Optimizing carbon tax for decentralized electricity markets using an agent-based model

Averting the effects of anthropogenic climate change requires a transition from fossil fuels to low-carbon technology. A way to achieve this is to decarbonize the electricity grid. However, further efforts must be made in other fields such as transport and heating for full decarbonization. This would reduce carbon emissions due to electricity generation, and also help to decarbonize other sources such as automotive and heating by enabling a low-carbon alternative. Carbon taxes have been shown to be an efficient way to aid in this transition. In this paper, we demonstrate how to to find optimal carbon tax policies through a genetic algorithm approach, using the electricity market agent-based model ElecSim. To achieve this, we use the NSGA-II genetic algorithm to minimize average electricity price and relative carbon intensity of the electricity mix. We demonstrate that it is possible to find a range of carbon taxes to suit differing objectives. Our results show that we are able to minimize electricity cost to below \textsterling10/MWh as well as carbon intensity to zero in every case. In terms of the optimal carbon tax strategy, we found that an increasing strategy between 2020 and 2035 was preferable. Each of the Pareto-front optimal tax strategies are at least above \textsterling81/tCO2 for every year. The mean carbon tax strategy was \textsterling240/tCO2.Comment: Accepted at The Eleventh ACM International Conference on Future Energy Systems (e-Energy'20) AMLIES Worksho

Tidal streams, fish and seabirds : understanding the linkages between mobile predators, prey, and hydrodynamics

Fundings: Natural Environment Research Council (GrantNumber(s): VertIBase project [NE/N01765X/1]) Department for Business, Energy and Industrial Strategy, UK Government (GrantNumber(s): Offshore Energy Strategic Environmental Assessment) ACKNOWLEDGMENTS We gratefully acknowledge the support of the crew and scientists of the MRV Scotia 2016 (0916S) and 2018 (1018S) cruises: Marianna Chimienti, Helen Wade, Laura Williamson, Ewan Edwards, Ross Culloch, Tom Evans, Sarah Fenn, David Hunter, Eric Armstrong, and Adrian Tait. This work was supported by the NERC VertIBase Project [NE/N01765X/1] and the UK Department for Business, Energy and Industrial Strategy’s Offshore Energy Strategic Environmental Assessment Programme.Peer reviewedPublisher PD

Paying for free delivery: dependent self-employment as a measure of precarity in parcel delivery

This article explores supply chain pressures in parcel delivery and how the drive to contain costs to ‘preserve value in motion’, including the costs of failed delivery, underpins contractual differentiation. It focuses on owner-drivers and home couriers paid by delivery. It considers precarity through the lens of the labour process, while locating it within the supply chain, political economy and ‘instituted economic process’ that define it. Focus on the labour process shows how ‘self-employment’ is used to remove so-called ‘unproductive’ time from the remit of paid labour. Using Smith’s concept of double indeterminacy the article captures the dynamic relationship between those on standard and non-standard contracts and interdependency of effort power and mobility power. It exposes the apparent mobility and autonomy of dependent selfemployed drivers while suggesting that their presence, alongside the increased use of technology, reconfigures the work-effort bargain across contractual status

Energy Trends: September 2020

Energy Trends and Energy Prices are produced by the Department for Business, Energy and Industrial Strategy (BEIS) on a quarterly basis. Both periodicals are published concurrently in June, September, December and March. The September editions cover the second quarter of the current year