Energiportföljoptimering : Portföljförvaltning åt företagskunder på den svenska elmarknaden

• Main Authors: Garoosi, Shahrzad, Redgert, Jessica
• Format: Others
• Language: Swedish
• Published: Mälardalens högskola, Akademin för ekonomi, samhälle och teknik 2021
• Subjects: Portfolio management; portfolio optimization; energy portfolio; derivatives; risk; risk management; business to business customers.; Engineering and Technology; Teknik och teknologier; Energy Engineering; Energiteknik
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-55380

The competitive electricity market faces low margins while the energy transition entails volatile electricity prices and major risks in the market. Along with these problems, there are challenges in optimizing energy portfolios, as they are based on maximized return and minimized risks. Portfolio managers handle electricity contracts for customers with the aim of offering competitive electricity contracts and at the same time achieving profit. This study therefore aims to investigate how electricity trading companies can optimize the energy portfolio for corporate customers in the Swedish electricity market. In addition, it is analyzed how these companies can adapt portfolio optimization to the challenges of the electricity market and what kind of digital systems are needed to support portfolio optimization. Previous studies in the subject have mainly focused on a quantitative approach. In this study on the other hand, a qualitative method is used. This in order to use interviews, models and theories to investigate how electricity trading companies can optimize the portfolio for their corporate customers. The study is divided into an empirical part that includes interviews with 12 electricity trading companies, as well as a theoretical part. The theoretical part deals with theories for risk management, including portfolio optimization, price hedging with electricity derivatives and the Risk Management Payoff model. In addition, the Customer Relationship Management (CRM) model is included, with the aim of strengthening relationships. The theoretical framework has been used to analyze the empirical data of the study and has resulted in conclusions that answer the research questions. The results show that in order to achieve energy portfolio optimization, futures contract is the derivative that provides the lowest risk and can be used as the optimal hedging tool. For larger corporate customers, however, forward contract is a more suitable hedging tool. This is because larger customers prefer to secure monthly contracts, rather than daily settled contracts with futures. To support portfolio management with electricity contracts, there is a need for support systems. Electricity trading companies are in need of a common system for both financial and physical trading to enable easier management. In addition, security functions in systems as well as more informative and customer-friendly systems are of interest. Portfolio optimization is customer centric, thus a strong relationship between portfolio manager and customer, with good trust and reputation, is important. Finally, adaptation in portfolio management with diversification and automation with AI, can be a way to achieve competitiveness in the electricity market also in the future.