Optimisation study of geographical allocation of solar PV generation capacity for grid support

Date
2016-12
Journal Title
Journal ISSN
Volume Title
Publisher
Stellenbosch : Stellenbosch University
Abstract
ENGLISH ABSTRACT: Due to growing concerns regarding environmental impacts and energy security, the renewable energy sector and its role in large-scale power generation is becoming increasingly signi cant, both locally and internationally. While it reduces reliance on fossil fuels, however, grid-integration of renewable energy generation also introduces considerable risks at high penetration levels due to the intermittent nature of sources such as photovoltaic (PV) solar and wind energy. The development of methodologies for addressing these concerns has become a prominent eld of research, which includes aspects such as smart-grid technologies and optimal siting and sizing of renewable energy plants with regard to the grid infrastructure and demand pro le. This project investigates one such aspect, namely optimisation of the allocation of solar PV generation capacity in the context of grid-related metrics such as the seasonal and daily peak demand periods and energy supply variability. The main research objectives focus on determining the impacts of optimal geographical distribution of solar PV sources in the South African context, using grid support metrics de ned in terms of diurnal and seasonal trends as performance criteria. The development and implementation of the optimisation strategy required the identi cation and speci cation of appropriate optimisation parameters, such as sets of potential locations that re ect the seasonal and diurnal diversity of the local solar resource, a comprehensive range of objective functions that is representative potential grid support metrics and a range of optimisation algorithms. Three groups of locations, referred to as site groups, were selected based on geographical signi cance with regard to diurnal and seasonal solar cycles. A set of optimisation objectives were de ned based on grid-support considerations such as maximising average energy delivery, prioritising delivery during peak demand periods and minimising the day-to-day variability of the solar PV renewable energy contribution. A selection of candidate metaheuristic optimisation algorithms were identi ed for evaluation, namely the genetic algorithm, two standard variations of the pattern search technique and an additional pattern search variation that incorporates a genetic algorithm for a hybrid approach. The various site groups, diurnal and seasonal speci cations, optimisation objectives and optimisation algorithms were consolidated to de ne a comprehensive set of optimisation problem cases. The evaluation and subsequent analysis of the problem cases was implemented via an integrated software platform that forms part of an ongoing software application development project. Based on the designated optimisation strategy, a solar PV optimisation module was developed and integrated with an established database-driven user interface. The corresponding relational database structure was optimised for all current and future applications. The simulation software for implementing the optimisation problem cases on an external simulation platform was developed and amalgamated with the solar PV optimisation module. The results of the optimisation study confirm the seasonal and diurnal significance of the geographical distribution of solar PV generation, with seasonal variation occurring along a north-south axis and diurnal variation occurring along an east-west axis. The results for the same optimisation objectives evaluated for different seasonal and diurnal periods often show disparities. This indicates that solar PV distributions that exhibit the best performance characteristics overall are not necessarily ideal for supporting peak demand periods. This supports the notion that variable feed-in tariffs rather than the commonly used at tariffis should apply to renewable energy generation, since this would encourage development that supports the grid without sacrificing plant profitability. The results for the different optimisation objectives also show a clear trade-off between maximising the annual cumulative energy yield and minimising variability of supply. In general, the daily variability throughout a seasonal period decreases as geographical dispersion increases, often at the cost of lowering the cumulative annual energy yield. With regard to the optimisation algorithms investigated, the technique combining pattern search and the genetic algorithm proved to be the most robust. Due to its non-deterministic nature, however, the algorithm generally necessitated multiple evaluations to ensure high quality solutions. The quantitative impacts of the results achieved in the study are, to a degree, limited due to the geographical parameters of the South African case study considered in the investigation. The proposed optimisation strategy, however, has excellent potential in the context of larger interconnected grids, such as the European grid, United States mainland and the Southern African power pool region where an increased range of diurnal and seasonal characteristics applies. With regard to future work, it is recommended that a similar optimisation strategy should be investigated for combined wind and solar PV generation, since the contrasting characteristics of these sources could produce much more optimal aggregated power profiles.
AFRIKAANSE OPSOMMING: As gevolg van groeiende kommer rakende omgewingsimpak en energie-sekuriteit word die hernubare energiesektor en die rol daarvan in grootskaalse kragopwekking tans van toenemend belang, plaaslik sowel as internasionaal. Alhoewel dit afhanklikheid van fossielbrandstowwe verminder, bied die netwerkintegrasie van hernubare energie-opwekking by hoë penetrasievlakke ook aansienlike risikos as gevolg van die onderbroke aard van bronne soos fotovoltaïese (PV) sonkrag en windkrag. Die ontwikkeling van metodes vir die hantering van hierdie probleme het 'n prominente navorsingsgebied geword, wat aspekte soos slimnetwerk tegnologie en optimale plasing en vermoëns van hernubare energieaanlegte met betrekking tot die kragstelsel infrastruktuur en aanvraagprofiel insluit. Hierdie projek ondersoek een van hierdie aspekte, naamlik optimisering van die toekenning van PV opwekkingskapasiteit in die konteks van netwerkverwante eienskappe soos die seisoenale en daaglikse spitsaanvraag periodes en variasie in energieverskaffing. Die belangrikste navorsingsdoelwitte fokus op bepaling van die impakte van optimale geografiese verspreiding van PV sonkragbronne in die Suid-Afrikaanse konteks, deur gebruik te maak van netwerkondersteunende kriteria soos gedefinieer word in die konteks van daaglikse en seisoenale tendense as prestasiekriteria. Die ontwikkeling en implementering van die optimiseringstrategie het die identifisering en spesifikasie van gepaste optimiseringsparameters, soos stelle van potensiële liggings wat die seisoenale en daaglikse diversiteit van die sonkrag hulpbron re ekteer, 'n omvattende reeks van optimeringsfunksies wat verteenwoordigend is van netwerk ondersteunings kriteria en reeks van optimiseringsalgoritmes. Drie groepe van liggings, waarna verwys word as liggingsgroepe, is gekies op grond van geografiese belang met verwysing na daaglikse en seisoenale sonsiklusse. 'n Stel van optimeringsdoelwitte is gedefinieer, gebaseer op netwerk ondersteuningsoorwegings soos maksimering van gemiddelde energielewering, prioritisering van lewering gedurende spitstyd aanvraagperiodes en die mimimering van die dag-tot-dag wisselvalligheid van die PV hernubare energiebydrae. 'n Seleksie van metaheuristiese optimeringsalgoritmes is geïdentifiseer vir evaluering, naamlik die genetiese algoritme, twee standaard variasies van die patroonsoek tegniek en 'n bykomende patroonsoek variasie wat 'n genetiese algoritme vir 'n hibriede benadering inkorporeer. Die verskillende liggingsgroepe, daaglikse en seisoenale spesifikasies, optimeringsdoelwitte en optimeringsalgoritmes is gekonsolideer om 'n omvattende stel optimerings probleemgevalle te definieer. Die evaluering en daaropvolgende ontleding van die probleemgevalle is geïmplementeer deur middel van 'n geïntegreerde sagtewareplatform wat deel vorm van 'n deurlopende sagteware ontwikkelingsprojek. Gebaseer op die aangewese optimiseringstrategie, is 'n PV sonkrag optimiseringsmodule ontwikkel en met die gevestigde databasis-gedrewe gebruikerskoppelvlak geïntegreer. Die relasionele databasisstruktuur is geoptimiseer vir alle huidige en toekomstige toepassings. Die simulasiesagteware vir die evaluering van die optimerings probleemgevalle is op 'n eksterne simulasieplatform ontwikkel en met die PV son optimiseringsmodule gekombineer. Die resultate van die optimiseringstudie bevestig die seisoenale en daaglikse belangrikheid van die geografiese verspreiding van PV sonkragopwekking, met seisoenale variasie wat voorkom langs 'n noord-suid-as en daaglikse variasie wat voorkom langs 'n oos-wes-as. Die resultate vir dieselfde optimiseringsdoelwitte, geïvalueer vir verskillende seisoenale en daaglikse periodes, toon dikwels verskille. Dit dui daarop dat PV sonverspreidings wat die beste algehele prestasie eienskappe toon nie noodwendig ideaal is vir die ondersteuning van spitsaanvraag periodes nie. Dit ondersteun die idee dat veranderlike invoertariewe eerder as die algemeen gebruikte plat tariewe van toepassing moet wees vir hernubare energieopwekking, aangesien dit ontwikkeling sal aanmoedig wat die netwerk ondersteun sonder om die winsgewendheid van aanlegte te benadeel. Die resultate vir die verskillende optimiseringsdoelwitte toon ook 'n duidelike uitruil tussen maksimering van die kumulatiewe jaarlikse energieopbrengs en mimimering van variansie in voorsiening. In die algemeen neem die daaglikse variansie deur die loop van 'n seisoenale tydperk af soos die geografiese verspreiding verhoog, dikwels ten koste van n verlaging in die kumulatiewe jaarlikse energieopbrengs. Met betrekking tot die optimiseringsalgoritmes wat ondersoek is, is bevind dat die die gekombineerde patroonsoek en genetiese algoritme tegniek die mees robuuste is. As gevolg van die nie-deterministiese aard daarvan het die algoritme verskeie evaluerings vereis om kwaliteit oplossings te verseker. Die kwantitatiewe impakte van die resultate behaal in die studie is, tot 'n mate, beperk as gevolg van die geografiese parameters van die Suid-Afrikaanse gevallestudie wat in die ondersoek aangespreek is. Die voorgestelde optimeringsstrategie het egter uitstekende potensiaal in die konteks van groter tussenverbinde netwerke, soos die Europese netwerk, Verenigde State vasteland en die Suider-Afrikaanse kragpoel netwerk waar n wyer reeks van daaglikse en seisoenale karakteristieke van toepassing is. Met betrekking tot verdere werk word aanbeveel dat 'n soortgelyke optimiseringstrategie ondersoek word vir gesamentlike wind en PV sonkrag opwekking, aangesien die kontrasterende eienskappe van hierdie bronne baie meer optimale kumulatiewe kragprofiele kan produseer.
Description
Thesis (MEng)--Stellenbosch University, 2016.
Keywords
Energy security -- Environmental impact analysis, Photovoltaic power generation, Satellite solar power stations, UCTD
Citation