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.

This paper develops, implements, and applies a mathematical model for economic unit dispatch for a novel cogeneration concept (CHP-HP-FG-CS (CHP with compression heat pump and cold storage using flue gas heat)) that increases the plant's operational flexibility. The CHP-HP-FG-CS concept is a high-efficiency and widely applicable option in distributed cogeneration better supporting the co-existence between cogenerators and intermittent renewables in the energy system. The concept involves integrating an efficient high-temperature compression heat pump that uses only waste heat recovered from flue gases as low-temperature heat source, and an intermediate cold thermal storage allowing for non-concurrent operation of the cogeneration unit and the heat pump unit. The model is applied for a paradigmatic case study that shows how the integration of a heat pump affects the operational strategy of a cogeneration plant. It is found that CHP-HP-FG-CS offers significant reductions in fuel consumption (-8.9%) and operational production costs (-11.4%). The plant's fuel-to-energy efficiency increases from 88.9 to 95.5%, which is state-of-the-art. The plant's intermittency-friendliness coefficient Rc improves only marginally due to the constrained nature of the low-temperature heat source and the associated small capacity of the heat pump unit. Significant improvements in Rc are found when increasing the heat pump capacity assuming the availability of an unconstrained heat source

The share of renewable liquid fuels (ethanol, fatty acid methyl ester, biogas, and renewable electricity) in the total transportation fuel in Sweden, has increased by the end of 2009 to such level that e.g. domestic bioethanol production is unable to satisfy current ethanol fuel demand. Regional small-scale ethanol production can assist the region in covering the regional needs in transport fuel supply.

Current case study system includes the production of ethanol, biogas, heat and power from locally available cereals straw. A mixed integer programming (MIP) model is developed for cost optimization of regional transport fuel supply (ethanol, biogas and petrol). The model is applied for two cases, one when ethanol production plant is integrated with an existing CHP plant (polygeneration), and one with a standalone ethanol production plant.

The optimization results show that for both cases the changes in ethanol production costs have the biggest influence on the costs for supplying regional passenger car fleet with transport fuel. Petrol fuel price and straw production costs have also a significant effect on costs for supplying cars with transport fuel for both standalone ethanol production and integrated production system.

By integrating the ethanol production process with a CHP plant, the costs for supplying regional passenger car fleet with transport fuel can be cut by 31%, from 150 to 104 €/MW h fuel, which should be compared with E5 costs of 115 €/MW h (excl VAT).

Energy security and the mitigation of greenhouse gas emissions (GHG) are the driving forces behind the development of renewable fuel sources worldwide. In Sweden, a relatively rapid development in bioethanol usage in transportation has been driven by the implementation of national taxation regulations on carbon neutral transport fuels. The demand for bioethanol to fuel transportation is growing and cannot be met through current domestic production alone. Lignocellulosic ethanol derived from agricultural crop residues may be a feasible alternative source of ethanol to secure a consistent regional fuel supply in Swedish climatic conditions. This paper analyzes how the regional energy system can contribute to reducing CO2 emissions by realizing local small scale bioethanol production and substituting petrol fuel with high blend ethanol mixtures for private road transport. The results show that about 13 000 m3 of bioethanol can be produced from the straw available in the studied region and that this amount can meet the current regional ethanol fuel demand. Replacing the current demand for petrol fuel for passenger cars with ethanol fuel can potentially reduce CO2 emissions from transportation by 48%.

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. 

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.

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.

Ethanol can be produced with little impact on the environment through the use of polygeneration technology. This paper evaluates the potential of integrating a lignocellulosic ethanol plant into a district heating system by case study; the plant has an ethanol capacity of 95 MW with biogas. electricity and heat as by-products. Stockholms district heating system is used as the case study, but the results may be relevant also for other urban areas. The system has been studied using MODEST - an optimisation model framework. The results show that introducing the plant would lead to a significant reduction in the cost of heat production. The income from the biofuels and electricity produced would be about (sic)76 million and (sic)130 million annually, respectively, which is an increase of 70% compared to the income from the electricity produced in the system today. Assuming that the electricity produced will replace marginal electricity on the European electricity market and that the biofuel produced will replace gasoline in the transport sector, the introduction of the polygeneration plant in the district heating system would lead to a reduction of global CO(2) emissions of about 0.7 million tonnes annually.

This paper evaluates the effects on profitability of biofuel production if biofuel producers would sell the waste heat from the production to a local district heating system. All analyses have been performed considering four different technology cases for biofuel production. Two technology cases include ethanol production which is followed by by-production of raw biogas. This biogas can be upgraded and sold as biofuel (the first technology case) or directly used for combined heat and power production (the second technology case). The third and the fourth technology cases are Fischer-Tropsch diesel and dimethyl ether production plants based on biomass gasification. Two different district heating price levels and two different future energy market scenarios were considered. The sensitivity analyses of the discount rate were performed as well. In the case of energy market conditions, the profitability depends above all on the price ratio between biomass (used as the feedstock for biofuel production) and crude oil (used as the feedstock for fossil diesel and gasoline production). The reason for this is that the gate biofuel prices (the prices on which the biofuel would be sold) were calculated assuming that the final prices at the filling stations are the same as the prices of the replaced fossil fuel. The price ratios between biomass and district heating, and between biomass and electricity, also have an influence on the profitability, since higher district heating and electricity prices lead to higher revenues from the heat/electricity by-produced. Due to high biofuel (ethanol + biogas) efficiency, the ethanol production plant which produces upgraded biogas has the lowest biofuel production costs. Those costs would be lower than the biofuel gate prices even if the support for transportation fuel produced from renewable energy sources were not included. If the raw biogas that is by-produced would instead be used directly for combined heat and power production, the revenues from the electricity and heat would increase, but at the same time the biofuel efficiency would be lower, which would lead to higher production costs. On the other hand, due to the fact that it has the highest heat efficiency compared to the other technologies, the ethanol production in this plant shows a high sensitivity to the district heating price level, and the economic benefit from introducing such a plant into a district heating system is most obvious. Assuming a low discount rate (6%), the introduction of such a plant into a district heating system would lead to between 28% and 52% (depending on the district heating price level and energy market scenario) lower biofuel production costs. Due to the lower revenues from the heat and electricity co-produced, and higher capital investments compared to the ethanol production plants, Fischer-Tropsch diesel and dimethyl ether productions are shown to be profitable only if high support for transportation fuel produced from renewable energy sources is included. The results also show that an increase of the discount rate from 6% to 10% does not have a significant influence on the biofuel production costs. Depending on the biofuel production plant, and on the energy market and district heating conditions, when the discount rate increases from 6% to 10%, the biofuel production costs increase within a range from 2.2% to 6.8%. 

Biofuel production through polygeneration with heat as one of the by-products implies a possibility for cooperation between transport and district heating sectors by introducing large-scale biofuel production into district heating systems. The cooperation may have effects on both the biofuel production costs and the district heating production costs. This paper is the second part of the study that investigates those effects. The biofuel production costs evaluation, considering heat and electricity as by-products, was performed in the first part of the study. In this second part of the study, an evaluation of how such cooperation would influence the district heating production costs using Stockholm's district heating system as a case study was performed. The plants introduced in the district heating system were chosen depending on the future development of the transport sector. In order to perform sensitivity analyses of different energy market conditions, two energy market scenarios were applied. Despite the higher revenues from the sale of by-products, due to the capital intense investments required, the introduction of large-scale biofuel production into the district heating system does not guarantee economic benefits. Profitability is highly dependent on the types of biofuel production plants and energy market scenarios. The results show that large-scale biogas and ethanol production may lead to a significant reduction in the district heating production costs in both energy market scenarios, especially if support for transportation fuel produced from renewable energy sources is included. If the total biomass capacity of the biofuel production plants introduced into the district heating system is 900 MW, the district heating production costs would be negative and the whole public transport sector and more than 50% of the private cars in the region could be run on the ethanol and biogas produced. The profitability is shown to be lower if the raw biogas that is by-produced in the biofuel production plants is used for combined and power production instead of being sold as transportation fuel; however, this strategy may still result in profitability if the support for transportation fuel produced from renewable energy sources is included. Investments in Fischer-Tropsch diesel and dimethyl ether production are competitive to the investments in combined and power production only if high support for transportation fuel produced from renewable energy sources is included. 

In this study, cooperation between Stockholm's transport and district heating sectors is analysed. The cooperation concerns the integration of biofuel polygeneration production. A MODEST optimisation model framework is used, assuming various energy market and transport sector scenarios for the year 2030. The scenarios with biofuel production and increased biofuel use in the region are compared with reference scenarios where all new plants introduced into the district heating sector are combined heat and power plants, and the share of biofuel used in the transport sector is the same as today. The results show that the cooperation implies an opportunity to reduce fossil fuel consumption in the sectors by between 20% and 65%, depending on energy market conditions and assumed transport sector scenarios. If we consider biomass an unlimited resource, the potential for greenhouse gas emissions reduction is significant. However, considering that biomass is a limited resource, the increase of biomass use in the district heating system may lead to a decrease of biomass use in other energy systems. The potential for reduction of global greenhouse gas emissions is thus highly dependent on the alternative use of biomass. If this alternative is used for co-firing in coal condensing power plants, biomass use in combined heat and power plants would be more desirable than biofuel production through polygeneration. On the other hand, if this alternative is used for traditional biofuel production (without co-production of heat and electricity), the benefits of biofuel production through polygeneration from a greenhouse gas emissions perspective is superior. However, if carbon capture and storage technology is applied on the biofuel polygeneration plants, the introduction of large-scale biofuel production into the district heating system would result in a reduction of global greenhouse gas emissions independent of the assumed alternative use of biomass. 

Due to its relatively high total energy efficiency, the application of cogeneration, i.e. simultaneous exploitation of power and heat from the energy transformation process, is receiving increased attention. In many countries cogeneration is today an essential element in the energy supply system. In order to improve the operation of such systems, it is necessary to have detailed and reliable optimization models and methods available. The same is also desirable for pure heating systems, and for pure power systems. However, finding the optimal plan for production of heat and power, possibly also taking into account the optimal use of storage devices, is a difficult optimization problem.

Finding the optimal production schedule for the near future is known as the short-term planning problem or the unit commitment and economic dispatch problem. Typically a time horizon of up to one week, partitioned into one-hour time intervals, is considered. The problem may be characterized as a nonlinear mixed integer optimization problem, often large scale. In line with the development of optimization tools, a large number of optimization methods have been applied to obtain the solution. In recent years, methods based on Lagrangian relaxation have become the dominant ones, motivated by the separable structure of the problem.

The present thesis deals with mathematical models and Lagrangian relaxation based algorithms for short-term planning of cogeneration and power systems. Both deterministic and stochastic models are discussed. Using Lagrangian multipliers, Lagrangian relaxation is applied to the problem by either relaxing all unit-coupling constraints or all time-coupling constraints, which will decompose the (relaxed) problem into independent subproblems. This will also generate a corresponding dual problem. make the algorithms successful, it is necessary to have reliable methods for the solution of the dual problem and for the independent subproblems. The aim with the thesis is to present ideas and theories that may be exploited in such algorithms to make them more efficient.

During the last decade, there has been an intensive debate on-going in Sweden about how power generation and use affect global warming. More precisely, the discussion has considered how electricity shall be assessed from an environmental and climate perspective in different situations. This article gives a critical analysis on the main viewpoints. A number of environmental-impact assessment principles are outlined and critically examined. Concepts like average electricity and marginal electricity are discussed, and Electricity Disclosure as a basis for evaluation is addressed. The impact from Emission Trading and Tradable Green Certificates is also considered. Recommendations to concerned stakeholders are given. The clash points in the Swedish debate are highlighted and thus made available to a broader audience outside Scandinavia.

The use of waste for energy purposes becomes increasingly interesting both with respect to waste management and for the energy systems. The decisions on alternative uses of waste for energy are mainly influenced by different policies, waste management, energy supply and use, as well as technologies. Two important issues, namely, a clear priority of waste prevention in waste management within EU and the growing concern for food losses and food waste at global and at national level, shall be carefully considered and addressed. This paper proposes scenarios for waste to energy systems with focus on Sweden and with a broader EU approach is applied: Biofuels Sweden, Electric vehicles and Bioenergy Europe. As baseline for the scenario development inventory of waste-to-energy related policies and goals on international, national, regional and local level as well as inventory of existing scenarios and reports with future trends is made. A low waste availability level is recommended to be included in sensitivity analysis for scenarios.

The use of waste for energy purposes becomes increasingly interesting with respect to waste management and the energy systems. The decisions on alternative uses of waste for energy are mainly influenced by different policies, waste management, energy supply and use, as well as technologies. Two important issues, namely, a clear priority of waste prevention in waste management within EU and the growing concern for food losses and food waste at global and national level, shall be carefully considered and addressed. This paper proposes policy based scenarios for waste-to-energy systems with a focus on Sweden and with a broader EU approach. As baseline for the scenario development an inventory of waste-to-energy related policies and goals on international, national, regional and local level as well as inventory of existing scenarios and reports with future trends is made. The main substitute for fossil fuels and the possibilities for renewable energy export are basic elements that define scenarios. Biofuels and electricity are identified as main substitutes for the fossil fuels. A low waste availability level is recommended to be included in sensitivity analysis for scenarios. This paper assumes relative decoupling in Low Waste scenario in 2030, and absolute decoupling first in 2050.

 Energy recovery from waste becomes increasingly interesting both with respect to waste management and for the sustainable energy supply. The REMOWE (Regional Mobilizing of Sustainable Waste-to-Energy Production) project, seeks to facilitate the implementation of sustainable systems for waste-to-energy in the project regions. Based on investigations done within the REMOWE project this paper discusses increased waste-to-energy utilization in Poland with focus on a comparison with the current state in Sweden. There are big differences between Sweden and Poland, and between Lower Silesia Voivodship in Poland and Västmanland County in Sweden. The REMOWE project through its outputs and discussions during meetings support transfer of technology, knowledge and best practice. Procedural justice and early involvement of public can increase social acceptance and successful implementation of projects regarding incineration, biogas production and separate collection of biodegradable waste.

A dynamic model of a regional energy system has been developed to support sustainable waste treatmentwith greenhouse gases (GHG) mitigation, addressing the possibility for development towardsa regional fossil fuel-free society between 2011 and 2030. The model is based on conventional mixedinteger linear programming (MILP) techniques to minimize the total cost of regional energy systems. TheCO2 emission component in the developed model includes both fossil and biogenic origins whenconsidering waste, fossil fuels and other renewable sources for energy production. A case study for thecounty of Västmanland in central Sweden is performed to demonstrate the applicability of the developedMILP model in five distinct scenarios. The results show significant potential for mitigating CO2 emissionby gradually replacing fossil fuels with different renewable energy sources. The MILP model can be usefulfor providing strategies for treating wastes sustainably and mitigating GHG emissions in a regionalenergy system, which can function as decision bases for formulating GHG reduction policies andassessing the associated economic implications.

Three optional pellet production processes integrated with an existing biomass-based CHP plant using different raw materials (wood chips and solid hydrolysis residues) are studied. The year is divided into 12 periods, and the integrated biorefinery systems are modeled and simulated for each period. The annual economic performance of three integrated biorefinery systems is analyzed based on the simulation results. The option of pellet production integrated with the existing CHP plant with the exhaust flue gas and superheated steam as drying mediums has the lowest specific pellet production cost of 105 €/tpellet, the shortest payback time of less than 2 years and the greatest CO2 reduction of the three options. An advantage in common among the three options is a dramatic increase of the total annual power production and significant CO2 reduction in spite of a small decrease of power efficiency.

Bioethanol is an alternative to fossil fuels in the transportation sector. The use of pellet for heating is also an efficient way to mitigate greenhouse gas emissions. This paper evaluates the techno-economic performance of a biorefinery system in which an existing combined heat and power (CHP) plant is integrated with the production of bioethanol and pellet using straw as feedstock. A two-stage acid hydrolysis process is used for bioethanol production, and two different drying technologies are applied to dry hydrolysis solid residues. A sensitivity analysis is performed on critical parameters such as the bioethanol selling price and feedstock price. The bioethanol production cost is also calculated for two cases with either 10 year or 15 year payback times. The results show that the second case is currently a more feasible economic configuration and reduces production costs by 36.4%-77.3% compared to other types of poly-generation plants that are not integrated into existing CHP plants. 

Combined heat and power (CHP) plants fired by forest wood can significantly contribute to attaining the target of increasingthe share of renewable energy production. However, the spatial distribution of biomass supply and of heat demand limits thepotentials of CHP production. This article assesses CHP potentials using a mixed integer programming model that optimizeslocations of bioenergy plants. Investment costs of district heating infrastructure are modeled as a function of heat demanddensities, which can differ substantially. Gasification of biomass in a combined cycle process is assumed as productiontechnology. Some model parameters have a broad range according to a literature review. Monte-Carlo simulations havetherefore been performed to account for model parameter uncertainty in our analysis. The model is applied to assess CHPpotentials in Austria. Optimal locations of plants are clustered around big cities in the east of the country. At current powerprices, biomass-based CHP production allows producing around 3% of the total energy demand in Austria. Yet, the heatutilization decreases when CHP production increases due to limited heat demand that is suitable for district heating.Production potentials are most sensitive to biomass costs and power prices.

Concerning production and use of biofuels, mismatch between the locations of feedstock and the biofuel consumer may lead to high transportation costs and negative environmental impact. In order to minimize these consequences, it is important to locate the production plant at an appropriate location. In this paper, a case study of the county of Norrbotten in northern Sweden is presented with the purpose to illustrate how an optimization model could be used to assess a proper location for a biomass based methanol production plant. The production of lignocellulosic based methanol via gasification has been chosen, as methanol seems to be one promising alternative to replace fossil gasoline as an automotive fuel and Norrbotten has abundant resources of woody biomass. If methanol would be produced in a stand-alone production plant in the county, the cost for transportation of the feedstock as well as the produced methanol would have great impact on the final cost depending on where the methanol plant is located. Three different production plant sizes have been considered in the study, 100, 200 and 400 MW (biomass fuel input), respectively. When assessing a proper location for this kind of plant, it is important to also consider the future motor fuel demand as well as to identify a heat sink for the residual heat. In this study, four different automotive fuel- and district heating demand scenarios have been created until the year 2025. The results show that methanol can be produced at a maximum cost of 0.48 €/l without heat sales. By selling the residual heat as district heating, the methanol production cost per liter fuel may decrease by up to 10% when the plant is located close to an area with high annual heat demand.

Methanol appears to be a new alternative fuel in the transport sector. Methanol can be produced through gasification of lignocellulosic biomass, which makes it a renewable fuel, and its utilization has therefore an impact on greenhouse gas emissions. The county of Norrbotten in northern Sweden has the characteristic to have great amount of woody biomass, and a sparsely inhabited area. Transportation distances of both biomass and methanol would then have a great impact on the final cost of methanol depending on where the methanol plant is located. This county was therefore studied as a case study with a twenty year perspective in order to validate an optimization model. The optimal locations of three different sizes of methanol plants were studied for four demographic scenarios. From this study it appears that methanol plants of 100 MWbiomass and 200 MWbiomass would be set up closer to the demand area than a 400 MWbiomass that would optimally be set up more inlands close to the available biomass.

Second generation biofuels from wood gasification are thought to become competitive in the face of effective climate and energy security policies. Cost competitiveness crucially depends on the optimization of the entire supply chain-field-wheel involving optimal location, scaling and logistics. In this study, a linear mixed integer programming model has been developed to determine the optimal geographic locations and sizes of methanol plants and gas stations in Austria. Optimal locations and sizes are found by the minimization of costs with respect to biomass and methanol production and transport, investments for the production plants and the gas stations. Hence, the model covers competition in all levels of a biofuel production chain including supply of biomass, biofuel and heat, and demand for bio- and fossil fuels. The results show that Austria could be self-sufficient in the production of methanol for biofuels like M5, M10 or M20, using up to 8% of the arable land share. The plants are optimally located close to the potential supply of biomass (i.e. poplar) in Eastern Austria, and produce methanol around 0.4 is an element of(-1). Moreover, heat production could lower the methanol cost by 12%.

Second generation biofuels from wood gasification are thought to become competitive in the face of effective climate and energy security policies. Cost competitiveness crucially depends on the optimization of the entire supply chain-field-wheel involving optimal location, scaling and logistics. In this study, a linear mixed integer programming model has been developed to determine the optimal geographic locations and sizes of methanol plants and gas stations in Austria. Optimal locations and sizes are found by the minimization of costs with respect to biomass and methanol production and transport, investments for the production plants and the gas stations. Hence, the model covers competition in all levels of a biofuel production chain including supply of biomass, biofuel and heat, and demand for bio- and fossil fuels.The results show that Austria could be self-sufficient in the production of methanol for biofuels like M5, M10 or M20, using up to 8% of the arable land share. The plants are optimally located close to the potential supply of biomass (i.e. poplar) in Eastern Austria, and produce methanol around 0.4 is an element of(-1). Moreover, heat production could lower the methanol cost by 12%.

The integration of ethanol production with combined heat and power plants is considered in this paper. An energy balance process model has been used to generate data for the production of ethanol, electricity, heat and biogas. The geographical position of such plants becomes of importance when using local biomass and delivering transportation fuel and heat. An optimization model has thus been used to determine the optimal locations for such plants in Sweden. The entire energy supply and demand chain from biomass outtake to gas stations filling is included in the optimization. Input parameters have been studied for their influence on both the final ethanol cost and the optimal locations of the plants. The results show that the biomass cost, biomass availability and district heating price are crucial for the positioning of the plant and the ethanol to be competitive against imported ethanol. The optimal location to set up polygeneration plants is demonstrated to be in areas where the biomass cost is competitive and in the vicinity of small to medium size cities. Carbon tax does not influence the ethanol cost, but solicits the production of ethanol in Sweden, and changes thus the geography of the plant locations.

The integration of ethanol production with combined heat and power plants is considered in this paper. An energy balance process model has been used to generate data for the production of ethanol, electricity, heat and biogas. The geographical position of such plants becomes of importance when using local biomass and delivering transportation fuel and heat. An optimization model has thus been used to determine the optimal locations for such plants in Sweden. The entire energy supply and demand chain from biomass outtake to gas stations filling is included in the optimization. Input parameters have been studied for their influence on both the final ethanol cost and the optimal locations of the plants. The results show that the biomass cost, biomass availability and district heating price are crucial for the positioning of the plant and the ethanol to be competitive against imported ethanol. The optimal location to set up polygeneration plants is demonstrated to be in areas where the biomass cost is competitive and in the vicinity of small to medium size cities. Carbon tax does not influence the ethanol cost, but solicits the production of ethanol in Sweden, and changes thus the geography of the plant locations.

The objective of this study is to analyze the biofuel potential in Europe fromlignocellulosic waste (wood waste and paper and cardboard waste). Ethanol from fermentationand Fischer-Tropsch (FT) diesel from gasification are the two biofuels considered. As thosebiofuels are not yet commercially available, the optimal locations of the production plants haveto be determined. The analysis is carried out with a geographic explicit model that minimizes thetotal cost of the biofuel supply chain. A mixed integer linear program is used for theoptimization. The results show that ethanol production plants are selected in a majority of thestudied cases. Ethanol plants are mainly set up in areas with a high heat demand and/or highelectricity or heat price, whereas FT diesel production plants are set up in areas where the heatdemand is low all year round. A high cost for emitting CO2 as well as high transport fossil fuelprices favor the selection of FT diesel over ethanol production plants. With a CO2 cost of 100€/tCO2 applied, the biofuel production from waste can potentially meet around 4% of theEuropean transport fuel demand.

In this study, the opportunity to invest in combined heat and power (CHP) plants and second-generation biofuel production plants in Europe is investigated. To determine the number and type of production plants, a mixed integer linear model is used, based on minimization of the total cost of the whole supply chain. Different policy scenarios are studied with varying values of carbon cost and biofuel support. The study focuses on the type of technology to invest in and the CO2 emission substitution potential, at constant energy prices. The CHP plants and the biofuel production plants are competing for the same feedstock (forest biomass), which is available in limited quantities. The results show that CHP plants are preferred over biofuel production plants at high carbon costs (over 50 EUR/tCO2) and low biofuel support (below 10 EUR/GJ), whereas more biofuel production plants would be set up at high biofuel support (over 15 EUR/GJ), irrespective of the carbon cost. Regarding the CO2 emission substitution potential, the highest potential can be reached at a high carbon cost and low biofuel support. It is concluded that there is a potential conflict of interest between policies promoting increased use of biofuels, and policies aiming at decreased CO 2 emissions.

Guarantees of Origin (GO) and Electricity Disclosure, as defined in the EU's Renewable Energy and Electricity Market Directives, require that European consumers should be provided with reliable information about the origin of their electricity supply. At the same time, the Renewable Energy Directive requires that support mechanisms be implemented with the aim of increasing the proportion of energy from renewable sources. The Quota System with Tradable Green Certificates (TGC) was established in Sweden as a support mechanism in 2003 and is, from 2012, planned to be extended to become a Swedish-Norwegian system. This article discusses the effects of Electricity Disclosure and the TGC system when working as two separate entities, and the potential interaction between the systems when working in tandem. It appears that Electricity Disclosure may create a customer-driven demand for renewable electricity, which can supplement the TGC system. In the long-term, GOs may thus influence the decisions made by investors in renewable energy. However, currently Electricity Disclosure has very low, or no, impact on the total production of electricity from renewable sources when compared with a stand-alone TGC system.

The Finnish biofuel industry is undergoing a major change in particular second generation Fischer Tropsch (FT) biodiesel production. However, efficient geographical energy planning is essential to optimally allocate the limited natural resources between biomass based industries. Therefore, a decision tool was formulated which includes three different models: (1) a spatial model that estimates the amount of biomass supply and industrial residues available for energy production, (2) an energy demand model calculates the amount of heat and transport fuel that can be delivered to the customers, (3) an optimization model that minimizes the complete costs of biodiesel supply chain from biomass supply to biodiesel delivery at the fuel stations to determine the optimal location, size and configurations of FT biodiesel production plants in Finland. Model results show that five cost-optimal biodiesel production plant locations of 390 MWfeedstock are needed to be built to meet the 2020 renewable energy share in transport (25.2 PJ). The unit cost of FT biodiesel produced in Finland could range between 1.1 and 1.4 €/l2011 without heat sales.

As a forest resource rich country (73% of total land area) and a pioneer in forest technology, Finland has a long standing tradition of utilizing forest biomass for bioenergy production. The National Renewable Action Plan 2010 strives to increase the present consumption of forest chips from 6 million m(3) to 13.5 million m(3) (97 PJ) by 2020, mainly for combined heat and power (CHP) production and separate heat production. In 2013, the forest chip consumption was 8.7 million m(3). To achieve, 2020 target of forest chip consumption, Finland would still need either 8 new CHP production plants (200 MWbio) or increase the share of wood chip consumption at the existing plants (e.g., co-firing, boiler substitution, peat replaced by wood chips). The aim of this study is to apply a Mixed Integer Linear Programming model to optimize the 8 new CHP plant locations and production configurations by minimizing the entire costs and emissions of supply chain with respect to biomass resource availability, energy demand and existing industrial competition. The model results also present the feedstock resource allocation strategy with regards on the parameter sensitivity (e.g., less forest harvesting, price increase). Logging residues (92% biomass share) and sawmill residuals (8% biomass share) would be the favorite feedstock choice under current market situation. Subsidy for young thinning wood is essential for energy wood supply in future as well.

Finland considers energy production from woody biomass as an efficient energy planning strategy to increase the domestic renewable energy production in order to substitute fossil fuel consumption and reduce greenhouse gas emissions. Consequently, a number of developmental activities are implemented in the country, and one of them is the installation of second generation liquid biofuel demonstration plants. In this study, two gasification-based biomass conversion technologies, methanol and combined heat and power (CHP) production, are assessed for commercialization. Spatial information on forest resources, sawmill residues, existing biomass-based industries, energy demand regions, possible plant locations, and a transport network of Eastern Finland is fed into a geographically explicit Mixed Integer Programming model to minimize the costs of the entire supply chain which includes the biomass supply, biomass and biofuel transportation, biomass conversion, energy distribution, and emissions. The model generates a solution by determining the optimal number, locations, and technology mix of bioenergy production plants. Scenarios were created with a focus on biomass and energy demand, plant characteristics, and cost variations. The model results state that the biomass supply and high energy demand are found to have a profound influence on the potential bioenergy production plant locations. The results show that methanol can be produced in Eastern Finland under current market conditions at an average cost of 0.22 €/l with heat sales (0.34 €/l without heat sales). The introduction of energy policy tools, like cost for carbon, showed a significant influence on the choice of technology and CO ₂ emission reductions. The results revealed that the methanol technology was preferred over the CHP technology at higher carbon dioxide cost (>145 €/t _CO2). The results indicate that two methanol plants (360 MW _biomass) are needed to be built to meet the transport fuel demand of Eastern Finland

A country level spatially explicit mixed integer linear programming model has been applied to identify the optimal Fischer Tropsch biodiesel production plants locations in Finland. The optimal plant locations with least cost options are identified by minimizing the complete costs of the supply chain with respect to feedstock supply (energywood, pulpwood, sawmill residuals, wood imports), industrial competition (pulp mill, sawmill, combined heat and power plants, pellet industries) and energy demand (biodiesel, heat, biofuel import). Model results show that five biodiesel production plants of 390MW feedstock are needed to be built to meet the 2020 renewable energy target in transport (25.2PJ). Given current market conditions, the Fischer Tropsch biodiesel can be produced at a cost around 18€/GJ including by-products income. Furthermore, the parameter sensitivity analysis shows that the production plant parameters such as investment costs and conversion efficiency are found to have profound influence on the biodiesel cost, and then followed by feedstock cost and plant size. In addition, the variations in feedstock costs and industrial competition determine the proportion of feedstock resource allocation to the production plants. The results of this study could help decision makers to strategically locate the FT-biodiesel production plants in Finland.

The classical Quadratic Programming (QP) formulation of the well-known portfolio selection problem has traditionally been regarded as cumbersome and time consuming. This paper formulates two additional models, (i) maximin, and (ii) minimization of mean absolute deviation. Data from 67 securities over 48 months are used to examine to what extent all three formulations provide similar portfolios. As expected, the maximin formulation yields the highest return and risk, while the QP formulation provides the lowest risk and return, which also creates the efficient frontier. The minimization of mean absolute deviation is close to the QP formulation. When the expected returns are confronted with the true ones at the end of a six months period, the maximin portfolios seem to be the most robust of all.

Italy is a large producer of biogas from anaerobic digestion, which is mainly used for power generation with limited use of cogenerated heat. Other utilization pathways, such as biomethane injection into the natural gas grid or biomethane used as a vehicle fuel, remain unexplored. Given the dense grid of natural gas pipelines and existing Compressed Natural Gas (CNG) refueling stations in northern Italy, significant market opportunities for biogas could also arise in the heating and transport sectors. The main objectives of this paper are to explore the potential role of agricultural biogas in different utilization pathways. Biogas combustion for simultaneous production of heat and power in small Combined Heat and Power (CHP) facilities is also assessed, as is upgrading to biomethane for transport or natural gas grid injection in the specific context of northern Italy. The spatially explicit optimization model BeWhere is used to identify optimal locations where greenfield biogas plants could be installed and to determine the most economic and environmentally beneficial mix of conversion technologies and plant capacities. Carbon price, for instance in the form of tradable emission permits, is assessed as a policy instrument and compared with other options such as price premiums on biomethane or electricity costs. Results show that starting from a carbon price of 15EUR/tCO<inf>2</inf>, the cogeneration option is preferable if plants are located in the proximity of existing district heating infrastructure. CNG plants are only competitive starting at a carbon price of 70EUR/tCO<inf>2</inf> in areas with high feedstock availability. The sensitivity analysis for energy prices reveals that a larger number of CNG facilities are included in the optimal mix at higher gas wholesale prices. This further indicates that specific premiums are needed to expand the biomethane market share, while greenhouse gas emission reductions would primarily be achieved by fostering cogeneration of electricity and heat supported by carbon price-based policy instruments.

Concerns have been voiced that implementing climate change mitigation measures could come at the cost of employment, especially in the context of the US coal sector. However, repurposing US coal plants presents an opportunity to address emission mitigation and job creation, if the right technology change is adopted. In this study, the transformation of the US coal sector until 2050 is modeled to achieve ambitious climate targets. Results show that the cost-optimal strategy for meeting 2050 emission reductions consistent with 2°C stabilization pathways is through the early deployment of BECCS and by replacing 50% of aging coal plants with natural gas plants. This strategy addresses the concerns surrounding employment for coal workers by retaining 40,000 jobs, and creating 22,000 additional jobs by mid-century. Climate change mitigation does not have to come at the cost of employment, and policymakers could seek to take advantage of the social co-benefits of mitigation.

Hosting capacity (HC) is described as the maximum amount of new production or consumption that can be added to the grid without causing a violation. In this case study, a deterministic approach is used to investigate the HC of electric vehicle (EV) charging in a low-voltage grid, containing 13 detached single-family houses. It investigates how different parameters affect the HC, and what is causing the violation in the grid. Two different performance indices (PI) are used in the study: power cable overloading and voltage drop. The local grid is simulated for one year for four cases and the HC is derived for these. The cases are distinguished by two different violation thresholds for the voltage drop and two different implementation orders of the location of the charging. The results show that the HC of the grid is 6-11 EVs charging simultaneously. The difference in HC is primarily due to variation in the baseload through the year and location of charging. The cable between the substation and the first cable cabinet was the major contributor to the fault, and the PI causing the violation differed depending on what case was used.

The deployment of electric vehicles (EVs) is growing significantly in recent years. The increasing EV charging loads pose great stress on power grids in Sweden, as many existing power grids are not designed to host such large shares of new electric loads. Hence, studies investigating the impact of EV charging are needed. This study conducts a case study based on an existing Swedish residential power grid using real-life EV charging data to estimate the local grid hosting capacity (HC) for EVs. A combined time-series and stochastic HC assessment method is used with voltage deviation, cable loading and transformer loading as the performance indices. Uncertainty in EV charging locations and individual charging behaviour have been considered via Monte Carlo simulations. The power grid HC is analysed and compared under three charging strategies and four EV penetration levels. Study results show that a charging strategy based on low electricity prices gave lower HC due to simultaneous EV loads compared to the other two strategies: charging directly after plugging in the EV and an even charging load through the plug-in session. This implies the need for coordinated charging controls of EV fleets or diversified power tariffs to balance power on a large scale.

Die Biotreibstoffproduktion mit Technologien der zweiten Generationverspricht geringere Treibhausgasemissionen im Vergleich zu Technologiender ersten Generation. Die Kosten, Emissionen und optimaleStandorte von Biomassekraftwerken, die diese neuen Technologienverwenden, werden mit Hilfe eines linearen Integer- Optimierungsmodellsfür Österreich abgeschätzt. Holz aus der Forstproduktion undvon Kurzumtriebsanlagen geht als biogener Rohstoff in das Modell ein.Einnahmen durch den Verkauf der Nebenprodukte Wärme, Strom undBiogas, die in der Treibstoffproduktion entstehen, werden ebenfallsberücksichtigt. Die Modellresultate zeigen, dass der Ausstoß vonTreibhausgasemissionen in Österreich durch den Einsatz von Biotreibstoffenum 2%-3,5% verringert werden kann. Allerdings ist nur dieFermentierungstechnologie in der Lage, Treibstoffe zu konkurrenzfähigenKosten zu produzieren, weil höhere Erlöse durch den Verkaufder Nebenprodukte erzielt werden können.

Combined Heat and Power (CHP) plants fired by forest wood can significantly contribute to attaining the target of increasing the share of renewable energy production. However, the spatial distribution of biomass supply and of heat demand limit the potentials of CHP production. This paper assesses CHP potentials using a mixed integer programming model that optimizes locations of bioenergy plants. Investment costs of district heating infrastructure are modeled as a function of heat demand densities, which can differ substantially. Gasification of biomass in a combined cycle process is assumed as production technology. Some model parameters have a broad range according to a literature review. Monte-Carlo simulations have therefore been performed to account for model parameter uncertainty in our analysis. The model is applied to assess CHP potentials in Austria. Optimal locations of plants are clustered around big cities in the east of the country. At current power prices, biomass based CHP production allows producing around 3% of the total energy demand in Austria. Yet, the heat utilization decreases when CHP production increases due to limited heat demand that is suitable for district heating. Production potentials are most sensitive to power prices, biomass costs and biomass availability.

Climate change mitigation and security of energy supply are important targets of Austrian energy policy. Bioenergy production based on resources from agriculture and forestry is an important option for attaining these targets. To increase the share of bioenergy in the energy supply, supporting policy instruments are necessary. The cost-effectiveness of these instruments in attaining policy targets depends on the availability of bioenergy technologies. Advanced technologies such as second-generation biofuels, biomass gasification for power production, and bioenergy with carbon capture and storage (BECCS) will likely change the performance of policy instruments. This article assesses the cost-effectiveness of energy policy instruments, considering new bioenergy technologies for the year 2030, with respect to greenhouse gas emission (GHG) reduction and fossil fuel substitution. Instruments that directly subsidize bioenergy are compared with instruments that aim at reducing GHG emissions. A spatially explicit modeling approach is used to account for biomass supply and energy distribution costs in Austria. Results indicate that a carbon tax performs cost-effectively with respect to both policy targets if BECCS is not available. However, the availability of BECCS creates a trade-off between GHG emission reduction and fossil fuel substitution. Biofuel blending obligations are costly in terms of attaining the policy targets