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Abstract Model scale testing is vital for developing technologies like tidal turbines. Reduced-scale tests follow numerical design and are cost-effective in controlled environments, allowing parameter adjustments. However, controlled tests face drawbacks, such as blockage effects and the inability to replicate real sea conditions. Sea trials, conducted in actual marine environments, offer realistic data and continuous collection, potentially being cost-effective despite environmental variability and complex data processing. This work aims to measure real sea effects, such as marine growth and stream turbulence, on fixed and moving parts, of a scaled model of GEMSTAR tidal stream energy converter, a twin rotors submerged tethered device, designed to tap tidal current energy. The planned model installation site is at the Renewable Marine Energy Laboratory, a natural facility located on the East coast of the Strait of Messina (southern Italy), characterized by tidal currents with a maximum speed of about 1.25 m/s. Due to the low stream speed, in order to get significant data, an up-scaling of the existing model rotor diameter has been necessary, and a specific new blade design has been performed, in order to lower the cut-in speed, increasing in this way the useful power production time of the model. The paper illustrates the different phases of model scale design.

Abstract Model scale testing is vital for developing technologies like tidal turbines. Reduced-scale tests follow numerical design and are cost-effective in controlled environments, allowing parameter adjustments. However, controlled tests face drawbacks, such as blockage effects and the inability to replicate real sea conditions. Sea trials, conducted in actual marine environments, offer realistic data and continuous collection, potentially being cost-effective despite environmental variability and complex data processing. This work aims to measure real sea effects, such as marine growth and stream turbulence, on fixed and moving parts, of a scaled model of GEMSTAR tidal stream energy converter, a twin rotors submerged tethered device, designed to tap tidal current energy. The planned model installation site is at the Renewable Marine Energy Laboratory, a natural facility located on the East coast of the Strait of Messina (southern Italy), characterized by tidal currents with a maximum speed of about 1.25 m/s. Due to the low stream speed, in order to get significant data, an up-scaling of the existing model rotor diameter has been necessary, and a specific new blade design has been performed, in order to lower the cut-in speed, increasing in this way the useful power production time of the model. The paper illustrates the different phases of model scale design.

This work deals with the simultaneous coordinated tuning of the FACTS (flexible AC transmission systems) POD power oscillation damping) controller and the conventional PSS (power system stabilizer) controllers in multimachine power systems. Using the linearized system model and the parameter-constrained nonlinear optimization algorithm, interactions among FACTS controller and PSS controllers are considered. Furthermore, their parameters are optimized simultaneously. Simulation results of multimachine power system validate the efficiency of this new approach. The proposed algorithm is an effective method for the tuning of multicontrollers in large power systems.

This work deals with the simultaneous coordinated tuning of the FACTS (flexible AC transmission systems) POD power oscillation damping) controller and the conventional PSS (power system stabilizer) controllers in multimachine power systems. Using the linearized system model and the parameter-constrained nonlinear optimization algorithm, interactions among FACTS controller and PSS controllers are considered. Furthermore, their parameters are optimized simultaneously. Simulation results of multimachine power system validate the efficiency of this new approach. The proposed algorithm is an effective method for the tuning of multicontrollers in large power systems.

AbstractSmart meter roll-outs provide easy access to granular meter measurements, enabling advanced energy services, ranging from demand response measures, tailored energy feedback and smart home/building automation. To design such services, train and validate models, access to data that resembles what is expected of smart meters, collected in a real-world setting, is necessary. The REFIT electrical load measurements dataset described in this paper includes whole house aggregate loads and nine individual appliance measurements at 8-second intervals per house, collected continuously over a period of two years from 20 houses. During monitoring, the occupants were conducting their usual routines. At the time of publishing, the dataset has the largest number of houses monitored in the United Kingdom at less than 1-minute intervals over a period greater than one year. The dataset comprises 1,194,958,790 readings, that represent over 250,000 monitored appliance uses. The data is accessible in an easy-to-use comma-separated format, is time-stamped and cleaned to remove invalid measurements, correctly label appliance data and fill in small gaps of missing data.

AbstractSmart meter roll-outs provide easy access to granular meter measurements, enabling advanced energy services, ranging from demand response measures, tailored energy feedback and smart home/building automation. To design such services, train and validate models, access to data that resembles what is expected of smart meters, collected in a real-world setting, is necessary. The REFIT electrical load measurements dataset described in this paper includes whole house aggregate loads and nine individual appliance measurements at 8-second intervals per house, collected continuously over a period of two years from 20 houses. During monitoring, the occupants were conducting their usual routines. At the time of publishing, the dataset has the largest number of houses monitored in the United Kingdom at less than 1-minute intervals over a period greater than one year. The dataset comprises 1,194,958,790 readings, that represent over 250,000 monitored appliance uses. The data is accessible in an easy-to-use comma-separated format, is time-stamped and cleaned to remove invalid measurements, correctly label appliance data and fill in small gaps of missing data.

Abstract An attractive path to the production of hydrogen from water is a two-step thermo chemical cycle powered by concentrated sunlight from a solar tower system. In the first process step the redox system, a ferrite coated on a monolithic honeycomb absorber, is present in its reduced form while the concentrated solar energy hits the ceramic absorber. When water vapour is fed to the honeycomb at 800 °C, oxygen is abstracted from the water molecules, bond in the redox system and hydrogen is produced. When the metal oxide system is completely oxidised it is heated up for regeneration at 1100–1200 °C in an oxygen-lean atmosphere. Under those conditions and in the second process step, oxygen is set free from the redox system, so the metal oxide is being reduced and after completion of the reaction again capable for water splitting. Since the overall process consists of two core reaction steps, which need to be carried out sequentially in a reactor unit at two different temperature steps, a special process and plant concept had to be developed enabling the continuous supply of product regardless of the alternating nature of the solar reactor operation. The challenge of the process control is to keep the two core reaction temperatures constant and to ensure regular temperature switches after completion of the individual process steps, independent of the weather conditions, like DNI fluctuation, clouds and wind speed. Also start-up, the fast switching after completion of half-cycles and the shutdown must be controlled. State of the art is the manual switching of heliostats to fulfil those control tasks. This paper describes the development and use of a system model of this process. The model consists of three main parts: the simulation of the solar flux distribution at the receiver aperture, the simulation of the temperatures in the reactor modules and the simulation of the hydrogen generation. It can be used for the analysis of the operational behaviour. The model is intended to be used in the future for the control of the whole process.

Abstract An attractive path to the production of hydrogen from water is a two-step thermo chemical cycle powered by concentrated sunlight from a solar tower system. In the first process step the redox system, a ferrite coated on a monolithic honeycomb absorber, is present in its reduced form while the concentrated solar energy hits the ceramic absorber. When water vapour is fed to the honeycomb at 800 °C, oxygen is abstracted from the water molecules, bond in the redox system and hydrogen is produced. When the metal oxide system is completely oxidised it is heated up for regeneration at 1100–1200 °C in an oxygen-lean atmosphere. Under those conditions and in the second process step, oxygen is set free from the redox system, so the metal oxide is being reduced and after completion of the reaction again capable for water splitting. Since the overall process consists of two core reaction steps, which need to be carried out sequentially in a reactor unit at two different temperature steps, a special process and plant concept had to be developed enabling the continuous supply of product regardless of the alternating nature of the solar reactor operation. The challenge of the process control is to keep the two core reaction temperatures constant and to ensure regular temperature switches after completion of the individual process steps, independent of the weather conditions, like DNI fluctuation, clouds and wind speed. Also start-up, the fast switching after completion of half-cycles and the shutdown must be controlled. State of the art is the manual switching of heliostats to fulfil those control tasks. This paper describes the development and use of a system model of this process. The model consists of three main parts: the simulation of the solar flux distribution at the receiver aperture, the simulation of the temperatures in the reactor modules and the simulation of the hydrogen generation. It can be used for the analysis of the operational behaviour. The model is intended to be used in the future for the control of the whole process.