Stein-Erik Fleten

Aneo is one of the first Nordic power companies to apply stochastic programming for day-ahead bidding of hydropower. This paper describes our experiences in implementing, testing, and operating a stochastic programming-based bidding method aimed at setting up an automated process for day-ahead bidding. The implementation process has faced challenges such as generating price scenarios for the optimization model, post-processing optimization results to create feasible and understandable bids, and technically integrating these into operational systems. Additionally, comparing the bids from the new stochastic-based method to the existing operator-determined bids has been challenging, which is crucial for building trust in new procedures. Our solution is a rolling horizon comparison, benchmarking the performance of the bidding methods over consecutive two-week periods. Our benchmarking results show that the stochastic method can replicate the current operator-determined bidding strategy. However, additional work is needed before we can fully automate the stochastic bidding setup, particularly in addressing inflow uncertainty and managing special constraints on our watercourses.

The transition to a zero-emission passenger vehicle fleet has become imperative because of the growing concerns about climate change. Here, we investigate the trends and socioeconomic determinants influencing emitting and battery electric vehicle ownership using longitudinal data of Norwegian households with any vehicle ownership record from 2005 to 2022, accounting for over 2.7 million unique households. Intriguingly, battery electric vehicle ownership has been concentrated on the wealthiest of those owners. Moreover, almost one in ten households once owned battery electric vehicles discontinued ownership by 2022. Our population-level panel data analysis indicates that larger household size, having children, and working away from the residence municipality are positively linked to owning emitting vehicles, while demonstrating the opposite effect regarding battery electric vehicle ownership. Higher income also appears to drive vehicle ownership positively, irrespective of fuel type.

Analyses of climate policies often assume the economy is in a first-best equilibrium with well-functioning markets. This paper studies policy effects in power systems characterized by a market failure known as the missing market problem, whereby the incompleteness of long-term markets leaves investors exposed to uninsured risk. We find that renewable tax credits and CO$_2$ taxes may partly correct this market failure, thus providing an economic benefit additional to climate change mitigation. Consequently, illustrative experiments show the costs of these policies to be lower, and in some cases even negative, in power systems with missing risk markets.