Performance of industrial melting pots in the provision of dynamic frequency response in the Great Britain power system

As a result of the increasing integration of Renewable Energy Source (RES), maintenance of the balance between supply and demand in the power system is more challenging because of RES’s intermittency and uncontrollability. The smart control of demand is able to contribute to the balance by providing the grid frequency response. This paper uses the industrial Melting Pot (MP) loads as an example. A thermodynamic model depicting the physical characteristics of MPs was firstly developed based on field measurements carried out by Open Energi. A distributed control was applied to each MP which dynamically changes the aggregated power consumption of MPs in proportion to changes in grid frequency while maintaining the primary heating function of each MP. An aggregation of individual MP models equipped with the control was integrated with the Great Britain (GB) power system models. Case studies verified that the aggregated MPs are able to provide frequency response to the power system. The response from MPs is similar but faster than the conventional generators and therefore contributes to the reduction of carbon emissions by replacing the spinning reserve capacity of fossil-fuel generators. Through the reviews of the present balancing services in the GB power system, with the proposed frequency control strategy, the Firm Frequency Response service is most beneficial at present for demand aggregators to tender for. All studies have been conducted in partnership between Cardiff University, Open Energi London – Demand Aggregator, and National Grid – System Operator in GB to ensure the quality and compliance of results

Power system frequency response from the control of bitumen tanks

Bitumen tanks were tested to investigate the capability of industrial heating loads to provide frequency response to an electric power system. A decentralized control algorithm was developed enabling the tanks to alter their power consumption in proportion to the variations of grid frequency. The control maintains the normal operation of tanks and causes little impact on their primary function of storing hot bitumen. Field investigations were undertaken on 76 tanks with power ratings from 17 to 75 kW. A model of a population of controlled tanks was developed. The behavior of the tanks was compared between the simulations and the field tests. The model of controlled tanks was then integrated with a simplified Great Britain power system model. It was shown that the controlled tanks were able to contribute to the grid frequency control in a manner similar to and faster than that provided by frequency-sensitive generation

Effects of infection-induced migration delays on the epidemiology of avian influenza in wild mallard populations

Wild waterfowl populations form a natural reservoir of Avian Influenza (AI) virus, and fears exist that these birds may contribute to an AI pandemic by spreading the virus along their migratory flyways. Observational studies suggest that individuals infected with AI virus may delay departure from migratory staging sites. Here, we explore the epidemiological dynamics of avian influenza virus in a migrating mallard (Anas platyrhynchos) population with a specific view to understanding the role of infection-induced migration delays on the spread of virus strains of differing transmissibility. We develop a host-pathogen model that combines the transmission dynamics of influenza with the migration, reproduction and mortality of the host bird species. Our modeling predicts that delayed migration of individuals influences both the timing and size of outbreaks of AI virus. We find that (1) delayed migration leads to a lower total number of cases of infection each year than in the absence of migration delay, (2) when the transmission rate of a strain is high, the outbreak starts at the staging sites at which birds arrive in the early part of the fall migration, (3) when the transmission rate is low, infection predominantly occurs later in the season, which is further delayed when there is a migration delay. As such, the rise of more virulent AI strains in waterfowl could lead to a higher prevalence of infection later in the year, which could change the exposure risk for farmed poultry. A sensitivity analysis shows the importance of generation time and loss of immunity for the effect of migration delays. Thus, we demonstrate, in contrast to many current transmission risk models solely using empirical information on bird movements to assess the potential for transmission, that a consideration of infection-induced delays is critical to understanding the dynamics of AI infection along the entire flyway.<br /

Human-mediated seed dispersal over long distances

Human activities have fundamental impacts on the distribution of species through altered land use, but also directly by dispersal of propagules. Rare long-distance dispersal events have a disproportionate importance for the spread of species including invasions. While it is widely accepted that humans may act as vectors of long-distance dispersal, there are few studies that quantify this process. We studied in detail a mechanism of human-mediated dispersal (HMD). For two plant species we measured, over a wide range of distances, how many seeds are carried by humans on shoes. While over half of the seeds fell off within 5m, seeds were regularly still attached to shoes after 5km. Semi-mechanistic models were fitted, and these suggested that long-distance dispersal on shoes is facilitated by decreasing seed detachment probability with distance. Mechanistic modelling showed that the primary vector, wind, was less important as an agent of long-distance dispersal, dispersing seeds less than 250m. Full dispersal kernels were derived by combining the models for primary dispersal by wind and secondary dispersal by humans. These suggest that walking humans can disperse seeds to very long distances, up to at least 10km, and provide some of the first quantified dispersal kernels for HMD