• Energy Research
• 9. Industry and infrastructure close
• NL close
• Transport Research close
• Energy Research close

The term eco-innovation has been coined to label those innovations expected to reduce the life cycle environmental burdens resulting from their use. Claims of environmental superiority are usually supported by technology-oriented analyses, such as product-level life cycle assessment. However, the environmental superiority of an innovation depends not only on its technical characteristics but also on technology-demand interactions. In this article, such interactions are incorporated through the concept of the environmental rebound effect. Using the Dynamic IPAT-Life cycle assessment with Environmental Rebound effect or DILER model, environmental superiority claims of seven alleged transport eco-innovations were evaluated by comparing alternative macro-level scenarios (with and without innovation) for Europe. The results support the claims of environmental superiority of only three out of seven studied innovations. That is, a majority of innovations actually induced increases in various environmental pressures. Such increases can be attributed mostly to the influence of generally noteworthy environmental rebound effects. The magnitude of the rebound effect is found to be highly correlated with two variables: the total change in effective income resulting from the use of the innovation and the difference between the environmental pressures per monetary unit of the studied innovations and that of the rest of consumption. The article contributes to the literature by (a) applying a comprehensive approach to the rebound effect and its relationship with the eco-innovation concept, (b) by calculating original rebound estimates of specific transport innovations and assessing these in absolute terms, as well as by (c) obtaining novel insights into the drivers behind the rebound effect. The counterintuitive results of this study also invite to re-assess the use of technology-oriented tools for guiding environmental policy. Other policy implications of this study relate to the relevance of transport cost differences, the targeted promotion of actual eco-innovations and its combination with broader policies as well as the achievement of higher quality mobility.

This paper presents an analysis that frames the impact of various smart grid technologies, with an objective to provide a transparent framework for residential smart grid demonstration projects based on predefined and clearly formulated key performance indicators. The analysis inspects measured energy data of 217 households from three smart grid pilot projects in the Netherlands and a public dataset with smart meter data from 70 households as a reference. The datasets were evaluated for one year and compared to provide insights on technologies and other differences based on seven key performance indicators, giving a comprehensive overview: monthly electricity consumption (100–600 kWh) and production (4–200 kWh); annually imported (3.1–4.5 MWh) and exported (0.2–1 MWh) electricity; residual load; peak of imported (4.8–6.8 kW) and exported (0.3–2.2 kW) electricity; import simultaneity (20–70.5%); feed in simultaneity (75–89%); self-sufficiency (18–20%); and self-consumption (50–70%). It was found that the electrification of heating systems in buildings by using heat pumps leads to an increase of annual electricity consumption and peak loads of approximately 30% compared to the average Dutch households without heat pumps. Moreover, these peaks have a high degree of simultaneity. To increase both the self-sufficiency and self-consumption of households, further investigations will be required to optimize smart grid systems.

Climate change has become one of the most serious challenges facing humanity; developing a low-carbon economy provides new opportunities for addressing this issue. Building a low-carbon city has been pursued by people with a high degree of enthusiasm in China. Different from actions at the national level and distinct from practices of developed countries, low-carbon development in Chinese cities should be placed on diverse concerns. Taking Suzhou of Jiangsu Province of China as a case city, this paper adopts a scenario analysis approach to explore strategic focal points in the transition to a low-carbon city. Within this transition, we mainly focus on the different contributions from two factors-economic restructuring and technological upgrading. Scenario analysis results show that 1) in the case of no breakthrough technologies, it is difficult to achieve absolute emission reductions; 2) technologies involved in optimizing energy structure and improving energy efficiency of basic service sectors should be highly emphasized in local planning; 3) in comparison with technological upgrading, economic structural adjustment could be a stronger contributor to mitigation, which is one of the main differences from developed countries. However, the key issue of economic restructuring is to promote the growth of emerging low-carbon industries, which requires not only a strategic choice of new industries but also an introduction of advanced low-carbon technologies. It is also found that establishing a local carbon emissions accounting system is a prerequisite and the first priority for realizing a low-carbon transition and government capacity buildings should be strengthened accordingly.

Will automotive be the future of mobility or will the motorcar era come to an end in the 21st century? Today, auto-mobility is still growing, but in the future, this will depend on its ability to adapt to the needs of modern society. Disruptive technologies like electrification, automation, and connectivity can make automotive more sustainable by striving for the Six Zero goals: Zero Emission, Zero Energy, Zero Congestion, Zero Accident, Zero Empty, and Zero Cost. These tempting goals can lead not only to a more sustainable ecology, but also to a new economy with more efficient use of the time and money needed for mobility. In this future mobility framework, this article describes the practice-oriented research of the Rotterdam University of Applied Sciences with its regional partners to achieve these goals.

This paper identifies the risks for the functionality and reliability of the grid that arise from the integration of the transport and supply chain. The electrification of transport is a promising option for the transition to a low carbon energy and transport system. But on the short term, the electrification of transport also creates risks. More specifically, when promising technological such as vehicle-to-grid and smart-grids are not yet available on a large scale, the rapid diffusion of electric vehicles and the recharging behaviour of consumers can create risks for grid functioning. In order to assess these risks, this paper present a GIS-based simulation method that assesses electricity demand and supply on the neighbourhood level. The paper combines local level electric vehicle diffusion forecasts, with neighbourhood level data about the grid additional capacity. Application of the model to the Netherlands shows that risks for grid functioning already appear as early as 2015. More specifically, the diffusion of electric vehicles is found to compromise the functioning of the grid on the short term in densely populated areas such as Amsterdam. In these neighbourhoods early and fast adoption of electric vehicles coincides with the presence of an older grid with less additional capacity. The model provides insights for grid operators as well as for policy makers that seek to stimulate the transition to sustainable energy and transport systems, and can be used as a strategic tool to plan (smart) grid investments.

In this paper, a framework is presented for the evaluation of smart grid environment which is called the three-layer model. This three-layer model comprises three specific categories, or ‘layers’, namely, the stakeholder, market and technologies layers. Each layer is defined and explored herein, using an extensive literature study regarding their key elements, their descriptions and an overview of the findings from the literature. The assumption behind this study is that a solid understanding of each of the three layers and their interrelations will help in more effective assessment of residential smart grid pilots in order to better design products and services and deploy smart grid technologies in networks. Based on our review, we conclude that, in many studies, social factors associated with smart grid pilots, such as markets, social acceptance, and end-user and stakeholder demands, are most commonly defined as uncertainties and are therefore considered separately from the technical aspects of smart grids. As such, it is recommended that, in future assessments, the stakeholder and market layers should be combined with the technologies layer so as to enhance interaction between these three layers, and to be able to better evaluate residential smart energy systems in a multidisciplinary context.

Demand-side management and demand response are proposed as a means to solve different objectives in smart grids, such as, e.g., maximizing self-consumption of a house or peak shaving. Crucial components in these approaches are load shiftable/steerable devices, so-called smart appliances. Although several studies already use these devices and determine how to use their flexibility, their impact on — or value for — the overall system is not studied. This paper provides a methodology to calculate the value of flexibility of smart devices. The methodology makes it possible to quantitatively compare the impact of these devices for different kinds of objectives. The developed methodology is applied in a case study to compare the flexibility of white goods, home batteries and electric vehicles. The results indicate among others that smart white goods may not always be that important for smart grids.