Heating, Ventilation And Air Conditioning System Research Articles

Feasibility study with EnergyPlus simulation for solar chemical heat pump unit introduced into building as next-generation energy supply system

From the viewpoint of rising energy demand and energy costs in buildings, there is an urgent need to develop next generation building energy supply systems characterized by improved resource efficiency and environmental friendliness. The solar chemical heat pump (SCHP) unit can provide heating and cooling in buildings with high efficiency and sustainability, positioning it as a potential candidate. A feasibility study is conducted to introduce the SCHP units into a building in Chiba, Japan, to evaluate the operating characteristics and energy-saving potentials. The building and its HVAC (Heating, Ventilation, and Air Conditioning) system featuring the SCHP unit are introduced into the building energy simulation through EnergyPlus software for the first-step examination. 3E (energy, environment, economy) analysis of the distinctions among conventional, chemical heat pump (CHP), and SCHP systems is conducted to enhance the efficiency of building energy supply systems. Furthermore, the effects of different climate zones and heat and electricity storage equipment on operation characteristics are studied. The study reveals that the SCHP system demonstrates a 75% lower energy consumption, 72% decreased CO2 emissions, and 73% reduced running costs than the conventional system in Chiba City. Moreover, it is shown that integrating the heat storage tank and the electricity storage battery into the SCHP system can reduce reliance on external energy, significantly enhancing the system efficiency.

A hybrid clustering approach integrating first-principles knowledge with data for fault detection in HVAC systems

The building sector, primarily through heating, ventilation, and air conditioning (HVAC) systems, accounts for 30% of global final energy consumption and 26% of energy-related emissions, highlighting the urgency for efficient energy management and effective fault detection. Optimizing HVAC system performance is crucial for energy conservation and sustainability. This study introduces a hybrid modeling methodology to enhance HVAC systems’ fault detection and isolation (FDI). Using feature extraction through principal component analysis (PCA) and autoencoder (AE), the proposed approach integrates first-principles knowledge with data to improve the performance of different clustering algorithms (K-means, density-based spatial clustering of applications with noise (DBSCAN), and ordering points to identify the clustering structure (OPTICS) to distinguish datasets of different operating conditions (normal and faulty conditions). The proposed approach is applied to detect common faults in HVAC systems, demonstrating superior performance compared to purely data-driven methods.

Geothermal energy concept applied to All-Air HVAC system

The novel method of combining geothermal energy with an all-air heating, ventilation, and air conditioning (HVAC) system is presented in this work. A building in Lebanon serves as the case study, which aims to determine the necessary mass flow rate for the conditioned space. Rather than permitting ambient air to enter the Air Handling Unit (AHU) directly, the plan calls for a 2-meter-deep geothermal duct to be buried. By adjusting the air temperature prior to it entering the AHU, this geothermal duct helps to improve the efficiency of the HVAC system and lowers the AHU’s yearly energy usage. Furthermore, the idea guarantees that there will always be 100% fresh air available, which means that the all-air HVAC system won’t need to recycle treated air from the conditioned space—also known as return air. According to the findings, the heat rate of the geothermal duct may reach 210 kW, which would result in a large decrease in CO2 emissions and cost savings for the HVAC system.

Design Change and Operational Consideration of the HVAC System during Nuclear Power Plant Decommissioning

The heating, ventilation, and air conditioning (HVAC) system plays a crucial role in ensuring the safety of workers and preventing the release of gaseous radioactive materials into the environment during the decommissioning of a nuclear power plant (NPP). To establish an HVAC operation strategy, decommissioning phases were divided into four stages, and the HVAC systems were reclassified. In addition, assumptions have been made regarding design modifications and maintenance for the reactor containment building (RCB) HVAC, fuel handling building (FHB) HVAC, and main control room (MCR) HVAC. Based on these, for RCB HVAC operation, natural ventilation and RCB purge operation during the transition period are proposed. In the decommissioning stage, recirculation operation, entire ventilation operation consisting of continuous operation and purge operation, and finally partial ventilation operation to purify local space were proposed. Moreover, during the transition period, the FHB HVAC was proposed to operate as normal NPP, and the MCR HVAC was suggested to operate with safety-related equipment removed.

Review of energy-efficient HVAC technologies for sustainable buildings

This review paper provides a comprehensive examination of energy-efficient Heating, Ventilation, and Air Conditioning (HVAC) technologies for sustainable buildings. The focus is on exploring the latest advancements, benefits, challenges, and future prospects in the realm of HVAC systems designed to enhance energy efficiency and promote sustainability in building operations. The review begins with an overview of the importance of energy-efficient HVAC technologies in the context of sustainable building design and operation. It underscores the critical role of HVAC systems in reducing energy consumption, minimizing environmental impact, and enhancing occupant comfort and well-being. The paper delves into various categories of energy-efficient HVAC technologies, including advanced heating and cooling systems, ventilation strategies, and smart controls. Each category is examined in detail, highlighting key features, performance metrics, and real-world applications. Furthermore, the review evaluates the benefits associated with energy-efficient HVAC technologies, such as significant energy savings, reduced operating costs, improved indoor air quality, and enhanced building resilience. It also discusses the potential challenges and barriers to adoption, such as high upfront costs, complexity of implementation, and retrofitting existing buildings. The paper explores emerging trends and innovations in the field of energy-efficient HVAC technologies, including the integration of renewable energy sources, smart sensors and actuators, and predictive maintenance algorithms. These advancements have the potential to further optimize energy performance, increase system reliability, and enable proactive management of HVAC systems. In conclusion, the review emphasizes the importance of energy-efficient HVAC technologies as a cornerstone of sustainable building practices. It underscores the need for continued research, innovation, and collaboration among stakeholders to overcome existing challenges and unlock the full potential of energy-efficient HVAC systems in contributing to a more sustainable built environment. Overall, this comprehensive review provides valuable insights into the current state of energy-efficient HVAC technologies, their applications, benefits, and challenges, while also highlighting opportunities for future advancements and their crucial role in achieving sustainability goals in the building sector.

Heating load prediction in buildings using decision tree machine learning method

In recent years, the burgeoning imperative of energy-efficient building management practices has surged dramatically, underscoring an urgent mandate for comprehensive studies that integrate cutting-edge optimization algorithms with precise heating load forecasting techniques. These studies are not merely endeavors; they represent concerted efforts to increase building energy efficiency and address mounting concerns regarding sustainability and resource utilization. In the intricate domain of heating, ventilation, and air conditioning (HVAC) systems, energy optimization challenges are being meticulously confronted through rigorous exploration and the application of innovative problem-solving methodologies. This pioneering study introduces groundbreaking methodologies by seamlessly integrating two state-of-the-art optimization algorithms— the Red Fox Optimization and the Golden Eagle Optimizer— with the Decision Tree model. This fusion is aimed at enhancing the accuracy of heating load predictions and streamlining HVAC system optimization processes, marking a significant leap toward achieving heightened energy efficiency and operational efficacy in building management practices. The study emphasizes the significance of precise heating load prediction in advancing energy efficiency, realizing cost savings, and fostering environmental sustainability in building management. Furthermore, it delves into the multifaceted impact of various building features on heating load, encompassing variables such as glazing area, orientation, height, relative compactness, roof area, surface area, and wall area. These insights furnish actionable intelligence for refined decision-making processes in both building design and operation. Based on the results, the DT single model experienced the weakest performance among the three models, with R2 = 0.975 and RMSE = 1.608. The model DTFO (DT + FOX) achieves an extraordinary R2 value of 0.996 and RMSE value of 0.961 for heating load prediction, surpassing the performance benchmarks set by other models. This achievement holds considerable promise for aiding engineers in crafting energy-efficient buildings, particularly within the swiftly evolving landscape of smart home technologies.

CIBSE TM54 energy projections III: A case study using dynamic simulation with detailed system modelling

CIBSE TM54 was recently revised and covers best practice methods to evaluate the operational energy use of buildings. TM54 is a guidance document on performance evaluation at every stage of the design and construction process, and during the occupied stage, to ensure that long-term operational performance is in line with the design intent. The main performance evaluation principles in TM54 are a step-by-step modelling approach and scenario testing, to improve the robustness of the design proposal calculations. The latest version brings an updated perspective to the modelling approaches, including dynamic simulation with Heating, Ventilation and Air Conditioning (HVAC) systems. It also incorporates more detailed guidance around risks, target setting, scenario testing and sensitivity analysis. A case study approach is used to explore some of the important aspects described in TM54. TM54 recommends three modelling approaches (aka implementation routes) that a project can follow depending on its scale and complexity: using quasi-steady state tools; using dynamic simulation with a template HVAC system; and using dynamic simulation with detailed HVAC system modelling. As part of a series of three, this case study provides an application of the third implementation route: dynamic simulation using detailed HVAC modelling.

Single imbalanced domain generalization network for intelligent fault diagnosis of compressors in HVAC systems under unseen working conditions

Effective fault diagnosis of compressors in heating, ventilation, and air conditioning (HVAC) systems is critical to ensure service reliability and boost energy efficiency. HVAC compressors are distributed in different areas and work under heterogeneous conditions, which poses emerging challenges to their data-driven modeling. Most existing methods assume multiple category-balanced source domains for model training. Although domain adaptation and generalization methods have emerged to address the data distribution discrepancies in cross-domain fault diagnosis, limited source domains and imbalanced fault categories across domains still constrain the real-world applicability of data-driven models in HVAC compressor fault diagnosis under unseen working conditions. Therefore, this paper studies a significant fault diagnosis problem named single imbalanced domain generalization (SIDG) and proposes a corresponding network (SIDGNet) for intelligent HVAC compressor fault diagnosis. Specifically, a rare fault diagnosis module combined with focal loss is introduced to tackle the class imbalance problem. To achieve better diagnostic boundaries and resist unknown data distribution discrepancies, joint supervised contrastive learning and adversarial learning with specialized data augmentation are introduced as auxiliary modules to improve the robustness and generalizability of SIDGNet. An improved uncertainty-based dynamic weighting mechanism is developed to intelligently balance the weights of module-specific losses during training, which ensures an efficient and stable optimization process. Extensive SIDG fault diagnosis experiments conducted on HVAC compressors demonstrate the superiority of SIDGNet over existing models in SIDG scenarios.

Advancing energy efficiency in livestock building: Simplified building energy simulation tool for geometric design of pigsty

Concerns related to food security and animal welfare have led to increasing interest in analyzing the energy demands of heating, ventilation, and air conditioning (HVAC) systems in livestock buildings. However, building energy simulation (BES) model, which facilitates precise HVAC systems energy analysis, is difficult to use for non-experts, and particularly, its usability drops significantly in livestock buildings, which are often constructed without involvement of building engineers. This study, therefore, developed a tool that can analyze the energy demand of pigsties by changing geometric design variables with only several numerical inputs without separate 3D modeling. Pigsty geometric design types were classified by examining pigsty architectural design manual and web portal map search. A simplified tool, utilizing EnergyPlus and MATLAB graphical user interface, was developed to analyze energy demand in pigsties by leveraging simple user inputs for geometric design modeling. This tool simplifies exploring potential energy savings through geometric design changes in the early design stages of livestock buildings. The methodology introduced in this study lays the groundwork for future enhancements, including the integration of various design-phase variables beyond geometric design.

Performance investigation of a novel positively or negatively pressurized operating room for infection control

Operating rooms are often positively pressurized and maintained at a higher pressure than adjacent areas, preventing contaminated air from entering the sterile surgical environment. However, the COVID-19 outbreak has necessitated the construction of negatively pressurized operating rooms for contagious patients, preventing contaminated air from escaping into adjacent spaces. Therefore, this study developed a heating, ventilation, and air-conditioning (HVAC) system that can have a dual function pressurization, positively or negatively pressurized. High-efficiency particulate air (HEPA) filters were used for filtration. Then, a variable-speed driven (VSD) HVAC system modulates the pressure in response to environmental conditions when changing the pressure from positive to negative or while the door opens. At the same time, the air change rate (ACR) for dilution was implemented through the separated HVAC systems control schemes. Field measurements were performed to validate the results of a computational fluid dynamics (CFD) simulation, which was conducted to compare air particle distributions in a positively and negatively pressurized operating room and the effects of air curtains. The results showed that the positive pressurized operating room has a better airflow pattern and dilutes contaminants faster. In contrast, the negative pressurized system is the best solution for reducing the chance of airborne infection, particularly for contagious patients. Furthermore, utilizing air curtains can provide a better barrier against airborne contaminants, increasing the efficiency of contaminant control measures. The ventilation efficiency could be increased by approximately 10 % by applying an air curtain with a velocity of 0.5 m/s under both types of pressurization.

CIBSE TM54 energy projections II: A case study using dynamic simulation with template systems modelling

CIBSE TM54 was recently revised and covers best practice methods to evaluate the operational energy use of buildings. TM54 is a guidance document on performance evaluation at every stage of the design and construction process, and during the occupied stage, to ensure that long-term operational performance is in line with the design intent. The main performance evaluation principles in TM54 are a step-by-step modelling approach and scenario testing, to improve the robustness of the design proposal calculations. The latest version brings an updated perspective to the modelling approaches, including dynamic simulation with Heating, Ventilation and Air Conditioning (HVAC) systems. It also incorporates more detailed guidance around risks, target setting, scenario testing and sensitivity analysis. A case study approach is used to explore some of the important aspects described in TM54. TM54 recommends three modelling approaches (aka implementation routes) that a project can follow depending on its scale and complexity: using quasi-steady state tools; using dynamic simulation with template HVAC system; and using dynamic simulation with detailed HVAC system modelling. As part of a series of three, this case study provides an application of the second implementation route: using dynamic simulation with template HVAC. This case study provides detailed guidance on undertaking CIBSE TM54 modelling and projecting design stage building performance. The study covers the interpretation and clarifications of how TM54 can be applied, through the dynamic modelling tools using template HVAC systems.

CIBSE TM54 energy projections I: A case study using quasi-steady state modelling

CIBSE TM54 was recently revised and covers best practice methods to evaluate the operational energy use of buildings. TM54 is a guidance document that can be used for performance evaluation at every stage of the design and construction process, and during the occupied stage, to ensure that long-term operational performance aligns with the design intent. The main performance evaluation principles in TM54 are a step-by-step modelling approach and scenario testing, to improve the robustness of the design proposal calculations. The latest edition of this technical memorandum brings an updated perspective to the modelling approaches, including detailed Heating, Ventilation and Air Conditioning (HVAC) modelling and simulation. It also incorporates more detailed guidance around risks, target setting, scenario testing and sensitivity analysis. A case study approach is used to explore and demonstrate some important aspects described in TM54. TM54 recommends three modelling approaches (aka implementation routes) that a project can follow depending on its scale and complexity: using quasi-steady state tools; dynamic simulation with a template HVAC system; and dynamic simulation with detailed HVAC system modelling. As part of a series of three, this case study provides an application of the first implementation route: modelling using quasi-steady state tools. Practical Application This case study provides detailed guidance on undertaking CIBSE TM54 modelling and projecting design stage building performance. The study covers the interpretation and clarifications of how TM54 can be applied, through the quasi-steady-state modelling tools.

Medium spatiotemporal characteristics based global optimization method for energy efficiency trade-off issue in variable flow rate HVAC system

During the optimization and control processes of variable flow rate heating, ventilation, and air conditioning (HVAC) systems, the medium temporal and spatial characteristics often significantly influence the control effectiveness and energy efficiency of the overall system. Unfortunately, much of the existing research predominantly concentrates on enhancing the performance of specific individual components, neglecting the impact of medium temporal and spatial characteristics on the overall HVAC system performance. Consequently, issues such as energy efficiency trade-offs in practical systems remain inadequately addressed. In this paper, the medium spatiotemporal characteristics of HVAC systems are systematically illustrated and modeled. A novel optimization method based on these characteristics is proposed to improve the overall performance of the HVAC system. This method adopts an event-driven optimization strategy to determine the optimal timing with consideration of temporal characteristics, and an adaptive hybrid algorithm is proposed to determine the optimal setpoints with consideration of spatial characteristics. By comparing to conventional methods with constant setpoints, genetic algorithm (GA) based setpoints, and differential evolution (DE) based setpoints in both simulation test and experiment, the proposed method demonstrates the ability to reduce electricity consumption by 21.2%, 13.1%, and 10.0%, respectively. The methodology in this research provides significant guidance for engineers to promote the decoupling control and overall optimization of HVAC systems. Additionally, the results have referable values for implementing the most appropriate algorithm in practice.

Design and optical simulation of heating, ventilation, and air conditioning duct incorporating ultraviolet-C channels based on Bunimovich stadium

A recent breakout of the COVID-19 pandemic inspired researchers to find ideal solutions for removing SARS-CoV-2 from indoor air. In-duct ultraviolet germicidal irradiation was employed in rooms with heating, ventilation, and air conditioning (HVAC) systems to stop the spread of COVID-19. The current investigation introduces Bunimovich stadium-inspired flow channels inside the square-shaped duct. The impact of the Bunimovich channel shape on light distribution is studied and compared with the traditional rectangular-shaped duct. The core of the Bunimovich channel is a square with δ and γ equal to 0.5. A semi-circle surrounds the square's left and right sides. The air velocity in the HVAC system with the Bunimovich channels varies from 10 m/s to 15 m/s, resulting in variation in aerosol particles’ residence period in front of the ultraviolet-C (UVC) source. The Bunimovich channel delivered better UVC irradiance uniformity than a rectangular duct. The uniformity ratio for the Bunimovich channel was 0.788 compared to 0.6949 for the rectangular duct. The UVC dose delivered by the source in the Bunimovich channel varies from 1.48 mJ/cm2 to 3.03 mJ/cm2. The delivered dose is higher than the required 1.2 mJ/cm2 dose for log-4 reduction (i.e. 99.99%).

Modeling, Implementing and Evaluation a Decision Support System Used for Choosing the Best HVAC System in The Buildings, Case Study in Iraq

The life cycle cost of a building is affected by the heating, ventilation, and air conditioning (HVAC) system chosen by the Life Cycle Costs (LCC). Quality, constructability, appearance of the structure's interior and exterior, HVAC size and weight, and LCC are some of the criteria influencing the choice. Methods: To monitor a project's progress based on energy savings, standard measures such as cost variance (CV) and schedule variation have used an idea when tracking the performance of intelligent buildings. Also, as described in the article, this research compared the decision-making limits of Building Information Modelling (BIM) and (MCDM). Analysis: The conventional approach cannot reveal information regarding divergence from the expected level of performance. Based on the outcomes of the construction cost variables, the key finding was the observation of 12 efficient elements. Finding and Novelty: According to the R, a building's most valuable features are its (Energy Saving Features, Warranties, Budget, Protect Your Unit, SEER Ratings, and Home Square Footage). The findings of Actual value (AV) and planned value (PV) were significantly different, as noted by the Multi-Criteria Decision Maker (MCDM). The new method also makes it possible to track project costs and timetables more accurately. The paper will characterize the HVAC Decision Support System's architecture (HVACDSS). Also, a case study of action modeling is provided, and the preliminary findings are addressed. Six criteria characteristics are used by the HVACDSS technique by an analysis of building construction conducted using the WEKA mining tool (decision tree).

Unsupervised separation of the thermosensitive contribution in the power consumption at a country scale

A large part of French electricity consumption variation is due to temperature fluctuations. While HVAC (heating, ventilation and air-conditioning) systems consumption are directly affected by the temperature, other systems (refrigerator, freezer, water heater) can also be driven by weather changes making thermal contribution to overall consumption difficult to extract. This paper presents a “by-design” unsupervised data-driven method to separate the consumptions due to the weather in the overall electricity consumption. The proposed deep-learning model is based on the separation of meteorological parameters from calendar ones within the model architecture. The performances of this model, in particular its ability to split consumption mechanisms, is tested on a synthetic dataset and on the french consumption dataset. Being relatively simple and interpretable, this approach can be generalized to other countries whereasenergy sobriety represents an important challenge we are facing.

Effect of unidirectional airflow ventilation on surgical site infection in cardiac surgery: environmental impact as a factor in the choice for turbulent mixed air flow

Surgical site infection (SSI) in the form of postoperative deep sternal wound infection (DSWI) after cardiac surgery is a rare, but potentially fatal, complication. In addressing this, the focus is on preventive measures, as most risk factors for SSI are not controllable. Therefore, operating rooms are equipped with heating, ventilation and air conditioning (HVAC) systems to prevent airborne contamination of the wound, either through turbulent mixed air flow (TMA) or unidirectional air flow (UDAF). To investigate if the risk for SSI after cardiac surgery was decreased after changing from TMA to UDAF. This observational retrospective single-centre cohort study collected data from 1288 patients who underwent open heart surgery over 2 years. During the two study periods, institutional SSI preventive measures remained the same, with the exception of the type of HVAC system that was used. Using multi-variable logistic regression analysis that considered confounding factors (diabetes, obesity, duration of surgery, and re-operation), the hypothesis that TMA is an independent risk factor for SSI was rejected (odds ratio 0.9, 95% confidence interval 0.4-1.8; P>0.05). It was not possible to demonstrate the preventive effect of UDAF on the incidence of SSI in patients undergoing open heart surgery when compared with TMA. Based on these results, the use of UDAF in open heart surgery should be weighed against its low cost-effectiveness and negative environmental impact due to highelectricity consumption. Reducing energy overuse by utilizing TMA for cardiac surgerycandiminish the carbon footprint of operating rooms, and their contribution to climate-related health hazards.

INTEGRATING SUSTAINABILITY INTO HVAC PROJECT MANAGEMENT: CHALLENGES AND OPPORTUNITIES

As environmental concerns continue to escalate, the integration of sustainability principles into project management practices has emerged as a crucial endeavor across various industries. In the realm of Heating, Ventilation, and Air Conditioning (HVAC) systems, where energy consumption and environmental impact are significant, the incorporation of sustainable practices presents both challenges and opportunities. This review provides an overview of the challenges and opportunities associated with integrating sustainability into HVAC project management. Challenges in integrating sustainability into HVAC project management stem from various factors, including technological limitations, cost considerations, and organizational barriers. Technologically, the adoption of sustainable HVAC solutions often requires investments in advanced equipment and systems, which may not always be readily available or affordable for all projects. Additionally, the upfront costs of implementing sustainable practices can be perceived as prohibitive, especially in industries where budget constraints are prevalent. Moreover, organizational inertia and resistance to change pose significant challenges, as stakeholders may be hesitant to deviate from traditional HVAC methodologies. Despite these challenges, there exist ample opportunities for integrating sustainability into HVAC project management. Advancements in technology, such as the development of energy-efficient HVAC systems and renewable energy integration, provide opportunities to reduce environmental impact while enhancing operational efficiency. Furthermore, the growing emphasis on green building certifications, such as LEED (Leadership in Energy and Environmental Design), incentivizes the adoption of sustainable HVAC practices by offering recognition and financial benefits to projects that meet stringent sustainability criteria. Moreover, the increasing awareness of environmental issues and regulatory requirements underscores the importance of integrating sustainability into HVAC project management. By aligning with regulatory standards and industry best practices, organizations can mitigate risks associated with non-compliance while enhancing their reputation as environmentally responsible entities. While challenges persist, the integration of sustainability into HVAC project management presents significant opportunities for organizations to mitigate environmental impact, enhance operational efficiency, and foster a culture of innovation. By addressing these challenges proactively and leveraging available opportunities, organizations can position themselves as leaders in sustainable HVAC project management.
 Keywords: HVAC, Project Management, Challenges, Sustainability, Review.

Design–operation gap caused by parameter variance in HVAC system control sequences: A simulation-based study on energy efficiency and temperature controllability

During the design phase, the annual energy consumption of heating, ventilation, and air-conditioning (HVAC) systems is frequently simplified or fixed under certain assumptions due to uncertain parameters within the control sequence, resulting in a performance gap between the intended and actual performances. This study assessed the impact of six uncertain parameters on system energy consumption and indoor temperature control under various updating scenarios. First, sensitivity analysis was conducted using the one-at-a-time method to identify the influential impact of the single uncertain parameter. Then, mutual impact analysis was conducted to showcase how different parameters affect each other, and mixed impact analysis was applied to evaluate how intended design performance converges to actual operating outcomes. A detailed physical model of a single-zone variable air volume system was developed to enable a comprehensive evaluation across different operational conditions. The results indicate that a 10% change in some parameters can lead to a 20∼30% increase in energy consumption, especially during low-load winter months. Properly evaluating the influence of one parameter is difficult without taking the effects of additional parameters into account, and some combinations of parameters can significantly decrease the system performance. These results underscore the necessity of considering the updating and combination scenarios of different parameters within the control sequences during the design phase.

Grey-box model-based demand side management for rooftop PV and air conditioning systems in public buildings using PSO algorithm

As the major power consumer in buildings, Heating, ventilation and air conditioning (HVAC) systems can significantly contribute to the economical operation of the power system during the peak periods in summer or winter, by flexibly responding to the grid demands. Indoor air temperature set-point resetting is a typical passive demand response (DR) control strategy that have potentials to be widely implemented by inverter air conditioners in residential buildings. However, in the existing small and medium-size public buildings, the compressor motor of HVAC systems mostly does not allow for stepless speed changes. This means that the indoor temperature set-point resetting strategy may results in frequent on/off switching of the chiller plant, leading to a compromised lifespan. Although rooftop photovoltaic systems (PVs) are expected to be widely adopted in new buildings, their potential for peak load shaving or valley load filling has received limited investigation. This study proposes a grey-box model-based demand side management (DSM) method for variable air volume systems (VAVs) and rooftop PVs in public buildings. The DSM method utilizes the particle swarm optimization (PSO) algorithm to determine optimal indoor air temperature and/or evaporator outlet water temperature set-point schedules for the VAVs, as well as optimal charging/discharging schedules for the storage battery of rooftop PVs. This approach aims to reduce the peak power demands of the integrated system without causing severe thermal discomfort, increasing chiller mechanical costs (refers to frequent on/off switching of the chiller plant in this paper), or overcharging/over-discharging of storage batteries. The results of case studies demonstrate that the strategy of co-resetting indoor air temperature – evaporator outlet water temperature set-points outperforms the indoor air temperature set-point resetting strategy in terms of both peak power demands reduction and mechanical cost saving when applied to the VAVs in low performance buildings. In comparison, for the VAVs installed in normal buildings, both the strategies yield significant decreases in peak power demands and mechanical cost by fully utilizing the thermal capacity of the building internal thermal mass. Furthermore, by implementing the DSM method for rooftop PVs, the integrated system can achieve zero or near-zero net power demands during the DR periods. The proposed DSM method can also be utilized in valley load filling programs to facilitate the accommodation of renewable energy.