityen_ZA
dc.rights.holderStellenbosch Universityen_ZA
dc.subject.lcshElectric power systems -- Load dispatchingen_ZA
dc.subject.lcshVariable renewable energy (VRE)en_ZA
dc.subject.lcshRenewable energy sourcesen_ZA
dc.subject.lcshProbabilistic analysesen_ZA
dc.subject.lcshUCTDen_ZA
dc.titleInvestigating probabilistic techniques for calculating the system capacity in the South African transmission networken_ZA
dc.typeThesisen_ZA
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