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Microalgae have tremendous potential for producing liquid renewable fuel. Many methods for converting microalgae to biofuel have been proposed; however, an economical and energetically feasible route for algal fuel production is yet to be found. This paper presents a review on the comparison of the most promising conversion pathways of microalgae to liquid fuel: hydrothermal liquefaction (HTL), wet extraction and non-destructive extraction. The comparison is based on important assessment parameters of product quality and yield, nutrient recovery, GHG emissions, energy and the cost associated with the production of fuel from microalgae, in order to better understand the pros and cons of each method. It was found that the HTL pathway produces more oil than the wet extraction pathway; however, higher concentrations of unwanted components are present in the HTL oil produced. Less nutrients (N and P) can be recovered in HTL compared to wet extraction. HTL consumes more fossil energy and generates higher GHG emissions than wet extraction, while the production cost of fuel from HTL pathway is lower than wet extraction pathway. There is considerable uncertainty in the comparison of the energy consumption and economics of the HTL pathway and the wet extraction pathway due to different scenarios analysed in the assessment studies. To be able to appropriately compare methodologies, the conversion methods should be analysed from growth to upgradation of oil utilising sufficiently similar assumptions and scenarios. Based on the data in available literature, wet oil extraction is the more appropriate system for biofuel production than HTL. However, the potential of alternative extraction/conversion technologies, such as, non-destructive extraction, need to be further assessed.

AbstractBioenergy projects can lead to direct and indirect land use change (LUC), which can substantially affect greenhouse gas balances with both beneficial and adverse outcomes for bioenergy's contribution to climate change mitigation. The causes behind LUC are multiple, complex, interlinked, and change over time. This makes quantification uncertain and sensitive to many factors that can develop in different directions—including land use productivity, trade patterns, prices and elasticities, and use of by‐products associated with biofuels production. Quantifications reported so far vary substantially and do not support the ranking of bioenergy options with regard to LUC and associated emissions. There are however several options for mitigating these emissions, which can be implemented despite the uncertainties. Long‐rotation forest management is associated with carbon emissions and sequestration that are not in temporal balance with each other and this leads to mitigation trade‐offs between biomass extraction for energy use and the alternative to leave the biomass in the forest. Bioenergy's contribution to climate change mitigation needs to reflect a balance between near‐term targets and the long‐term objective to hold the increase in global temperature below 2°C (Copenhagen Accord). Although emissions from LUC can be significant in some circumstances, the reality of such emissions is not sufficient reason to exclude bioenergy from the list of worthwhile technologies for climate change mitigation. Policy measures to minimize the negative impacts of LUC should be based on a holistic perspective recognizing the multiple drivers and effects of LUC.This article is categorized under: Bioenergy > Economics and Policy Bioenergy > Climate and Environment

Abstract Electricity markets in Europe become increasingly interconnected due to new grid connections and market coupling regulations. This paper examines the interdependencies between the Swiss electricity market and those of neighbouring countries. The Swiss market serves as a good example for a smaller electricity market which is increasingly affected by developments in the large neighbouring countries. To study these cross-border effects, especially those on Swiss electricity prices, we apply two different methodologies, an econometric and a Nash-Cournot equilibrium model. The analyses show that the Swiss electricity price correlates strongly with the German electricity price in the summer, but tends to follow the French electricity price in the winter. Another finding is that gas prices and the electricity load of neighbouring countries have a significant influence on prices. In particular, the load of France and Italy is driving up Swiss prices in the winter, while the German electricity demand and renewable energy generation have a larger influence on Swiss prices in the summer.

Abstract Social acceptance of innovative technologies is a key element of an effective transition towards more sustainable energy economies. However, innovative technologies like genetic modification also tend to spark controversy and backlash. So far, efforts to inform the public about any risks and benefits of novel technologies not only have struggled to foster acceptance but also neglect the interdependent foundations of consumer decision-making. Through a controlled experiment with German consumers (N = 322), we examine whether consumer support and rejection of genetic modification in bioenergy crops is influenced by the statements and actions of actors throughout the supply chain. In specific, we show that the decision of energy companies to sell and support GM bioenergy positively impacts consumer decisions to support. To ensure that decision outcomes were specifically impacted by the expressions of corporate actors, we controlled for the content and valence of information by random assignment to one of three treatments in which participants received positive, negative, or balanced (risks and benefits) information. We find that negative messaging diminished support and increased rejection relative to the other treatments. Lastly, the statements and actions of corporate actors also exerted an indirect influence on consumer decisions through their interactions with social trust and labels, e.g. greater support by farmers had a positive influence only for those who are more generally trustworthy. Given these results, we anticipate more attention to the importance of actors such as farmers and energy companies for the social acceptance of novel technologies in the energy sphere.

Parabolic trough power plants are currently the most commercially applied systems for CSP power generation. To improve their cost-effectiveness, one focus of industry and research is the development of processes with other heat transfer fluids than the currently used synthetic oil. One option is the utilization of water/steam in the solar field, the so-called direct steam generation (DSG). Several previous studies promoted the economic potential of DSG technology [1–3]. Analyses’ results showed that live steam parameters of up to 500°C and 120 bars are most promising and could lead to a reduction of the levelized electricity cost (LEC) of about 11% [4]. However, all of these studies only considered plants without thermal energy storage (TES). Therefore, a system analysis including integrated TES was performed by Flagsol GmbH and DLR together with Solar Millennium AG, Schott CSP GmbH and Senior Bergho¨fer GmbH, all Germany. Two types of plants are analyzed and compared in detail: a power plant with synthetic oil and a DSG power plant. The design of the synthetic oil plant is very similar to the Spanish Andasol plants [5] and includes a molten salt two-tank storage system. The DSG plant has main steam parameters of 500 °C and 112 bars and uses phase change material (PCM) for the latent and molten salt for the sensible part of the TES system. To enable comparability, both plants share the same gross electric turbine capacity of 100 MWel, the same TES capacity of nine hours of full load equivalent and the same solar multiple of the collector field of about two. This paper describes and compares both plants’ design, performance and investment. Based on these results, the LEC are calculated and the DSG plant’s potential is evaluated. One key finding is that with currently proposed DSG storage costs, the LEC of a DSG plant could be higher than those of a synthetic oil plant. When considering a plant without TES on the other hand, the DSG system could reduce the LEC. This underlines the large influence of TES and the still needed effort in the development of a commercial storage system for DSG.

Global fossil fuel reserves are declining due to differential uses, especially for power generation. Everybody can help to do their bit for the environment by using solar energy. Geographically, Bangladesh is a potential zone for harnessing solar energy. In March 2021, the renewable generation capacity in Bangladesh amounted to 722.592 MW, including 67.6% from solar, 31.84% from hydro, and 0.55% from other energy sources, including wind, biogas, and biomass, where 488.662 MW of power originated from over 6 million installed solar power systems. Concurrently, over 42% of rural people still suffer from a lack of electricity, where solar energy can play a vital role. This paper highlights the present status of various forms of solar energy progress in Bangladesh, such as solar parks, solar rooftops, solar irrigation, solar charging stations, solar home systems, solar-powered telecoms, solar street lights, and solar drinking water, which can be viable alternative sources of energy. This review will help decision-makers and investors realize Bangladesh’s up-to-date solar energy scenario and plan better for the development of a sustainable society.

Abstract The Renewable energy power generation capacity has been rapidly increasing in China recently. Meanwhile, the contradiction between power supply and demand is becoming increasingly more prominent due to the intermittence of renewable energies. On the other hand, on the mitigation of carbon dioxide (CO2) emissions in China needs immediate attention. Power-to-Gas (PtG), a chemical energy storage technology, can convert surplus electricity into combustible gases. Subsurface energy storage can meet the requirements of long term storage with its large capacity. This paper provides a discussion of the entire PtG energy storage technology process and the current research progress. Based on the comparative study of different geological storage schemes for synthetic methane, their respective research progress and limitations are noted. In addition, a full investigation of the distribution and implementation of global PtG and CO2 capture and storage (CCS) demonstration projects is performed. Subsequently, the opportunities and challenges of the development of this technology in China are discussed based on techno-economic and ecological effects analysis. While PtG is expected to be a revolutionary technology that will replace traditional power systems, the main issues of site selection, energy efficiency and the economy still need to be adequately addressed. Additionally, based on the comprehensive discussion of the results of the analysis, power-to-gas and subsurface energy storage implementation strategies, as well as outlook in China are presented.

This paper presents a comparative study in predicting the monthly average solar radiation for Darwin, Australia (latitude 12.46 deg S longitude 130.84 deg E). The city of Darwin, Northern Territory (NT), has the highest and most consistent sunshine duration among all the other Australian states. This unique climate presents an opportunity for photovoltaic (PV) applications. Reliable and accurate predictions of solar radiation enable potential site locations, which exhibit high solar radiations and sunshine hours, to be identified for PV installation. Three predictive models were investigated in this study—the linear regression (LR), Angstrom–Prescott–Page (APP), and the artificial neural network (ANN) models. The mean global solar radiation coupled with the climate data (mean minimum and maximum temperatures, mean rainfall, mean evaporation, and sunshine fraction) obtained from the Australian Bureau of Meteorology (BoM) formed the basis of the dataset. Using simple and easily obtainable climate data presents an added advantage by reducing model complexity. Predictive results showed the root mean square errors (RMSEs) obtained were 6.72%, 13.29%, and 8.11% for the LR, APP, and ANN models, respectively. The predicted solar exposure from the LR model was then compared with the satellite-derived data to assess the accuracy of the LR method.