info
We’re currently testing a new search engine
<p>If you encounter any issues or have comments, please share your feedback using the short survey on the search results page.</p>
Search in the TU Delft Repository Collections
TU Delft Repository
209,013
Records
237,576
Files
80,841
Contributors
Recently Added Records
The integration of massive offshore wind into hybrid AC-HVDC grids demands robust DC voltage regulation, yet conventional fixed-gain droop controllers struggle under severe stochastic volatility. This paper bridges the gap between system-level dispatch and converter-level control by proposing a Stochastic Optimal Power Flow (SOPF)-based adaptive droop framework. Rather than relying on heuristic or reactive tuning, wind forecast uncertainty is modeled using a zone-wise Beta distribution that accurately captures the heteroscedastic nature of wind errors across low, mid, and high-power regimes. By leveraging Polynomial Chaos Expansion (PCE) within a chance-constrained SOPF, the system’s stochastic states are formulated analytically. Crucially, the adaptive droop gain is extracted directly from the first-order PCE coefficients through a sensitivity analysis, transferring the probabilistic voltage-security information of the stochastic dispatch to the local converter control. Validation on a 4-terminal AC-HVDC system demonstrates that scenario-adaptive gains significantly outperform standard fixed-coefficient approaches, effectively minimizing active-power tracking errors during extreme wind disturbances.
...
The integration of massive offshore wind into hybrid AC-HVDC grids demands robust DC voltage regulation, yet conventional fixed-gain droop controllers struggle under severe stochastic volatility. This paper bridges the gap between system-level dispatch and converter-level control by proposing a Stochastic Optimal Power Flow (SOPF)-based adaptive droop framework. Rather than relying on heuristic or reactive tuning, wind forecast uncertainty is modeled using a zone-wise Beta distribution that accurately captures the heteroscedastic nature of wind errors across low, mid, and high-power regimes. By leveraging Polynomial Chaos Expansion (PCE) within a chance-constrained SOPF, the system’s stochastic states are formulated analytically. Crucially, the adaptive droop gain is extracted directly from the first-order PCE coefficients through a sensitivity analysis, transferring the probabilistic voltage-security information of the stochastic dispatch to the local converter control. Validation on a 4-terminal AC-HVDC system demonstrates that scenario-adaptive gains significantly outperform standard fixed-coefficient approaches, effectively minimizing active-power tracking errors during extreme wind disturbances.
The transition from point-to-point HVDC links to multiterminal HVDC (MT-HVDC) grids increases the need to understand how the interruption of DC current shapes transient dielectric stress on connected cable systems. This paper develops a compact parameterization of the DC circuit breaker–cable interface in a reduced 525 kV MT-HVDC grid. The interruption process is characterized by transient interruption voltage (TIV), fault neutralization time, fault current limiting reactor (FCLR) value, and source-side condition. Kirchhoff-based circuit relations interpret the dominant mechanisms, while EMT simulations with a frequency-dependent cable model quantify the healthy-cable voltage response. A 54-case screening study shows that the highest peak stress occurs for high TIV, long tf, low FCLR, and source-supported operation. Several cases exceed the DC long transient overvoltage (DC-LTrOV) reference level, showing that TIV reduction or source removal alone is insufficient to mitigate the associated cable stresses. The results provide traceable input for insulation coordination and assessment of interruption-driven cable stress exposure.
...
The transition from point-to-point HVDC links to multiterminal HVDC (MT-HVDC) grids increases the need to understand how the interruption of DC current shapes transient dielectric stress on connected cable systems. This paper develops a compact parameterization of the DC circuit breaker–cable interface in a reduced 525 kV MT-HVDC grid. The interruption process is characterized by transient interruption voltage (TIV), fault neutralization time, fault current limiting reactor (FCLR) value, and source-side condition. Kirchhoff-based circuit relations interpret the dominant mechanisms, while EMT simulations with a frequency-dependent cable model quantify the healthy-cable voltage response. A 54-case screening study shows that the highest peak stress occurs for high TIV, long tf, low FCLR, and source-supported operation. Several cases exceed the DC long transient overvoltage (DC-LTrOV) reference level, showing that TIV reduction or source removal alone is insufficient to mitigate the associated cable stresses. The results provide traceable input for insulation coordination and assessment of interruption-driven cable stress exposure.
Carbon data as design material
Architecture and urban design towards the decarbonization of the built environment
This thesis investigates how environmental data can be integrated into early-stage Architecture and Urban Design processes, taking embodied carbon data as a critical case. Positioned within Design Research, it argues that carbon data should not be treated only as a technical input for Life-Cycle Assessment or late-stage compliance metric, but as a design material: something architects and urban designers can interpret, simplify, visualize, negotiate, and mobilize alongside sketches, drawings, models, and diagrams.
The built environment is a major contributor to global carbon emissions, and European and Dutch regulatory frameworks increasingly require environmental performance to be quantified in design and permitting processes. However, embodied carbon data is often introduced too late, after key decisions about materiality, structure, density, infrastructure, spatial organization, and urban form have been made.
The thesis uses a mixed-methods, research-by-design methodology combining literature review, practice-based research, autoethnographic reflection, and five empirical case studies in architecture and urban design practice. Together, these cases reveal recurring bottlenecks related to data access, tool interoperability, system boundaries, uneven levels of detail, undocumented assumptions, spatial visualization, simplified communication, and practical workflows.
The main output is a data-supported design framework balancing data-scientific methods with designerly ways of knowing. The thesis advances the concept of data as design material; proposes and tests a methodological framework to integrate carbon data across design scales; and reframes the designer’s role as a knowledge integrator towards the decarbonization of the built environment. ...
The built environment is a major contributor to global carbon emissions, and European and Dutch regulatory frameworks increasingly require environmental performance to be quantified in design and permitting processes. However, embodied carbon data is often introduced too late, after key decisions about materiality, structure, density, infrastructure, spatial organization, and urban form have been made.
The thesis uses a mixed-methods, research-by-design methodology combining literature review, practice-based research, autoethnographic reflection, and five empirical case studies in architecture and urban design practice. Together, these cases reveal recurring bottlenecks related to data access, tool interoperability, system boundaries, uneven levels of detail, undocumented assumptions, spatial visualization, simplified communication, and practical workflows.
The main output is a data-supported design framework balancing data-scientific methods with designerly ways of knowing. The thesis advances the concept of data as design material; proposes and tests a methodological framework to integrate carbon data across design scales; and reframes the designer’s role as a knowledge integrator towards the decarbonization of the built environment. ...
This thesis investigates how environmental data can be integrated into early-stage Architecture and Urban Design processes, taking embodied carbon data as a critical case. Positioned within Design Research, it argues that carbon data should not be treated only as a technical input for Life-Cycle Assessment or late-stage compliance metric, but as a design material: something architects and urban designers can interpret, simplify, visualize, negotiate, and mobilize alongside sketches, drawings, models, and diagrams.
The built environment is a major contributor to global carbon emissions, and European and Dutch regulatory frameworks increasingly require environmental performance to be quantified in design and permitting processes. However, embodied carbon data is often introduced too late, after key decisions about materiality, structure, density, infrastructure, spatial organization, and urban form have been made.
The thesis uses a mixed-methods, research-by-design methodology combining literature review, practice-based research, autoethnographic reflection, and five empirical case studies in architecture and urban design practice. Together, these cases reveal recurring bottlenecks related to data access, tool interoperability, system boundaries, uneven levels of detail, undocumented assumptions, spatial visualization, simplified communication, and practical workflows.
The main output is a data-supported design framework balancing data-scientific methods with designerly ways of knowing. The thesis advances the concept of data as design material; proposes and tests a methodological framework to integrate carbon data across design scales; and reframes the designer’s role as a knowledge integrator towards the decarbonization of the built environment.
The built environment is a major contributor to global carbon emissions, and European and Dutch regulatory frameworks increasingly require environmental performance to be quantified in design and permitting processes. However, embodied carbon data is often introduced too late, after key decisions about materiality, structure, density, infrastructure, spatial organization, and urban form have been made.
The thesis uses a mixed-methods, research-by-design methodology combining literature review, practice-based research, autoethnographic reflection, and five empirical case studies in architecture and urban design practice. Together, these cases reveal recurring bottlenecks related to data access, tool interoperability, system boundaries, uneven levels of detail, undocumented assumptions, spatial visualization, simplified communication, and practical workflows.
The main output is a data-supported design framework balancing data-scientific methods with designerly ways of knowing. The thesis advances the concept of data as design material; proposes and tests a methodological framework to integrate carbon data across design scales; and reframes the designer’s role as a knowledge integrator towards the decarbonization of the built environment.
Conference paper
(2026)
-
C. Doh, Motiejus Cicenas, A.M. van Voorden, Laurens De Vries, M. Cvetkovic
Historically, district heating networks (DHNs) and electricity distribution networks (EDNs) have been planned independently, as heat demand was mostly met by natural gas. However, the proliferation of power-to-heat (P2H) technologies intensifies the interactions between these two networks, making their operations more intertwined. This study proposes a soft-linking approach to enable a high-fidelity assessment of the interactions between these networks and to quantify the impacts of their interdependency. The proposed approach couples an operational optimization model of a DHN and a full AC time series power flow simulation model of an EDN. Historical and future scenarios are analyzed under market, weather, and demand-driven scenarios. Results show that nearly half of the DHN’s heat demand is met by P2H and geothermal units by 2030, consequently causing 660 instances of network limit violations in the EDN. Interestingly, a strategic placement of P2H units alleviates EDN congestion from peak supply by absorbing surplus generation from local distributed energy resources like PVs. These findings highlight the need for coordinated planning and operation between DHNs and EDNs to achieve a cost-efficient and reliable energy transition.
...
Historically, district heating networks (DHNs) and electricity distribution networks (EDNs) have been planned independently, as heat demand was mostly met by natural gas. However, the proliferation of power-to-heat (P2H) technologies intensifies the interactions between these two networks, making their operations more intertwined. This study proposes a soft-linking approach to enable a high-fidelity assessment of the interactions between these networks and to quantify the impacts of their interdependency. The proposed approach couples an operational optimization model of a DHN and a full AC time series power flow simulation model of an EDN. Historical and future scenarios are analyzed under market, weather, and demand-driven scenarios. Results show that nearly half of the DHN’s heat demand is met by P2H and geothermal units by 2030, consequently causing 660 instances of network limit violations in the EDN. Interestingly, a strategic placement of P2H units alleviates EDN congestion from peak supply by absorbing surplus generation from local distributed energy resources like PVs. These findings highlight the need for coordinated planning and operation between DHNs and EDNs to achieve a cost-efficient and reliable energy transition.
In this article, we propose a model predictive control (MPC) scheme with an exponential cost function, along with an observer for the Modular Multilevel Converter (MMC), to enhance converter dynamic performance. In particular, as the prediction horizon (NP) increases, the numerical conditioning deteriorates rapidly, especially when a large NP is employed. This research work uses an appropriate cost function weighted to overcome the limitations of a large NP. We further analyze the effects of constraints, observing that the designed MPC strictly adheres to them and that the control variable influences the MMC plant’s response. The presence of the observer improves the prediction of the output, particularly for setpoint changes in the reference signal. We also analyze the prescribed performance, which provides a priori guarantees of closed-loop stability using the exponential-based MPC.
...
In this article, we propose a model predictive control (MPC) scheme with an exponential cost function, along with an observer for the Modular Multilevel Converter (MMC), to enhance converter dynamic performance. In particular, as the prediction horizon (NP) increases, the numerical conditioning deteriorates rapidly, especially when a large NP is employed. This research work uses an appropriate cost function weighted to overcome the limitations of a large NP. We further analyze the effects of constraints, observing that the designed MPC strictly adheres to them and that the control variable influences the MMC plant’s response. The presence of the observer improves the prediction of the output, particularly for setpoint changes in the reference signal. We also analyze the prescribed performance, which provides a priori guarantees of closed-loop stability using the exponential-based MPC.