"uuid","repository link","title","author","contributor","publication year","abstract","subject topic","language","publication type","publisher","isbn","issn","patent","patent status","bibliographic note","access restriction","embargo date","faculty","department","research group","programme","project","coordinates"
"uuid:df684419-a59f-4d19-a593-b16b88dee87a","http://resolver.tudelft.nl/uuid:df684419-a59f-4d19-a593-b16b88dee87a","Demolition or retention of buildings: drivers at the masterplan scale","Baker, Hannah (University of Cambridge); Moncaster, Alice (Open University); Wilkinson, Sara (University of Technology Sydney); Remøy, H.T. (TU Delft Real Estate Management)","","2023","Current adaptation theory tends to consider individual buildings or the city level, which cannot address decisions related to masterplan developments on large brownfield sites. This paper investigates the drivers for building demolition or retention and adaptation decisions at the masterplan scale. Expert interviews and three case studies are used to explore how and why decisions to demolish, or to retain and adapt, are made at this scale. The research compared three different geopolitical contexts: Cambridge in the UK; Eindhoven in the Netherlands; and Sydney in Australia. Additional factors and complexities that should be considered at the masterplan scale are identified. The theoretical underpinnings of urban development processes are used to explain these complexities in relation to four existing models and demonstrate that no one model is adequate to describe the interactions. With increasing awareness of climate change impacts, it is critical that demolition decisions on masterplan developments are reviewed in the light of retaining carbon as well as heritage.","adaptation; buildings; demolition; heritage; life cycle assessment; masterplan; planning; retrofit; reuse; urban development","en","journal article","","","","","","","","","","","Real Estate Management","","",""
"uuid:e29c644e-4bf7-48a5-8b8d-f1e8ec7afe91","http://resolver.tudelft.nl/uuid:e29c644e-4bf7-48a5-8b8d-f1e8ec7afe91","A Unifying Framework for Reinforcement Learning and Planning","Moerland, Thomas M. (Universiteit Leiden); Broekens, D.J. (Universiteit Leiden); Plaat, Aske (Universiteit Leiden); Jonker, C.M. (TU Delft Interactive Intelligence; Universiteit Leiden)","","2022","Sequential decision making, commonly formalized as optimization of a Markov Decision Process, is a key challenge in artificial intelligence. Two successful approaches to MDP optimization are reinforcement learning and planning, which both largely have their own research communities. However, if both research fields solve the same problem, then we might be able to disentangle the common factors in their solution approaches. Therefore, this paper presents a unifying algorithmic framework for reinforcement learning and planning (FRAP), which identifies underlying dimensions on which MDP planning and learning algorithms have to decide. At the end of the paper, we compare a variety of well-known planning, model-free and model-based RL algorithms along these dimensions. Altogether, the framework may help provide deeper insight in the algorithmic design space of planning and reinforcement learning.","framework; model-based reinforcement learning; overview; planning; reinforcement learning; synthesis","en","journal article","","","","","","","","","","","Interactive Intelligence","","",""
"uuid:12b04a10-47f4-41e7-b0d9-de361f520a43","http://resolver.tudelft.nl/uuid:12b04a10-47f4-41e7-b0d9-de361f520a43","Coordinated expansion planning of transmission and distribution systems integrated with smart grid technologies","Moradi Sepahvand, M. (TU Delft Intelligent Electrical Power Grids); Amraee, Turaj (K.N. Toosi University of Technology); Aminifar, Farrokh (University of Tehran); Akbari, Amirhossein (K.N. Toosi University of Technology)","","2022","Integration of smart grid technologies in distribution systems, particularly behind-the-meter initiatives, has a direct impact on transmission network planning. This paper develops a coordinated expansion planning of transmission and active distribution systems via a stochastic multistage mathematical programming model. In the transmission level, in addition to lines, sitting and sizing of utility-scale battery energy storage systems and wind power plants under renewable portfolio standard policy are planned. Switchable feeders and distributed generations are decision variables in the distribution level while the impact of demand response programs as a sort of behind-the-meter technologies is accommodated as well. Expansion of electric vehicle taxi charging stations is included as a feasible option in both transmission and distribution levels. In order to deal with short-term uncertainty of load demand, renewable energy sources output power, and the charging pattern of electric vehicle taxis in each station, a chronological time-period clustering algorithm along with Monte Carlo simulation is utilized. The proposed model is tackled by means of Benders Dual Decomposition (BDD) method. The IEEE RTS test system (as the transmission system) along with four IEEE 33-node test feeders (as distribution test systems) are examined to validate effectiveness of the proposed model.","Distribution system operator; transmission system operator; Transmission and distribution expansion; planning; Smart grid technologies","en","journal article","","","","","","","","","","","Intelligent Electrical Power Grids","","",""
"uuid:75a45bcd-c318-4b16-bb31-04a72f4e9368","http://resolver.tudelft.nl/uuid:75a45bcd-c318-4b16-bb31-04a72f4e9368","System-Level Design for Reliability and Maintenance Scheduling in Modern Power Electronic-Based Power Systems","Peyghami, S. (Aalborg University); Palensky, P. (TU Delft Intelligent Electrical Power Grids); Fotuhi-Firuzabad, Mahmoud (Sharif University of Technology); Blaabjerg, Frede (Aalborg University)","","2020","Power electronic converters will serve as the fundamental components of modern power systems. However, they may suffer from poorer reliability if not properly designed, consequently affecting the overall performance of power systems. Accordingly, the converter reliability should be taken into account in design and planning of Power Electronic-based Power Systems (PEPSs). Optimal decision-making in planning of PEPSs requires precise reliability modeling in converters from component up to system-level. This paper proposes model-based system-level design and maintenance strategies in PEPSs based on the reliability model of converters. This will yield a reliable and economic planning of PEPSs by proper sizing of converters, cost-effective design of converter components, identifying and strengthening the converter weakest links, as well as optimal maintenance scheduling of converters. Numerical case studies demonstrate the effectiveness of the proposed design and planning strategies for modern power systems.","Design; maintenance; planning; power converter; power system; reliability; wear-out failure","en","journal article","","","","","","","","","","","Intelligent Electrical Power Grids","","",""
"uuid:c5feade4-db7a-4d99-8207-75be8609f90e","http://resolver.tudelft.nl/uuid:c5feade4-db7a-4d99-8207-75be8609f90e","Distributed agency between 2D and 3D representation of the subsurface","Hooimeijer, F.L. (TU Delft Environmental Technology and Design); van Campenhout, Ignace (Gemeente Rotterdam)","","2019","Although severely altered, the urban subsurface is the base of the natural system, and is crucial for a stable, green, healthy, and liveable city. It is also the technical space, the engine room of the city where vital functions such as water, electricity, sewers, and drainage are located. This hybrid state needs to be recognized when designing resilient and durable (subsurface) infrastructure within urban renewal projects, so as to properly employ the parameters of both natural and technical systems. Interdisciplinary work is needed in order to be able to link natural systems (a) the water cycle, (b) soil and subsurface conditions, (c) soil improvement technology, and (d) opportunities for urban renewal (e.g. urban growth or shrinkage) in an efficient way.
The importance of implementing “boundary spanning” when doing interdisciplinary work that deals with the effects of climate change is a widely recognized method, and has been an object of study in the city of Rotterdam in the past decade. The particular need for a “distributed agency” became clear during several research projects dealing with climate change, because it enables different actors to contribute to the development of the project at different phases. The representation of the city as both a natural and technical construction has been tested through the use of 2D and 3D information, which has played a significant role in enabling designs to incorporate the dimension of the subsurface. 2D and 3D information needs to anticipate different scales of specific planning and/or design phases, and they must also address various topics of the subsurface. For each phase of urban development, the distributed agency between 2D and 3D information is investigated and reflected upon. Conclusions are then drawn on the relationship between 2D and 3D information, and how it could relate in a productive, boundary spanning act that is inclusive of the subsurface. Based on these potential connections, the design of a new concept which implements boundary spanning as a facilitator is presented.