On Risk Management of Electrical Distribution Systems and the Impact of Regulations

Sammanfattning: The Swedish electricity market was de-regulated in 1996, followed by new laws and a new regulation applied to the natural monopolies of electrical distribution systems (EDS). These circumstances have motivated distribution systems operators (DSOs) to introduce more comprehensive analysis methods. The laws, the regulation and additional incentives have been investigated within this work and results from this study can be valuable when developing risk methods or other quantitative methods applied to EDS. This tendency is not unique for Sweden, the results from a comparative study of customer outage compensation laws between Sweden and UK is for example included.As a part of investigating these incentives, studies of the Swedish regulation of customer network tariffs have been performed which provide valuable learning when developing regulation models in different countries. The Swedish regulatory model, referred to as the Network Performance Assessment Model (NPAM), was created for one of the first de-regulated electricity markets in the world and has a unique and novel approach. For the first time, an overall presentation of the NPAM has been performed including description of the underlying theory as a part of this work. However, the model has been met by difficulties and the future usage of the model is uncertain. Furthermore, the robustness of the NPAM has been evaluated in two studies with the main conclusion that the NPAM is sensitive toward small variations in input data. Results from these studies are explained theoretically investigating algorithms of the NPAM.A pre-study of a project on developing international test systems is presented and this ongoing project aims to be a useful input when developing risk methods. An application study is included with the approach to systematically describe the overall risk management process at a DSO including an evaluation and ideas of future developments. The main objective is to support DSOs in the development of risk management, and to give academic reference material to utilize industry experience. An idea of a risk management classification has been concluded from this application study. The study provides an input to the final objective of a quantitative risk method.