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Photoexcitation and charge carrier thermalization inside semiconductor photocatalysts are two important steps in solar fuel production. Here, photoexcitation and charge carrier thermalization in a silicon wafer are for the first time probed by a novel, yet simple and user-friendly Attenuated Total Reflectance Infrared spectroscopy (ATR-IR) system.

Photoexcitation and charge carrier thermalization inside semiconductor photocatalysts are two important steps in solar fuel production. Here, photoexcitation and charge carrier thermalization in a silicon wafer are for the first time probed by a novel, yet simple and user-friendly Attenuated Total Reflectance Infrared spectroscopy (ATR-IR) system.

The presented article will describe an 'effect-cause' model for the purpose of simulating the energy consumption of DC fed light rail vehicles. The model will assess the advantages of hybrid vehicles in terms of energy consumption, network power and voltage variations, line current and losses; and will help sizing and designing a supercapacitor based energy storage system (ESS) for both on-board, and stationary applications. The proposed modeling needs to allow the ESS sizing according to the objective that needs to be achieved, being braking energy recovery, voltage drop compensation and peak power shaving the most common goals of ESS use in hybrid vehicles. The needed power and energy levels will vary in function of the vehicle features and the driving cycle followed. This all can be determined by the quasi-static simulation tool to ease the design process. Another objective of the modeling tool is to evaluate the behaviour of the vehicle power flow controller, which manages the power from/to the ESS in function of the state of several variables.

The presented article will describe an 'effect-cause' model for the purpose of simulating the energy consumption of DC fed light rail vehicles. The model will assess the advantages of hybrid vehicles in terms of energy consumption, network power and voltage variations, line current and losses; and will help sizing and designing a supercapacitor based energy storage system (ESS) for both on-board, and stationary applications. The proposed modeling needs to allow the ESS sizing according to the objective that needs to be achieved, being braking energy recovery, voltage drop compensation and peak power shaving the most common goals of ESS use in hybrid vehicles. The needed power and energy levels will vary in function of the vehicle features and the driving cycle followed. This all can be determined by the quasi-static simulation tool to ease the design process. Another objective of the modeling tool is to evaluate the behaviour of the vehicle power flow controller, which manages the power from/to the ESS in function of the state of several variables.

It is well known that the efficiency of PV modules decreases with increasing module temperatures. Many studies have paid attention to the development and validation of heuristic models to calculate the PV module temperature in higher latitudes, however only a few focus on the thermal behaviour of PV modules in tropical regions of the world, where constantly high temperatures prevail. Also, little is known about the effect of including wind speed in these thermal models. This study evaluates three of such models - one that excludes wind, and two others including the wind influence - using hourly data for two tropical locations. Results show that the average hourly wind speeds in Singapore and Jayapura (Indonesia) are low and therefore the influence of the wind on the PV module temperature is minor. The three evaluated models produce about the same results with RMSE between 1.5-3.8 °C during daytime, which corresponds to a deviation in power output in the range of 0.3-1.6 %, depending on the PV module technology.

It is well known that the efficiency of PV modules decreases with increasing module temperatures. Many studies have paid attention to the development and validation of heuristic models to calculate the PV module temperature in higher latitudes, however only a few focus on the thermal behaviour of PV modules in tropical regions of the world, where constantly high temperatures prevail. Also, little is known about the effect of including wind speed in these thermal models. This study evaluates three of such models - one that excludes wind, and two others including the wind influence - using hourly data for two tropical locations. Results show that the average hourly wind speeds in Singapore and Jayapura (Indonesia) are low and therefore the influence of the wind on the PV module temperature is minor. The three evaluated models produce about the same results with RMSE between 1.5-3.8 °C during daytime, which corresponds to a deviation in power output in the range of 0.3-1.6 %, depending on the PV module technology.

Saving energy in greenhouses is an important issue for growers. Here, we present a method to minimize the total energy that is required to heat and cool a greenhouse. Using this method, the grower can define bounds for temperature, humidity, CO2 concentration, and the maximum amount of CO2 available. Given these settings, optimal control techniques can be used to minimize energy input. To do this, an existing greenhouse climate model for temperature and humidity was expanded to include a CO2 balance. Heating, cooling, the amount of natural ventilation, and the injection of industrial CO2 were used as control variables.Standard optimization settings were defined in order to compare the grower's strategy with the optimal solution. This optimization resulted in a theoretical 47% reduction in heating, 15% reduction in cooling, and 10% reduction in CO2 injection for the year 2012. The optimal control does not need to maintain a minimum pipe temperature, in contrast to current practice. When the minimum pipe temperature strategy of the grower was implemented, heating and CO2 were reduced by 28% and 10% respectively.We also analyzed the effect of different bounds on optimal energy input. We found that as more freedom is given to the climate variables, the higher the potential energy savings. However, in practice the grower is in charge of defining the bounds. Thus, the potential energy savings critically depend on the choice of these bounds. This effect was analyzed by varying the bounds. However, because the effect can be demonstrated to the grower, the outcome has value to the grower with respect to decision making, an option that is not currently available in practice today.

Saving energy in greenhouses is an important issue for growers. Here, we present a method to minimize the total energy that is required to heat and cool a greenhouse. Using this method, the grower can define bounds for temperature, humidity, CO2 concentration, and the maximum amount of CO2 available. Given these settings, optimal control techniques can be used to minimize energy input. To do this, an existing greenhouse climate model for temperature and humidity was expanded to include a CO2 balance. Heating, cooling, the amount of natural ventilation, and the injection of industrial CO2 were used as control variables.Standard optimization settings were defined in order to compare the grower's strategy with the optimal solution. This optimization resulted in a theoretical 47% reduction in heating, 15% reduction in cooling, and 10% reduction in CO2 injection for the year 2012. The optimal control does not need to maintain a minimum pipe temperature, in contrast to current practice. When the minimum pipe temperature strategy of the grower was implemented, heating and CO2 were reduced by 28% and 10% respectively.We also analyzed the effect of different bounds on optimal energy input. We found that as more freedom is given to the climate variables, the higher the potential energy savings. However, in practice the grower is in charge of defining the bounds. Thus, the potential energy savings critically depend on the choice of these bounds. This effect was analyzed by varying the bounds. However, because the effect can be demonstrated to the grower, the outcome has value to the grower with respect to decision making, an option that is not currently available in practice today.