2879. On the integration of discrete choice models in load scheduling for energy communities
Invited abstract in session TB-12: Emerging trends, challenges and innovations in scheduling and project management, stream Scheduling and Project Management.
Tuesday, 10:30-12:00Room: Clarendon SR 1.02
Authors (first author is the speaker)
| 1. | Maria Elena Bruni
|
| Department of Mechanical, Energy and Management Engineering, unical | |
| 2. | Dario Vezzali
|
| Department of Mechanical, Energy and Management Engineering, University of Calabria | |
| 3. | Sara Khodaparasti
|
| University of calabria | |
| 4. | HAOQI XIE
|
| Dipartimento di Economia, Università degli studi di Genova |
Abstract
Load scheduling for energy communities represents an innovative application at the boundary between operations research and energy management. An energy community consists of traditional consumers, prosumers, and distributed storage units, and is conceived with the objective of minimising the load collected from the public grid by shifting so-called controllable loads. This may come at the cost of reducing the service level and satisfaction of users who are not willing to change their habits to optimize energy consumption within the energy community. Discrete choice models (DCM) are able to capture the impact of these decisions on users’ behaviour, considering the heterogeneity of their preferences, and have been successfully integrated into optimization models. In this work, we introduce a novel mixed integer linear programming (MILP) model with an embedded DCM, which captures user preferences in terms of utility functions, to solve the load scheduling problem for energy communities.
Keywords
- Scheduling
- OR in Energy
- Behavioural OR
Status: accepted
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