In Sweden, the iron and steel industry (ISI) is a major source of greenhouse gas (GHG) emissions. Most of the emissions result from the use of fossil reducing agents. Nevertheless, the use of fossil fuels for other purposes must also be eliminated in order to reach the Swedish emissions reduction targets. In this study, we investigate the possibility to replace fossil gaseous and liquid fuels used for heating in the ISI, with liquefied biomethane (LBG) produced through gasification of forest residues. We hypothesize that such utilization of fuels in the Swedish ISI is insufficient to independently drive the development of large-scale LBG production, and that other sectors demanding LBG, e.g., for transportation, can be expected to influence the economic potential for the ISI to switch to LBG. The paper investigates how demand for LBG from other sectors can contribute to, or prevent, a phase-out of fossil fuels used for heating purposes in the ISI under different future energy market scenarios, with additional analysis of the impact of a CO2 emissions charge. A geographically explicit cost-minimizing biofuel production localization model is combined with heat integration and energy market scenario analysis. The results show that from a set of possible future energy market scenarios, none yielded more than a 9% replacement of fossil fuels used for heating purposes in the ISI, and only when there was also a demand for LBG from other sectors. The scenarios corresponding to a more ambitious GHG mitigation policy did not achieve higher adoption of LBG, due to corresponding higher biomass prices. A CO2 charge exceeding 200 EUR/tonCO2 would be required to achieve a full phase-out of fossil fuels used for heating purposes in the ISI. We conclude that with the current policy situation, substitution of fossil fuels by LBG will not be economically feasible for the Swedish ISI.

In this paper we present a novel concept to efficiently harvest vibrational energy at low frequencies and very small displacement. We describe and evaluate an electromagnetic energy harvester which generates power from a magnetic circuit with motion induced variations of an air gap. External vibrations induce oscillations of the gap length around an equilibrium point, due to a linear spring counteracting the magnetic force. The relative position of the spring can be adjusted to optimize the harvester output for excitation amplitude and frequency. A simulation model is built in COMSOL and verified by comparison with lab measurements. The simulation model is used to determine the potential performance of the proposed concept under both harmonic and non-harmonic excitation. Under harmonic excitation, we achieve a simulated RMS load power of 26.5 μW at 22 Hz and 0.028 g acceleration amplitude. From a set of comparable EH we achieve the highest theoretical power metric of 1712.2 µW/cm3/g2 while maintaining the largest relative bandwidth of 81.8%. Using measured non-harmonic vibration data, with a mean acceleration of 0.039 g, resulted in a mean power of 52 μW. Moreover, the simplicity and robustness of our design makes it a competitive alternative for use in practical situations.

In the face of green energy initiatives and progressively increasing shares of more energy-efficient buildings, there is a pressing need to transform district heating towards low-temperature district heating. The substantially lowered supply temperature of low-temperature district heating broadens the opportunities and challenges to integrate distributed renewable energy, which requires enhancement on intelligent heating load prediction. Meanwhile, to fulfill the temperature requirements for domestic hot water and space heating, separate energy conversion units on user-side, such as building-sized boosting heat pumps shall be implemented to upgrade the temperature level of the low-temperature district heating network. This study conducted hybrid heating load prediction methods with long-term and short-term prediction, and the main work consisted of four steps: (1) acquisition and processing of district heating data of 20 district heating supplied nursing homes in the Nordic climate (2016–2019); (2) long-term district heating load prediction through linear regression, energy signature curve in hourly resolution, providing an overall view and boundary conditions for the unit sizing; (3) short-term district heating load prediction through two Artificial Neural Network models, f72 and g120, with different prediction input parameters; (4) evaluation of the predicted load profiles based on the measured data. Although the three prediction models met the quality criteria, it was found that including the historical hourly heating loads as the input to the forecasting model enhanced the prediction quality, especially for the peak load and low-mild heating season. Furthermore, a possible application of the heating load profiles was proposed by integrating two building-sized heat pumps in low-temperature district heating, which may be a promising heat supply method in low-temperature district heating. © 2022 The Authors

Flexible resources aids in enhancing the resilience of a renewable dominated power system. Space heating systems equipped with heat pumps is one such flexible resource. With this background, the current study deals with the quantification of flexibility potential of space heating systems in houses equipped with various heat pump types. A heat pump model is represented using a vapour compression heat pump cycle. This model is integrated with a thermal model of a house to estimate electricity consumption, for maintaining the indoor temperature at a set value, as flexibility quantification depends on electricity consumption. In addition to this, flexibility potential is quantified by, analysing and incorporating the results on minimum acceptable indoor temperature from twelve interviews with households owning heat pumps, into the integrated model. The results from interviews reveal that, there is an uncertainty in minimum acceptable indoor temperature, as it is dependant on a number of factors such as frequency and duration of interruption, access to additional heating and motivation to be flexible. Hence, to quantify flexibility using thermal simulations, the indoor temperature is reduced from 20 °C to values between 18 °C and 15 °C, based on minimum acceptable temperatures stated in the interviews. The flexibility potential is quantified in terms of an instantaneous reduction in electric power and reduction in electric energy. By reducing the indoor temperature from 20 °C to the aforementioned values at an outdoor ambient temperature of -5 °C, in about a million single family houses in southern half of Sweden, an instantaneous reduction in electric power is estimated to be 1.6 GW, for the power system with 23 GW plannable power. Additionally, considering the recovery of the indoor temperature to 20 °C in 24 h, electric energy reduction is found to be between 4.06 GWh and 7.4 GWh, when the reference indoor temperature is reduced to values between 18 °C and 15 °C respectively, over 17.25 h. Furthermore, with time the amount of flexibility offered reduces, becomes negative during the recovery period and finally reaches zero, when the indoor temperature is restored. The results reveal that space heating systems in houses equipped with heat pumps have the potential to enhance the resilience of the power grid during severe grid disturbances. 

A wave energy converter (WEC) comprises many components with distinct functions. The whole WEC system is complicated, as each component is also a complex subsystem. It is challenging to properly model and couple these subsystems to achieve a global simulation of the whole system. This study proposes an FMI-based co-simulation framework to tackle this challenge. Through the use of a co-simulation technique requiring minimal programming effort, a suite of numerical solvers serving for modelling various WEC components is coupled to create a comprehensive system model for a single WEC unit. The modules of the Ansys software, Aqwa and Rigid Dynamics, are employed to model hydrodynamic loads and motion responses. Simulink is utilized to model the power take-off (PTO) system and then integrate all models into a global simulation. The capability and accuracy of the FMI-based co-simulation framework are validated against an experimental heave decay test and verified by cross-comparing a numerical model built in SESAM. Furthermore, the framework is expanded to encompass the modelling of a large-scale wave park that includes multiple WEC units. Based on a novel WEC concept called NoviOcean, two study cases of a single unit and an 18-unit wave park are investigated. Buoy motions and power performance under several regular and irregular sea states are analysed. The hydrodynamic interactions between the units are evaluated quantitatively regarding the power performance. It is found that the interactions improve the power performance, with a maximum increase of up to 36%. 

We have investigated and modeled the injection of biomass into blast furnaces (BF), in place of pulverized coal (PC) from fossil sources. This is the easiest way to reduce CO2 emissions, beyond efficiency-improvements. The considered biomass is either pelletized, torrefied or pyrolyzed. It gives us three cases where we have calculated the maximum replacement ratio for each. It was found that charcoal from pyrolysis can fully replace PC, while torrefied material and pelletized wood can replace 22.8% and 20.0% respectively, by weight. Our energy and mass balance model (MASMOD), with metallurgical sub-models for each zone, further indicates that (1) more Blast Furnace Gas (BFG) will be generated resulting in reduced fuel consumption in an integrated plant, (2) lower need of limestone can be expected, (3) lower amount of generated slag as well, and (4) reduced fuel consumption for heating the hot blast is anticipated. Overall, substantial energy savings are possible, which is one of the main findings in this paper. Due to the high usage of PC in Sweden, large amounts of biomass is required if full substitution by charcoal is pursued (6.19 TWh/y). But according to our study, it is likely available in the long term for the blast furnace designated M3 (located in Luleå). Finally, over a year with almost fully used production capacity (2008 used as reference), a 28.1% reduction in on-site emissions is possible by using charcoal. Torrefied material and wood pellets can reduce the emissions by 6.4% and 5.7% respectively. The complete replacement of PC in BF M3 can reduce 17.3% of the total emissions from the Swedish steel industry.

Wind power curtailment becomes a major problem in many countries. The wind accommodation mechanisms and energy saving potentials for the combined heat and power plant with thermal energy storage, electric heat pump and both should be evaluated more systematically and accurately to accommodate more wind power. Heat-power peak shaving capacities for thermal energy storage, electric heat pump and both are analyzed using a graphical method, while the operation strategy is proposed to maximize wind accommodation. A simulation model for wind power accommodation considering the energy balances and constraints of all production units is developed based on EnergyPRO. A regional energy supply system in Jilin Province, China is selected as the case study, where the influences of different peak shaving technologies and their parameters on the wind accommodation and energy saving are studied. The wind curtailment ratio is reduced from 20.31% to 13.04% and 7.51% with thermal energy storage and electric heat pump respectively, and it is further reduced to 4.21% with both. Systems with electric heat pump can save energy from 1.1% to 5.8% with different parameters of the peak shaving devices. It was found that electric heat pump has better accommodation capability than that of thermal energy storage. Wind accommodation can be improved by adding thermal energy storage to electric heat pump, but the effect gradually decreases as the storage size increases. Electric heat pump can increase the system’s energy efficiency, but it is not always energy efficient by adding thermal energy storage to electric heat pump. In fact, thermal energy storage should not be too large, otherwise the system’s energy efficiency will be reduced. 

More flexibility measures are required due to the increasing capacities of variable renewable energies (VRE). In buildings, the integration of energy supplies forms integrated energy systems (IES). IESs can provide flexibility and increase the VRE penetration level. To upgrade a current building energy system into an IES, several energy conversion and storage components are needed. How to decide the component capacities and operate the IES were investigated separately in studies on system planning and system operation. However, a research gap exists that the system configuration from system planning is not validated by actual operation conditions in system operation. Meanwhile, studies on system operation assume that IES configurations are predetermined. This work combines system planning and system operation. The IES configuration is determined by mixed integer linear programming in system planning. Actual operation conditions and forecast errors are considered in system operation. The actual operation profiles are obtained through year-round simulations of different energy management systems. The results indicate that the system configuration from system planning can meet energy demands in system operation. Among different energy management systems, the combination of robust optimization and receding horizon optimization achieves the lowest yearly operation cost. Meanwhile, two scenarios that represent high and low forecast accuracies are studied. Under the high and low forecast accuracy scenarios, the yearly operation costs are about 4% and 6% higher than that obtained from system planning.