Aligning prosumers' electricity consumption to the availability of self-generated electricity decreases CO₂ emissions and costs. Nudges are proposed as one behavioral intervention to orchestrate such changes. At the same time, fragmented findings in the literature make it challenging to identify suitable behavioral interventions for specific households and contexts - specifically for optimizing self-consumption. We test three sequentially applied interventions (feedback, benchmark, and default) delivered by digital tools in a field experiment with 111 German households with rooftop-photovoltaics. The experiment design with a control-group, baseline measurements, and high-frequency smart-meter-data allows us to examine the causal effects of each intervention for increasing self-consumption. While feedback and benchmark deliver small self-consumption increases (3–4 percent), the smart changing default leads to a 16 percent increase for active participants. In general, households with controllable electric vehicles show stronger effects than those without. For upscaling behavioral interventions for other prosumers, we recommend interventions that require little interaction and energy literacy because even the self-selected, motivated sample rarely interacted with the digital tools.

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With the diffusion of prosumerism, where households act both as producers and consumers of energy, policy makers must strike a balance between encouraging microgeneration and regulating this new prosumer segment on the energy market. However, effective policy implementation depends on prosumers’ behavioural reactions. This paper provides evidence on the interplay between digital real-time information and regulation of self-consumption for rooftop photovoltaics (PV) in Croatia. Croatian households that produce more annual electricity than they consume are automatically re-classified as renewable traders, which means additional administrative duties and less favorable tax treatment. This creates perverse incentives to reduce PV generation or increase energy consumption by year-end. We document the behavioural reactions to this policy design, indicating that energy production and consumption are highly elastic regarding regulatory incentives, but only if these incentives are made transparent and accessible with timely information. We collected two survey waves (n = 54 and n = 80) and smart meter data (n = 39), which illustrate the behavioural reaction before and after year-end. According to the survey wave before year-end, almost half of the participants considered curtailing their PV output. According to the smart meter data, a sizable share did indeed take action by shutting down PV production or by powering additional devices to reduce the surplus near year-end. In a second survey wave in the new year, prosumers provide ex-post insights on the specific measures taken to reduce surplus. We discuss research insights regarding the transparency and control offered by metering feedback, and how this can influence household behaviour within regulatory frameworks.@en

Households equipped with flexible technologies, such as electric vehicles, can support the energy transition by shifting electricity consumption to times of high renewable supply and by preventing consumption peaks that cannot be covered by existing grid and generation infrastructure. Demand response services support households in performing these consumption shifts. Households ask for specifications of services that stand partly in contrast to each other. For instance, while electric vehicle owners tend to insist on retaining control over their charging, others prefer data-driven automation to minimize their active involvement. Recent studies exploring the acceptance of demand response services focused either solely on specific household groups (e.g. electric vehicle users) or on a broad representative sample without further differentiation. Complementarily to fill this gap, we examine differences in preferences for contrasting service designs between household groups. Specifically, we consider: (i) the type of flexible technology to which demand response is applied, and (ii) the adoption level, i.e., whether the households plan to, or currently own, a flexible technology. In a vignette survey, we examine the preferences towards four contrasting service designs with German households that either own or have expressed interest in acquiring a flexible technology (n = 962). Our results show that the preferences do not fundamentally differ between the kind of flexible technology and adoption level. Generally, participants prefer automated demand response services with data sharing. The added value of realizing energy cost savings effectively and efficiently stands out as the main driver for the diffusion of demand response services, outweighing data privacy concerns. Contrary to our expectations, electric vehicle owners did not show a special need for control and households not yet owning flexible technologies did not express a need for little effort. We discuss the implications of our findings for demand response service providers and outline pathways of future research in this domain.

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Electric vehicle (EV) users who aim to become flexibility providers face a tradeoff between staying in control of charging and minimizing their electricity costs. The common practice is to charge immediately after plugging in and use more electricity than necessary. Changing this can increase the EV’s flexibility potential and reduce electricity costs. Our extended electricity cost optimization model systematically examines how different changes to this practice influence electricity costs. Based on the Prospect Theory and substantiated by empirical data, it captures EV users’ tradeoff between relinquishing control and reducing charging costs. Lowering the need to control charging results in disproportionally large savings in electricity costs. This finding incentivizes EV-users to relinquish even more control of charging. We analyzed changes to two charging settings that express the need for control. We found that changing only one setting offsets the other and reduces its positive effect on cost savings. Behavioral aspects, such as rebound effects and inertia that are widely documented in the literature, support this finding and underline the fit of our model extension to capture different charging behaviors. Our findings suggest that service providers should convince EV-users to relinquish control of both settings.

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The potential of households to adapt their energy use to the conditions of the energy system remains largely untapped due to shortcomings in consumer governance (i.e., the organization of household energy use). A lack of price signals and services leads to uncoordinated household energy use. Various proposals exist for updating consumer governance (e.g., virtual power plants, variable tariffs, energy communities). A research gap arises from the fact that a single governance design cannot meet all household needs and that the priorities of household needs are ambiguous.

The empirical research in this dissertation demonstrates that a governance design should focus on enabling households to achieve energy cost savings, convincing them to participate by safeguarding their control needs and keeping them involved by limiting their operational burden. These priorities speak for virtual power plants as consumer governance design. If intermediaries could anticipate latent, upcoming household needs in the design, make tradeoffs transparent for households, and create dedicated points for decision-making, then they would support households in making more informed decisions and taking on an active role in the energy system.@en

Since heating-related energy consumption is one of the main sources of greenhouse gas emissions and accounts for a large part of domestic energy use in Europe, reducing heating-related energy consumption has great potential to reduce Europe’s greenhouse gas emissions. This study examines which factors determine people's intention to decrease heating-related energy usage, specifically lowering the temperature in winter. It was part of a larger European project focused on promoting energy reduction. This study presents a smaller-scale model tested among 363 individuals from five pilot countries, i.e., Belgium (n = 58), Croatia (n = 82), Germany (n = 105), Greece (n = 33), and Portugal (n = 85). We applied three robust theoretical frameworks: the Theory of Planned Behaviour, the Value Belief Norm Theory, and the Prototype Willingness Model. We conducted a confirmatory factor analysis to ensure construct validity, followed by a structural equation model. Our findings suggest that willingness (from the Prototype Willingness Model) is the most important predictor in explaining someone’s intention to reduce heating-related energy consumption. Additionally, perceived behavioural control, subjective norms, and attitudes (part of Theory of Planned Behaviour) also play an important role in predicting the intention to reduce energy consumption. Lastly, personal moral norms (from the Value Belief Norm Theory) have a significant impact, but their effect is moderate compared to the other predictors.

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In this paper, we report evidence collected in the context of the Horizon 2020 NUDGE project about the effectiveness of digital tools such as smartphone apps and web portals to realize nudging interventions towards different energy efficiency goals: from the reduction of heating energy and electricity to the increase of self-consumption in energy prosumer households. We analyse recorded events from the interaction of participants with those tools in the context of three different pilot experiments. We first assess the level of end user engagement with the apps and the portal, counting the number of distinct days that they interact with them. We find it to be highly heterogeneous, with up to 25% of participants in the Greek pilot and 12% in the Portuguese pilot not using the mobile app at all, and the rest forming three distinct groups of low, medium and high engagement. The interaction with the apps almost always lasts fractions of a minute and involves accessing a few app screens. We next turn to the actual users’ exposure to the nudging features of the digital tools to find out that high percentages of users (up to 50%) exhibit zero or very occasional exposure to the app screens that implement nudges. The mobile app users, in particular, can be grouped into four clusters depending on the level of engagement with the app and their exposure to its nudging features. Disappointingly, more than half the pilot participants belong to the cluster combining low engagement with low exposure to nudging. Combining these data with self-statements of participants in post-intervention surveys, we find no significant correlation between the level of nudging exposure and the (self-stated) motivation/ intentions to save energy.and communication emerged as one of the most prominent factors affecting EERs' acceptance. The paper analysed the online information sources based on readability, credibility, and interactivity, focusing on accessibility and the ability to generate tailor-made suggestions. The analysis revealed that the online information sources are disorganised and dispersed. The online platforms rarely provide information on prior case studies and more on financial subsidies, guidelines, and EER benefits. Lastly, we discussed the main barriers and potential solutions for these challenges.@en

Smart metering and home energy management systems (HEMS) support households with roof-top photovoltaic (PV) to optimize self-consumption. These HEMS can convey subtle guidance for consumption shifts that address intuitive consumption routines. However, the efficacy of the guidance depends on the regulation of self-consumption. This presentation provides experimental evidence on the interplay between both for the case of Croatia, where households that produce more electricity than they consume over the year are automatically re-classified as renewable traders and have additional administrative duties, as well as less favorable tax treatment. This creates perverse incentives to reduce PV generation or increase energy consumption. We document strong behavioral reactions within a real-life field experiment, which was conducted as part of the larger Horizon 2020 project NUDGE. The project collected both survey and smart meter data, which allows for a comprehensive picture of the behavioral reaction. According to the survey wave before the end of the year, almost half of the participants considered curtailing their PV output. According to the smart meter data, a sizable share did indeed take action by shutting down production or by powering additional devices to reduce the surplus near the end of the calendar year. In the final survey wave, prosumers provide ex-post insights on the specific measures taken to reduce surplus. Finally, we discuss insights from the experiment regarding the transparency and control offered by the HEMS, as well as how this can influence household behavior regarding the regulatory framework.@en

Reducing heating-related energy consumption is vital in Europe, where it accounts for a significant portion of domestic energy usage. We studied the factors that influence reduced heating-related consumption by using three theoretical frameworks: the Theory of Planned Behaviour, the Value Belief Norm theory, and the Prototype Willingness Model. Our sample consisted of 3098 people from 29 European countries. We conducted a confirmatory factor analysis to verify whether our observed variables measure our latent factors, followed by a structural equation model that incorporated these three behavioural models. We find that perceived behavioural control, subjective norms and attitudes (as part of the Theory of Planned Behaviour) are significant predictors of intent to reduce consumption. However, perceived behavioural control was not statistically significantly associated with behaviour. Environmental concern had a more significant influence on attitudes towards energy reduction than bill consciousness. Attitude was additionally significantly associated with fear of losing comfort and energy knowledge. Moreover, personal moral norms (as part of Value Belief Norm Theory) and willingness (as part of the Prototype Willingness Model) contributed to explaining the intent to reduce consumption, while willingness was also associated with behaviour.@en

Platforms facilitate the participation of households and their energy assets in the energy system. Platform services are considered attractive for households if the energy cost savings exceed the transaction cost of the service. We conceptualize different platform architecture, quantify their transaction cost and compare it to potential energy cost savings from the literature. The design of its communication infrastructure especially influences the attractiveness of the platform architecture for two reasons. First, its other cost, particularly the platform core, accounts only for a minor cost share. Second, the grey and scientific literature discusses multiple communication infrastructure designs referring to smart metering. For the German case, two key design options, the certified and regulated advanced metering infrastructure and the agile Internet of Things based communication are combined into a third option to create a fully functional and certified infrastructure. This is the most attractive option for households deploying multiple flexibility sources or one large and predominantly controllable one (such as a heat pump). @en

Household electricity use has an increasing impact on the overall energy system. Numerous proposals have been made to support households to consume electricity in a system-friendlier manner. By breaking these proposals down into functions and how they are performed, this paper identifies four distinctive governance designs: energy communities, variable electricity tariffs, local energy markets and virtual power plants. None covers all the functions required and each addresses different trade-offs that households face. Energy communities focus on investing in energy assets, while the others target the operation of households’ assets, including demand response. Virtual power plants attract profit-oriented consumers, while the others primarily target normative consumers.@en

In order to design interventions in energy systems, it is key to combine existing models and simulations. As the interplay of different steps along the energy value chain, various actors and regional scopes makes it difficult for one model or model owner to cover the entire complexity of the system, the usage of present resources instead of creating new ones is a consequential approach to tackle todays and tomorrows challenges. Identifing suitable models, combining them and critically analysing their outcomes are essential skills in this context. This is taught in the course “Design of Integrated Energy Systems” at TU Delft. During the course, groups of students define their own design problem they want to adress, develop a modelling strategy for it and translate it with the existing models and simulations. A range of existing models from students themselves, from researchers and from the energy industry are provided. Self-reflection, peer-review, the academic debate on modelling and feedback by the teachers after presenting preliminary results are key elements for stimulating the progress of the group work. Both students and model owners have expressed their enthusiasm for this approach, the students have learned a lot from this confrontation with reality, the model ownens gained valuable insight from the fresh eye that the students could deliver on their modelling practice.@en