Energy transition under scenario uncertainty: a mean-field game approach

We study the impact of transition scenario uncertainty, and in particular, the uncertainty about future carbon price and electricity demand, on the pace of decarbonization of the electricity industry. To this end, we build a discrete time mean-field game model for the long-term dynamics of the electricity market subject to common random shocks affecting the carbon price and the electricity demand. These shocks depend on a macroeconomic scenario, which is not observed by the agents, but can be partially deduced from the frequency of the shocks. Due to this partial observation feature, the common noise is non-Markovian. We consider two classes of agents: conventional producers and renewable producers. The former choose an optimal moment to exit the market and the latter choose an optimal moment to enter the market by investing into renewable generation. The agents interact through the market price determined by a merit order mechanism with an exogenous stochastic demand. We prove the existence of Nash equilibria in the resulting mean-field game of optimal stopping with common noise, developing a novel linear programming approach for these problems. We illustrate our model by an example inspired by the UK electricity market, and show that scenario uncertainty leads to significant changes in the speed of replacement of conventional generators by renewable production.Comment: 41 pages, 3 figure

Operational management in pot plant production

Operational management in pot plant production was investigated by means of system analysis and simulation. A theoretical framework for operational decision-making consisted of elaboration decisions, progress decisions, and adoption decisions. This framework was incorporated in a pot plant nursery model, which simulated the implementation of a given tactical production plan under uncertainty. In this model, crop growth as well as price formation (of the foliage plant Schefflera arboricola 'Compacta') were affected by randomly simulated exogenous conditions, which resulted in plant sizes and plant prices deviating from planning premises. Operational decision-making related to the adaptation of cultivation-schedules (and delivery patterns) in order to restore compatibility between plan and reality.Regression metamodelling was applied to analyze simulations results with respect to differences in annual net farm income due to operational decision-making, tactical planning, price variability, and the grower's attitude to operational price risk. All differences could be explained by individual decision events triggered by the strategy of operational management applied in the particular simulation.In conclusion, the applied methodology was successful in exploring the opportunities for operational management in pot plant production based on a rather normative approach and integrating theory from various scientific disciplines. Furthermore, simulation experimentation showed significant impact of operational management on the nursery's performance. Hence, the present study indicates several opportunities for beneficial support of operational management on pot plant nurseries

Influenza Vaccine Type-Dependent Antibody Response in Patients with Autoimmune Inflammatory Rheumatic Diseases

BACKGROUND: The study aimed to explore influenza antibody response in patients with autoimmune inflammatory rheumatoid diseases (AIIRDs) stratified by the different vaccine types applied in Denmark during the 2018-2019 influenza season.METHODS: Included patients were diagnosed with rheumatoid arthritis, psoriatic arthritis, or spondyloarthritis receiving biological disease-modifying antirheumatic drugs (bDMARDs) with or without conventional synthetic disease-modifying antirheumatic drugs. Influenza vaccination status in the 2018-2019 season and vaccine type received were reviewed in the Denmark. Blood samples were drawn ≥ 14 days post vaccination, and antibody titers were determined by the hemagglutinin inhibition (HAI) assay for the serotypes A/Michigan/H1N1, A/Singapore/H3N2, and B/Colorado included in the influenza vaccines in the 2018-2019 season. An overall serotype HAI geometric mean titer (GMT) was calculated from the 3 serotype-specific HAI titers. An overall serotype HAI GMT ≥ 40 was considered protective.RESULTS: Of the 205 included patients, 105 (51%) had received influenza vaccination. One-quarter of vaccinated patients achieved post-vaccination overall serotype HAI GMT ≥40. For patients vaccinated with Influvac, a significantly higher proportion had HAI titers ≥ 40 for 2 serotypes, namely, A/Michigan/H1N1 and A/Singapore/H3N2, than patients vaccinated with Vaxigrip or VaxigripTetra. The same applied to all serotypes HAI GMT, where significantly more patients who received Influvac achieved postvaccination HAI GMT≥40 versus patients who received Vaxigrip (p=0.02) or VaxigripTetra (p=0.002). The latter outcome was explored in a multivariable logistic regression analysis and remained significant when including the following variables: age, sex, treatment with methotrexate and/or prednisolone, type of influenza vaccine, time interval from vaccination to antibody measurement, and previous vaccination status.CONCLUSION: Influenza antibody levels following vaccination with Influvac in bDMARD-treated patients with AIIRDs were superior to Vaxigrip and VaxigripTetra. Treatment with methotrexate (MTX) did not reduce the antibody response.</p