A dual-benchmark based energy analysis method to evaluate control strategies for building HVAC systems

Du, Zhimin; Jin, Xinqiao; Fang, Xing; Fan, Bo

doi:10.1016/j.apenergy.2016.09.019

Cited by 26 publications

(17 citation statements)

References 23 publications

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“…In China, the total energy consumption of HVAC systems is expected to account for 65% of residential buildings by 2020 [2]. Optimal control strategies have been increasingly developed in building HVAC systems [3]. The energy consumption of building energy systems can be greatly reduced by developing effective control strategies for building HVAC systems [4].…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Control Strategy Using the Load Forecast for Air Conditioning System

Zhao

2020

Energies

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The energy consumption of air-conditioning systems is a major part of energy consumption in buildings. Optimal control strategies have been increasingly developed in building heating, ventilation, and air-conditioning (HVAC) systems. In this paper, a load forecast fuzzy (LFF) control strategy was proposed. The predictive load based on the SVM method was used as the input parameter of the fuzzy controller to perform feedforward fuzzy control on the HVAC system. This control method was considered as an effective way to reduce energy consumption while ensuring indoor comfort, which can solve the problem of hysteresis and inaccuracy in building HVAC systems by controlling the HVAC system in advance. The case study was conducted on a ground source heat pump system in Tianjin University to validate the proposed control strategy. In addition, the advantages of the LFF control strategy were verified by comparing with two feedback control strategies, which are the supply water temperature (SWT) control strategy and the room temperature fuzzy (RTF) control strategy. Results show that the proposed LFF control strategy is capable not only to ensure the minimum indoor temperature fluctuations but also decrease the total energy consumption.

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Section: Introductionmentioning

confidence: 99%

A Fuzzy Control Strategy Using the Load Forecast for Air Conditioning System

Zhao

2020

Energies

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“…Model Predictive Control (MPC), Fuzzy Logic Control, Neuronal Network Control and Cyber-physical control [1], promised to increase the efficiency of building energy systems in order to reduce CO2 emissions and energy consumption [2]. To evaluate the developed control strategies, many researchers compare the developed control strategy with a standard control strategy such as On/Off control, PID control [3] or an ideal controller [4]. They point out the achieved savings with the newly developed control strategy in comparison to the standard one.…”

Section: Introductionmentioning

confidence: 99%

A Representative Simulation Model for Benchmarking Building Control Strategies

KÃ1⁄4mpel¹,

Stinner²,

Gauch³

et al. 2019

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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To increase the energy efficiency of building energy systems, many control strategies have been investigated in recent years. Researchers apply control strategies to different building energy systems in order to evaluate their performance. However, the scientific community lacks a commonly accepted reference building model and evaluation criteria. In this paper, we therefore propose a simulationbased benchmark to rate different control strategies for building energy systems. Based on identified requirements for benchmarking, we design a building model on which researchers can apply different control strategies and compare them with each other. The building consists of five different rooms and an energy system with several heat and cold generators. A concrete core activation and a central air-handling unit with additional decentralized cooling and heating registers supply each room individually. To benchmark a control strategy, the model calculates the consumed energy, the primary energy costs and the indicators of indoor air quality. We apply the benchmark to two different control strategies. The benchmark provides reproducible quantitative assessments of the performance of the tested control strategies. The diversity of the energy system as well as the individual airconditioning of the rooms allow complex and sophisticated control strategies to demonstrate their potentials.

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“…The set point temperatures utilized in the study were chosen to match the Korean government recommendations. In addition, the mechanical system was not considered to investigate changes in building loads solely using fumed silica VIPs in the building envelope, since energy consumptions in buildings have been significantly influenced by mechanical systems [47][48][49]. Contrary to office buildings, the operating schedule of the reference building were not considered in the present study due to uncertainty in occupants' schedules.…”

Section: Ies-ve Modeling Processmentioning

confidence: 99%

A Comparative Study of Energy Performance of Fumed Silica Vacuum Insulation Panels in an Apartment Building

2017

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Abstract:Building insulation materials has a significant impact on building energy consumptions. However, conventional materials are easily flammable and can cause fire disasters in buildings. Therefore, it is important to select appropriate insulation materials for building energy efficiency and safety and Vacuum Insulation Panels (VIPs) are increasingly applied to building insulation. Considering this, the present study investigates energy performance of VIPs with design alternatives, such as window systems, infiltration rates, etc., by using energy simulation. Among various VIPs, fumes silica VIPs were chosen. In addition, eight combinations were compared to find the best energy efficient design conditions. The results of the present study showed that building energy performance can be improved with an appropriate combination of design options including fumed silica VIPs.

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A dual-benchmark based energy analysis method to evaluate control strategies for building HVAC systems

Cited by 26 publications

References 23 publications

A Fuzzy Control Strategy Using the Load Forecast for Air Conditioning System

A Fuzzy Control Strategy Using the Load Forecast for Air Conditioning System

A Representative Simulation Model for Benchmarking Building Control Strategies

A Comparative Study of Energy Performance of Fumed Silica Vacuum Insulation Panels in an Apartment Building

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