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THERMAL ENERGY CONTROL IN BUILDING ENERGY SYSTEM

ABSTRACT
There is usually a waste of energy consumption in building systems. To help buildings reduce energy waste, the article established a building-sharing heat and power energy sharing system to achieve optimal energy allocation. Furthermore, the report determined the dual operation strategy model of using heat energy to determine power supply and electricity to determine heat energy. At the same time, we use stochastic programming and multi-objective optimization of the heating model and propose a two-level optimization model solution method based on the Benders decomposition algorithm. At the end of the thesis, the process was applied to actual cases to verify the method's effectiveness.
KEYWORDS
PAPER SUBMITTED: 2020-12-12
PAPER REVISED: 2021-01-18
PAPER ACCEPTED: 2021-02-04
PUBLISHED ONLINE: 2021-07-31
DOI REFERENCE: https://doi.org/10.2298/TSCI2104123C
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2021, VOLUME 25, ISSUE Issue 4, PAGES [3123 - 3131]
REFERENCES
  1. Zakharov, A. A., et al., The Thermal Regime Simulation and the Heat Management of a Smart Building, Tyumen State Univ. Herald. Phys. Math. Model, Oil, Gas, Energy, 4 (2018), 2, pp. 105-119
  2. Bachrun, A. S., et al., Building Envelope Component to Control Thermal Indoor Environment in Sustainable Building: A Review, Sinergi, 23 (2019), 2, pp. 79-98
  3. Vosughi, A., et al., Occupant-Location-Catered Control of IoT-enabled Building HVAC Systems, IEEE Transactions on Control Systems Technology, 28 (2019), 6, pp. 2572-2580
  4. Wu, S., Construction of Visual 3-D Fabric Reinforced Composite Thermal Performance Prediction System, Thermal Science, 23 (2019), 5, pp. 2857-2865
  5. Liberati, F., et al., Joint Model Predictive Control of Electric and Heating Resources in a Smart Building, IEEE Transactions on Industry Applications, 55 (2019), 6, pp. 7015-7027
  6. Szabłowski, L., The ANN-Supported Control Strategy for a Solid Oxide Fuel Cell Working on Demand for a Public Utility Building, International Journal of Hydrogen Energy, 43 (2018), 6, pp. 3555-3565
  7. Wu, S., Study and Evaluation of Clustering Algorithm for Solubility and Thermodynamic Data of Glycerol Derivatives, Thermal Science, 23 (2019), 5, pp. 2867-2875
  8. Chernyshov, V. N., et al., Microwave Method of Non-Destructive Control of Thermal Characteristics of Building Material, Industrial Laboratory, Diagnostics of Materials, 84 (2018), 10, pp. 29-34
  9. Demirezen, G., et al., Development and Optimization of Artificial Neural Network Algorithms for the Prediction of Building Specific Local Temperature for HVAC Control, International Journal of Energy Research, 44 (2020), 11, pp. 8513-8531

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence