A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level
By Eugenia D. Mehleri, Haralambos Sarimveis, N. Markatos, Lazaros G. Papageorgiou. 2012
314 citations recorded by the source corpus.
Subfields: Electrical and Electronic Engineering, Mechanical Engineering
View Paper: https://www.semanticscholar.org/paper/28ce89c80b7aa88c729a2aca42e2836b88aee9cc
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In Electrical and Electronic Engineering
- Dagoberto Cedillos Alvarado
- Nilay Shah
- Tomislav Capuder
- Pierluigi Mancarella
- Salvador Acha
- C. Markides
In Mechanical Engineering
Citations in the corpus
- A Technology Selection and Operation (TSO) optimisation model for distributed energy systems: Mathematical formulation and case study (2016, methodology): “The previous two studies allowed for the use a single specific technology (CHP) that can vary in size, while [2,9,17] enabled the possibility to select from various technologies (e.”
- Optimal investment and unit sizing of distributed energy systems under uncertainty: A robust optimization approach (2014, unknown): “A Mixed-Integer Linear Programming ( MILP) model for a small neighborhood area was represented in [13].”
- Techno-economic and environmental modelling and optimization of flexible distributed multi-generation options (2014, background): “Mehleri et al present a mathematical modelling approach to planning the entire district energy system taking into account the investment and the operation cost of different technologies [43].”
- Distributed energy resource system optimisation using mixed integer linear programming (2013, methodology): “While the aforementioned models are mainly focused on technology selection, more recent work carried out by Keirstead et al. (2012b), Mehleri et al. (2012, 2013), and Weber and Shah (2011) also include energy distribution in their models.”