The increasing atmospheric CO2 concentration has caused a transformative shift in global energy systems, which is contributing to an increased use of renewables. Sweden is among the countries trying to shift to a fossil-fuel-free system in all energy sectors. This paper addresses the fuel demand and supply in the transportation sector in the county of Västmanland in Sweden. A Mixed Integer Linear Programming optimization model is developed to minimize cost in the studied system. The model is further used to investigate the influence of three different scenarios on production planning of regional Combined Heat and Power (CHP) plants: (1) straw-based biofuel production integrated with existing CHP plants to fuel combustion engine vehicles, (2) use of electric vehicles, and (3) use of hybrid vehicles fueled by both electricity and bioethanol. Potential solar power generation from rooftop solar cells is also included in the model. The energy system in scenario 2 is found to have the highest overall system efficiency; however, a large amount of power needs to be imported to the system. Hybrid vehicles can potentially reduce the electricity import and CO2 emissions compared to the current situation. Electricity production from rooftop solar collectors could provide the energy needs of the vehicles during summer, while regionally produced straw-based bioethanol integrated with CHP plants can satisfy the fuel needs of the vehicles in winter. This approach could affect the production planning of CHP plants, result in less fuel use and increase the share of renewable resources in the regional transportation system. 

Air pollution and increased CO2 concentration in atmosphere and other energy related issues caused a transformative shift in energy system which contributes to increased utilization of renewables as alternative to generate green energy carriers. The potential of renewable resources in different region and potential energy conversion have been largely considered by many researcher in many countries. The energy conversion technologies to produce heat, electricity, and transportation fuels have made impressive technical advances. Sweden has also been challenging with mitigation of CO2 emission and trying to shift into a fossil fuel free system in all energy sectors. This paper deals with the current status of fuel demand and supply in the transport sector in a County in Sweden. A scenario for a fossil fuel free transport sector at a regional level is developed to investigate the potential biofuel production from regionally produced straw. The results and analysis indicate that the potential for cereal based bioethanol production in the region is sufficient to meet the biofuel demand of the County. Using the fallow land for cereal cultivation, it is feasible to shift into a fossil fuel free transportation system where all passenger cars are fueled by bioethanol. The results and finding from the current paper will be used to develop further study on optimization of local biofuel production integrated with CHP plants considering application of other feedstock such as municipal wastes.

In this study, possible alternations in a regional transport sector are assessed to increase the use of renewable resources. Three scenarios are developed aimed to investigate different alternatives including potential straw-based bioethanol supply to fuel regional cars with combustion engines, more use of Electrical Vehicles (EVs) with use of potential power from solar energy, and the feasibility of application of hybrid cars fueled with electricity and bioethanol. The evaluation considers the reduction in CO 2 emissions and increased balance in energy demand and supply. Results of the study indicate that application of hybrid vehicles with bioethanol-fueled engines and electrical motors could potentially reduce the CO 2 emissions compared with other proposed approaches in the studied scenarios. At the same time, there would be a balance in the system, so that, the bioethanol production from the available cereal straw in the region can meet the energy demand of suggested hybrid cars in wintertime. While, the energy supply from solar cells installed on the rooftop of the buildings can cover the electricity need of the motor during summer. This approach will also result in increased use of renewables in the transportation system.

Population growth and urbanization have led to increases in energy demand and consequently, greenhouse gas emissions. Therefore, the availability of the fossil fuel as the main source of energy supply has been changed. Utilization of renewable resources including solar, wind, and hydropower together with distributed energy systems could eliminate the dependency on fossil fuel energy sources. In this paper, energy use and supply trends have been studied for the Counties of Västmanland and Södermanland in Sweden in order to develop a scenario for the regional energy system in 2030. The aim is to use the scenario for evaluation of the impacts of regional renewable energy resources on the production planning of CHP plants. The scenario shows that there is not enough potential for electricity production from renewable resources such as solar, wind, and hydropower to fulfill the estimated demand in 2030. Around 75% of electricity needs in Västmanland and 89% of power demands in Södermanland need to be met by imported electricity to these regions. Efficiency improvements and a more complex energy system integrating also with other energy resources like biomass, waste and industrial waste heat are necessary to develop a sustainable energy system.

This paper discusses the accuracy of different types of models. Statistical models are based on process data and/or observations from lab measurements. This class of models are called black box models. Physical models use physical relationships to describe a process. These are called white box models or first principle models. The third group is sometimes called grey box models, being a combination of black box and white box models. Here we discuss two examples of model types. One is a statistical model where an artificial neural network is used to predict NO_x in the exhaust gases from a boiler at Mälarenergi AB in Västerås, Sweden. The second example is a grey box model of a continuous digester. The digester model includes mass balances, energy balances, chemical reactions and physical geometrical constraints to simulate the real digester. We also propose that a more sophisticated model is not required to increase the accuracy of the predicted measurements.