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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An important performance determinant in wheelchair sports is the power exchanged between the athletewheelchair combination and the environment, in short, mechanical power. Inertial measurement units (IMUs) might be used to estimate the exchanged mechanical power during wheelchair sports practice. However, to validly apply IMUs for mechanical power assessment in wheelchair sports, a well-founded and unambiguous theoretical framework is required that follows the dynamics of manual wheelchair propulsion. Therefore, this research has two goals. First, to present a theoretical framework that supports the use of IMUs to estimate power output via power balance equations. Second, to demonstrate the use of the IMU-based power estimates during wheelchair propulsion based on experimental data. Mechanical power during straight-line wheelchair propulsion on a treadmill was estimated using a wheel mounted IMU and was subsequently compared to optical motion capture data serving as a reference. IMU-based power was calculated from rolling resistance (estimated from drag tests) and change in kinetic energy (estimated using wheelchair velocity and wheelchair acceleration). The results reveal no significant difference between reference power values and the proposed IMU-based power (1.8% mean difference, N.S.). As the estimated rolling resistance shows a 0.9–1.7% underestimation, over time, IMU-based power will be slightly underestimated as well. To conclude, the theoretical framework and the resulting IMU model seems to provide acceptable estimates of mechanical power during straight-line wheelchair propulsion in wheelchair (sports) practice, and it is an important first step towards feasible power estimations in all wheelchair sports situations.
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A major challenge for disaster scholars and policymakers is to understand the power dimension in response networks, particularly relating to collaboration and coordination. We propose a conceptual framework to study interests and negotiations in and between various civic and professional, response networks drawing on the concepts of “programming” and “switching” proposed by Manuel Castells in his work on the network society. Programming in disaster response refers to the ability to constitute response networks and to program/reprogram them in terms of the goals assigned to the network. Switching is the ability to connect different net-works by sharing common goals and combining resources. We employ these concepts to understand how the US Federal Emergency Management Agency organized its response in the aftermath of Hurricanes Katrina and Sandy. Our conceptual framework can be used both by disaster scholars and policymakers to understand how networked power is constructed and utilized.
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In wheelchair rugby (WR) athletes with tetraplegia, wheelchair performance may be impaired due to (partial) loss of innervation of upper extremity and trunk muscles, and low blood pressure (BP). The objective was to assess the effects of electrical stimulation (ES)-induced co-contraction of trunk muscles on trunk stability, arm force/power, BP, and WR performance.
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Purpose: The aims of this study were to investigate how a variety of research methods is commonly employed to study technology and practitioner cognition. User-interface issues with infusion pumps were selected as a case because of its relevance to patient safety. Methods: Starting from a Cognitive Systems Engineering perspective, we developed an Impact Flow Diagram showing the relationship of computer technology, cognition, practitioner behavior, and system failure in the area of medical infusion devices. We subsequently conducted a systematic literature review on user-interface issues with infusion pumps, categorized the studies in terms of methods employed, and noted the usability problems found with particular methods. Next, we assigned usability problems and related methods to the levels in the Impact Flow Diagram. Results: Most study methods used to find user interface issues with infusion pumps focused on observable behavior rather than on how artifacts shape cognition and collaboration. A concerted and theorydriven application of these methods when testing infusion pumps is lacking in the literature. Detailed analysis of one case study provided an illustration of how to apply the Impact Flow Diagram, as well as how the scope of analysis may be broadened to include organizational and regulatory factors. Conclusion: Research methods to uncover use problems with technology may be used in many ways, with many different foci. We advocate the adoption of an Impact Flow Diagram perspective rather than merely focusing on usability issues in isolation. Truly advancing patient safety requires the systematic adoption of a systems perspective viewing people and technology as an ensemble, also in the design of medical device technology.
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The built environment requires energy-flexible buildings to reduce energy peak loads and to maximize the use of (decentralized) renewable energy sources. The challenge is to arrive at smart control strategies that respond to the increasing variations in both the energy demand as well as the variable energy supply. This enables grid integration in existing energy networks with limited capacity and maximises use of decentralized sustainable generation. Buildings can play a key role in the optimization of the grid capacity by applying demand-side management control. To adjust the grid energy demand profile of a building without compromising the user requirements, the building should acquire some energy flexibility capacity. The main ambition of the Brains for Buildings Work Package 2 is to develop smart control strategies that use the operational flexibility of non-residential buildings to minimize energy costs, reduce emissions and avoid spikes in power network load, without compromising comfort levels. To realise this ambition the following key components will be developed within the B4B WP2: (A) Development of open-source HVAC and electric services models, (B) development of energy demand prediction models and (C) development of flexibility management control models. This report describes the developed first two key components, (A) and (B). This report presents different prediction models covering various building components. The models are from three different types: white box models, grey-box models, and black-box models. Each model developed is presented in a different chapter. The chapters start with the goal of the prediction model, followed by the description of the model and the results obtained when applied to a case study. The models developed are two approaches based on white box models (1) White box models based on Modelica libraries for energy prediction of a building and its components and (2) Hybrid predictive digital twin based on white box building models to predict the dynamic energy response of the building and its components. (3) Using CO₂ monitoring data to derive either ventilation flow rate or occupancy. (4) Prediction of the heating demand of a building. (5) Feedforward neural network model to predict the building energy usage and its uncertainty. (6) Prediction of PV solar production. The first model aims to predict the energy use and energy production pattern of different building configurations with open-source software, OpenModelica, and open-source libraries, IBPSA libraries. The white-box model simulation results are used to produce design and control advice for increasing the building energy flexibility. The use of the libraries for making a model has first been tested in a simple residential unit, and now is being tested in a non-residential unit, the Haagse Hogeschool building. The lessons learned show that it is possible to model a building by making use of a combination of libraries, however the development of the model is very time consuming. The test also highlighted the need for defining standard scenarios to test the energy flexibility and the need for a practical visualization if the simulation results are to be used to give advice about potential increase of the energy flexibility. The goal of the hybrid model, which is based on a white based model for the building and systems and a data driven model for user behaviour, is to predict the energy demand and energy supply of a building. The model's application focuses on the use case of the TNO building at Stieltjesweg in Delft during a summer period, with a specific emphasis on cooling demand. Preliminary analysis shows that the monitoring results of the building behaviour is in line with the simulation results. Currently, development is in progress to improve the model predictions by including the solar shading from surrounding buildings, models of automatic shading devices, and model calibration including the energy use of the chiller. The goal of the third model is to derive recent and current ventilation flow rate over time based on monitoring data on CO₂ concentration and occupancy, as well as deriving recent and current occupancy over time, based on monitoring data on CO₂ concentration and ventilation flow rate. The grey-box model used is based on the GEKKO python tool. The model was tested with the data of 6 Windesheim University of Applied Sciences office rooms. The model had low precision deriving the ventilation flow rate, especially at low CO2 concentration rates. The model had a good precision deriving occupancy from CO₂ concentration and ventilation flow rate. Further research is needed to determine if these findings apply in different situations, such as meeting spaces and classrooms. The goal of the fourth chapter is to compare the working of a simplified white box model and black-box model to predict the heating energy use of a building. The aim is to integrate these prediction models in the energy management system of SME buildings. The two models have been tested with data from a residential unit since at the time of the analysis the data of a SME building was not available. The prediction models developed have a low accuracy and in their current form cannot be integrated in an energy management system. In general, black-box model prediction obtained a higher accuracy than the white box model. The goal of the fifth model is to predict the energy use in a building using a black-box model and measure the uncertainty in the prediction. The black-box model is based on a feed-forward neural network. The model has been tested with the data of two buildings: educational and commercial buildings. The strength of the model is in the ensemble prediction and the realization that uncertainty is intrinsically present in the data as an absolute deviation. Using a rolling window technique, the model can predict energy use and uncertainty, incorporating possible building-use changes. The testing in two different cases demonstrates the applicability of the model for different types of buildings. The goal of the sixth and last model developed is to predict the energy production of PV panels in a building with the use of a black-box model. The choice for developing the model of the PV panels is based on the analysis of the main contributors of the peak energy demand and peak energy delivery in the case of the DWA office building. On a fault free test set, the model meets the requirements for a calibrated model according to the FEMP and ASHRAE criteria for the error metrics. According to the IPMVP criteria the model should be improved further. The results of the performance metrics agree in range with values as found in literature. For accurate peak prediction a year of training data is recommended in the given approach without lagged variables. This report presents the results and lessons learned from implementing white-box, grey-box and black-box models to predict energy use and energy production of buildings or of variables directly related to them. Each of the models has its advantages and disadvantages. Further research in this line is needed to develop the potential of this approach.
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Modern manufacturing has to deal with global competition, in which customers have high purchasing power. Production efficiency and rapid response to customer demand are dominant conditions for enterprises to stay successful. Reconfigurable Manufacturing Systems (RMSs) are designed to have a modular architecture in both mechanical design and control system. The architecture enables change of the machine structure quickly, by adding and removing parts of the system, and by changing the corresponding software programming. It can handle short times to market. This paper presents an ‘Index-Method’ to monitor the reconfiguration of RMS. The method is able to categorise the reconfiguration and related development in seven stages. It focusses specifically on the Independence Axiom. The main goal is to find all relevant parameters to cause interactions, and to decouple them. The solution, aiming to be scientifically vigorous and practically applicable, was applied to a true case; the development of a manufacturing system for an inkjet print head for industrial applications. The realisation of the system required the development of new process technology. The index-method may be considered successful. It has the ability to structure the configuration process of RMSs. The method harmonises well with the industry known V-model.
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In solving systemic design challenges designers co-create with professionals from various fields. In the context of innovation in healthcare practices, this study investigates design abilities that healthcare professionals develop by participating in co-design projects. We conducted a mixed-methods research approach consisting of five retrospective interviews with healthcare researchers involved in co-design projects, and a multiple case study (three cases) on the collaboration between design researchers and healthcare professionals. The three cases all aimed at designing tools for healthcare innovation. The cases differ in the healthcare context and the professionals involved: Paediatric physical therapists in the treatment of babies (0-2 years), supervisors (e.g. in assisted living) of people with intellectual disabilities, and academic researchers in social sciences and design research developing e-health applications for elderly people with early stages of dementia. Literature states that healthcare professionals may be competent in specific abilities related to design, but they are not trained to mode-shift and to use two different ways of working for creativity. We found that the healthcare professionals involved in co-design projects developed design ability over time, and that the research setting was supportive. Based on design abilities that the five healthcare researchers explicated in the interviews as having adopted, we suggest eight mode-shift practices related to design, which we investigated in the cases. Findings of the case-study show that two mode-shift practices related to design and innovation are difficult to adopt for healthcare professionals: Generate and synthesize; and keeping track on overview and details. These two design abilities require more training and/or experience than the other six design abilities that ran smoothly in the cases, if healthcare professionals were facilitated in the process. Healthcare professionals specifically relate two of these practices to design: Collaboration and slow down – sprint. This study discusses these findings by referring to an analogy of kayaking on a wild water river: The collaboration aspect of switching between working in a group and by yourself, like a group of kayakers who collaborate in going down stream a river but peddle by themselves in their own boats; the slowdown and sprint aspect, like kayakers who oversee the river in turning waters and sprint in between, rather than go with the flow in a raft.
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This article traces the emergence of one particular genre of discourse, the genre of "new realism" in the Dutch public debates on multicultural society from the early 1990s till Spring 2002. The focus upon different "genres" implies an interest in the performative power of discourse, i.e. the way in which any discourse, in or by its descriptions of reality, (co)produces that reality. Four distinctive characteristics of "new realism" are detected in three subsequent public debates, culminating in the genre of "hyper-realism", of which the immensely successful and recently murdered politician Pim Fortuyn proved to be the consummate champion. Cet article explique le développement d'un genre particulier de discours, le "nouveau réalisme", au sein du débat public sur la société multiculturelle aux Pays Bas. La période étudidée s'étale du début des années 1990 jusqu'au printemps 2002. L'importance attribuée aux différents "genres" reflète un intérêt pour le pouvoir performatif du discours, notamment la facon dont le discours (co)produit la réalité qu'il décrit. On décèle quatre traits distinctifs du "nouveau réalisme" dans trois débats publics qui débouchent sur le "hyper-réalisme" genre dont Pim Fortuyn, homme politique ayant connu un grand succès et victime récente d'un meurtre,s'était fait le champion attitré.
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This text has become a performance of (affirmative) entrepreneurship. This is done by a set of writing (and methodological) techniques: autoethnography, the triptych of mimesis, poiesis, kinesis and a life journey that forms the base of the chapter. As such, this text challenges some well-known shortcomings of entrepreneurship research such as being enacted by a distant observer/writer, decontextualized accounts of entrepreneurship and disregard of creativity and playfulness. The main contribution of the chapter is methodological, in its broadest sense (Steyaert, 2011): I propose autoethnography as “more than method” for engaging with processes of (affirmative) Entrepreneuring that speak to the increased attention for narrativity and playfulness in entrepreneurship (see for example Hjorth, 2017: Hjorth and Steyaert, 2004: Gartner, 2007; Johannisson, 2011). The autoethnographic story offers an engaging and relevant account of the practice of entrepreneurship and provides rich emic insight into the socio-materiality of lived experience. It also highlights the temporality of entrepreneurship – both in terms of chronos (continuous flow of time) and Kairos (taking advantage of the “right moment”) (Johannisson, 2011). And as I continue performing affirmations, I am curious how you are Entrepreneuring your life – tell me. This is a draft chapter/article. The final version is available in Research Handbook on Entrepreneurial Behavior, Practice and Process edited by William B. Gartner and Bruce T. Teague, published in 2020, Edward Elgar Publishing Ltd https://doi.org/10.4337/9781788114523
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