Zoekresultaten

Project Panorama - vistas on validated information

Urban Innovation Systems

Introduction: There are good reasons to study urban innovation from a systemic perspective. A key finding in innovation research is that organizations rarely innovate in isolation, but in interaction with clients, competitors, suppliers, and other organizations. A system perspective is useful in understanding and analyzing these interactions. Cities and urban regions are increasingly recognized as key milieus in which these interactions occur. The urban innovation system approach conceptualizes the city or urban region as a context in which innovations emerge from complex interactions between urban actors—firms, citizens, governments, knowledge institutes— in a particular institutional setting. The systemic view of innovation departs from traditional linear models that depict innovation as a staged process that starts with (basic) scientific research and ends with commercialization by companies. Innovation processes are much more complex and diverse, influenced by multiple actors that interact in networks with feedback loops, and involving many types of knowledge beyond scientific knowledge. Urban innovation systems are nested in innovation systems on other spatial levels—regional, national, international. Studies on urban innovation systems seek to explain how innovations emerge in an urban context, why urban regions differ in their innovative performance, and also address questions on the governance and management of such systems. Studies in this field draw from a variety of disciplines including economic geography, urban and regional economics, political sciences, innovation studies, social sciences, and urban planning.

Cultivating Cooperative Relationships

The methodology of biomimicry design thinking is based on and builds upon the overarching patterns that all life abides by. “Cultivating cooperative relationships” within an ecosystem is one such pattern we as humans can learn from to nurture our own mutualistic and symbiotic relationships. While form and process translations from biology to design have proven accessible by students learning biomimicry, the realm of translating biological functions in a systematic approach has proven to be more difficult. This study examines how higher education students can approach the gap that many companies in transition are struggling with today; that of thinking within the closed loops of their own ecosystem, to do good without damaging the system itself. Design students should be able to assess and advise on product design choices within such systems after graduation. We know when tackling a design challenge, teams have difficulties sifting through the mass of information they encounter, and many obstacles are encountered by students and their professional clients when trying to implement systems thinking into their design process. While biomimicry offers guidelines and methodology, there is insufficient research on complex, systems-level problem solving that systems thinking biomimicry requires. This study looks at factors found in course exercises, through student surveys and interviews that helped (novice) professionals initiate systems thinking methods as part of their strategy. The steps found in this research show characteristics from student responses and matching educational steps which enabled them to develop their own approach to challenges in a systems thinking manner. Experiences from the 2022 cohort of the semester “Design with Nature” within the Industrial Design Engineering program at The Hague University of Applied Sciences in the Netherlands have shown that the mixing and matching of connected biological design strategies to understand integrating functions and relationships within a human system is a promising first step. Stevens LL, Whitehead C, Singhal A. Cultivating Cooperative Relationships: Identifying Learning Gaps When Teaching Students Systems Thinking Biomimicry. Biomimetics. 2022; 7(4):184. https://doi.org/10.3390/biomimetics7040184

Energy storage label

This report describes the creation and use of a database for energy storage technologies which was developed in conjunction with Netbeheer Nederland and the Hanze University of Applied Sciences. This database can be used to make comparisons between a selection of storage technologies and will provide a method for ranking energy storage technology suitability based on the desired application requirements. In addition, this document describes the creation of the energy storage label which contains detailed characteristics for specific storage systems. The layout of the storage labels enables the analysis of different storage technologies in a comprehensive, understandable and comparative manner. A sampling of storage technology labels are stored in an excel spreadsheet and are also compiled in Appendix I of this report; the storage technologies represented here were found to be well suited to enable flexibility in energy supply and to potentially provide support for renewable energy integration [37] [36]. The data in the labels is presented on a series of graphs to allow comparisons of the technologies. Finally, the use and limitations of energy storage technologies are discussed. The results of this research can be used to support the Dutch enewable Energy Transition by providing important information regarding energy storage in both technically detailed and general terms. This information can be useful for energy market parties in order to analyze the role of storage in future energy scenarios and to develop appropriate strategies to ensure energy supply.

Systems Thinking, Mapping and Change in Food and Agriculture

Societal actors across scales and geographies increasingly demand visual applications of systems thinking – the process of understanding and changing the reality of a system by considering its whole set of interdependencies – to address complex problems affecting food and agriculture. Yet, despite the wide offer of systems mapping tools, there is still little guidance for managers, policy-makers, civil society and changemakers in food and agriculture on how to choose, combine and use these tools on the basis of a sufficiently deep understanding of socio-ecological systems. Unfortunately, actors seeking to address complex problems with inadequate understandings of systems often have limited influence on the socio-ecological systems they inhabit, and sometimes even generate unintended negative consequences. Hence, we first review, discuss and exemplify seven key features of systems that should be – but rarely have been – incorporated in strategic decisions in the agri-food sector: interdependency, level-multiplicity, dynamism, path dependency, self-organization, non-linearity and complex causality. Second, on the basis of these features, we propose a collective process to systems mapping that grounds on the notion that the configuration of problems (i.e., how multiple issues entangle with each other) and the configuration of actors (i.e., how multiple actors relate to each other and share resources) represent two sides of the same coin. Third, we provide implications for societal actors - including decision-makers, trainers and facilitators - using systems mapping to trigger or accelerate systems change in five purposive ways: targeting multiple goals; generating ripple effects; mitigating unintended consequences; tackling systemic constraints, and collaborating with unconventional partners.

SynergyS: Multi-commodity energy systems

The increasing share of renewable production like wind and PV poses new challenges to our energy system. The intermittent behavior and lack of controllability on these sources requires flexibility measures like storage and conversion. Production, consumption, transportation, storage and conversion systems become more intertwined. The increasing complexity of the system requires new control strategies to fulfill existing requirements.The SynergyS project addresses the main question how to operate increasingly complex energy systems in a controllable, robust, safe, affordable, and reliable way. Goal of the project is to develop and test a smart control system for a multi-commodity energy system (MCES), with electricity, hydrogen and heat. In scope are an industrial cluster (Chemistry Park Delfzijl) and a residential cluster (Leeuwarden) and their mutual interaction. Results are experimentally tested in two real-life demo-sites scale models: Centre of Expertise Energy (EnTranCe) and The Green Village (TU Delft) represent respectively the industrial and residential cluster.The result will be a market-driven control system to operate a multi-commodity energy system, integrating the industrial and residential cluster. The experimental setup is a combination of physical demo-site assets complemented with (digital) asset models. Experimental validation is based on a demo-scenario including real time data, simulated data and several stress tests.In this session we’ll elaborate more on the project and present (preliminary) results on the testing criteria, scenarios and experimental setup.