Investigating the usability and utility of tangible modelling of socio-technical architectures

Socio-technical models are models that represent social as well as technical elements of the modeling subject, where the technical part consists of both physical and digital elements. Examples are enterprise models and models of the target of assessment used in risk assessment. Constructing and validating these models often implies a challenging task of extracting and integrating information from a multitude of stakeholders which are rarely modelling experts and don’t usually have the time or desire to engage in modelling activities.\ud We investigate a promising approach to overcome this challenge by using physical tokens to represent the model. We call the resulting models tangible models.\ud In this paper we illustrate this idea by creating a tangible representations of a socio-technical modelling language used in Risk Assessment and provide an initial validation of the relative usability and utility of tangible versus abstract modelling by an experiment and a focus group, respectively. We discuss possible psychological and social mechanisms that could explain the enhanced usability and utility of tangible modelling approaches for domain experts. Finally, we discuss the generalizability of this approach to other languages and modelling purposes

Towards Improving Resilience of Smart Urban Electricity Networks by Interactively Assessing Potential Microgrids

When a city adds a renewable generation to improve its carbon footprint, this step towards a greener city can be a step towards a smarter city. Strategical positioning of new urban electricity components makes the city more resilient to electricity outages. Money and resilience are two conflicting goals in this case. In case of blackouts, renewable generation, other than distributed combustion generations, can serve critical demand to essential city nodes, such as hospitals, water purification facilities, and police stations. Not the last, the city level stakeholders might be interested in envisioning monetary saving related to introducing a renewable. To provide decision makers with resilience and monetary information, it is needed to analyze the impact of introducing the renewable into the grid. This paper introduces a novel tool suitable for this purpose and reports on the validation efforts. The outcomes indicate that predicted outcomes of two alternative points of introducing renewables into the grid can be analyzed with the help of the tool and ultimately be meaningfully compared

Peak load reduction of multiple water heaters: Respecting consumer comfort and money savings

Demand Response programs can allow residential electricity consumers to cut their energy bills. However, in case of contingencies in the energy system when the guaranteed peak load reduction is needed, comfort of consumers can be significantly deteriorated and they can choose to opt out. This paper investigates the possibility of peak load reduction and yet highly respecting consumers' comfort by coordinating a group of electric tank water heaters. The proposed peak shaving mechanism accounts for interests of both utility companies and their customers. It employs two optimization models tailored to the needs of both sides to optimally schedule individual water heaters. The suggested Simulation results show the potential of the proposed mechanism to provide the guaranteed peak load reduction thus contributing to the stability of the electrical grid, while transparent balancing between comfort-money and comfort-energy incorporated in the control scheme is of interest and use to green consumers

Load shifting of domestic water heaters under double price tariffs: Bringing together money savings and comfort

Demand Side Management (DSM) programs can offer residential electricity consumers opportunities to cut their energy bills. However, if such programs significantly downgrade comfort of consumers, they can choose to opt them out. This impedes the DSM implementation in practice and declines the efficiency of DSM in overall. Finding ways how consumers can reduce their money expenses with least impact to their comfort is thus desirable. This paper focuses on tank electric water heaters (WHs) under double-price tariffs as a case of energy storage devices under simplified variable pricing. We investigate whether or not the WH load shifting can bring money savings while maintaining the user comfort based on the introduced expenses-comfort balancing approach. The proposed approach is based on daynight energy rates and the energy-comfort model suggested earlier. The refined energy model constitutes the first contribution of this paper. As the second contribution, we reformulate the energy-comfort balancing problem into the problem of ’expenses comfort balancing’. By simulating diverse hot water usage we show that the proposed mechanism can enable monetary savings without significant drop of comfort. Specifically, the customers can reach up to 20 percent of daily money savings compared to the regular operation of the heater during weekdays. The reported research can be of interest to utilities that focus on improving consumer uptake of DSM

Throw in the i-Drone

Although many consider drones to be toys, multiple industries, such as the agriculture and mining industry, already know what advantages professional Unmanned Aerial Vehicles (UAVs) can offer. However, many companies in the construction industry do not seem to be familiar yet with the possible advantages of UAVs for their projects. In our 3TU Lighthouse project “Throw in the I-drone” we, the University of Twente, Delft University of Technology, and BeemFlights, would like to make the construction industry aware of the possibilities UAVs have by demonstrating possible usages, by providing a protocol on how to use them and by simplifying the interpretation of data collecte

An information fusion approach for filtering GNSS data sets collected during construction operations

Global Navigation Satellite Systems (GNSS) are widely used to document the on- and off-site trajectories of construction equipment. Before analyzing the collected data for better understanding and improving construction operations, the data need to be freed from outliers. Eliminating outliers is challenging. While manually identifying outliers is a time-consuming and error-prone process, automatic filtering is exposed to false positives errors, which can lead to eliminating accurate trajectory segments. This paper addresses this issue by proposing a hybrid filtering method, which integrates experts’ decisions. The decisions are operationalized as parameters to search for next outliers and are based on visualization of sensor readings and the human-generated notes that describe specifics of the construction project. A specialized open-source software prototype was developed and applied by the authors to illustrate the proposed approach. The software was utilized to filter outliers in sensor readings collected during earthmoving and asphalt paving projects that involved five different types of common construction equipmen