• Energy Research
• 2016-2025close
• Netherlands close
• Imperial College London close

We consider the problem of dispatching a fleet of distributed energy reserve devices to collectively meet a sequence of power requests over time. Under the restriction that reserves cannot be replenished, we aim to maximise the survival time of an energy-constrained islanded electrical system; and we discuss realistic scenarios in which this might be the ultimate goal of the grid operator. We present a policy that achieves this optimality, and generalise this into a set-theoretic result that implies there is no better policy available, regardless of the realised energy requirement scenario. Accepted for publication to the 2018 Power Systems Computation Conference (PSCC)

We consider the problem of dispatching a fleet of distributed energy reserve devices to collectively meet a sequence of power requests over time. Under the restriction that reserves cannot be replenished, we aim to maximise the survival time of an energy-constrained islanded electrical system; and we discuss realistic scenarios in which this might be the ultimate goal of the grid operator. We present a policy that achieves this optimality, and generalise this into a set-theoretic result that implies there is no better policy available, regardless of the realised energy requirement scenario. Accepted for publication to the 2018 Power Systems Computation Conference (PSCC)

Abstract. In eastern Africa droughts can cause crop failure and lead to food insecurity. With increasing temperatures, there is an a priori assumption that droughts are becoming more severe. However, the link between droughts and climate change is not sufficiently understood. Here we investigate trends in long-term agricultural drought and the influence of increasing temperatures and precipitation deficits. Using a combination of models and observational datasets, we studied trends, spanning the period from 1900 (to approximate pre-industrial conditions) to 2018, for six regions in eastern Africa in four drought-related annually averaged variables: soil moisture, precipitation, temperature, and evaporative demand (E0). In standardized soil moisture data, we found no discernible trends. The strongest influence on soil moisture variability was from precipitation, especially in the drier or water-limited study regions; temperature and E0 did not demonstrate strong relations to soil moisture. However, the error margins on precipitation trend estimates are large and no clear trend is evident, whereas significant positive trends were observed in local temperatures. The trends in E0 are predominantly positive, but we do not find strong relations between E0 and soil moisture trends. Nevertheless, the E0 trend results can still be of interest for irrigation purposes because it is E0 that determines the maximum evaporation rate. We conclude that until now the impact of increasing local temperatures on agricultural drought in eastern Africa is limited and we recommend that any soil moisture analysis be supplemented by an analysis of precipitation deficit.

Abstract. In eastern Africa droughts can cause crop failure and lead to food insecurity. With increasing temperatures, there is an a priori assumption that droughts are becoming more severe. However, the link between droughts and climate change is not sufficiently understood. Here we investigate trends in long-term agricultural drought and the influence of increasing temperatures and precipitation deficits. Using a combination of models and observational datasets, we studied trends, spanning the period from 1900 (to approximate pre-industrial conditions) to 2018, for six regions in eastern Africa in four drought-related annually averaged variables: soil moisture, precipitation, temperature, and evaporative demand (E0). In standardized soil moisture data, we found no discernible trends. The strongest influence on soil moisture variability was from precipitation, especially in the drier or water-limited study regions; temperature and E0 did not demonstrate strong relations to soil moisture. However, the error margins on precipitation trend estimates are large and no clear trend is evident, whereas significant positive trends were observed in local temperatures. The trends in E0 are predominantly positive, but we do not find strong relations between E0 and soil moisture trends. Nevertheless, the E0 trend results can still be of interest for irrigation purposes because it is E0 that determines the maximum evaporation rate. We conclude that until now the impact of increasing local temperatures on agricultural drought in eastern Africa is limited and we recommend that any soil moisture analysis be supplemented by an analysis of precipitation deficit.

Embedding tidal turbines within simulations of realistic large-scale tidal flows is a highly multi-scale problem that poses significant computational challenges. Here this problem is tackled using actuator disc momentum (ADM) theory and Reynolds-averaged Navier–Stokes (RANS) with, for the first time, dynamically adaptive mesh optimisation techniques. Both k−ωk−ω and k−ωk−ω SST RANS models have been developed within the Fluidity framework, an adaptive mesh CFD solver, and the model is validated against two sets of experimental flume test results. A brief comparison against a similar OpenFOAM model is presented to portray the benefits of the finite element discretisation scheme employed in the Fluidity ADM model. This model has been developed with the aim that it will be seamlessly combined with larger numerical models simulating tidal flows in realistic domains. This is where the mesh optimisation capability is a major advantage as it enables the mesh to be refined dynamically in time and only in the locations required, thus making optimal use of limited computational resources.