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The trade of global bioenergy commodities, such as ethanol, biodiesel and wood pellets has been growing exponentially in the past decade, and have by 2013 reached true "commodity" volumes, i.e. tens of millions of tonnes traded each year, and billions (both in US$/€) of annual turnover. IEA Bioenergy Task 40 was founded in 2004 and is now in its 4th triennium. For the past 9 years, task 40 has monitored the developments in international bioenergy trade, including the organization of about 20 workshops on trade-related topics, and the publication of over 100 studies, country reports, newsletters, etc. The amount of material produced over the years and insights gained in how biomass markets and international trade of biomass and biofuels has developed is impressive. Besides that the group has produced overviews and insights, also a large amount of practical experience has been brought together in what works and what doesn't. Last but not least, based on all this, there are clear(er) views on how to proceed to build working sustainable international biomass markets in the future. This book compiles those lessons and insights into an easily accessible book publication

Hydrogen represents a versatile energy carrier with net zero end use emissions. Power-to-Liquid (PtL) includes the combination of hydrogen with CO2 to produce liquid fuels and satisfy mostly transport demand. This study assesses the role of these pathways across scenarios that achieve 80–95% CO2 reduction by 2050 (vs. 1990) using the JRC-EU-TIMES model. The gaps in the literature covered in this study include a broader spatial coverage (EU28+) and hydrogen use in all sectors (beyond transport). The large uncertainty in the possible evolution of the energy system has been tackled with an extensive sensitivity analysis. 15 parameters were varied to produce more than 50 scenarios. Results indicate that parameters with the largest influence are the CO2 target, the availability of CO2 underground storage and the biomass potential. Hydrogen demand increases from 7 mtpa today to 20–120 mtpa (2.4–14.4 EJ/yr), mainly used for PtL (up to 70 mtpa), transport (up to 40 mtpa) and industry (25 mtpa). Only when CO2 storage was not possible due to a political ban or social acceptance issues, was electrolysis the main hydrogen production route (90% share) and CO2 use for PtL became attractive. Otherwise, hydrogen was produced through gas reforming with CO2 capture and the preferred CO2 sink was underground. Hydrogen and PtL contribute to energy security and independence allowing to reduce energy related import cost from 420 bln€/yr today to 350 or 50 bln€/yr for 95% CO2 reduction with and without CO2 storage. Development of electrolyzers, fuel cells and fuel synthesis should continue to ensure these technologies are ready when needed. Results from this study should be complemented with studies with higher spatial and temporal resolution. Scenarios with global trading of hydrogen and potential import to the EU were not included.

Improving energy system modeling capabilities can directly affect the quality of applied studies. However, some modeling trade-offs are necessary as the computational capacity and data availability are constrained. In this paper, we demonstrate modeling trade-offs resulting from the modification in the resolution of four modeling capabilities, namely, transitional scope, European electricity interconnection, hourly demand-side flexibility description, and infrastructure representation. We measure the cost of increasing resolution in each capability in terms of computational time and several energy system modeling indicators, notably, system costs, emission prices, and electricity import and export levels. The analyses are performed in a national-level integrated energy system model with a linear programming approach that includes the hourly electricity dispatch with European nodes. We determined that reducing the transitional scope from seven to two periods can reduce the computational time by 75% while underestimating the objective function by only 4.6%. Modelers can assume a single European Union node that dispatches electricity at an aggregated level, which underestimates the objective function by 1% while halving the computational time. Furthermore, the absence of shedding and storage flexibility options can increase the curtailed electricity by 25% and 8%, respectively. Although neglecting flexibility options can drastically decrease the computational time, it can increase the sub-optimality by 31%. We conclude that an increased resolution in modeling flexibility options can significantly improve the results. While reducing the computational time by half, the lack of electricity and gas infrastructure representation can underestimate the objective function by 4% and 6%, respectively.

Improving energy system modeling capabilities can directly affect the quality of applied studies. However, some modeling trade-offs are necessary as the computational capacity and data availability are constrained. In this paper, we demonstrate modeling trade-offs resulting from the modification in the resolution of four modeling capabilities, namely, transitional scope, European electricity interconnection, hourly demand-side flexibility description, and infrastructure representation. We measure the cost of increasing resolution in each capability in terms of computational time and several energy system modeling indicators, notably, system costs, emission prices, and electricity import and export levels. The analyses are performed in a national-level integrated energy system model with a linear programming approach that includes the hourly electricity dispatch with European nodes. We determined that reducing the transitional scope from seven to two periods can reduce the computational time by 75% while underestimating the objective function by only 4.6%. Modelers can assume a single European Union node that dispatches electricity at an aggregated level, which underestimates the objective function by 1% while halving the computational time. Furthermore, the absence of shedding and storage flexibility options can increase the curtailed electricity by 25% and 8%, respectively. Although neglecting flexibility options can drastically decrease the computational time, it can increase the sub-optimality by 31%. We conclude that an increased resolution in modeling flexibility options can significantly improve the results. While reducing the computational time by half, the lack of electricity and gas infrastructure representation can underestimate the objective function by 4% and 6%, respectively.

Rural communities in developing countries lack access to affordable, reliable, and sustainable forms of energy, which are essential factors for improving living conditions. These communities rely on diesel and kerosene, which are highly polluting compared to renewable energy technologies, to satisfy their energy needs. In this study, hybrid renewable energy systems (HRESs) have been analyzed, which are designed to overcome the fluctuating nature of renewables, for off-grid electrification. The results of this study-which covers many countries and examples-show that the successful integration of HRES is influenced by factors such as government support-and community organization - which is essential to keep these systems operating over the project lifetime. The levelized cost of energy (LCOE) of different mini-grids was compared and analyzed. The results reveal that by comparing the LCOE range of diesel (between USD 0.92/kWh and USD 1.30/kWh), solar photovoltaic (USD 0.40/kWh and USD 0.61/kWh), and hybrid solar photovoltaic/diesel (USD 0.54/kWh to USD 0.77/kWh), diesel is the most expensive technology. Additionally, the study addressed barriers that can hinder the implementation of mini-grids, such as lack of supportive policies and high capital cost. However, governments' incentives are instrumental in lowering capital costs. These results are of particular importance for developing countries, where electricity supply via HRES is often quicker and cheaper than grid extension. The insights from this paper are a good starting point for in-depth research on optimal local design and ownership models, which can help accelerate the implementation, and lower the costs of sustainable electricity supply in remote areas.