Payal Soni, J. Subhashini^*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1225-1242, 2023, DOI:10.32604/iasc.2023.038155 - 29 April 2023

Abstract In the current context, a smart grid has replaced the conventional grid through intelligent energy management, integration of renewable energy sources (RES) and two-way communication infrastructures from power generation to distribution. Energy management from the distribution side is a critical problem for balancing load demand. A unique energy management strategy (EMS) is being developed for office building equipment. That includes renewable energy integration, automation, and control based on the Artificial Neural Network (ANN) system using Matlab Simulink. This strategy reduces electric power consumption and balances the load demand of the traditional grid. This strategy is More >

Lifan Zhao^1,2, Zetian Huang^1,2, Qiming Fu^1,2,3,*, Nengwei Fang⁴, Bin Xing⁴, Jianping Chen^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2741-2758, 2023, DOI:10.32604/cmes.2023.025500 - 09 March 2023

Abstract Aiming at optimizing the energy consumption of HVAC, an energy conservation optimization method was proposed for HVAC systems based on the sensitivity analysis (SA), named the sensitivity analysis combination method (SAC). Based on the SA, neural network and the related settings about energy conservation of HVAC systems, such as cooling water temperature, chilled water temperature and supply air temperature, were optimized. Moreover, based on the data of the existing HVAC system, various optimal control methods of HVAC systems were tested and evaluated by a simulated HVAC system in TRNSYS. The results show that the proposed More >

Zhengkai Ding^1,2, Qiming Fu^1,2,*, Jianping Chen^2,3,4,*, You Lu^1,2, Hongjie Wu¹, Nengwei Fang⁴, Bin Xing⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2759-2785, 2023, DOI:10.32604/cmes.2023.026091 - 09 March 2023

Abstract The optimization of multi-zone residential heating, ventilation, and air conditioning (HVAC) control is not an easy task due to its complex dynamic thermal model and the uncertainty of occupant-driven cooling loads. Deep reinforcement learning (DRL) methods have recently been proposed to address the HVAC control problem. However, the application of single-agent DRL for multi-zone residential HVAC control may lead to non-convergence or slow convergence. In this paper, we propose MAQMC (Multi-Agent deep Q-network for multi-zone residential HVAC Control) to address this challenge with the goal of minimizing energy consumption while maintaining occupants’ thermal comfort. MAQMC… More >

Peter van den Engel^1,*, Michael Malin², Nikhilesh Kodur Venkatesh¹, Luigi Antonio de Araujo Passos¹

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.3, pp. 783-805, 2023, DOI:10.32604/fdmp.2022.021962 - 29 September 2022

Abstract This research evaluates the performance of a Phase Change Material (PCM) battery integrated into the climate system of a new transparent meeting center. The main research questions are: a. “Can the performance of the battery be calculated?” and b. “Can the battery reduce the heating and cooling energy demand in a significant way?” The first question is answered in this document. In order to be able to answer the second question, especially the way the heat loading in winter should be improved, then more research is necessary. In addition to the thermal battery, which consists… More > Graphic Abstract

Albio D. Gutierrez^a,*, Hayri Sezer^b, Jose L. Ramirez^c

Frontiers in Heat and Mass Transfer, Vol.18, pp. 1-12, 2022, DOI:10.5098/hmt.18.4

Abstract This paper presents a computational model along with a thermal comfort criterion aimed at assisting the design of operating rooms (ORs) from the perspective of meeting suitable flow patterns and thermal comfort conditions for the occupants. The computational model is based on the finite volume method (FVM) to describe the air inside ORs along with the human thermoregulation model implemented in virtual mannequins for thermal comfort. The air model considers turbulent fluid motion, species transport and the conservation of energy, including thermal radiation. The human thermoregulation model incorporates two interacting systems of thermoregulation. Namely, the… More >

Fuyun Zhu, Guoqing Wu^*

Energy Engineering, Vol.118, No.6, pp. 1703-1712, 2021, DOI:10.32604/EE.2021.015602 - 10 September 2021

Abstract Accurate power load forecasting plays an important role in the power dispatching and security of grid. In this paper, a mathematical model for power load forecasting based on the random forest regression (RFR) was established. The input parameters of RFR model were determined by means of the grid search algorithm. The prediction results for this model were compared with those for several other common machine learning methods. It was found that the coefficient of determination (R²) of test set based on the RFR model was the highest, reaching 0.514 while the corresponding mean absolute error (MAE) More >

Koushik Mandlem, Bhaskaran Gopalakrishnan^*, Ashish Nimbarte, Roseline Mostafa, Rupa Das

Energy Engineering, Vol.117, No.4, pp. 165-183, 2020, DOI:10.32604/EE.2020.011406 - 31 July 2020

Abstract The research details the design and development of a spreadsheet based software system that has been built using the principles of Monte Carlo simulation. The simulation has been applied to a residential building with a certain number of rooms, each with specific characteristics pertaining to volume, occupancy, and thermostat set point. The consideration of variables related to the building envelope and weather, and the HVAC system have provided a realistic view that enables the accurate estimation of annual energy usage and costs. The main findings of the research are reflected in the sensitivity analysis that… More >