Reliability Analysis of Power Suply Including Renewable Energy Sources

Načrtovano povečanje deleža obnovljivih virov energije prinaša v elektroenergetske sisteme (EES) nove izzive, kjer je potrebno preučiti prispevek vetrne in sončne proizvodnje k splošni zanesljivosti sistema in zagotavljanju zadostnih zmogljivosti. Za konvencionalne tehnologije proizvodnje električne energije so specifični faktorji razpoložljivosti znani, medtem ko so dejavniki razpoložljivosti obnovljivih virov energije, kot sta vetrna in sončna energija, odvisni od hitrosti vetra in sončnega obsevanja na posameznih lokacijah. Zaradi volatilne narave vetrne in sončne energije je zelo težko natančno določiti nivo dodatnih operativnih rezerv moči za zagotavljanje zanesljivega delovanja elektroenergetskega sistema in neprekinjenega napajanja odjemalcev. Glavni cilj magistrskega dela je razvoj ustreznega modela za analizo zanesljivosti oskrbe z električno energijo z vključenimi obnovljivimi viri energije. Za ocenjevanje zanesljivosti so uporabljene sekvenčne Monte Carlo simulacije, njihova glavna prednosti je v tem, da upoštevajo kronološko zaporedje dogodkov in stohastično naravo sistema, kar je bistveno pri ocenjevanju zanesljivosti elektroenergetskih sistemov, ki vključujejo obnovljive vire energije, kot sta vetrna in sončna energija, ki so časovno odvisni in korelirani. Modeliranje vetrne in sončne energije za potrebe ocenjevanja zanesljivosti zahteva veliko zgodovinskih meritev hitrosti oz. moči vetrne ali sončne energije, da bi uspešno zajeli stohastično naravo in nestanovitno vedenje vetra in sončnega obsevanja na določeni lokaciji. Ker pa so v večini primerov takšni podatki nedostopni, lahko uporabimo simulacijske tehnike, s pomočjo katerih lahko ohranimo glavne značilnosti izhodiščnih meritev. Prikazana je tehnika simuliranja sintetičnih časovnih vrst vetrne in sončne energije z markovskimi verigami, s pomočjo katerih ohranjamo glavne lastnosti izhodiščnih meritev, kot sta sledenje mesečnim vzorcem sončne in vetrne energije in avtokorelacija. Prikazana metoda omogoča razvoj različnih scenarijev elektroenergetskih sistemov, kjer lahko spreminjamo deleže integriranja tako sončne, vetrne kot tudi konvencionalne energije v skupno zmogljivost sistema ter omogoča računanje indeksov zanesljivosti tako predstavlja uporabno orodje pri načrtovanju elektroenergetskih sistemov.The planned increase of the share of renewable energy brings new challenges in power systems. For instance, the contribution of wind and solar energy generation to the overall reliability of systems and to the provision of sufficient capacity needs to be examined. While the specific factors of availability for conventional power generation technologies are known, the availability factors of renewable sources such as wind and solar energy depend on wind speed and solar radiation at specific locations. Due to the volatile nature of wind and solar energy it is very difficult to accurately determine the level of additional operational reserves to ensure reliable operation of the electricity system and the continuity of supply to customers. Hence the main objective of this work is to develop an appropriate model for the analysis of the reliability of power supply with incorporated renewable energy sources. For reliability assessment the sequential Monte Carlo simulations are used. Their main advantage is that they take into account the chronological sequence of events and the stochastic nature of the systems, which is essential in assessing the reliability of electric power systems with incorporated time-dependent and correlated renewable energy sources. Modelling wind and solar energy requires a lot of historical wind and solar energy measurements in order to successfully capture the stochastic nature and random behavior of solar and wind energy at specific locations. In most cases, such data are inaccessible, so we can use simulation techniques which preserve the main features of the initial measurements. The Markov chain technique is presented to simulate time series of wind and solar energy. It preserves the main features of initial measurements such as tracking the monthly patterns of solar and wind energy and autocorrelation. The presented method allows to develop different scenarios with changing proportions of integrated solar, wind and conventional energy sources in the total installed capacity of systems. It also allows to calculate different reliability indices, which makes it a useful tool for the design of power systems