Search

Climate change intensifies the likelihood of extreme flood events worldwide, amplifying the potential for compound flooding. This evolving scenario represents an escalating risk, emphasizing the urgent need for comprehensive climate change adaptation strategies across society. Vital to effective response are models that evaluate damages, costs, and benefits of adaptation strategies, encompassing non-linearities and feedback between anthropogenic and natural systems. While flood risk modeling has progressed, limitations endure, including inadequate stakeholder representation and indirect risks such as business interruption and diminished tax revenues. To address these gaps, we propose an innovative version of the Climate-economy Regional Agent-Based model that integrates a dynamic, rapidly expanding agglomeration economy populated by interacting households and firms with extreme flood events. Through this approach, feedback loops and cascading effects generated by flood shocks are delineated within a socio-economic system of boundedly-rational agents. By leveraging extensive behavioral data, our model incorporates a risk layering strategy encompassing bottom-up and top-down adaptation, spanning individual risk reduction to insurance. Calibrated to resemble a research-rich coastal megacity in China, our model demonstrates how synergistic adaptation actions at all levels effectively combat the mounting climate threat. Crucially, the integration of localized risk management with top-down approaches offers explicit avenues to address both direct and indirect risks, providing significant insights for constructing climate-resilient societies., Multi Actor Systems, Policy Analysis, System Engineering

The reliance of the petrochemical industry on fossil-based sources will need to be reduced by the introduction of Alternative carbon sources (ACS). Introducing ACS in a petrochemical cluster will require existing processes to be modified or replaced, potentially affecting other chemical processes within the cluster due to existing material and energy interconnections. Therefore, it is important to understand the current level of interconnections, functioning, and performance of the petrochemical cluster before introducing ACS. In this work, a representative cluster model based on the petrochemical cluster of the Port of Rotterdam was developed and considered as a case study. This model was analyzed using complex network analysis and environmental and technical key performance indicators. The selected key performance indicators (KPIs) provide insight into the performance of a petrochemical cluster, while the network properties give an understanding of the exchange of material and energy in an industrial cluster., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Energy and Industry, System Engineering

Bioregenerative life support systems (BLSS) are vital for long-duration and remote space missions to increase mission sustainability. These systems break down human waste materials into nutrients and CO2 for plants and other edible organisms, which in turn provide food, fresh water, and oxygen for astronauts. The central idea is to create a materially closed loop, which can significantly reduce mission mass and volume by cutting down or even eliminating disposable waste. In most BLSS studies only a fraction of the resources, such as food, are provided by the system itself, with the rest taken on board at departure or provided through resupply missions. However, for autonomous long-duration space missions without any possibility of resupply, a BLSS that generates all resources with minimal or no material loss, is essential. The goal of this study is to develop a stoichiometric model of a conceptually fully closed BLSS that provides all the metabolic needs of the crew and organisms. The MELiSSA concept of the European Space Agency is used as reference system, consisting of five interconnected compartments, each inhabited by different types of organisms. A detailed review of publicly available MELiSSA literature from 1989 to 2022 revealed that no existing stoichiometric model met the study’s requirements. Therefore, a new stoichiometric model was developed to describe the cycling of the elements C, H, O, and N through all five MELiSSA compartments and one auxiliary compartment. A compact set of chemical equations with fixed coefficients was established for this purpose. A spreadsheet model simulates the flow of all relevant compounds for a crew of six. By balancing the dimensions of the different compartments, a high degree of closure is attained at steady state, with 12 out of 14 compounds exhibiting zero loss, and oxygen and CO2 displaying only minor losses between iterations. This is the first stoichiometric model of a MELiSSA-inspired BLSS that describes a continuo, System Engineering

Agent-based modelling and simulation (ABMS), whether simple toy models or complex data-driven ones, is regularly applied in various domains to study the system-level patterns arising from individual behaviour and interactions. However, ABMS still faces diverse challenges such as modelling more representative agents or improving computational efficiency. Research shows that machine learning (ML) techniques, when used in ABMS can address such challenges. Yet, the ABMS literature is still marginally leveraging the benefits of ML. One reason is the vastness of the ML domain, which makes it difficult to choose the appropriate ML technique to overcome a specific modelling challenge. This paper aims to bring ML more within reach of the ABMS community. We first conduct a structured literature review to investigate how the ABMS process uses ML techniques. We focus specifically on articles where ML is applied for the structural specifications of models such as agent decision-making and behaviour, rather than just for analysing output data. Given that modelling challenges are mainly linked to the purpose a model aims to serve (e.g., behavioural accuracy is required for predictive models), we frame our analysis within different modelling purposes. Our results show that Reinforcement Learning algorithms may increase the accuracy of behavioural modelling. Moreover, Decision Trees, and Bayesian Networks are common techniques for data pre-processing of agent behaviour. Based on the literature review results, we propose guidelines for purposefully integrating ML in ABMS. We conclude that ML techniques are specifically fit for currently underrepresented modelling purposes of social learning and illustration; they can be used in a transparent and interpretable manner., Energie and Industrie, System Engineering, Applied Sciences

Fast growth of cities decreases the quality of life in these places. In response, Municipalities install policies aiming to improve local livability. While literature suggests social structures to have a defining impact on policy effectiveness, current evaluation metrics are not able to take this into account. This paper presents the Social Neighbourhood model, an agent-based model used to simulate and explore how livability changes in a neighbourhood given various social structures and policies. The model is applied to a neighbourhood in The Hague, Netherlands. The main result of the modelling experiments is that social structures have a very strong influence on whether or not a policy to improve livability is effective. Three hypotheses, concerning this relationship between social structures, livability, and policy interventions are drawn up as a starting point for future research., System Engineering

This paper presents a theoretical framework for a new concept of organizational control, that stimulates organizational change and adaptation. It introduces Participatory Control Systems (PCS) as a distinct type of control based on the complex adaptive system literature. These control systems are fundamentally different from the traditional notion of (management) control. Building on the notion of complex systems and the concept of social learning, PCS increase organizational adaptivity by enabling and facilitating social learning processes that may emerge to transformational change over time. To illustrate the PCS concept in practice, three examples are given in this paper. Moreover, some key implications for internal auditors and suggestions for future research are provided., System Engineering

Cities consume almost 80 percent of world’s energy and account for 60 percent of all the emissions of carbon dioxide and significant amounts of other greenhouse gases (GHG). The ongoing rapid urbanization will further increase GHG emissions of cities. The quantification of the environmental impact generated in cities is an important step to curb the impact. In fact, quantifying the consumption activities taking place inside a city, if differentiated by socioeconomic and demographic groups, can provide important insights for sustainable-consumption policies. However, the lack of high-resolution data related to these activities makes it difficult to quantify urban GHG emissions (as well as other impacts). This paper presents a methodology that can quantify the carbon footprint of households in cities using consumption data from a national or European level, where the resource consumption is linked to socioeconomic attributes of a population. The methodology is applied to analyzing the environmental impact by household resource consumption in the city of The Hague in the Netherlands. The key insights reveal potential intervention areas regarding resource consumption categories and demographic groups that can be targeted to reduce GHG emissions due to consumption-driven activities in the city., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., System Engineering, Policy Analysis

Energy communities are gaining momentum in the context of the energy transition. Given the distributed and collective action nature of energy communities, energy security of these local energy systems is more than just security of supply and related to issues such as affordability and acceptability of energy to members of the community. We build an agent-based model of energy communities to explore their security challenges. The security dimensions we consider are availability, affordability, accessibility and acceptability, which are referred to as the 4As. The results confirmed that there is always a trade-off between all four dimensions and that although it is difficult to achieve a high energy security performance, it is feasible. Results also showed that among factors influencing energy security, the investment of the community plays the biggest role., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Energy and Industry, System Engineering

Industrial Symbiosis Networks (ISNs) consist of firms that exchange residual materials and energy locally, in order to gain economic, environmental and/or social advantages. In practice, ISNs regularly fail when partners leave and the recovery of residual streams ends. Regarding the current societal need for a shift towards sustainability, it is undesirable that ISNs should fail. Failures of ISNs may be caused by actor behaviour that leads to unanticipated economic losses. In this paper, we explore the effect of these behaviours on ISN robustness by using an agent-based model (ABM). The constructed model is based on insights from both literature and participatory modelling in three real-world cases. It simulates the implementation of synergies for local waste exchange and compost production. The Theory of Planned Behaviour (TPB) was used to model agent behaviour in time-dependent bilateral negotiations and synergy evaluation processes. We explored model behaviour with and without TPB logic across a range of possible TPB input variables. The simulation results show how the modelled planned behaviour affects the cash flow outcomes of the social agents and the robustness of the network. The study contributes to the theoretical development of industrial symbiosis research by providing a quantitative model of all ISN implementation stages, in which various behavioural patterns of entrepreneurs are included. It also contributes to practice by offering insights on how network dynamics and robustness outcomes are not only related to context and ISN design, but also to actor behaviour., Energy & Industry, System Engineering, Applied Sciences

The viability of novel network-level circular business models (CBMs) is debated heavily. Many companies are hesitant to implement CBMs in their daily practice, because of the various roles, stakes and opinions and the resulting uncertainties. Testing novel CBMs prior to implementation is needed. Some scholars have used digital simulation models to test elements of business models, but this this has not yet been done systematically for CBMs. To address this knowledge gap, this paper presents a systematic iterative method to explore and improve CBMs prior to actual implementation by means of agent-based modelling and simulation. An agent-based model (ABM) was co-created with case study participants in three Industrial Symbiosis networks. The ABM was used to simulate and explore the viability effects of two CBMs in different scenarios. The simulation results show which CBM in combination with which scenario led to the highest network survival rate and highest value captured. In addition, we were able to explore the influence of design options and establish a design that is correlated to the highest CBM viability. Based on these findings, concrete proposals were made to further improve the CBM design, from company level to network level. This study thus contributes to the development of systematic CBM experimentation methods. The novel approach provided in this work shows that agent-based modelling and simulation is a powerful method to study and improve circular business models prior to implementation., Energy & Industry, System Engineering, Applied Sciences

The viability of novel network-level circular business models (CBMs) is debated heavily. Many companies are hesitant to implement CBMs in their daily practice, because of the various roles, stakes and opinions and the resulting uncertainties. Testing novel CBMs prior to implementation is needed. Some scholars have used digital simulation models to test elements of business models, but this this has not yet been done systematically for CBMs. To address this knowledge gap, this paper presents a systematic iterative method to explore and improve CBMs prior to actual implementation by means of agent-based modelling and simulation. An agent-based model (ABM) was co-created with case study participants in three Industrial Symbiosis networks. The ABM was used to simulate and explore the viability effects of two CBMs in different scenarios. The simulation results show which CBM in combination with which scenario led to the highest network survival rate and highest value captured. In addition, we were able to explore the influence of design options and establish a design that is correlated to the highest CBM viability. Based on these findings, concrete proposals were made to further improve the CBM design, from company level to network level. This study thus contributes to the development of systematic CBM experimentation methods. The novel approach provided in this work shows that agent-based modelling and simulation is a powerful method to study and improve circular business models prior to implementation., Energie and Industrie, System Engineering, Applied Sciences

Industrial Symbiosis Networks (ISNs) consist of firms that exchange residual materials and energy locally, in order to gain economic, environmental and/or social advantages. In practice, ISNs regularly fail when partners leave and the recovery of residual streams ends. Regarding the current societal need for a shift towards sustainability, it is undesirable that ISNs should fail. Failures of ISNs may be caused by actor behaviour that leads to unanticipated economic losses. In this paper, we explore the effect of these behaviours on ISN robustness by using an agent-based model (ABM). The constructed model is based on insights from both literature and participatory modelling in three real-world cases. It simulates the implementation of synergies for local waste exchange and compost production. The Theory of Planned Behaviour (TPB) was used to model agent behaviour in time-dependent bilateral negotiations and synergy evaluation processes. We explored model behaviour with and without TPB logic across a range of possible TPB input variables. The simulation results show how the modelled planned behaviour affects the cash flow outcomes of the social agents and the robustness of the network. The study contributes to the theoretical development of industrial symbiosis research by providing a quantitative model of all ISN implementation stages, in which various behavioural patterns of entrepreneurs are included. It also contributes to practice by offering insights on how network dynamics and robustness outcomes are not only related to context and ISN design, but also to actor behaviour., Energie and Industrie, System Engineering, Applied Sciences

System Engineering, Organisation and Governance

Flood adaptation measures implemented at the household level play an important role in reducing communities' vulnerability. The aim of this study is to enhance the current modelling practices of human-flood interaction to draw new insights for flood risk management (FRM) policy design. The paper presents a coupled agent-based and flood model for the case of Hamburg, Germany, to explore how individual adaptation behaviour is influenced by flood event scenarios, economic incentives and shared and individual strategies. Simulation results show that a unique trajectory of adaptation measures and flood damages emerges from different flood event series. Another finding is that providing subsidies increases the number of coping households in the long run. Households' social network also has a strong influence on their coping behaviour. The paper also highlights the role of simple measures such as adapted furnishings, which do not incur any monetary cost, in reducing households' vulnerability and preventing millions of euros of contents damages. Generally, we demonstrate that coupled agent-based and flood models can potentially be used as decision support tools to examine the role of household adaptation measures in flood risk management. Although the findings of the paper are case-specific, the improved modelling approach shows the potential to be applied in testing policy levers and strategies considering heterogeneous individual behaviours., BT/Environmental Biotechnology, Energy & Industry, System Engineering

The transition process towards renewable energy systems is facing challenges in both fluctuating electricity generation of photovoltaic and wind power as well as socio-economic disruptions. With regard to sector integration, solutions need to be developed, especially for the mobility and the industry sector, because their ad hoc electrification and decarbonization seem to be unfeasible. Power-to-fuel (P2F) technologies may contribute to bridge the gap, as renewable energy can be transferred into hydrogen and hydrocarbon-based synthetic fuels. However, the renewable fuels production is far from economically competitive with conventional fuels. With a newly developed agent-based model, potential developments in the German energy markets were simulated for a horizon of 20 years from 2016 to 2035. The model was constructed through a participatory modeling process with relevant actors and stakeholders in the field. Model findings suggest that adjusted regulatory framework conditions (e.g., exemptions from electricity surtaxes, accurate prices for CO2-certificates, strong start-up subsidies, and drastic emission reduction quotas) are key factors for economically feasible P2F installations and will contribute to its large-scale integration into the German energy system. While plant capacities do not exceed 0.042 GW in a business-as-usual scenarios, the above-mentioned adjustments lead to plant capacities of at least 3.25 GW in 2035 with concurrent reduction in product prices., Energy & Industry, System Engineering

Finding leverage points for sustainability transformation of industrial and infrastructure systems is challenging, given that transformation is emergent from the complex interactions among socio-technical system elements over time within a specific social, technical and geographical context. Participatory multi-modelling, in which modellers and stakeholders collaborate to develop multiple interacting models to support a shared understanding of systems, is a promising approach to support sustainability transformations. The participatory process of modeling can serve as a leverage point by facilitating social learning amongst stakeholders, in which models can function as boundary objects that facilitate dialogue between stakeholders from different social worlds. We propose that participatory multi-modeling allows for the creation of a boundary object ecology, which involves a set of interacting and co-evolving boundary objects emerging throughout the modeling process. To explore this, we analyse the participatory multi-modelling process in the Windmaster project in the Rotterdam Port industrial cluster to understand which design choices were key to the creation of boundary objects. Our analysis shows that two types of design choices were key: design choices that enabled translations between participants, and those between participants and their organisation. We conclude that conceptualising participatory multi-modelling as a process of an evolving boundary object ecology, creating and adapting multiple interacting boundary objects provides a novel perspective that is useful for analysis and design of future participatory multi-modeling processes., System Engineering, Policy Analysis, Energy & Industry

The transition process towards renewable energy systems is facing challenges in both fluctuating electricity generation of photovoltaic and wind power as well as socio-economic disruptions. With regard to sector integration, solutions need to be developed, especially for the mobility and the industry sector, because their ad hoc electrification and decarbonization seem to be unfeasible. Power-to-fuel (P2F) technologies may contribute to bridge the gap, as renewable energy can be transferred into hydrogen and hydrocarbon-based synthetic fuels. However, the renewable fuels production is far from economically competitive with conventional fuels. With a newly developed agent-based model, potential developments in the German energy markets were simulated for a horizon of 20 years from 2016 to 2035. The model was constructed through a participatory modeling process with relevant actors and stakeholders in the field. Model findings suggest that adjusted regulatory framework conditions (e.g., exemptions from electricity surtaxes, accurate prices for CO2-certificates, strong start-up subsidies, and drastic emission reduction quotas) are key factors for economically feasible P2F installations and will contribute to its large-scale integration into the German energy system. While plant capacities do not exceed 0.042 GW in a business-as-usual scenarios, the above-mentioned adjustments lead to plant capacities of at least 3.25 GW in 2035 with concurrent reduction in product prices., Energie and Industrie, System Engineering

System Engineering, Organisation & Governance

Finding leverage points for sustainability transformation of industrial and infrastructure systems is challenging, given that transformation is emergent from the complex interactions among socio-technical system elements over time within a specific social, technical and geographical context. Participatory multi-modelling, in which modellers and stakeholders collaborate to develop multiple interacting models to support a shared understanding of systems, is a promising approach to support sustainability transformations. The participatory process of modeling can serve as a leverage point by facilitating social learning amongst stakeholders, in which models can function as boundary objects that facilitate dialogue between stakeholders from different social worlds. We propose that participatory multi-modeling allows for the creation of a boundary object ecology, which involves a set of interacting and co-evolving boundary objects emerging throughout the modeling process. To explore this, we analyse the participatory multi-modelling process in the Windmaster project in the Rotterdam Port industrial cluster to understand which design choices were key to the creation of boundary objects. Our analysis shows that two types of design choices were key: design choices that enabled translations between participants, and those between participants and their organisation. We conclude that conceptualising participatory multi-modelling as a process of an evolving boundary object ecology, creating and adapting multiple interacting boundary objects provides a novel perspective that is useful for analysis and design of future participatory multi-modeling processes., System Engineering, Policy Analysis, Energie and Industrie

Flood adaptation measures implemented at the household level play an important role in reducing communities' vulnerability. The aim of this study is to enhance the current modelling practices of human-flood interaction to draw new insights for flood risk management (FRM) policy design. The paper presents a coupled agent-based and flood model for the case of Hamburg, Germany, to explore how individual adaptation behaviour is influenced by flood event scenarios, economic incentives and shared and individual strategies. Simulation results show that a unique trajectory of adaptation measures and flood damages emerges from different flood event series. Another finding is that providing subsidies increases the number of coping households in the long run. Households' social network also has a strong influence on their coping behaviour. The paper also highlights the role of simple measures such as adapted furnishings, which do not incur any monetary cost, in reducing households' vulnerability and preventing millions of euros of contents damages. Generally, we demonstrate that coupled agent-based and flood models can potentially be used as decision support tools to examine the role of household adaptation measures in flood risk management. Although the findings of the paper are case-specific, the improved modelling approach shows the potential to be applied in testing policy levers and strategies considering heterogeneous individual behaviours., BT/Environmental Biotechnology, Energie and Industrie, System Engineering

Agent-based modelling and simulation is now accepted as a valuable tool for describing the dynamics of complex socio-technical systems, and for studying complex adaptive systems. This chapter surveys the opportunities and challenges in agent-based models (ABM) for the social dynamics of energy end use. Following an introduction to the methodology of ABM, we discuss the ability of ABM to capture heterogeneous, boundedly rational and imperfectly informed behavioural factors at the individual, household, and neighbourhood levels, including the usage of micro-generation and local storage. We review three archetypal case studies of ABM: energy efficiency in domestic heating, electric vehicle adoption, and energy management in smart grids. We conclude with directions for the future, pointing out the importance of ABM in the context of multidisciplinary studies of energy behaviours., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Energy & Industry, System Engineering, Algorithmics

In this paper, we describe a modelling framework that allows the integration of human and physical components of flood risk. Within this framework, flood risk management is conceptualized as a coupled human-flood system. The human subsystem includes individuals and their behaviour and institutions that shape human-flood interaction. The framework presents a dynamic integration between agent-based models of individuals and institutions and numerical flood models. We demonstrate the framework's modelling application by examining the effects of three institutions in the Caribbean island of Sint Maarten. The case study shows the capabilities of the framework by exploring impacts of existing policies on flood risk reduction. Coupled agent-based-flood models built using the framework are useful to analyse policy options that address flood hazard and communities' vulnerability and exposure to support policy decision making. These models also show how flood risk changes over time in relation to the human dynamics on the urban environment., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Energy & Industry

Disaster risk reduction is a major concern of small island developing states. Measures to reduce risk should not only be based on the magnitude of physical hazard, but also on the exposure and vulnerability of communities. In this article, we examine flood risk management policies in the Caribbean island of Sint Maarten using coupled agent-based and flood models. The agent-based model is used to model actors' behaviour in relation to urban building development and policies that are designed to reduce flood hazard and communities' vulnerability and exposure. The policies considered in the model are a Beach Policy, a Building and Housing Ordinance, a Flood Zoning policy and hazard mitigation structural measures. The flood model is used to simulate coastal and pluvial floods on the island. Agent behaviour such as building new houses and implementing hazard reduction measures affect the flood model as these actions affect the rainfall-runoff process. The flood maps generated from the updated flood model simulations are then used to assess the impact and update agents’ attributes and behaviour. The simulations results show that low-lying areas are populated, which increases the exposure, and the number of vulnerable houses is also high. Hence, out of the four policies, implementing hazard reduction measures is the most important. Reducing the flood hazard by widening existing drainage channels, constructing new ones and building dykes as coastal flood defence would reduce the hazard, hence reducing the number of flooded houses. As it affects all households on the island, the Building and Housing Ordinance is an important policy to reduce vulnerability. In general, the coupled model outputs can be used to inform policy decision making and provide insights to policymakers on the island., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Energy & Industry, System Engineering

Nederland is op weg naar een CO2-neutrale samenleving in 2050. Zo ook het haven industrieel cluster van Rotterdam (HIC). Om dat te bereiken zal de energievoorziening de komende jaren moeten veranderen. Deze verandering heeft een grote impact op de energieinfrastructuur. In het Windmaster project wordt gefocust op de huidige aardgas-,H2- en elektriciteits infrastructuur binnen het HIC. Het plannen van infrastructuur kent lange implementatie- en afschrijvingstermijnen waardoor het voor de infrabeheerders bij wijze van spreken vandaag 2030 is en overmorgen 2050. Gezien de vele onzekerheden rondom de toekomstige energieconsumptie en -productie in het HIC en de rest van Europa vraagt dit om een nieuw investeringsparadigma. Een paradigma dat moet voorkomen dat groene industrie in de toekomst niet gefaciliteerd kan worden. Dat een nieuw investeringsparadigma nodig is, blijkt onder andere uit het feit dat zonneparken in het noorden van het land niet aangesloten kunnen worden op het elektriciteitsnet als gevolg van capaciteitsknelpunten. Zonder verandering in het investeringsparadigma is de kans groot dat andere groene industrie in de toekomst niet kan worden aangesloten op de benodigde energie-infrastructuur en als gevolg daarvan zich niet kan vestigen in het HIC. Het hoofddoel van het Windmaster project is om te onderzoeken of een participatieve multimodel aanpak inzicht kan creëren in welk investeringsbeleid tot een robuuste adaptieve investeringsstrategie voor de energie-infrastructuur leidt. Het investeringsbeleid is het reguleringskader waarbinnen infrabeheerders haar strategisch netplanningsproces moeten uitvoeren. Dit beleid is bepalend voor de uiteindelijke ontwikkeling van transportcapaciteit in energie-infrastructuur. Binnen het Windmaster project is samen met de stakeholders (TU Delft, Siemens, TenneT, Stedin, Gasunie, Havenbedrijf Rotterdam, Provincie Zuid-Holland, Deltalinqs en ISPT) gewerkt aan een multi-model dat inzicht geeft in de effectiviteit van invester, Opdrachtgevers: Gasunie, TenneT, Stedin, Port of Rotterdam, Provincie Zuid-Holland, System Engineering, Policy Analysis, Organisation and Governance, Energy & Industry

Human and Organizational Factors (HOFs) are considered to have significant impacts on structural reliability. Yet how structural reliability is affected by these factors and how large this impact is remains inadequately studied. A model that is designed to reveal such relationships is proposed in this paper. First, a review of problem related studies from three different methodological viewpoints is presented. The proposed model integrates the reviewed methods under an Agent-Based Modeling (ABM) framework that is capable of capturing the dynamics and nonlinear influences of HOFs on the structural reliability. Subsequently, preliminary results of the structural failure probability frequency distribution from a case study of a simple floor slab structure are presented to illustrate the possibilities of the model. It is found out that the failure probability distribution changes significantly due to the influence by HOFs and checking for errors., Safety and Security Science, Applied Mechanics, System Engineering

System Engineering, Policy Analysis, Energy & Industry, Intelligent Electrical Power Grids

System Engineering, Energy & Industry, Policy Analysis

Transparent, consistent accounting of climate-related energy targets is a fundamental building block to the architecture of international climate agreements. Many of these climate targets focus on the transition of the energy system which has led to the development of various energy transition scenarios. Now that fossil resources are being replaced by non-combustible and renewable energy sources a re-assessment of the applicability of the current set of metrics on which these energy scenarios are based is necessary. Now that energy derived from renewable and non-combustible resources with abundant availability but limited instantaneous availability becomes more prominent the ongoing electrification of the energy system combined with the decarbonisation of the electricity system has caused the current set of energy scenario metrics to become ambiguous. More specifically we show that Total Primary Energy (TPE) and its related indicators, Energy Efficiency (EE), Energy Intensity (EI) as well as the key metric Electricity Generation Capacity (EGC) have become unrepresentative, potentially misleading and for a large part irrelevant. This is problematic as these metrics steer climate policy and investment decisions based on statistical artefacts rather than valid representation of the energy system. This study concludes with a set of requirements on energy scenarios to overcome these problems that will lead energy scenarios to focus on Total Final Consumption within a mix of related energy metrics., Energy & Industry, System Engineering

Full decarbonisation of the electricity system is one of the key elements to limit global warming. As this transition takes place, the electricity system must maintain system adequacy and remain affordable to consumers. In liberalised electricity markets investors are seen as key actors driving this transition. Due to the intermittent character of renewable assets, such as wind or solar parks, electricity systems with large shares of renewable electricity will need to become increasingly flexible. Evaluating whether specific market designs provide the right incentives to invest in flexibility, requires the simulation of realistic investor behaviour. Agent-based modelling provides the means to explore heterogeneous, imperfectly informed and boundedly rational investor behaviour within different electricity market designs. We evaluated two market designs; “energy-only” markets and markets with a Capacity Remuneration Mechanism (CRM). We conclude that energy-only markets, even with strong carbon pricing, do not incentivise investors to deliver a fully renewable, reliable and affordable energy system. Therefore policy makers should focus on developing CRMs which can work in combination with market incentives to reach a fully renewable, reliable and affordable electricity system in the second half of this century., Energy & Industry, System Engineering

Coherent responses to important problems such as climate change require involving a multitude of stakeholders in a transformative process leading to development of policy pathways. The process of coming to an agreement on policy pathways requires critical reflection on underlying system conceptualizations and commitment to building capacity in all stakeholders engaged in a social learning process. Simulation models can support such processes by providing a boundary object or negotiating artifact that allows stakeholders to deliberate through a multi-interpretable, consistent, transparent, and verifiable representation of reality. The challenge is how to structure the transdisciplinary process of involving stakeholders in simulation modeling and how to know when such a process can be labeled as transformative. There is a proliferation of approaches for this across disciplines, of which this article identifies Group Model Building, Companion Modeling, Challenge-and-Reconstruct Learning, and generic environmental modeling as the most prominent. This article systematically reviews relevant theories, terminology, principles, and methodologies across these four approaches to build a framework that can facilitate further learning. The article also provides a typology of approaches to modeling with stakeholders. It distinguishes transformative approaches that involve stakeholders from representative, instrumental and nominal forms. It is based on an extensive literature review, supported by twenty-three semi-structured interviews with participatory and non-participatory modelers. The article brings order into the abundance of conceptions of transformation, the role of simulation models in transformative change processes, the role of participation of stakeholders, and what type of approaches to modeling with stakeholders are befitting in the development of policy pathways., Energy & Industry, Policy Analysis

Understanding the possible transition pathways of the energy system requires the integration of human behaviour in energy system models. In order to model the influence of actor behaviour we have developed ACT (Agent-Based Model of Critical Transitions), an agent-based model inspired by an existing conceptualisation of critical transitions. ACT allows us to depart from the current mean-field approach and explicitly explore the effects of heterogeneity, leaders, and networks on the transition. Two key finding are (1) the importance of local communities and (2) leaders can both encourage and discourage the energy transition; a finding that nuances existing literature on critical transitions. We conclude with a reflection on the strengths and weaknesses of our modeling approach., Energy & Industry, Executive board

In this paper, we describe a modelling framework that allows the integration of human and physical components of flood risk. Within this framework, flood risk management is conceptualized as a coupled human-flood system. The human subsystem includes individuals and their behaviour and institutions that shape human-flood interaction. The framework presents a dynamic integration between agent-based models of individuals and institutions and numerical flood models. We demonstrate the framework's modelling application by examining the effects of three institutions in the Caribbean island of Sint Maarten. The case study shows the capabilities of the framework by exploring impacts of existing policies on flood risk reduction. Coupled agent-based-flood models built using the framework are useful to analyse policy options that address flood hazard and communities' vulnerability and exposure to support policy decision making. These models also show how flood risk changes over time in relation to the human dynamics on the urban environment., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Energie and Industrie

Agent-based modelling and simulation is now accepted as a valuable tool for describing the dynamics of complex socio-technical systems, and for studying complex adaptive systems. This chapter surveys the opportunities and challenges in agent-based models (ABM) for the social dynamics of energy end use. Following an introduction to the methodology of ABM, we discuss the ability of ABM to capture heterogeneous, boundedly rational and imperfectly informed behavioural factors at the individual, household, and neighbourhood levels, including the usage of micro-generation and local storage. We review three archetypal case studies of ABM: energy efficiency in domestic heating, electric vehicle adoption, and energy management in smart grids. We conclude with directions for the future, pointing out the importance of ABM in the context of multidisciplinary studies of energy behaviours., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Energy and Industry, System Engineering, Algorithmics

Disaster risk reduction is a major concern of small island developing states. Measures to reduce risk should not only be based on the magnitude of physical hazard, but also on the exposure and vulnerability of communities. In this article, we examine flood risk management policies in the Caribbean island of Sint Maarten using coupled agent-based and flood models. The agent-based model is used to model actors' behaviour in relation to urban building development and policies that are designed to reduce flood hazard and communities' vulnerability and exposure. The policies considered in the model are a Beach Policy, a Building and Housing Ordinance, a Flood Zoning policy and hazard mitigation structural measures. The flood model is used to simulate coastal and pluvial floods on the island. Agent behaviour such as building new houses and implementing hazard reduction measures affect the flood model as these actions affect the rainfall-runoff process. The flood maps generated from the updated flood model simulations are then used to assess the impact and update agents’ attributes and behaviour. The simulations results show that low-lying areas are populated, which increases the exposure, and the number of vulnerable houses is also high. Hence, out of the four policies, implementing hazard reduction measures is the most important. Reducing the flood hazard by widening existing drainage channels, constructing new ones and building dykes as coastal flood defence would reduce the hazard, hence reducing the number of flooded houses. As it affects all households on the island, the Building and Housing Ordinance is an important policy to reduce vulnerability. In general, the coupled model outputs can be used to inform policy decision making and provide insights to policymakers on the island., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Energie and Industrie, System Engineering

Nederland is op weg naar een CO2-neutrale samenleving in 2050. Zo ook het haven industrieel cluster van Rotterdam (HIC). Om dat te bereiken zal de energievoorziening de komende jaren moeten veranderen. Deze verandering heeft een grote impact op de energieinfrastructuur. In het Windmaster project wordt gefocust op de huidige aardgas-,H2- en elektriciteits infrastructuur binnen het HIC. Het plannen van infrastructuur kent lange implementatie- en afschrijvingstermijnen waardoor het voor de infrabeheerders bij wijze van spreken vandaag 2030 is en overmorgen 2050. Gezien de vele onzekerheden rondom de toekomstige energieconsumptie en -productie in het HIC en de rest van Europa vraagt dit om een nieuw investeringsparadigma. Een paradigma dat moet voorkomen dat groene industrie in de toekomst niet gefaciliteerd kan worden. Dat een nieuw investeringsparadigma nodig is, blijkt onder andere uit het feit dat zonneparken in het noorden van het land niet aangesloten kunnen worden op het elektriciteitsnet als gevolg van capaciteitsknelpunten. Zonder verandering in het investeringsparadigma is de kans groot dat andere groene industrie in de toekomst niet kan worden aangesloten op de benodigde energie-infrastructuur en als gevolg daarvan zich niet kan vestigen in het HIC. Het hoofddoel van het Windmaster project is om te onderzoeken of een participatieve multimodel aanpak inzicht kan creëren in welk investeringsbeleid tot een robuuste adaptieve investeringsstrategie voor de energie-infrastructuur leidt. Het investeringsbeleid is het reguleringskader waarbinnen infrabeheerders haar strategisch netplanningsproces moeten uitvoeren. Dit beleid is bepalend voor de uiteindelijke ontwikkeling van transportcapaciteit in energie-infrastructuur. Binnen het Windmaster project is samen met de stakeholders (TU Delft, Siemens, TenneT, Stedin, Gasunie, Havenbedrijf Rotterdam, Provincie Zuid-Holland, Deltalinqs en ISPT) gewerkt aan een multi-model dat inzicht geeft in de effectiviteit van invester, Opdrachtgevers: Gasunie, TenneT, Stedin, Port of Rotterdam, Provincie Zuid-Holland, System Engineering, Policy Analysis, Organisation & Governance, Energie and Industrie

Human and Organizational Factors (HOFs) are considered to have significant impacts on structural reliability. Yet how structural reliability is affected by these factors and how large this impact is remains inadequately studied. A model that is designed to reveal such relationships is proposed in this paper. First, a review of problem related studies from three different methodological viewpoints is presented. The proposed model integrates the reviewed methods under an Agent-Based Modeling (ABM) framework that is capable of capturing the dynamics and nonlinear influences of HOFs on the structural reliability. Subsequently, preliminary results of the structural failure probability frequency distribution from a case study of a simple floor slab structure are presented to illustrate the possibilities of the model. It is found out that the failure probability distribution changes significantly due to the influence by HOFs and checking for errors., Safety and Security Science, Applied Mechanics, System Engineering

Transparent, consistent accounting of climate-related energy targets is a fundamental building block to the architecture of international climate agreements. Many of these climate targets focus on the transition of the energy system which has led to the development of various energy transition scenarios. Now that fossil resources are being replaced by non-combustible and renewable energy sources a re-assessment of the applicability of the current set of metrics on which these energy scenarios are based is necessary. Now that energy derived from renewable and non-combustible resources with abundant availability but limited instantaneous availability becomes more prominent the ongoing electrification of the energy system combined with the decarbonisation of the electricity system has caused the current set of energy scenario metrics to become ambiguous. More specifically we show that Total Primary Energy (TPE) and its related indicators, Energy Efficiency (EE), Energy Intensity (EI) as well as the key metric Electricity Generation Capacity (EGC) have become unrepresentative, potentially misleading and for a large part irrelevant. This is problematic as these metrics steer climate policy and investment decisions based on statistical artefacts rather than valid representation of the energy system. This study concludes with a set of requirements on energy scenarios to overcome these problems that will lead energy scenarios to focus on Total Final Consumption within a mix of related energy metrics., Energie and Industrie, System Engineering

System Engineering, Energie and Industrie, Policy Analysis

System Engineering, Policy Analysis, Energie and Industrie, Intelligent Electrical Power Grids

Full decarbonisation of the electricity system is one of the key elements to limit global warming. As this transition takes place, the electricity system must maintain system adequacy and remain affordable to consumers. In liberalised electricity markets investors are seen as key actors driving this transition. Due to the intermittent character of renewable assets, such as wind or solar parks, electricity systems with large shares of renewable electricity will need to become increasingly flexible. Evaluating whether specific market designs provide the right incentives to invest in flexibility, requires the simulation of realistic investor behaviour. Agent-based modelling provides the means to explore heterogeneous, imperfectly informed and boundedly rational investor behaviour within different electricity market designs. We evaluated two market designs; “energy-only” markets and markets with a Capacity Remuneration Mechanism (CRM). We conclude that energy-only markets, even with strong carbon pricing, do not incentivise investors to deliver a fully renewable, reliable and affordable energy system. Therefore policy makers should focus on developing CRMs which can work in combination with market incentives to reach a fully renewable, reliable and affordable electricity system in the second half of this century., Energie and Industrie, System Engineering

Coherent responses to important problems such as climate change require involving a multitude of stakeholders in a transformative process leading to development of policy pathways. The process of coming to an agreement on policy pathways requires critical reflection on underlying system conceptualizations and commitment to building capacity in all stakeholders engaged in a social learning process. Simulation models can support such processes by providing a boundary object or negotiating artifact that allows stakeholders to deliberate through a multi-interpretable, consistent, transparent, and verifiable representation of reality. The challenge is how to structure the transdisciplinary process of involving stakeholders in simulation modeling and how to know when such a process can be labeled as transformative. There is a proliferation of approaches for this across disciplines, of which this article identifies Group Model Building, Companion Modeling, Challenge-and-Reconstruct Learning, and generic environmental modeling as the most prominent. This article systematically reviews relevant theories, terminology, principles, and methodologies across these four approaches to build a framework that can facilitate further learning. The article also provides a typology of approaches to modeling with stakeholders. It distinguishes transformative approaches that involve stakeholders from representative, instrumental and nominal forms. It is based on an extensive literature review, supported by twenty-three semi-structured interviews with participatory and non-participatory modelers. The article brings order into the abundance of conceptions of transformation, the role of simulation models in transformative change processes, the role of participation of stakeholders, and what type of approaches to modeling with stakeholders are befitting in the development of policy pathways., Energie and Industrie, Policy Analysis

Understanding the possible transition pathways of the energy system requires the integration of human behaviour in energy system models. In order to model the influence of actor behaviour we have developed ACT (Agent-Based Model of Critical Transitions), an agent-based model inspired by an existing conceptualisation of critical transitions. ACT allows us to depart from the current mean-field approach and explicitly explore the effects of heterogeneity, leaders, and networks on the transition. Two key finding are (1) the importance of local communities and (2) leaders can both encourage and discourage the energy transition; a finding that nuances existing literature on critical transitions. We conclude with a reflection on the strengths and weaknesses of our modeling approach., Energie and Industrie, Executive board

The energy consumer is at the centre of the European Union's energy policies. Consumer's active participation is considered as a prerequisite for managing the energy transition successfully and in a cost-effective way. The recent measures proposed by the European Commission with the 'Clean Energy for all Europeans' rely on smart grid technologies, solutions and concepts to accelerate, transform and consolidate the EU clean energy transition. In this context, the aim of this report is to present an agent based model of the electricity consumer (SIMP – Subjective Individual Model of Prosumer). The model can be used as a tool to better understand the impact that innovative energy services, enabled by smart grid technologies, may have on the electricity consumers and the society at large. Furthermore, the model can be used as a tool to gain insight into diffusion patterns of energy services (in this report represented by electricity contracts) and associated switching rates. As such, it contributes to the understanding of what fosters and what hinders an effective deployment of innovative energy services., System Engineering

Change in consumer behavior that leads to increased waste separation and recycling has been identified as a critical component of Chinese national strategy for constructing a “Circular Economy”. Various innovative solutions at community level targeting consumer behaviors are emerging in Chinese cities, using information technology that can track the volume and quality of the sorting process. In order to evaluate the potential impact of these novel solutions, we studied the behavioral change of households by initiating an experimental recycling program in a residential community in Beijing, and developed an Agent Based Model based on Theory of Planned Behavior (TPB) to identify key factors in changing behavior. The results show that the Social Norm (SN) has a decisive effect on whether an area starts recycling or not. As to the effectiveness of intervention, the Perceived Behavioral Control (PBC) plays a large role in the determination of the recycling behavior in this study, while the role of attitude is relatively small. The model outcomes can be corroborated with observations in different communities using similar technical solutions. In conclusion, we suggest that efficient local interactions among various stakeholders are needed in forming the social norm and common space that favorite recycling activities at the community level., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Energy & Industry, System Engineering, Education and Student Affairs, Policy Analysis, Circuits and Systems

This chapter explores potential ways to implement, and benefits for policymaking of, the complementary use of two different types of modelling for analysing residential energy consumption and ethnographic research. The more traditional approach of techno-economic modelling is considered alongside agent-based modelling that incorporates both causal and intentional relationships; ethnographic approaches provide 'thick understanding' of the relationships between social and technical elements and the environment. In doing so, the chapter builds on real examples from academic-policy engagement in the EU on energy demand, consumption and services. We examine three myths of the role of modelling in policymaking and propose practical ways of employing different types of modelling in a complementary way to increase policymakers' understanding of residential energy demand, consumption and services. Finally, we make three concrete recommendations for developing future interdisciplinary work on integrating social and technical models for informing policy., Energy & Industry

Now that renewable technologies are both technically and commercially mature, the imperfect rational behaviour of investors becomes a critical factor in the future success of the energy transition. Here, we take an agent-based approach to model investor decision making in the electricity sector by modelling investors as actors with different (heterogeneous) anticipations of the future. With only a limited set of assumptions, this generic model replicates the dynamics of the liberalised electricity market of the last decades and points out dynamics that are to be expected as the energy transition progresses. Importantly, these dynamics are emergent properties of the evolving electricity system resulting from actor (investor) behaviour. We have experimented with varying carbon price scenarios and find that incorporating heterogeneous investor behaviour results in a large bandwidth of possible transition pathways, and that the depth of renewables penetration is correlated with the variability of their power generation pattern. Furthermore, a counter-intuitive trend was observed, namely that average profits of investors are seen to increase with carbon prices. These results are a vivid and generic illustration that outcome-based policy cannot be solely based on market instruments that rely on perfect rational and perfectly informed agents., Energy & Industry

The energy consumer is at the centre of the European Union's energy policies. Consumer's active participation is considered as a prerequisite for managing the energy transition successfully and in a cost-effective way. The recent measures proposed by the European Commission with the 'Clean Energy for all Europeans' rely on smart grid technologies, solutions and concepts to accelerate, transform and consolidate the EU clean energy transition. In this context, the aim of this report is to present an agent based model of the electricity consumer (SIMP – Subjective Individual Model of Prosumer). The model can be used as a tool to better understand the impact that innovative energy services, enabled by smart grid technologies, may have on the electricity consumers and the society at large. Furthermore, the model can be used as a tool to gain insight into diffusion patterns of energy services (in this report represented by electricity contracts) and associated switching rates. As such, it contributes to the understanding of what fosters and what hinders an effective deployment of innovative energy services., System Engineering

Change in consumer behavior that leads to increased waste separation and recycling has been identified as a critical component of Chinese national strategy for constructing a “Circular Economy”. Various innovative solutions at community level targeting consumer behaviors are emerging in Chinese cities, using information technology that can track the volume and quality of the sorting process. In order to evaluate the potential impact of these novel solutions, we studied the behavioral change of households by initiating an experimental recycling program in a residential community in Beijing, and developed an Agent Based Model based on Theory of Planned Behavior (TPB) to identify key factors in changing behavior. The results show that the Social Norm (SN) has a decisive effect on whether an area starts recycling or not. As to the effectiveness of intervention, the Perceived Behavioral Control (PBC) plays a large role in the determination of the recycling behavior in this study, while the role of attitude is relatively small. The model outcomes can be corroborated with observations in different communities using similar technical solutions. In conclusion, we suggest that efficient local interactions among various stakeholders are needed in forming the social norm and common space that favorite recycling activities at the community level., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Energie and Industrie, System Engineering, Education and Student Affairs, Policy Analysis, Signal Processing Systems

This chapter explores potential ways to implement, and benefits for policymaking of, the complementary use of two different types of modelling for analysing residential energy consumption and ethnographic research. The more traditional approach of techno-economic modelling is considered alongside agent-based modelling that incorporates both causal and intentional relationships; ethnographic approaches provide 'thick understanding' of the relationships between social and technical elements and the environment. In doing so, the chapter builds on real examples from academic-policy engagement in the EU on energy demand, consumption and services. We examine three myths of the role of modelling in policymaking and propose practical ways of employing different types of modelling in a complementary way to increase policymakers' understanding of residential energy demand, consumption and services. Finally, we make three concrete recommendations for developing future interdisciplinary work on integrating social and technical models for informing policy., Energy and Industry

Now that renewable technologies are both technically and commercially mature, the imperfect rational behaviour of investors becomes a critical factor in the future success of the energy transition. Here, we take an agent-based approach to model investor decision making in the electricity sector by modelling investors as actors with different (heterogeneous) anticipations of the future. With only a limited set of assumptions, this generic model replicates the dynamics of the liberalised electricity market of the last decades and points out dynamics that are to be expected as the energy transition progresses. Importantly, these dynamics are emergent properties of the evolving electricity system resulting from actor (investor) behaviour. We have experimented with varying carbon price scenarios and find that incorporating heterogeneous investor behaviour results in a large bandwidth of possible transition pathways, and that the depth of renewables penetration is correlated with the variability of their power generation pattern. Furthermore, a counter-intuitive trend was observed, namely that average profits of investors are seen to increase with carbon prices. These results are a vivid and generic illustration that outcome-based policy cannot be solely based on market instruments that rely on perfect rational and perfectly informed agents., Energie and Industrie