Diffusion Of New Energy Technologies Research Articles

Revolution of new energy industry: Spatio-temporal dynamics and drivers of technological diffusion in Zhejiang, China

The new energy that aims to reduce pollution is the technological trend of energy development in the future. The development of the new energy industry is a complex system. Studying the spatio-temporal revolution of new energy industry helps analyse the development trend, supply, and demand of new energy. Thus, taking Zhejiang Province as an example, the spatial evolution of the new energy industry from 2016 to 2021 is studied. The evolution trend of spatial agglomeration of the new energy industry shows the coexistence of agglomeration and diffusion. No overall agglomeration of the new energy industry in Zhejiang Province is observed. The development performs solid spatial dependence. The results indicate that it is challenging to aggregate resources and achieves economies of scale without a leading enterprise. The diffusion of new energy technologies in the future depends on industrial agglomeration and the cultivation of leading enterprises.

Failing the formative phase: The global diffusion of nuclear power is limited by national markets

Understanding the role of technology characteristics and the context in the diffusion of new energy technologies is important for assessing feasibility of climate mitigation. We examine the historical adoption of nuclear power as a case of a complex large scale energy technology. We conduct an event history analysis of grid connections of first sizable commercial nuclear power reactors in 79 countries between 1950 and 2018. We show that the introduction of nuclear power can largely be explained by contextual variables such as the proximity of a country to a major technology supplier (‘ease of diffusion’), the size of the economy, electricity demand growth, and energy import dependence (‘market attractiveness’). The lack of nuclear newcomers in the early 1990s can be explained by the lack of countries with high growth in electricity demand and sufficient capacities to build their first nuclear power plant, either on their own or with international help. We also find that nuclear accidents, the pursuit of nuclear weapons, and the advances made in competing technologies played only a minor role in nuclear technology failing to be established in more countries. Our analysis improves understanding of the feasibility of introducing contested and expensive technologies in a heterogenous world with motivations and capacities that differ across countries and by a patchwork of international relations. While countries with high state capacity or support from a major technology supplier are capable of introducing large-scale technologies quickly, technology diffusion to other regions might undergo significant delays due to lower motivations and capacities.

Understanding international trade network complexity of platinum: The case of Japan

In recent decades, platinum-group metals have become increasingly important to the development and diffusion of cleaner technologies being developed to achieve a “low carbon” society. Countries engaged in the development and diffusion of new energy technologies are concerned about steadily importing scarce rare metals. Nevertheless, the question of what kind of competitive relationships exist among demand countries is not well addressed. This study focused on platinum primary product used to produce greener products like next-generation vehicles and analyzed the international trade network complexity of the platinum primary product using the clustering method. From the results, we found that (1) there exit well-separated nine trade clusters (i.e., trade networks with higher exchanges) in the international trade network of 2005, (2) the group including South Africa and the group consisting of Western countries together account for approximately half the total international trade flow in platinum primary products, and (3) international coordination of purchases and sales of platinum among relevant trade partners in the identified largest cluster: South Africa, Russia, Japan, China, Hong Kong, and Switzerland is crucial in securing the stable supply and demand for platinum.

Modeling cascading diffusion of new energy technologies: case study of residential solid oxide fuel cells in the U.S. and internationally

Subsidy programs for new energy technologies are motivated by the experience curve: increased adoption of a technology leads to learning and economies of scale that lower costs. Geographic differences in fuel prices and climate lead to large variability in the economic performance of energy technologies. The notion of cascading diffusion is that regions with favorable economic conditions serve as the basis to build scale and reduce costs so that the technology becomes attractive in new regions. We develop a model of cascading diffusion and implement via a case study of residential solid oxide fuel cells (SOFCs) for combined heating and power. We consider diffusion paths within the U.S. and internationally. We construct market willingness-to-pay curves and estimate future manufacturing costs via an experience curve. Combining market and cost results, we find that for rapid cost reductions (learning rate = 25%), a modest public subsidy can make SOFC investment profitable for 20-160 million households. If cost reductions are slow however (learning rate = 15%), residential SOFCs may not become economically competitive. Due to higher energy prices in some countries, international diffusion is more favorable than domestic, mitigating much of the uncertainty in the learning rate.

Preface to Special Topic: Selected Papers from the First International Workshop on “Diffusion of New Energy Technologies in China,” Shanghai, China, 2011

China’s fast growing economy is inducing various technology dynamics. Much attention and resources are being paid to new energy technologies in China. These eight selected papers are a collection of academic studies on modeling and policy analysis of the diffusion of new energy technologies in China. These studies were all presented during the First International Workshop on “Diffusion of New Energy Technologies in China,” held from 25–26 March 2011, in Shanghai, China.

Technology diffusion and carbon intensity of electric power in China

The relationship between technology and carbon intensity has received a lot of attention in recent years. This paper focuses on the impacts of diffusion of new energy technologies and thermal power technology on carbon intensity of electricity production during 1996–2009. The results show that new energy maintained less than 20% over the period 1996–2009, and it can also decrease the carbon intensity of electricity power. However, the decline of thermal power carbon intensity driven by its technology diffusion was the main driver force of electricity power carbon intensity. However, the effect of thermal power technology diffusion was also different in different years as the speed of thermal power technology diffusion and technological learning ability was different.

Towards a low-carbon economy: Coping with technological bifurcations with a carbon tax

Technological learning is understood as an endogenous mechanism for the diffusion of advanced clean energy technologies. Technological learning is quite uncertain. Previous research showed that an optimization model with uncertain technological learning could generate technological bifurcations: various local optimal solutions of technology development strategies with very similar total costs but different environmental impacts. With a simplified energy system optimization model, this paper explores technological bifurcations and the effect of a carbon tax on the development and diffusion of new energy technologies. With a three-stage analysis, the main findings of this paper are (1) that technological learning, instead of its uncertainty, is an essential mechanism for technological bifurcations, and (2) a carbon tax can reduce carbon emission but not necessarily technological bifurcations. An implication from these findings is that with a carbon tax, there still could be potential for other policy interventions to reduce carbon emissions without much additional cost.

Accelerating the development and diffusion of new energy technologies: Beyond the “valley of death”

There are at least three motivations for government intervention in GHG mitigation: (1) inducing the private sector to reduce GHG emissions directly by setting a price on emissions, (2) increasing the amount of innovative activity in GHG mitigation technology development, and (3) educating the public regarding GHG-reducing investment opportunities, allowing consumers to make better private decisions. This paper discusses the pros and cons of policy instruments that might be used to respond to these motivations and makes recommendations for an appropriate mix of policy instruments over time given both economic and policital/instituional considerations.

Is there a relationship between public expenditures in energy R&D and carbon emissions per GDP? An empirical investigation

Energy innovation plays a crucial role in the reduction of carbon emissions. In order to design climate and energy policies that promote the development, deployment and diffusion of new energy technologies, policy makers not only require a theoretical understanding of the energy innovation system, but also empirical evidence of the effects that policy actions have had. This paper focuses on public energy R&D, a traditional and controversial option among the various climate technology policies, and empirically analyses its relationship with carbon emissions per GDP (i.e. carbon intensity) and its two components: energy intensity and the carbon factor. Evidence of the causality links that have prevailed in 13 advanced economies over the 1980–2004 period has been obtained through dynamic panel models. Our findings confirm that government R&D spending is not sufficient by itself to boost the energy innovation process. Public energy R&D has been successful in improving energy efficiency at country level, but it has failed to have a significant impact on the carbon factor and carbon intensity. At the same time the formation of energy R&D budgets is found to be significantly affected by carbon trends.

Technological progress and long-term energy demand — a survey of recent approaches and a Danish case

This paper discusses different approaches to incorporating technological progress in energy-economy models and the effect on long-term energy demand projections. Approaches to modelling based on an exogenous annual change of energy efficiency to an endogenous explanation of innovation for energy technologies are covered. Technological progress is an important issue for modelling long-term energy demand and is often characterised as the main contributor to the different energy demand forecasts from different models. New economic theoretical developments in the fields of endogenous growth and industrial organisation have important implications for the attempts to endogenise technological innovation and diffusion of new energy technologies. A range of analytical and empirical models with different descriptions of technological progress is surveyed in the paper. To analyse the importance of the technology description, two models of residential energy demand in Denmark are compared. A Danish macroeconometric model is compared to a technological vintage model that is covering electric appliances and residential heating demand. The energy demand projection of the two models diverges, and the underlying assumptions regarding technological progress must be made comparable in order to demonstrate whether or not these assumptions are the reason. Assumptions about energy efficiency improvement in the vintage models are found to be important for the projection. The vintage modelling approach is found to be less important for long-term projections. A limitation of the vintage modelling approach applied in the long term explains some of the differences in projections among the two types of models. The applied vintage model of electric appliances does not adequately describe the category of new energy-consuming appliances that are expected to become available in the long term. If it is to be used for long-term projections this category must be more carefully modelled.