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A stochastic computer model for heating and cooling loads
Abstract
The authors review the concept of demand-side management, particularly in regard to utility intervention into the setpoint adjustment of customers' thermostats for heating and/or cooling loads. As part of a larger effort to develop a large simulation to evaluate performance of various management strategies, they have created a simple, realistic, easily implementable model for the temperature of a house having a heater/air-conditioner which is regulated by a thermostat and operates in an environment that contains random elements. Two models previously given in the literature are reviewed before giving the details of the model, the feature of which is that it is a stochastic model operating in discrete time. Computer results show good agreement with basic physical principles, and suggest that the probability distributions of on-time and off-time are negative binomial. It is concluded that this model will provide a useful tool in the evaluation of load-management strategies.>
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Citations
Cited by
Callaway, D. S. (2009) · Energy Conversion and Management · doi:10.1016/j.enconman.2008.12.012 · Cited by 759
Human-in-the-Loop AI for HVAC Management Enhancing Comfort and Energy Efficiency
Liang, X., de Nijs, F., Say, B., & Wang, H. (2025) · Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems · doi:10.1145/3679240.3734587 · Cited by 14
Metadata
- Authors
- Mortensen, R. E., & Haggerty, K. P.
- Venue
- IEEE Transactions on Power Systems
- Published
- 1988-08
- Volume
- 3
- Issue
- 3
- Pages
- 1213-1219
- ISSN
- 0885-8950 (ISSN-L)
- 1558-0679
- OpenAlex
- W2121069325
- Cited by
- 164
- References
- 0
- FWCI
- 4.83
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A stochastic computer model for heating and cooling loads. https://app.cochat.ai/papers/10.1109/59.14584
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- Mortensen, R. E., & Haggerty, K. P. (1988). A stochastic computer model for heating and cooling loads. IEEE Transactions on Power Systems. https://doi.org/10.1109/59.14584
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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.
