• Energy Research

Abstract A recent article in this journal claimed to assess the socio-technical potential for onshore wind energy in Europe. We find the article to be severely flawed and raise concerns in five general areas. Firstly, the term socio-technical is not precisely defined, and is used by the authors to refer to a potential that others term as merely technical. Secondly, the study fails to account for over a decade of research in wind energy resource assessments. Thirdly, there are multiple issues with the use of input data and, because the study is opaque about many details, the effect of these errors cannot be reproduced. Fourthly, the method assumes a very high wind turbine capacity density of 10.73 MW/km2 across 40% of the land area in Europe with a generic 30% capacity factor. Fifthly, the authors find an implausibly high onshore wind potential, with 120% more capacity and 70% more generation than the highest results given elsewhere in the literature. Overall, we conclude that new research at higher spatial resolutions can make a valuable contribution to wind resource potential assessments. However, due to the missing literature review, the lack of transparency and the overly simplistic methodology, Enevoldsen et al. (2019) potentially mislead fellow scientists, policy makers and the general public.

Abstract A recent article in this journal claimed to assess the socio-technical potential for onshore wind energy in Europe. We find the article to be severely flawed and raise concerns in five general areas. Firstly, the term socio-technical is not precisely defined, and is used by the authors to refer to a potential that others term as merely technical. Secondly, the study fails to account for over a decade of research in wind energy resource assessments. Thirdly, there are multiple issues with the use of input data and, because the study is opaque about many details, the effect of these errors cannot be reproduced. Fourthly, the method assumes a very high wind turbine capacity density of 10.73 MW/km2 across 40% of the land area in Europe with a generic 30% capacity factor. Fifthly, the authors find an implausibly high onshore wind potential, with 120% more capacity and 70% more generation than the highest results given elsewhere in the literature. Overall, we conclude that new research at higher spatial resolutions can make a valuable contribution to wind resource potential assessments. However, due to the missing literature review, the lack of transparency and the overly simplistic methodology, Enevoldsen et al. (2019) potentially mislead fellow scientists, policy makers and the general public.

Concentrating solar power (CSP) capacity has expanded slower than other renewable technologies and its costs are still high. Until now, there have been too few CSP projects to derive robust conclusions about its cost development. Here we present an empirical study of the cost development of all operating CSP stations and those under construction, examining the roles of capacity growth, industry continuity, and policy support design. We identify distinct CSP expansion phases, each characterized by different cost pressure in the policy regime and different industry continuity. In 2008–2011, with low cost pressure and following industry discontinuity, costs increased. In the current phase, with high cost pressure and continuous industry development, costs decreased rapidly, with learning rates exceeding 20%. Data for projects under construction suggest that this trend is continuing and accelerating. If support policies and industrial structure are sustained, we see no near-term factors that would hinder further cost decreases. Concentrating solar power with thermal storage offers dispatchable renewable power but has enjoyed less support than photovoltaics. This study of global concentrating solar power projects finds a learning rate of 20%, which should be sustained if policy support and industrial development continue.

Concentrating solar power (CSP) capacity has expanded slower than other renewable technologies and its costs are still high. Until now, there have been too few CSP projects to derive robust conclusions about its cost development. Here we present an empirical study of the cost development of all operating CSP stations and those under construction, examining the roles of capacity growth, industry continuity, and policy support design. We identify distinct CSP expansion phases, each characterized by different cost pressure in the policy regime and different industry continuity. In 2008–2011, with low cost pressure and following industry discontinuity, costs increased. In the current phase, with high cost pressure and continuous industry development, costs decreased rapidly, with learning rates exceeding 20%. Data for projects under construction suggest that this trend is continuing and accelerating. If support policies and industrial structure are sustained, we see no near-term factors that would hinder further cost decreases. Concentrating solar power with thermal storage offers dispatchable renewable power but has enjoyed less support than photovoltaics. This study of global concentrating solar power projects finds a learning rate of 20%, which should be sustained if policy support and industrial development continue.

Energy system and integrated assessment models (IAMs) are widely used techniques for knowledge production to assess costs of future energy pathways and economic effects of energy/climate policies. With their increased use for policy assessment and increasing dominance in energy policy science, such models attract increasing criticism. In the last years, such models – especially the highly complex IAMs, have been accused of being arbitrary. We challenge this view and argue that the models and their assumptions are not arbitrary, but they are normative and reflect the modelers’ understanding of the functioning of the society, the environment-societal relations and respective appropriate scientific tools and theories – in short: models are shaped by discursive structures, reproducing and reinforcing particular societal discourses. We identify 9 distinct paths, all relating to crucial model decisions, via which discourses enter models: for each of these decisions, there are multiple “correct” answers, in the sense that they can be justified within a particular discourse. We conclude that decisions of modelers about the structure and about assumptions in energy modeling are not arbitrary but contingent to the discursive context the modeler is related to. This has two implications. First, modelers and consumers of model output must reflect on what a model and its assumptions represent, and not only whether are they correct. Second, models hardly need to add more (mathematical) complexity, but rather be reduced and simplified so that they can continue to fulfill their main function as formalized and powerful instruments for thought experiments about future energy pathways.

Energy system and integrated assessment models (IAMs) are widely used techniques for knowledge production to assess costs of future energy pathways and economic effects of energy/climate policies. With their increased use for policy assessment and increasing dominance in energy policy science, such models attract increasing criticism. In the last years, such models – especially the highly complex IAMs, have been accused of being arbitrary. We challenge this view and argue that the models and their assumptions are not arbitrary, but they are normative and reflect the modelers’ understanding of the functioning of the society, the environment-societal relations and respective appropriate scientific tools and theories – in short: models are shaped by discursive structures, reproducing and reinforcing particular societal discourses. We identify 9 distinct paths, all relating to crucial model decisions, via which discourses enter models: for each of these decisions, there are multiple “correct” answers, in the sense that they can be justified within a particular discourse. We conclude that decisions of modelers about the structure and about assumptions in energy modeling are not arbitrary but contingent to the discursive context the modeler is related to. This has two implications. First, modelers and consumers of model output must reflect on what a model and its assumptions represent, and not only whether are they correct. Second, models hardly need to add more (mathematical) complexity, but rather be reduced and simplified so that they can continue to fulfill their main function as formalized and powerful instruments for thought experiments about future energy pathways.

After three years of low growth and an increase in global costs, the announcement and implementation of the Chinese demonstration programme for concentrating solar power (CSP) has changed the outlook for the technology from gloomy to better than ever. Here, we analyse the Chinese CSP strategy, its drivers, and its effects on CSP industry and costs in China and globally. We find that the Chinese demonstration programme has led to the emergence of new CSP industry actors, and that it helped to the reduce global average costs of new CSP stations to USD 0.12 per kWh. However, the Chinese expansion, which is supplied almost exclusively by Chinese companies, follows a wholly different cost trajectory than the expansion in the rest of the world, which is almost exclusively served by non-Chinese companies: whereas costs in both markets have decreased, the cost of Chinese CSP stations under construction is 40% lower than that of plants built elsewhere. We conclude that the Chinese support programme has thus succeeded in its central aims of leapfrogging and has built up a domestic industry capable of building stations and most components at lower costs than foreign competitors. However, Chinese companies are not yet active outside China, nor do we find many foreign participants in the Chinese market. The effects of the Chinese CSP programme on markets and industries outside China have thus far been limited: the Chinese and non-Chinese markets currently largely exist in parallel, each with their own supply chains. Whether the new Chinese companies seek to and manage to conquer the global market as well remains to be seen but so far, they have not.