7 citations · 11 across the 12 of their papers we have counts for
13 papers
Scenario Reduction for Two-Stage Stochastic Mixed-Integer Programs
Yannick Werner, Juan Miguel Morales, Salvador Pineda +2
Two-stage stochastic mixed-integer programs are important tools for decision-making under uncertainty. Representing the uncertainty with many scenarios, however, can make them chal…
Towards time-variant scenario reduction for energy system optimization modeling under uncertainty
Yannick Werner, Juan Miguel Morales, Salvador Pineda +1
Stochastic programming has become a popular tool for supporting decision-making under uncertainty in the long-term planning of energy systems. Existing scenario reduction methods,…
Modelling the Correlation Structure of Uncertain Input Parameters for Energy System Optimization
Klara Maggauer, Yannick Werner, Stefan Strömer +1
Statistical dependence among uncertain input parameters in stochastic energy system optimization models is often ignored, even though this can substantially bias outcomes. To addre…
Temperature-Aware Heat Pump Modeling for Large-Scale Energy System Optimization
Simon Malacek, Sonja Wogrin, Yannick Werner
Heat pumps are expected to dominate the heating sector, substantially increasing peak electricity demand. At the same time, building thermal inertia enables operational strategies,…
Voltage-Aware Grid Aggregation: Expanding the European High-Voltage Network
Benjamin Stöckl, Marco Anarmo, Sonja Wogrin +1
Energy system optimization models are indispensable for planning the European energy transition. Yet their applicability is constrained by the fundamental trade-off between spatial…
Simplification Ad Absurdum? Revisiting Gas Flow Modeling for Integrated Energy System Planning
Thomas Klatzer, Yannick Werner, Sonja Wogrin
This paper analyzes the implications of simplified pipeline gas flow models for integrated energy system planning. A case study of an integrated power-hydrogen expansion planning p…
NPAP: Network Partitioning and Aggregation Package for Python
Marco Anarmo, Benjamin Stöckl, Yannick Werner +1
NPAP (Network Partitioning and Aggregation Package) is an open-source Python library for reducing the spatial complexity of network graphs. Built on NetworkX, it provides an access…
QGas: Interactive Gas Infrastructure Toolkit
Marco Quantschnig, Yannick Werner, Sonja Wogrin +1
Gas infrastructure datasets are essential inputs for energy system planning to support strategic decision-making toward decarbonization. However, relevant data are typically scatte…
Mapping Austria's Natural Gas and Hydrogen Infrastructure Plans
Marco Quantschnig, Yannick Werner, Thomas Klatzer +1
This paper presents a comprehensive, spatially disaggregated dataset of Austria's natural gas and hydrogen infrastructure towards 2040. The dataset covers the complete gas transmis…
Scenario Reduction for the Two-Stage Stochastic Unit Commitment Problem
Yannick Werner, Juan Miguel Morales, Salvador Pineda +2
The two-stage stochastic unit commitment problem has become an important tool to support decision-making under uncertainty in power systems. Representing the uncertainty by a large…
Congestion-Sensitive Grid Aggregation for DC Optimal Power Flow
Benjamin Stöckl, Yannick Werner, Sonja Wogrin
The vast spatial dimension of modern interconnected electricity grids challenges the tractability of the DC optimal power flow problem. Grid aggregation methods try to overcome thi…
Towards time series aggregation with exact error quantification for optimization of energy systems
Beltrán Castro Gómez, Yannick Werner, Sonja Wogrin
Energy system optimization models are becoming increasingly popular for analyzing energy markets, such as the impact of new policies or interactions between energy carriers. One ke…
Generating Building-Level Heat Demand Time Series by Combining Occupancy Simulations and Thermal Modeling
Simon Malacek, José Portela, Yannick Marcus Werner +1
Despite various efforts, decarbonizing the heating sector remains a significant challenge. To tackle it by smart planning, the availability of highly resolved heating demand data i…