Implementing collective intelligence in demand side management
Nik, Vahid M. LU
and Moazami, Amin
(2020)
12th International Conference on Applied Energy, ICAE 2020
In Energy Proceedings
10.
- Abstract
Collective intelligence (CI) is a form of distributed intelligence emerging from collaborative problem solving and decision making. It has the advantages of simple communication and less need of data transfer and computationally extensive central decision making systems. This work implements CI in demand side management (DSM) of a hypothetical urban area in Stockholm, created based on the representative residential buildings in the city. A simple platform and algorithm are developed for modelling CI-DSM, considering the timescales of 15min for communication and applying or disapplying adaptation measures. According to the results, CI increases the autonomy of the system and decreases the heating demand of buildings effectively,... (More)
Collective intelligence (CI) is a form of distributed intelligence emerging from collaborative problem solving and decision making. It has the advantages of simple communication and less need of data transfer and computationally extensive central decision making systems. This work implements CI in demand side management (DSM) of a hypothetical urban area in Stockholm, created based on the representative residential buildings in the city. A simple platform and algorithm are developed for modelling CI-DSM, considering the timescales of 15min for communication and applying or disapplying adaptation measures. According to the results, CI increases the autonomy of the system and decreases the heating demand of buildings effectively, consequently increasing the demand flexibility based on climate conditions. CI results in decreasing the energy demand considerably, decreasing the total heating demand over a year by around 50%.
(Less)
- author
- Nik, Vahid M.
LU
and Moazami, Amin
- organization
- publishing date
- 2020
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- climate flexibility, climate resilience, collective intelligence, demand flexibility, demand side management, urban energy system
- host publication
- Sustainable Energy Solutions for Changing the World : Part II - Part II
- series title
- Energy Proceedings
- volume
- 10
- conference name
- 12th International Conference on Applied Energy, ICAE 2020
- conference location
- Bangkok, Thailand
- conference dates
- 2020-12-01 - 2020-12-10
- external identifiers
-
- scopus:85202455810
- DOI
- 10.46855/energy-proceedings-7184
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2020 ICAE.
- id
- 82032f54-5a15-4fe3-b4ff-b6f1d70a9785
- date added to LUP
- 2024-12-16 21:53:13
- date last changed
- 2025-04-04 14:30:53
@inproceedings{82032f54-5a15-4fe3-b4ff-b6f1d70a9785,
abstract = {{<p>Collective intelligence (CI) is a form of distributed intelligence emerging from collaborative problem solving and decision making. It has the advantages of simple communication and less need of data transfer and computationally extensive central decision making systems. This work implements CI in demand side management (DSM) of a hypothetical urban area in Stockholm, created based on the representative residential buildings in the city. A simple platform and algorithm are developed for modelling CI-DSM, considering the timescales of 15min for communication and applying or disapplying adaptation measures. According to the results, CI increases the autonomy of the system and decreases the heating demand of buildings effectively, consequently increasing the demand flexibility based on climate conditions. CI results in decreasing the energy demand considerably, decreasing the total heating demand over a year by around 50%.</p>}},
author = {{Nik, Vahid M. and Moazami, Amin}},
booktitle = {{Sustainable Energy Solutions for Changing the World : Part II}},
keywords = {{climate flexibility; climate resilience; collective intelligence; demand flexibility; demand side management; urban energy system}},
language = {{eng}},
series = {{Energy Proceedings}},
title = {{Implementing collective intelligence in demand side management}},
url = {{http://dx.doi.org/10.46855/energy-proceedings-7184}},
doi = {{10.46855/energy-proceedings-7184}},
volume = {{10}},
year = {{2020}},
}