The power system in Europe is undergoing a rapid transition with the expansion of renewable capacity and a decrease in dispatchable conventional technologies. An important part of planning for the power system is ensuring the security of the electricity supply. The focus of the work within the dissertation is to investigate the role of interconnectors in maintaining the security of the electricity supply. With this focus in mind, three sets of research questions are answered: How to assess the Security of Supply in a power system? With the decrease in available conventional generation capacity, how much and what new investment would be required? What role do grid interconnections play in maintaining the security of supply? These research questions are answered by starting with a framework of analysis which classifies various aspects relevant to ensuring the security of electricity supply into uncertainties, systematic risks and specific risks. A scenario-based analysis has been carried out by using a deterministic capacity expansion model to investigate systematic risks and capacity expansion requirements. This is followed by a Monte-Carlo-based stochastic generation adequacy assessment to assess specific risks. The results show significantly reduced capacity requirements from cross-border reliance in maintaining generation adequacy. Furthermore, the interaction between the increase in renewables, capacity expansion requirements and generation adequacy are analyzed.:1. Introduction 2. Literature Overview and Framework for Assessing Security of Supply 3. Numerical Analysis of Germany's Electricity Trade Surplus 4. Description of Deterministic Capacity Expansion Model 5. Description of Stochastic Modelling used to Assess Generation Adequacy 6. Scenario Based Analysis of Capacity Expansion 7. Stochastic Assessment of Generation Adequacy 8. Summary and Further Research

Pagrindinis šio darbo tikslas yra sukurti energijos tiekimo saugumo trikdžių scenarijų matematinį modelį, kuriuo būtų galima modeliuoti įvairių galimų energetinių trikdžių scenarijus. Priklausomai nuo trikdžio sudėtingumo lygio jis gali neturėti visiškai jokios įtakos ir pasekmių arba priešingai – gali turėti labai didelę įtaką ir labai sunkias pasekmes energijos tiekimo saugumui. Todėl energetinio trikdžio įtaka ir pasekmės suskirstomi balais: nuo 0 (nėra pasekmių) iki 5 balų (labai sunkios pasekmės). Nagrinėjama to trikdžio įtaka įvairiems valstybės sektoriams: ekonominiui, socialiniui ir politiniui. Energetinio trikdžio įtaka ir sukeltos pasekmės ekonominiui, socialiniui ir politiniui sektoriams ir suprantamas kaip atskiras scenarijus. Energetiniam trikdžiui buvo suteikti parametrai ir su įvairiais parametrų rinkiniais sumodeliuoti 100 scenarijų. Iš tų scenarijų išrinktas pats tikėtiniausias, nustatyti sunkiausi (kritiniai) bei lengviausi (sukeliantys mažas pasekmes) scenarijai. Taip pat suskaičiuojamos tokių scenarijų tikimybės bei trikdžių pasirodymo tikimybės. Tam naudojami Markovo grandinės bei procesai ir tikimybiniai skirstiniai. / The main objective of this paper is to develop a mathematical model of energy supply disturbances for modelling energy supply disturbance scenarios. The level of energy supply disturbance depends on the impact it does to energy security of supply. The level of energy supply disturbance expressible with points: from 0 points (no impact) to 5 points (very heavy impact). It is analysed impact of this disturbance to different sectors of state: economical, social and political. The impact and caused damage of energy supply disturbance to economical, social and political sectors is understandable like a different scenario. Energy supply disturbance depends on different parameters. Scenarios of disturbances were modeled considering three parameters. For comparison there were developed 100 different long term energy supply disturbance scenarios. There were selected most common, most heavy (critical) and easiest scenarios, evaluated such scenarios probabilities and energy supply disturbance probabilities. In thia paper was used Markov chains and processes, probability distributions.