Energy Performance Evaluation Research Articles

Energy performance and decarbonization evaluation of a novel positive energy building using solar PV

Positive Energy Buildings (PEBs) are vital for reducing energy consumption and promoting renewable energy. This study introduces a progressive method to evaluate the energy performance and decarbonization of a PEB warehouse in Central Taiwan, utilizing Building Integrated Photovoltaic (BIPV) façades and recycled coal ash concrete. The research analyzes building energy performance and renewable energy generation through energy modeling, considering different ventilation configurations and BIPV arrangements. The findings emphasize that a VRF cooling system saves 16.39% energy compared to a chiller system. The study also revealed that improving the arrangement of BIPV on the building façade significantly enhances solar energy generation efficiency even with fewer photovoltaics (PVs). The decarbonization aspect is evaluated by estimating the embodied carbon and CO2 emissions during the operational period. The PEB is projected to have a 70-year operational lifespan, functioning as a PEB for approximately 42 years, a Net Zero Energy Building (NZEB) for the following 10 years, and maintaining energy efficiency for an additional 20 years. The BIPV system enables the building to remain carbon-free for up to 50 years of operation and achieve substantial carbon savings, with 90% CO2 emissions reduction after 70 years, amounting to 243,111 kgCO2e/year. The study concludes that adequate maintenance and preservation can significantly enhance building performance and longevity.

Energy performance evaluation of the ASHRAE Guideline 36 control and reinforcement learning–based control using field measurements

This study evaluates the energy performance of ASHRAE Guideline 36–compliant control (ASHRAE 36 control) and reinforcement learning (RL)–based control through experimental field tests and a simulation study. Three field tests were conducted at Oak Ridge National Laboratory’s commercial building test facility in Oak Ridge, Tennessee: a baseline with a baseline conventional control, a test with ASHRAE 36 control, and a test with RL-based control. The selected ASHRAE 36 controls were trim and respond control, as well as variable air volume (VAV) box control. We compared the measured supply air temperature of the rooftop unit, VAV box supply air temperature, and VAV box supply airflow rate across the three test cases. The field data indicated that ASHRAE 36 controls operated as specified by ASHRAE Guideline 36. Based on these data, ASHRAE 36 control achieved a 45 % reduction in hourly averaged HVAC energy consumption compared with the baseline, and RL-based control achieved a 66 % reduction. These potential annual energy savings were confirmed using a calibrated whole-building energy model. Compared with the baseline, ASHRAE 36 control reduced HVAC energy consumption by 42 %, and RL-based control achieved a 54 % reduction. Furthermore, RL-based control reduced total HVAC energy consumption by 21 % more than ASHRAE 36 control.

Investigation of Building Profiles for the Energy Simulation of a Factory Building: A Case Study in South Korea

In the Republic of Korea, the 2030 Nationally Determined Contributions aim for carbon neutrality by 2050, with the building sector targeting a 32.8% reduction in carbon emissions by 2030 compared with the 2018 baseline. To achieve these goals, significant efforts are underway to improve the energy efficiency of buildings. Building energy simulation is a standard method for evaluating energy performance as it assesses the current performance and predicts the potential contributions of energy retrofitting initiatives. However, industrial factories often lack specific energy simulation profiles, posing a challenge for accurate energy performance assessment. This case study aims to bridge this gap by investigating a detailed building profile for factory building based on the extended operational data and experimental measurements within a live factory setting. Energy simulations employing these factory-specific profiles yielded R2 values (coefficient of determination) of 98.2% and 94.1% for cooling and heating energy accuracy, respectively, when compared with the actual monthly consumption data. Additionally, simulations with these profiles demonstrated a 2.81% improvement in R2 accuracy compared to those using conventional office building profiles, particularly enhancing the precision during the cooling season. These findings highlight the effectiveness of customized profiles in building energy simulations, ensuring more precise and reliable energy efficiency assessments.

Comprehensive evaluation of solar floating photovoltaic prospective in Saudi Arabia: Comparative experimental investigation and thermal performance analysis

Recently, floating photovoltaic systems have been regarded as a promising technology for producing clean energy by utilizing the surface of water bodies, such as lakes, rivers and oceans. This study introduces a comparative experimental study and energy performance evaluation of a 1.0 kW offshore floating photovoltaic (FPV) system and a nearby traditional ground-based PV system (GPV) installed in the eastern province of Saudi Arabia. The FPV system was deployed in the Arabian Gulf, 25 m off the coast, at an average depth of 1 to 1.5 m depending on tide, wave, and current intensity. The FPV system employs a strong novel eco-friendly platform structure made of recycled buoyant materials such as engineered plastic drums and wood. This system is anchored with tension cables and concrete blocks that can withstand the changing sea water conditions. The GPV system, on the other hand, was installed 150 m inland from the shore. Real-time monthly data monitoring and assessment indicated that FPV systems outperformed GPV systems in terms of lower PV panel surface temperatures, higher power output, and panel efficiency. Based on daily average back surface temperatures, FPV system temperature was decreased by 7.5 % to 21.34 % when compared to GPV. Moreover, the FPV system efficiency was also increased by 12.2 % when compared to the GPV system. This study aims to assist in promoting the applicability of solar floating photovoltaic systems to synergistically fulfill the requirements of sustainable electricity production for the arid costal community in Saudi Arabia and similar areas.

Large-scale energy cost optimization and performance analysis for dedicated outdoor air system: simulation results from ASHRAE RP-1865

This is the first journal article from the ASHRAE research project RP 1865, “Optimizing Supply Air Temperature Control for Dedicated Outdoor Air Systems,” focusing on the large-scale energy performance evaluation of the optimal control of dedicated outdoor air systems (DOAS). DOAS is a type of air handling system that is installed in buildings to ensure proper ventilation for the built environment. It is acknowledged that DOAS with proper operation strategies can provide sufficient ventilation and dehumidification while achieving energy efficiency. In this regard, there have been efforts to develop advanced control sequences (e.g., optimal control) for DOAS. Still, limited studies have demonstrated the effectiveness of such DOAS controls on a larger scale under varying climate zones with different DOAS configurations. To fill the research gap, this study aims to quantify the energy-saving potentials of applying an optimal supply air temperature (SAT) control strategy for DOAS considering diverse configurations of HVAC systems in various climate conditions across the United States. For this study, we first developed a total of 180 EnergyPlus models accommodating different types of buildings (i.e., detailed medium-sized office and primary school) and HVAC systems (i.e., DOAS types, DOAS sizes, and terminal units) under varying ASHRAE climate zones (i.e., 2A, 3B, 4A, 4C, 6A, and 6B). Next, genetic algorithm (GA)-based optimizations were conducted to determine the optimal DOAS SAT control that would minimize the energy cost of the entire HVAC system operation. Our study of comparing the optimal control to a typical rule-based control (i.e., outdoor air temperature-based reset control) revealed approximately 4–34% of energy cost saving potential by optimizing the DOAS SAT control sequence.

Energy and Exergy-Based Modeling and Performance Evaluation of a Natural Gas-Fired Combined-Cycle Power Plant

Energy and Exergy-Based Modeling and Performance Evaluation of a Natural Gas-Fired Combined-Cycle Power Plant

IMPACT OF THE CLIMATE CHANGE ON THE ENERGY CERTIFICATION OF A MULTI-FAMILIY BUILDING IN VALENCIA

: The European EPBD directive initially emerged as a way to label buildings to inform the consumer. At that time, it sought to compare its performance with other products, such as a washing machine. However, the climatic, economic-social, and energy context is forcing the evaluation of the actual energy performance with pecuniary links. This article compares the actual Valencia weather in 1992, 2002, 2012, 2022, and 2023 with the official one used by the Spanish certification scheme. An old, existing multi-family building is rehabilitated to get a label A. Additionally, it meets the restrictions of the current CTE-HE. The paper assesses the impact of considering the actual weather on their energy performance in both states, before and after rehabilitation, as well as on their energy rating, and discusses the outcomes. All computations have been performed with the recognized software tool CERMA.

The Role of Blockchain-Secured Digital Twins in Promoting Smart Energy Performance-Based Contracts for Buildings

Energy performance-based contracts (EPCs) offer a promising solution for enhancing the energy performance of buildings, which is an overarching step towards achieving Net Zero Carbon Buildings, addressing climate change and improving occupants’ comfort. Despite their potential, their execution is constrained by difficulties that hinder their diffusion in the architecture, engineering, construction, and operation industry. Notably, the Measurement and Verification process is considered a significant impediment due to data sharing, storage, and security challenges. Nevertheless, there have been minimal efforts to analyze research conducted in this field systematically. A systematic analysis of 113 identified journal articles was conducted to fill this gap. A paucity of research tackling the utilization of digital technologies to enhance the implementation of EPCs was found. Consequently, this article proposes a framework integrating Digital Twin and Blockchain technologies to provide an enhanced EPC execution environment. Digital Twin technology leverages the system by monitoring and evaluating energy performance in real-time, predicting future performance, and facilitating informed decisions. Blockchain technology ensures the integrity, transparency, and accountability of information. Moreover, a private Blockchain infrastructure was originally introduced in the framework to eliminate high transaction costs related to on-chain storage and potential concerns regarding the confidentiality of information in open distributed ledgers.

The Early Determination Method of Reservoir Drive of Oil Deposits Based on Jamalbayli Indexes

Summary Historically, the concept of “reservoir drive” aimed to simplify the mathematical modeling in reservoir engineering. Within this framework, the energy of the reservoir, particularly its aquifer, was idealized, leading to classifications such as “partial waterdrive,” “full waterdrive,” “gas cap drive,” and so forth. However, in reality, all existing energy sources interact simultaneously within reservoirs. Accordingly, this study aims to develop a new concept for a more realistic description of reservoir drive mechanisms and evaluation of reservoir energy performance. Numerous computer simulations have revealed a strong correlation between the ratio of relative changes in pore volume to relative changes in reservoir pressure and the reservoir’s energy nature and activity level. Moreover, the noted ratio did not depend on production technology, pressure/volume/temperature properties of hydrocarbon systems, rheological properties of reservoir rocks, or other factors. Based on this correlation, specific parameters termed as Jamalbayli Indexes (JI) have been identified to quantitatively describe reservoir energetic performance. JI consist of two parameters. One of them describes the relative change in pore volume per unit of relative change in reservoir pressure, and the second is the relative change in pore volume per unit of relative change in formation porosity. Here, “relative change” means a change in a parameter relative to its original value. These parameters are dimensionless and can have values around or equal to unity. A new conceptual framework for describing reservoir drive mechanisms based on JI has been formulated. According to this framework, reservoir drive mechanism is determined by comparing the computed JI values with unity rather than relying on subjective assessments of the trend of some functional dependencies. For the first time, it has become possible to express the reservoir drive performance quantitatively and determine the level of energy activity of the reservoirs with the help of JI. Additionally, a technique has been developed to evaluate the numerical values of JI for specific oil (including volatile oil) deposits based on the production data at any stage of production. The proposed methodology was tested using data from the eighth horizon of the Russkiy Khutor field in Russia. The test results not only confirmed the reliability of the obtained model but also demonstrated the adequacy of the proposed concept as a whole. Summarizing the results of other works by the authors, the adequacy of the proposed concept for both oil, gas, and gas condensate deposits has been confirmed. The research findings are expected to contribute to updating the traditional principles used for the mathematical problem statements in fluid flow in porous formations. Additional Key Terms and Phrases Reservoir Drive Mechanism; Early Determination Methods; Reservoir Performance Analysis; Production Data Interpretation; Enhanced Oil Recovery; Reservoir Management; Drive Mechanism Identification; Reservoir Fluid Dynamics; Production Rate Analysis; Reservoir Engineering Techniques; Field Development Planning; Reservoir Simulation; Pressure/Volume/Temperature (PVT) Analysis; Production Monitoring and Evaluation drive mechanisms; production data analysis; volatile oil; Jamalbayli indexes; drive performance indexes

On-site evaluation of indoor thermal comfort and energy performance of a liquid-desiccant assisted air-conditioning system in a high-latent-load building

Indoor humidity control is increasingly important because indoor sensible heat ratio decreases to reduce building energy consumption. However, reference vapor compression cooling systems exhibit energy inefficiency and limitations in maintaining indoor thermal comfort. Therefore, this study proposes an alternative heat-pump-driven liquid-desiccant air-conditioning system, independently controlling air temperature and humidity. The reference and proposed systems are applied to a high-latent-load building to investigate their onsite indoor thermal comfort and energy performance empirically and simultaneously under various outdoor summer conditions. The reference system exhibits a thermal comfort satisfaction ratio of 97% only under limited hot and dry weather. Conversely, the thermal comfort satisfaction ratio sharply drops to 2% or less under humid weather. The proposed system consistently achieves a high thermal comfort satisfaction ratio exceeding 90% under various outdoor summer conditions. In empirical comparisons, the proposed system can maintain a thermally comfortable room for an hour while achieving energy savings exceeding 92.4% and 12.1% under warm and humid (rainy season) and hot and humid outdoor conditions, respectively. The proposed system is concluded to consistently maintain indoor thermal comfort while using energy efficiently, demonstrating its widespread applicability for general high-latent-load buildings characterized by low indoor sensible heat ratio values of 0.56 on average.

Evaluation of energy performance and environmental benefits for transcritical CO2 thermal system in high-speed trains

The conventional air conditioning system used in high-speed railways has limitations in heating performance and environmental impact, necessitating the exploration of alternative refrigerants. The transcritical CO2 system has gained popularity due to its exceptional heating efficiency and environmental benefits. This study aims to evaluate the energy and environmental potentials for transcritical CO2 systems in high-speed trains based on four-vertical-and-four-horizontal railway lines within different climatic regions of China. A high-fidelity transcritical CO2 system model was first developed and validated through experiments. Then, a comprehensive energy and environmental evaluation method was proposed and applied to the four-vertical-and-four-horizontal railway lines. The results indicated that the transcritical CO2 system had a superior heating performance and competitive cooling performance based on daily and annual operations. Furthermore, the transcritical CO2 system exhibited significant environmental advantages with lower total life cycle climate performance for all lines, with an average emissions reduction ratio of 17.6% and a maximum emissions reduction ratio of 26.98%. These findings highlight the competitive energy performance and outstanding environmental benefits offered by transcritical CO2 systems as promising alternatives to air conditioning systems in railway transportation.

Evaluation of heating load energy performance in residential buildings through five nature-inspired optimization algorithms

This study evaluates a new hybrid approach for determining homes’ heating load (HL). The crow search algorithm (CSA), heap-based optimizer (HBO), seeker optimization algorithm (SOA), political optimizer (PO), and harmony search (HS) are the five components of the suggested paradigm. A nonlinear analysis of the effects of eight independent factors on the HL was conducted using the best structure identified in each model. The assessment procedure for the HS technique in this study consisted of three parts. The appropriate population size to utilize in the first phase was found to be the one that yields the best coefficient of determination (R2) value and the lowest root mean squared error (RMSE) value. For CSA-MLP, HBO-MLP, SOA-MLP, PO-MLP, and HS-MLP, respectively, the first phase yielded R2 = 0.96473, 0.95618, 0.96931, 0.97048, and 0.96702, and RMSE = 2.57119, 2.85968, 2.40125, 2.3554, and 2.46872. A battery of tests using a range of different nNew values (between 10 and 100) was applied to the HS-MLP with a population size of 50 in the second phase. The data indicates that the most reliable results are obtained with a nNew-value of 60. For training and testing, this value has RMSE values of 2.61518 and 2.4387 and R2 values of 0.9669 and 0.96783. In the third stage, an experiment with a population size of 50 and nNew of 60 was examined using a range of HMCR values (between 0.5 and 1.4). Concerning training and testing, the results indicate that the HMCR value 1.1 produces the most reliable results; its R2 values are 0.9739 and 0.97207, and its RMSE values are 2.32691 and 2.27488. Lastly, the results demonstrate that the accuracy of the HS-MLP method has been improved by the 3-phase analysis method.

Evaluation of energy performance and ecological benefit of free-cooling system for data centers in worldwide climates

Water-side economizer (WSE) is an effective free-cooling solution aiming to enhance the natural cooling duration and in turn reduce the cooling-energy consumption of data centers. However, the system's performance is constrained by the limited understanding of its control mechanisms and the influence of local climatic conditions on its free-cooling capabilities. To overcome these limitations, a thermodynamic model of the WSE system with control strategies is provided and its adaptability performance in diverse worldwide locations is systematically evaluated. Modelica-based models of chiller plants and control strategies are firstly developed, and then the energy consumption and ecological benefit of the WSE system are investigated via large-scale simulations in worldwide climates. The performance indicators and application potential of the system are demonstrated through visualization maps. The analysis reveals significant energy savings potential of the WSE system, with the capacity to reduce annual cooling energy consumption of data centers by 4.4–33.7 % in hot to marine zones, and even by a remarkable 62.6 % in plateaus and cold zones. Furthermore, it is observed that every 1 °C increase in outdoor air temperature can reduce energy efficiency ratio by 1.3–8.7 % while simultaneously increase PUE by 0.3–1.0 %. The ecological benefit results revealed that the WSE system can effectively harness larger quantities of stable free-cooling resources in mixed and cool climate zones, exceeding its capabilities in hot and warm regions. These results offer valuable insights for the impact of climate on the energy and ecological benefits of WSE system for data center, which can be helpful to guide the design or retrofit of such cooling systems in specific locations, presenting an immense opportunity to maximize cooling-energy savings.

Guidelines for data collection on energy performance of higher-education buildings in Egypt: a case study

ABSTRACT Reliable energy analysis of buildings relies heavily on high-quality data leading to proper indicators. Previous studies have highlighted the importance of data quality in analyzing energy usage in residential and non-residential buildings in order to transform declarations to actions, optimise energy efficiency policies and monitor progress and failures in countries. Collected data must adhere to national and international standards for energy performance in buildings. This study aims to provide practical guidelines for effectively collecting and preparing data suitable for evaluating energy performance in Egyptian higher-education (HE) buildings. The guidelines are developed based on a comprehensive case study, considering data availability in typical educational facilities. Architectural and civil engineering drawings, construction specifications, and occupancy details are accessible. However, actual monthly electrical and natural gas consumption data for individual buildings are lacking. To address this, the study proposes the creation of detailed datasheets for each building, encompassing all energy sources and their electrical and power specifications, such as equipment, machinery, and HVAC systems. These datasheets were utilized to calculate energy consumption and energy usage indicators (EUI). The findings demonstrate that the datasheets enable adequate assessment of energy usage in various spaces within educational buildings, including staff rooms, lecture halls, and laboratories. This facilitates the identification of areas in need of targeted energy efficiency improvements. Notably, the study reveals that electricity consumption in the Faculty of Engineering building is significantly influenced by PCs, laboratories, lighting, and air conditioning.

Energy and exergy performance evaluation of a drying coffee beans system using a photovoltaic–direct solar dryer at different drying temperature conditions

This study investigates the impact of various drying temperatures on the performance evaluation of photovoltaic – direct solar dryers in the coffee bean drying process. The use of photovoltaic systems in solar drying provides opportunities for the future to support clean and eco-friendly renewable energy. Three drying temperature conditions were tested, namely 40°C, 45°C, and 50°C, with the optimum temperature obtained at 50°C. During the drying process, the weather appears to be very sunny and cloudless, resulting in an average solar intensity of 974.36 W/m2. Utilising this solar dryer, it takes 12–16 hours for the coffee bean drying process to achieve a moisture content below 12.5% by the SNI 01-2907-2008 standard, starting from an initial moisture content of 45%. The drying and solar collector efficiencies ranged between 0% to 54% and 67.33% to 88.24%, respectively. Energy consumption is directly proportional to drying efficiency, depicted as the energy utilisation ratio (EUR), with the highest EUR being 22.96%. Meanwhile, the exergy flow (inlet, outlet, and loss) is directly proportional to the solar intensity, forming an open downward parabolic curve, with the average exergy efficiencies obtained at temperatures of 40°C, 45°C, and 50°C being 53.95%, 54.72%, and 56.88%, respectively.

Thermal Behavior and Safety of Fine TAGzT and Its CMDB Propellants Including Characterization and Energy Performance Evaluation

Thermal Behavior and Safety of Fine TAGzT and Its CMDB Propellants Including Characterization and Energy Performance Evaluation

Preparation and properties of nano B/NC/AP@F2602 double-layer energetic fiber

The nano-boron powder (n-B) exhibits remarkable efficacy as a combustion catalyst, making it a prime candidate for use in solid propellant metal burners. Nevertheless, throughout the storage phase, the surface of n-B powder is prone to oxidation and substantial agglomeration, resulting in challenges with ignition and incomplete energy dissipation when utilizing boron powder. In this study, we utilized the coaxial electrospinning technique to produce nanofibers comprised of nano-boron /nitrocellulose/ammonium perchlorate@fluororubber (n-B/NC/AP@F2602), with the nano boron uniformly distributed within the core-shell fibers. In the course of combustion, the fibrous composite of n-B/NC/AP@F2602 undergoes an escalation in the rates of energy output and energy release, owing to the constraints imposed by external F2602((C₂H₂F₂)n and (C₃F₆)n). The n-B/NC/AP@F2602 demonstrates a 1.4-fold increase in peak pressure and a 3.6-fold increase in maximum boost rate when compared to the n-B/NC/AP. The energy performance evaluation results reveal that the mean molecular weight (MC) of combusted products from n-B/NC/AP@F2602 is 29.2 g·mol−1, representing a substantial increase compared to that of n-B/NC/AP. The aforementioned findings exemplify that coaxial electrospinning is an exceedingly efficacious technique for enhancing nanostructures, thereby amplifying the reactivity of energetic particles and offering novel insights into their application in energetic materials.

A methodological framework for optimizing the energy consumption of deep neural networks: a case study of a cyber threat detector

AbstractThe growing prevalence of deep neural networks (DNNs) across various fields raises concerns about their increasing energy consumption, especially in large data center applications. Identifying the best combination of optimization techniques to achieve maximum energy efficiency while maintaining system performance is challenging due to the vast number of techniques available, their complex interplay, and the rigorous evaluation required to assess their impact on the model. To address this gap, we propose an open-source methodological framework for the systematic study of the influence of various optimization techniques on diverse tasks and datasets. The goal is to automate experimentation, addressing common pitfalls and inefficiencies of trial and error, saving time, and allowing fair and reliable comparisons. The methodology includes model training, automatic application of optimizations, export of the model to a production-ready format, and pre- and post-optimization energy consumption and performance evaluation at inference time using various batch sizes. As a novelty, the framework provides pre-configured "optimization strategies" for combining state-of-the-art optimization techniques that can be systematically evaluated to determine the most effective strategy based on real-time energy consumption and performance feedback throughout the model life cycle. As an additional novelty, "optimization profiles" allow the selection of the optimal strategy for a specific application, considering user preferences regarding the trade-off between energy efficiency and performance. Validated through an empirical study on a DNN-based cyber threat detector, the framework demonstrates up to 82% reduction in energy consumption during inference with minimal accuracy loss.

Wall-embedded micro heat pump for radiant heating in buildings: Evaluation of energy and thermal comfort performance

This paper presents a novel radiant heating system with a wall-embedded micro heat pump (WEMHP) for residential buildings. The interior surface temperature of the exterior wall-section empowered by the micro heat pump is independently controlled, enabling distributed thermal comfort delivery. The micro heat pump consists of a miniature compressor along with an aluminum roll-bond condenser and evaporator. In contrast to conventional hydronic radiant systems and heat pumps with separate indoor and outdoor units (i.e., split systems), the WEMHP is a “packaged” system that would not require on-site installation and charging of a secondary water loop and circulation pump or refrigerant piping. This could ultimately lead to reduced installation and maintenance costs. In this study, a detailed system model is presented and integrated with a single-zone building model to assess the energy performance of the WEMHP in heating mode. For a designed living room scenario with an external wall WEMHP-to-wall ratio (HPWR) of 0.6 and window-to-wall ratio (WWR) of 0.2, the simulation results show that up to 23 % energy savings compared with a baseline air-to-air heat pump are possible. The results also indicate the HPWR needs to be higher than 0.4 to achieve performance comparable to the baseline. Additionally, experiments were conducted in a laboratory environment in which surface temperatures were controlled to emulate different scenarios for integration of WEMHP technology and to evaluate thermal comfort conditions. The experimental results show that the median operative temperature differences in the indoor environment were within 0.5 °C for various locations while the largest radiant asymmetry was 2.2 °C for the designed room configuration. Moreover, simulations were conducted to evaluate thermal comfort conditions in applications having a smaller HPWR of 0.4 with various values of WWR. Overall, the combined simulation and experimental study shows that the WEMHP has potential to reduce energy use while maintaining thermal comfort at acceptable levels where the HPWR is higher than 0.4.

A Comparative Analysis of Machine Learning-Based Energy Baseline Models across Multiple Building Types

Building energy baseline models, particularly machine learning-based models, are a core aspect in the evaluation of building energy performance to identify inefficient energy consumption behavior. In smart city design, energy planners and decision makers require comprehensive information on energy consumption across diverse building types as well as comparisons between different types of buildings. However, there is no comprehensive study of baseline modeling across the main building types to help identify factors that influence the performance of different machine learning algorithms for baseline modeling. Therefore, the goal of this paper is to review and analyze energy consumption behavior and evaluate the prediction performance and interpretability of machine learning-based baseline modeling techniques across major building types. The results have shown that the Extreme Gradient Boosting Machine (XGBoost) model is the most accurate baseline modeling method for all building types. Time-related factors, especially the week of the year and the day of the week, have the most impact on energy consumption across all building types. This study is presented as a useful resource for smart city energy managers to help in choosing and setting up appropriate methodologies for better operational effectiveness and efficiencies when designing and planning smart energy systems.