This paper highlights the use of State Space Grids (SSGs) for studying real-time classroom discourse in an intervention targeting professional development. State Space Grid analysis is both a powerful way to visualise patterns in interactional data, and a starting point for further quantitative analysis. In the present study SSGs were used to explore patterns in teacher–student interactions. The study shows the importance of using micro-level time-serial data and illustrates how change in interactions during and after an intervention can be studied. SSG analysis was applied to study interaction in terms of the coupling of a teacher and a student variable: autonomy support and musical creativity. Video data from 40 music lessons of five teachers and their classes was used as input for plotting teacher–student interactions in SSGs, consisting of two dimensions. SSGs allow visualising change in the situation of interactions in the grid and identifying change in patterns to different grid areas. The findings show how interactions tended to settle in areas representing more productive interaction for all but one class. We discuss the benefits of using SSGs in intervention studies and the implications for educational practice and research of using this time-serial approach.
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In the Netherlands, energy cooperatives are increasingly active in the production of renewable energy. Many cooperatives have concrete plans to invest in energy projects, such as solar fields and wind turbines. Unfortunately, in the coming years there will hardly be any room for such projects in the electricity grid. In their quest to help solve this predicament, energy cooperatives develop new and innovative energy services, for example delivering grid services to distribution system operators (DSOs). However, in this endeavor they encounter legal as well as economic obstacles.
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In this research, the experiences and behaviors of end-users in a smart grid project are explored. In PowerMatching City, the leading Dutch smart grid project, 40 households were equipped with various decentralized energy sources (PV and microCHP), hybrid heat pumps, smart appliances, smart meters and an in-home display. Stabilization and optimization of the network was realized by trading energy on the market. To reduce peak loads on the smart grid, several types of demand side management were tested. Households received feedback on their energy use either based on costs, or on the percentage of consumed energy that had been produced locally. Furthermore, devices could be controlled automatically, smartly or manually to optimize the energy use of the households. Results from quantitative and qualitative research showed that: (1) feedback on costs reduction is valued most; (2) end-users preferred to consume self-produced energy (this may even be the case when, from a cost or sustainability perspective, it is not the most efficient strategy to follow); (3) automatic and smart control are most popular, but manually controlling appliances is more rewarding; (4) experiences and behaviors of end-users depended on trust between community members, and on trust in both technology (ICT infrastructure and connected appliances) and the participating parties.
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Battery energy storage (BES) can provide many grid services, such as power flow management to reduce distribution grid overloading. It is desirable to minimise BES storage capacities to reduce investment costs. However, it is not always clear how battery sizing is affected by battery siting and power flow simultaneity (PFS). This paper describes a method to compare the battery capacity required to provide grid services for different battery siting configurations and variable PFSs. The method was implemented by modelling a standard test grid with artificial power flow patterns and different battery siting configurations. The storage capacity of each configuration was minimised to determine how these variables affect the minimum storage capacity required to maintain power flows below a given threshold. In this case, a battery located at the transformer required 10–20% more capacity than a battery located centrally on the grid, or several batteries distributed throughout the grid, depending on PFS. The differences in capacity requirements were largely attributed to the ability of a BES configuration to mitigate network losses. The method presented in this paper can be used to compare BES capacity requirements for different battery siting configurations, power flow patterns, grid services, and grid characteristics.
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Author supplied: Abstract—The growing importance and impact of new technologies are changing many industries. This effect is especially noticeable in the manufacturing industry. This paper explores a practical implementation of a hybrid architecture for the newest generation of manufacturing systems. The papers starts with a proposition that envisions reconfigurable systems that work together autonomously to create Manufacturing as a Service (MaaS). It introduces a number of problems in this area and shows the requirements for an architecture that can be the main research platform to solve a number of these problems, including the need for safe and flexible system behaviour and the ability to reconfigure with limited interference to other systems within the manufacturing environment. The paper highlights the infrastructure and architecture itself that can support the requirements to solve the mentioned problems in the future. A concept system named Grid Manufacturing is then introduced that shows both the hardware and software systems to handle the challenges. The paper then moves towards the design of the architecture and introduces all systems involved, including the specific hardware platforms that will be controlled by the software platform called REXOS (Reconfigurable EQuipletS Operating System). The design choices are provided that show why it has become a hybrid platform that uses Java Agent Development Framework (JADE) and Robot Operating System (ROS). Finally, to validate REXOS, the performance is measured and discussed, which shows that REXOS can be used as a practical basis for more specific research for robust autonomous reconfigurable systems and application in industry 4.0. This paper shows practical examples of how to successfully combine several technologies that are meant to lead to a faster adoption and a better business case for autonomous and reconfigurable systems in industry.
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Acknowledging the knowledge gaps and novel paradigms outlined above within both coaching research and practice, the PhD research aims to investigate how need-supportive coaching—rooted in Self-Determination Theory (SDT)—effectively fulfils the satisfaction of beginning teachers’ basic psychological needs (BPNs) and autonomous motivation in pursuing their coaching goals within dyadic coaching relationships. To systematically explore this overarching objective, this PhD project and thesis adopt a structured, four-step approach, where each step investigates specific and complementary aspects of the coaching process. Collectively, these steps provide a comprehensive examination of how and under what conditions BPN-supportive coaching facilitates optimal motivational outcomes, enriching our understanding of the dynamic processes that shape coaching effectiveness among beginning teachers. Specifically, four research questions systematically guide the four research steps:1. What is the current state of empirical evidence linking BPN support, BPN satisfaction, and autonomous motivation within coach-coachee relationships?2. How do perceptual distances between coaches’ and coachees’ perceptions regarding BPN support relate to the coachees’ BPN satisfaction?3. How do coaches’ and coachees’ BPN satisfaction mutually predict autonomous motivation toward shared goals in their dyadic relationships?4. How do coaches and coachees dynamically co-regulate BPN interactions in real-time dyadic coaching conversations?Chapter 1 outlined a four-step empirical approach across Chapters 2 to 5 to understand BPN-supportive coaching. Chapter 2 meta-analysed the extant literature guided by a circular framework connecting BPN support, BPN satisfaction, and autonomous motivation for both parties. The results revealed that previous studies predominantly used individual-level data, neglecting the dynamic, reciprocal interactions in coaching. Chapter 3 investigated perceptual distance between coaches and coachees regarding BPN support using polynomial regression and response surface analysis. Results indicated that coachees reported greater BPN satisfaction when perceptions were closely aligned. Chapter 4 adopted the Actor-Partner Interdependence Model to examine how both parties’ BPN satisfaction is associated with their own and each other’s autonomous motivation. We found a positive unidirectional association between coachees’ relatedness satisfaction and coaches’ autonomous motivation and bidirectional associations for autonomy satisfaction. Chapter 5 employed State Space Grid analyses to capture the moment-to-moment co-regulation of autonomy in coach-coachee dyads. Results revealed recurrent patterns of predominant functional co-regulation (e.g., autonomy support met with proactive autonomy expression), and occasional dysfunctional co-regulation (e.g., evaluative feedback met with disengagement). Temporal evolvement in autonomy co-regulation was identified across coaching sessions in response to changing goals. Chapter 6 synthesised the contributions of the thesis. Collectively, BPN-supportive coaching can be viewed as a context-sensitive, interdependent, co-regulatory, and dynamic process, and we provided guidance for adaptive and relationally grounded coaching practices.
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Recent advancements in mobile sensing and wearable technologies create new opportunities to improve our understanding of how people experience their environment. This understanding can inform urban design decisions. Currently, an important urban design issue is the adaptation of infrastructure to increasing cycle and e-bike use. Using data collected from 12 cyclists on a cycle highway between two municipalities in The Netherlands, we coupled location and wearable emotion data at a high spatiotemporal resolution to model and examine relationships between cyclists' emotional arousal (operationalized as skin conductance responses) and visual stimuli from the environment (operationalized as extent of visible land cover type). We specifically took a within-participants multilevel modeling approach to determine relationships between different types of viewable land cover area and emotional arousal, while controlling for speed, direction, distance to roads, and directional change. Surprisingly, our model suggests ride segments with views of larger natural, recreational, agricultural, and forested areas were more emotionally arousing for participants. Conversely, segments with views of larger developed areas were less arousing. The presented methodological framework, spatial-emotional analyses, and findings from multilevel modeling provide new opportunities for spatial, data-driven approaches to portable sensing and urban planning research. Furthermore, our findings have implications for design of infrastructure to optimize cycling experiences.
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This report focuses on the feasibility of the power-to-ammonia concept. Power-to-ammonia uses produced excess renewable electricity to electrolyze water, and then to react the obtained hydrogen with nitrogen, which is obtained through air separation, to produce ammonia. This process may be used as a “balancing load” to consume excess electricity on the grid and maintain grid stability. The product, ammonia, plays the role of a chemical storage option for excess renewable energy. This excess energy in the form of ammonia can be stored for long periods of time using mature technologies and an existing global infrastructure, and can further be used either as a fuel or a chemical commodity. Ammonia has a higher energy density than hydrogen; it is easier to store and transport than hydrogen, and it is much easier to liquefy than methane, and offers an energy chain with low carbon emissions.The objective of this study is to analyze technical, institutional and economic aspects of power-to-ammonia and the usage of ammonia as a flexible energy carrier.
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This is a review of the literature on community energy. We analyze more than 250 studies that appeared in the academic literature in the period 1997-2018. We investigate the timing regarding the appearance of these studies, the geographical orientation of the research, and the journals in which the articles appeared. We also analyse the keywords used to identify the research. Further, we relate the articles to the theoretical perspectives employed. We also analyse keywords used by the authors in relation to the particular approaches employed and reflect on the country specifics of the case studies. We find that the majority of studies on community energy did appear in the last couple of years. Especially the UK, US, Germany and the Netherlands are being investigated. Energy Policy published most of the studies. Different theoretical perspectives study community energy, especially Governance, Sociology, Economics, Planning, Technology, and Transition. We conclude that the study of community energy is still in its infancy as there is little commonality in the terminology and key concepts used. Studying community energy requires further improvement in order to better integrate the different theoretical perspectives and to ground policy decisions.
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