Abstract
| Original language | English |
|---|---|
| Title of host publication | IEEE PES Powertech 2017, 18-22 June 2017, Manchester, United Kingdom |
| Place of Publication | Piscataway |
| Publisher | Institute of Electrical and Electronics Engineers |
| Pages | 1-6 |
| Number of pages | 6 |
| ISBN (Electronic) | 978-1-5090-4237-1 |
| ISBN (Print) | 978-1-5090-4238-8 |
| DOIs | |
| Publication status | Published - 2017 |
| Event | 12th IEEE PES PowerTech Conference - University of Manchester, Manchester, United Kingdom Duration: 18 Jun 2017 → 22 Jun 2017 Conference number: 12 http://ieee-powertech.org/ |
Conference
| Conference | 12th IEEE PES PowerTech Conference |
|---|---|
| Abbreviated title | PowerTech 2017 |
| Country | United Kingdom |
| City | Manchester |
| Period | 18/06/17 → 22/06/17 |
| Other | Towards and Beyond Sustainable Energy Systems |
| Internet address |
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Keywords
- Demand response
- genetic algorithm
- local RES integration
- physical system modeling
- smart microgrids
Cite this
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Optimizing electricity consumption of buildings in a microgrid through demand response. / Morales González, R.; Shariat Torbaghan, S.; Gibescu, M.; Cobben, J.F.G.; Bongaerts, M.; de Nes-Koedam, M.; Vermeiden, W.
IEEE PES Powertech 2017, 18-22 June 2017, Manchester, United Kingdom. Piscataway : Institute of Electrical and Electronics Engineers, 2017. p. 1-6.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Optimizing electricity consumption of buildings in a microgrid through demand response
AU - Morales González, R.
AU - Shariat Torbaghan, S.
AU - Gibescu, M.
AU - Cobben, J.F.G.
AU - Bongaerts, M.
AU - de Nes-Koedam, M.
AU - Vermeiden, W.
PY - 2017
Y1 - 2017
N2 - This paper optimizes the thermodynamic behavior of buildings through demand response (DR) by operating their mechanical heating/cooling systems at 50% or 100% output capacity on a 15-minute basis. The optimization's objective is either minimizing cost or net electricity consumption, considering hourly prices and renewable energy resource availability in the local microgrid. The proposed DR framework combines thermodynamic models with an automated, genetic-algorithm based optimization, resulting in demonstrable benefits in terms of cost and energy efficiency for the end-users. The optimal DR schedule with multiple heating/cooling output capacity is compared against an unoptimized, business-as-usual scenario and against a DR schedule which allows only a binary operation. Results show that flexibility can be harnessed from the buildings' thermal mass, and that a finer temporal granularity not only improves the cost- and energy performance of the system, but also the utilization of renewable energy sources in the microgrid.
AB - This paper optimizes the thermodynamic behavior of buildings through demand response (DR) by operating their mechanical heating/cooling systems at 50% or 100% output capacity on a 15-minute basis. The optimization's objective is either minimizing cost or net electricity consumption, considering hourly prices and renewable energy resource availability in the local microgrid. The proposed DR framework combines thermodynamic models with an automated, genetic-algorithm based optimization, resulting in demonstrable benefits in terms of cost and energy efficiency for the end-users. The optimal DR schedule with multiple heating/cooling output capacity is compared against an unoptimized, business-as-usual scenario and against a DR schedule which allows only a binary operation. Results show that flexibility can be harnessed from the buildings' thermal mass, and that a finer temporal granularity not only improves the cost- and energy performance of the system, but also the utilization of renewable energy sources in the microgrid.
KW - Demand response
KW - genetic algorithm
KW - local RES integration
KW - physical system modeling
KW - smart microgrids
UR - http://ieeexplore.ieee.org/document/7980983/
U2 - 10.1109/PTC.2017.7980983
DO - 10.1109/PTC.2017.7980983
M3 - Conference contribution
SN - 978-1-5090-4238-8
SP - 1
EP - 6
BT - IEEE PES Powertech 2017, 18-22 June 2017, Manchester, United Kingdom
PB - Institute of Electrical and Electronics Engineers
CY - Piscataway
ER -