November 2024
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11 Reads
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Publications (7)
October 2024
June 2024
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12 Reads
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1 Citation
January 2024
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14 Reads
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1 Citation
IEEE Transactions on Industry Applications
Building modeling, specifically heating, ventilation, and air conditioning (HVAC) load and equivalent energy storage calculations, represent a key focus for decarbonization of buildings and smart grid controls. In this paper, an ultra-fast one-minute resolution Hybrid Machine Learning Model (HMLM) is proposed as part of a novel contribution in the field of residential physics-based smart home surrogate modeling. Emulation of white box models, or digital twins, with editable parameters through machine learning (ML) meta-modeling serves as an alternative to wide-spread experimental big data collection. The HMLM employs combined k-means clustering with multiple linear regression (MLR) to emulate minutely HVAC power timestep-to-timestep with satisfactory nRMSE error of less than 10% across an entire year test set. An approach is also described to characterize HVAC systems as generalized storage (GES) devices to unify household appliance and virtual power plant (VPP) controls in accordance with industry Communication Technology Association (CTA) 2045 protocol and Energy Star metrics. Synthetic output data from experimentally calibrated EnergyPlus models for three existing smart homes managed by the Tennessee Valley Authority (TVA) is employed in residential case studies and a discussion provided for the large-scale application to hundreds of homes.
October 2023
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4 Reads
October 2022
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20 Reads
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6 Citations
September 2022
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13 Reads
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2 Citations
Citations (3)
... Крім того, варто зазначити праці наступних науковців: Boutahri Y., Tilioua A. [3], Mistry V. [4], Alden R., Jones E., Poore S., Ionel D. [5], Bai Y., Liu K., Wang Y. [6], Deng Z., Chen Q. [7], Vakiloroaya V., Samali B., Fakhar A., Pishghadam K. [8], Zhang W., Wen Y., Tseng K.J. [9], Chaudhuri T., Soh Y.C., Hua L., Li H., Xie L. [10], Cosma A.C., Simha R. [11], Nabavi A., Saluz U., Wolf M., Geyer P. [12], Sharma V., Singh A. [13], Faiz M., Sajid M., Sial S., Javed K., Ayaz Y. [14], Ogundiran J., Asadi E., Gameiro da Silva M. [15] та інших. ...
- Citing Article
January 2024
IEEE Transactions on Industry Applications
... We identify four distinct approaches in the context of our research: assistant, residual, surrogate, and augmentation. In the assistant strategy, the output from a physics-based model is used as an additional input to the data-driven model [6,2] or conversely, the data-driven model can provide inputs or corrections to the physics-based model [42,4,21]. This additional input may provide valuable context information, but also increases the number of input features. ...
- Citing Conference Paper
- Full-text available
October 2022
... The planning and operation of power systems have become more complex due to factors such as uncertainty from renewable power sources and electric vehicle charging, demand for reliable supply and power quality, competitive energy prices, and limited investment in network assets [1]. Several Smart Grids (SG) technologies have been designed to alleviate these challenges and enhance network operation, particularly for active components like generators, protection devices, transmission, and demand-side systems [2,3,4,5]. Simulation tools play a crucial role in evaluating device and system performance during the design stage, reducing development costs and time to market. However, simulations have limitations, and real-world validation through prototypes is essential. ...
- Citing Conference Paper
September 2022