• Energy Research
• Open Source close
• Embargo close
• Applied Energy close

Abstract Localisation of energy technologies and policies is increasing the need for high-resolution spatial and temporal energy demand simulation modelling, which goes beyond annual and national scale. Increasing the temporal resolution is crucial for demand side management modelling or for the simulation of load profile changes due to the installation of new technologies such as heat pumps. Increasing the spatial resolution enables regional energy planning and capturing the spatial dynamics of drivers of energy demand. Yet regional and local energy grids are interconnected with national and continental networks, so to capture multi-scale effects, high resolution is required everywhere. A high-resolution bottom-up engineering energy demand simulation model is introduced, which projects energy demands both for a high spatial and high temporal scale and enables spatial explicit simulation of model parameters. The model is applied for exploring implications of the electrification of heat by a large-scale uptake of heat pumps for water and space heating in the United Kingdom and to simulate heat pump related demand side management opportunities. We simulate a change in peak electricity heating load of −0.4 t– 21.5 GW for 50% heat pump uptake for space heating demands across different scenarios resulting in an increase of total peak electricity demand of 3.3–31.2 GW (6.3–59.8%). The simulation results show considerable regional differences in change of electricity load factors (−17.2–8.4%) and peak electricity demands (−9.9–206.1%). The potential to reduce national electricity peak load with managed heat pump load profiles for heating is simulated to be 0.2–5.8 GW (0.4–11.1%). These results exemplify the importance of discussing heat-pump induced change in peak electricity demands within a scenario context. Including different drivers in energy demands and their variability considerably affects the scale of anticipated electricity peak demand.

Abstract Localisation of energy technologies and policies is increasing the need for high-resolution spatial and temporal energy demand simulation modelling, which goes beyond annual and national scale. Increasing the temporal resolution is crucial for demand side management modelling or for the simulation of load profile changes due to the installation of new technologies such as heat pumps. Increasing the spatial resolution enables regional energy planning and capturing the spatial dynamics of drivers of energy demand. Yet regional and local energy grids are interconnected with national and continental networks, so to capture multi-scale effects, high resolution is required everywhere. A high-resolution bottom-up engineering energy demand simulation model is introduced, which projects energy demands both for a high spatial and high temporal scale and enables spatial explicit simulation of model parameters. The model is applied for exploring implications of the electrification of heat by a large-scale uptake of heat pumps for water and space heating in the United Kingdom and to simulate heat pump related demand side management opportunities. We simulate a change in peak electricity heating load of −0.4 t– 21.5 GW for 50% heat pump uptake for space heating demands across different scenarios resulting in an increase of total peak electricity demand of 3.3–31.2 GW (6.3–59.8%). The simulation results show considerable regional differences in change of electricity load factors (−17.2–8.4%) and peak electricity demands (−9.9–206.1%). The potential to reduce national electricity peak load with managed heat pump load profiles for heating is simulated to be 0.2–5.8 GW (0.4–11.1%). These results exemplify the importance of discussing heat-pump induced change in peak electricity demands within a scenario context. Including different drivers in energy demands and their variability considerably affects the scale of anticipated electricity peak demand.

One of the biggest challenges in converting wave energy is to enable the use of low frequency waves, since the highest waves in typical sea states have low frequencies, as can be seen from the corresponding wave spectra, such as the Pierson–Moskowitz or JONSWAP spectra. In this paper, we show that this challenge is indeed achievable for the operation of small autonomous drifting sensor platforms. We present the design and optimization of a compact wave energy converter that freely floats in random sea waves. An optimization of the dynamical behavior as well as the electromagnetic power take-off is conducted based on simulations and experiments. The platform has compact dimensions of 50 cm draft and 50 cm diameter, which leads to special requirements for size and appearance. To meet these requirements, a two-body self-reacting point absorber is designed and a flux switching permanent magnet linear machine is developed for the power take-off. The developed system is validated by experiments in a wave flume and the linear generator is analyzed on a test bench. A coupled model is used to simulate and optimize the corresponding mechanical system, which leads to an increased output power from below 10 mW for the simulated initial setup to a power output of more than 100 mW in the simulation. Simulations and experiments are performed for regular and random waves in order to provide realistic approximations of the total output power.

One of the biggest challenges in converting wave energy is to enable the use of low frequency waves, since the highest waves in typical sea states have low frequencies, as can be seen from the corresponding wave spectra, such as the Pierson–Moskowitz or JONSWAP spectra. In this paper, we show that this challenge is indeed achievable for the operation of small autonomous drifting sensor platforms. We present the design and optimization of a compact wave energy converter that freely floats in random sea waves. An optimization of the dynamical behavior as well as the electromagnetic power take-off is conducted based on simulations and experiments. The platform has compact dimensions of 50 cm draft and 50 cm diameter, which leads to special requirements for size and appearance. To meet these requirements, a two-body self-reacting point absorber is designed and a flux switching permanent magnet linear machine is developed for the power take-off. The developed system is validated by experiments in a wave flume and the linear generator is analyzed on a test bench. A coupled model is used to simulate and optimize the corresponding mechanical system, which leads to an increased output power from below 10 mW for the simulated initial setup to a power output of more than 100 mW in the simulation. Simulations and experiments are performed for regular and random waves in order to provide realistic approximations of the total output power.

Combining co-firing biomass and carbon capture and storage (CCS) in power plants offers attractive potential for net removal of carbon dioxide (CO2) from the atmosphere. In this study, the impact of co-firing biomass (wood pellets and straw pellets) on the emission profile of power plants with carbon capture and storage has been assessed for two types of coal-fired power plants: a supercritical pulverised coal power plant (SCPC) and an integrated gasification combined cycle plant (IGCC). Besides, comparative life cycle assessments have been performed to examine the environmental impacts of the combination of co-firing biomass and CCS. Detailed calculations on mass balances of the inputs and outputs of the power plants illustrate the effect of the different content of pollutants in biomass on the capture unit. Life cycle assessment results reveal that 30% co-firing biomass and applying CCS net negative CO2 emissions in the order of 67-85g/kWh are obtained. The impact in all other environmental categories is increased by 20-200%. However, aggregation into endpoint levels shows that the decrease in CO2 emissions more than offsets the increase in the other categories. Sensitivity analyses illustrate that results are most sensitive to parameters that affect the amount of fuel required, such as the efficiency of the power plant and assumptions regarding the supply chains of coal and biomass. Especially, assumptions regarding land use allocation and carbon debt of biomass significantly influence the environmental performance of BioCCS.

Combining co-firing biomass and carbon capture and storage (CCS) in power plants offers attractive potential for net removal of carbon dioxide (CO2) from the atmosphere. In this study, the impact of co-firing biomass (wood pellets and straw pellets) on the emission profile of power plants with carbon capture and storage has been assessed for two types of coal-fired power plants: a supercritical pulverised coal power plant (SCPC) and an integrated gasification combined cycle plant (IGCC). Besides, comparative life cycle assessments have been performed to examine the environmental impacts of the combination of co-firing biomass and CCS. Detailed calculations on mass balances of the inputs and outputs of the power plants illustrate the effect of the different content of pollutants in biomass on the capture unit. Life cycle assessment results reveal that 30% co-firing biomass and applying CCS net negative CO2 emissions in the order of 67-85g/kWh are obtained. The impact in all other environmental categories is increased by 20-200%. However, aggregation into endpoint levels shows that the decrease in CO2 emissions more than offsets the increase in the other categories. Sensitivity analyses illustrate that results are most sensitive to parameters that affect the amount of fuel required, such as the efficiency of the power plant and assumptions regarding the supply chains of coal and biomass. Especially, assumptions regarding land use allocation and carbon debt of biomass significantly influence the environmental performance of BioCCS.