Search

• Analytical method for estimating the size of a loss-of-generation disturbance. • Investigates a linear relationship between power and frequency deviations of CCGTs. • Improves disturbance size estimation accuracy with CCGT units' negative droop gain. • Estimates the disturbance size for pre-and post-event conditions. • Provide an approach that computes deviations in post-event demand-side consumption. With the substantial popularity of combined cycle gas turbine (CCGT) power plants in the nowadays power systems, special care must be taken to regulate frequency due to unique frequency response characteristic of the full-loaded CCGT units. This unique feature is documented in the literature; however, its effect on determining frequency response of the power systems was not addressed in detail. This study proposes a new analytical method to achieve a more accurate estimated size of a loss-of-generation disturbance. This method considers demand-side power deviations and transmission lines power loss as well as unique frequency response of the CCGT units following the event. Firstly, it is exposed that there is an approximately linear relationship between power and frequency deviations of these plants in a real-world power system despite the complexity of the CCGT model. This relationship may be represented by a negative droop gain. Next, the derived CCGT's linear characteristic is formulated in the disturbance size estimation process. Finally, the effectiveness of the proposed modifications is demonstrated through extensive simulations on a 36-zone Great Britain equivalent test system. [ABSTRACT FROM AUTHOR]

• EC-Earth large ensembles are used to drive hydrological models of catchments in Great Britain. • Estimates show the changing chance of unprecedented high temperatures and low rainfall. • Climate storylines describe changes in future dry spring-summers, autumn-winters and multiple dry winters. • Storylines can be used to stress test hydrological systems and inform decision-making. The UK has experienced recurring hydrological droughts in the past and their frequency and severity are predicted to increase with climate change. However, quantifying the risks of extreme droughts is challenging given the short observational record, the multivariate nature of droughts and large internal variability of the climate system. We use EC-Earth time-slice large ensembles, which consist of 2000 years of data each for present-day, 2°C and 3°C conditions relative to pre-industrial, to drive hydrological models of river catchments in Great Britain (GB) to obtain a large set of plausible droughts. Since future warming is certain, the uncertainty in drought is mainly associated with uncertainty in precipitation. Estimates of unprecedented extremes show that the chance of a summer month in a given year drier than the observed driest summer (1995) is projected to increase with future warming (from 9% in the present-day (PD) to 18% in a 3°C warmer world (3C) for southeast England). For winter, the chance of a dry winter month drier than the observed driest winter (1991–92) slightly decreases (from 10% - PD to 8% − 3C for southeast England) but the chance of the driest winter does not change significantly with future warming. We add value to these probabilistic estimates by sampling for physical climate storylines of drought sequences characterised by dry spring-summers, autumn-winters and consecutive dry winters. Dry spring-summers are estimated to become drier with future warming primarily driven by reduced precipitation in summer. Dry autumn-winters may become wetter mainly driven by the general trend of more precipitation in winter although drought conditions triggered by moderate autumn–winter precipitation deficits may worsen given the higher likelihood of being followed by a dry summer. Similarly, drought impacts of consecutive dry winters, a particular risk for slow-responding catchments in the English Lowlands, may worsen with future warming as the intervening summer is projected to become hotter and drier. These storylines can be used to stress-test hydrological systems and inform decision-making. [ABSTRACT FROM AUTHOR]