Renewable energy-based hybrid systems have become attractive energy supply options in
many countries because of global environmental concerns, access to electricity, and depleting
and rising cost of fossil fuel resources. These systems are increasingly becoming popular
solutions for electrification of off-grid locations where the grid extensions are difficult and/or
uneconomical. The main challenge, however, is the design of an optimal energy management
system that satisfies load demand considering the variable nature of renewable energy sources
and changes in demand.
This thesis aims to achieve an overall hybrid power management strategy that is capable of coordinating
the power flows among the different energy sources as the management and control
of energy distribution is a major problem associated with hybrid systems. The work deals with
the optimization of the operational cost of the photovoltaic–diesel–battery/ photovoltaic–
wind–diesel–battery power supply system from an energy efficiency perspective, as one of the
key characteristics of energy efficiency is the search for optimality. The optimization models
proposed in this work take into account the non-linearity of the operation costs associated
with the photovoltaic-diesel-battery/ photovoltaic–wind–diesel–battery hybrid systems and
this necessitates the use of quadratic programming while considering the weekday, weekend
and seasonal changes in demand, and variations in the renewable output. The first part of
this work considers the daily energy consumption variations for winter and summer weekdays
and weekends in order to compare the corresponding fuel costs and evaluate the operational
efficiency of the hybrid system. The second part minimizes fuel and battery wear costs, and
finds the optimal power flow, taking into account PV power availability, battery bank state
of charge and load power demand. The last part incorporates wind energy, and the energy
dispatch model satisfies the load demand, taking into account the intermittent nature of the
solar and wind energy sources and variations in demand. Model predictive control is applied
to the optimal energy management strategy of the hybrid system which is a more practical
approach to the energy management problem.
The results show that the hybrid model achieves considerable fuel savings in both winter
and summer seasons for days considered when compared to the case where a diesel generator
satisfies the load on its own. The model predictive control model is shown to be superior
to the open loop model owing to its ability to predict future system behavior and compute
appropriate corrective control actions required to meet variations in demand, radiation and
wind speed. The results of this work are important for remote area electrification, designers,
performance analyzers, control agents, and decision makers who are faced with multiple
objectives to make appropriate trade-offs, compromises or choices.
Hernubare energie-gebaseerde hibriede stelsels het ’n aantreklike energietoevoer-opsie in verskeie
lande geword, as gevolg van globale omgewingskwessies, elektrisiteitstoegang, verminderende
hulpbronne en stygende brandstofpryse. Hierdie stelsels neem toe in gewildheid
as oplossings vir die elektrifisering van buite-netwerkgebiede, asook vir areas waar netwerkverlenging
moeilik of onekonomies is. Die grootste uitdaging is die ontwerp van ’n optimale
energiebestuursisteem wat die aanvraag bevredig binne die veranderlike aard van hernubare
energiebronne en aanvraag.
Hierdie tesis beoog om ’n algehele hibriede drywingsbestuurstrategie te ontwikkel wat daartoe
in staat is om drywingsvloei met verskillende energiebronne te koördineer. Die werk ondersoek
fotovoltaïse-diesel-battery en fotovoltaïese-wind-diesel-battery-energievervoerstelsels
vanuit ’n energiedoeltreffendheidsperspektief, omdat een van die kenmerkende eienskappe van
energiedoeltreffendheid, optimaliteit is. Die optimeringsmodelle wat voorgestel word, neem
die nie-lineêre operasionele koste van bogenoemde kombinasies in ag, en dit noodsaak die
gebruik van kwadratiese programmering wat weeksdae, naweke, seisoenale veranderinge, en
die veranderlikheid van energiebronne en aanvraag in ag neem.
Die eerste gedeelte van die werk ondersoek die daaglikse energieverbruik-veranderinge vir
winter- en somersweeksdae en naweke ten einde die ooreenstemmende brandstofkostes en operasionele
doeltreffendheid van die hibriede stelsel te evalueer. Die tweede gedeelte minimeer
die brandstof-en batteryslytasiekoste, en vind die optimale energievloei, in ag genome die fotovoltaïese
drywingsbeskikbaarheid, batterybank-ladingstoestand, en drywingsaanvraag. Die
laaste gedeelte voeg windenergie by en die energieversendingsmodel bevredig die drywingsaanvraag,
in ag genome die wisselvallige aard van son- en windenergie en aanvraagsveranderlikheid.
Modelgebaseerde beheer word toegepas om die optimale energiebestuurstrategie van
die hibriede stelsel op ’n praktiese vlak op te los.
Die resultate wys dat die hibriede model merkbare brandstofbesparings behaal in beide
winter- en somerseisoene in vergelyking met ’n dieselkragopwekker wat alleen werk. Die modelgebaseerde
beheermodel oortref die ope-lusmodel as gevolg van eersgenoemde se vermoë om
korrektiewe beheeraksies te gebruik om veranderinge in die aanvraag, straling, en windspoed
te akkommodeer. Die resultate van hierdie werk is belangrik vir die elektrifisering van afgeleë
gebiede, asook vir ontwerpers, werkverrigtingsanaliste, beheeragente, en besluitnemers wat
gepaste kompromieë moet aangaan om veelvoudige doele te bevredig.
