Simplify Bidding on the Day-Ahead Electricity Market Nordpool through Structured Time-Series

Abstract: In Sweden, electricity is purchased on a so-called day-ahead spot market (Nordpool). The electricity is based on a predicted hourly need for the upcoming day [4, 5]. Production and consumption of electricity need to be balanced since it is hard to store electricity [25]. Today, electricity companies struggle to uphold this balance using currently available tools. A potential solution would be to support bidders by visualizing time-series. Then they could identify time-series lacking data crucial to the prediction phase and resolve them. In this thesis, a prototype was implemented consisting of different views/use-cases, aimed at simplifying the bidding process for balance responsible parties (BRPs). The prototype consisted of structured time-series and presents predicted data in a way that makes the decision making easier when placing bids. Results from a study using the prototype with BRPs and professionals showed that the use-cases/views are useful in terms of 1) getting a better structure, 2) identifying incomplete time series, 3) better quality assurance of the time-series and 4) lowering the time-consumption. Additionally, the bidders suggested that the addition of references, in terms of other prediction methods than the one that was used could improve their decision making.