3 resultados para Biased Random-key Genetic Algorithms
Resumo:
This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.
Resumo:
This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.
Resumo:
Hedgerows represent important components of agri-environment landscapes that are increasingly coming under threat from climate change, emergent diseases, invasive species and land use change. Given that population genetic data can be used to inform best-practice management strategies for woodland and hedgerow tree species, we carried out a study on hawthorn (Crataegus monogyna Jacq.), a key component of hedgerows, on a regional basis using a combination of nuclear and chloroplast microsatellite markers. We found that levels of genetic diversity were high and comparable to, or slightly higher than, other tree species from the same region. Levels of population differentiation for both sets of markers, however, were extremely low, suggesting extensive gene flow via both seed and pollen. These findings suggest that a holistic approach to woodland management, one which does not necessarily rely on the concept of “seed zones” previously suggested, but which also takes into account populations with high and/or rare chloroplast (i.e. seed-specific) genetic variation, might be the best approach to restocking and replanting.