The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Economic Model Predictive Control for building climate control in a Smart Grid
Abstract
Model Predictive Control (MPC) can be used to control a system of energy producers and consumers in a Smart Grid. In this paper, we use heat pumps for heating residential buildings with a floor heating system. We use the thermal capacity of the building to shift the energy consumption to periods with low electricity prices. In this way the heating system of the house becomes a flexible power consumer in the Smart Grid. This scenario is relevant for systems with a significant share of stochastic energy producers, e.g. wind turbines, where the ability to shift power consumption according to production is crucial. We present a model for a house with a ground source based heat pump used for supplying thermal energy to a water based floor heating system. The model is a linear state space model and the resulting controller is an Economic MPC formulated as a linear program. The model includes forecasts of both weather and electricity price. Simulation studies demonstrate the capabilities of the proposed model and algorithm. Compared to traditional operation of heat pumps with constant electricity prices, the optimized operating strategy saves 25-35% of the electricity cost.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A Lyapunov Function for Economic Optimizing Model Predictive Control
Diehl, M., Amrit, R., & Rawlings, J. B. (2010) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2010.2101291 · Cited by 513
Model predictive control of a building heating system: The first experience
Prívara, S., Široký, J., Ferkl, L., & Cigler, J. (2011) · Energy and Buildings · doi:10.1016/j.enbuild.2010.10.022 · Cited by 473
A review of heat pump water heating systems
Hepbaşlı, A., & Kalincı, Y. (2008) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2008.08.002 · Cited by 441
Oldewurtel, F., Parisio, A., Jones, C. N., Morari, M., Gyalistras, D., Gwerder, M., Stauch, V, Lehmann, B., & Wirth, K. (2010) · Proceedings of the 2010 American Control Conference · doi:10.1109/acc.2010.5530680 · Cited by 435
Estimation of continuous-time models for the heat dynamics of a building
Madsen, H., & Holst, J. (1995) · Energy and Buildings · doi:10.1016/0378-7788(94)00904-x · Cited by 277
Self-citationOptimizing Process Economic Performance Using Model Predictive Control
Rawlings, J. B., & Amrit, R. (2009) · Lecture notes in control and information sciences · doi:10.1007/978-3-642-01094-1_10 · Cited by 254
Oldewurtel, F., Ulbig, A., Parisio, A., Andersson, G., & Morari, M. (2010) · 49th IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2010.5717458 · Cited by 237
Modelling the heat dynamics of a building using stochastic differential equations
Andersen, K. K., Madsen, H., & Hansen, L. H. (2000) · Energy and Buildings · doi:10.1016/s0378-7788(98)00069-3 · Cited by 180
Self-citationDynamic Modeling and Advanced Control of Air Conditioning and Refrigeration Systems
Rasmussen, B. P., & Alleyne, A. G. (2006) · Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · Cited by 179
Städler, M., Krause, W., Sonnenschein, M., & Vogel, U. (2008) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2008.07.003 · Cited by 135
Cited by
Serale, G., Fiorentini, M., Capozzoli, A., Bernardini, D., & Bemporad, A. (2018) · Energies · doi:10.3390/en11030631 · Cited by 637
Benefits and challenges of electrical demand response: a critical review
O׳Connell, N., Pinson, P., Madsen, H., & O׳Malley, M. (2014) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2014.07.098 · Cited by 636
Self-citationOn heat pumps in smart grids: A review
Fischer, D., & Madani, H. (2017) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.11.182 · Cited by 445
Heat pumps and our low-carbon future: A comprehensive review
Gaur, A. S., Fitiwi, D. Z., & Curtis, J. (2021) · Energy Research & Social Science · doi:10.1016/j.erss.2020.101764 · Cited by 438
A bilevel model for electricity retailers' participation in a demand response market environment
Zugno, M., Morales, J. M., Pinson, P., & Madsen, H. (2013) · Energy Economics · doi:10.1016/j.eneco.2012.12.010 · Cited by 321
Self-citation
Metadata
- Authors
- Halvgaard, R., Poulsen, N. K., Madsen, H., & Jorgensen, J. B.
- Venue
- 2012 IEEE PES Innovative Smart Grid Technologies (ISGT)
- Publisher
- IEEE
- Published
- 2012-01
- Pages
- 1-6
- OpenAlex
- W2004584144
- Cited by
- 289
- References
- 13
- FWCI
- 73.88
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Economic Model Predictive Control for building climate control in a Smart Grid. https://app.cochat.ai/papers/10.1109/isgt.2012.6175631
- The paper
- Halvgaard, R., Poulsen, N. K., Madsen, H., & Jorgensen, J. B. (2012). Economic Model Predictive Control for building climate control in a Smart Grid. 2012 IEEE PES Innovative Smart Grid Technologies (ISGT). https://doi.org/10.1109/isgt.2012.6175631
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
