Impact of thermal plant cycling on the cost-optimal composition of a regional electricity generation system Lisa Göransson ⇑ , Joel Goop, Mikael Odenberger, Filip Johnsson Chalmers University of Technology, 412 96 Gothenburg, Sweden highlights  Thermal cycling impact the cost-optimal electricity system composition.  9–19% of investments are cycling dependent in systems studied with cap on CO 2 .  Cost-competitive, flexible thermal generation increases wind power investments.  System characteristics which result in cycling dependent capacity are identified. article info Article history: Received 16 September 2016 Received in revised form 27 March 2017 Accepted 8 April 2017 Keywords: Electricity system model Thermal cycling Intermittent generation Investment model abstract A regional cost-minimizing investment model that accounts for cycling properties (i.e., start-up time, minimum load level, start-up cost and emissions, and part-load costs and emissions) is developed to investigate the impact of thermal plant cycling on the cost-optimal composition of a regional electricity generation system. The model is applied to an electricity system that is rich in wind resources with and without accounting for cycling in two scenarios: one with favorable conditions for flexible bio-based gen- eration (Bio scenario); and one in which base load is favored (Base load scenario) owing to high prices for biomass. Both scenarios are subject to a tight cap on carbon dioxide emissions, limiting the investment options to technologies that have low or no carbon emissions. We report that in the Bio scenario, the cost-optimal system is dominated by wind power and flexible bio-based generation, whereas base-load generation dominates the Base load scenario, in line with the assumptions made, and the level of wind power is reduced. In the Base load scenario, 19% of the capacity is cycling-dependent, i.e., for this share of installed capacity, the choice of technology is different if cycling properties are included, compared to a case in which they are omitted. In the Bio scenario, in which flexible bio-based generation is less costly, 9% of the capacity is cycling-dependent. We conclude that it is critical to include cycling properties in investment modeling, to assess investments in thermal generation technologies that compete at utilization times in the range of 2000–5000 h. Ó 2017 Published by Elsevier Ltd. 1. Introduction The last decade has seen a drastic reduction in the costs for wind and solar power, making these generation technologies highly cost-competitive with other generation technologies with low or no carbon dioxide emissions. Combined with support schemes for renewable energy source (RES)-based electricity gen- eration, this has resulted in the expansion of wind and solar power in several regions of the world, in a development that is foreseen to continue. This increased adoption of wind and solar power moti- vates the development of electricity system modeling methods that account for variability as well as variation management, such as thermal cycling. In dispatch models, cycling costs and cycling emissions from thermal generation are common features, as exem- plified by the studies of Göransson et al. [1], Lew et al. [2], Meibom et al. [3], Bruce et al. [4], Troy et al. [5] and Mc Garrigle et al. [6]. Van Den Bergh et al. [7] present a further refined approach to account for thermal cycling in dispatch models. Göransson et al. [1] and Troy et al. [5] have shown how the inclusion of thermal cycling in dispatch modeling can modify the modeled dispatch order of the units in a wind-thermal electricity system. Van den Bergh et al. [8] show that cycling costs can be reduced with up to 40% if accounted for in the operation planning. Turconi et al. [9] show that, while cycling emissions do not negate the benefit of increased wind shares, emissions from cycling thermal http://dx.doi.org/10.1016/j.apenergy.2017.04.018 0306-2619/Ó 2017 Published by Elsevier Ltd. ⇑ Corresponding author. E-mail address: lisa.goransson@chalmers.se (L. Göransson). Applied Energy 197 (2017) 230–240 Contents lists available at ScienceDirect Applied Energy journal homepage: www.elsevier.com/locate/apenergy