Energy Performance Analysis Research Articles

Development of a geothermal-driven multi-output scheme for electricity, cooling, and hydrogen production: Techno-economic assessment and genetic algorithm-based optimization

This study aims to develop an environmentally friendly multi-energy system for sustainable production of electricity, cooling and hydrogen. The study introduces a pioneering geothermal-based system, integrating an ejector refrigeration cycle, a dual-loop organic Rankine cycle, and a hydrogen production unit with proton exchange membrane electrolyzers. The study provides a thorough analysis of the system's energy and exergy performance, as well as its economic feasibility. Through sensitivity and parametric analyses, the research identifies key parameters that significantly influence system performance. The system's innovative design promises minimal environmental impact while delivering multifaceted performance: generating 1.38 MW of electricity, supplying 436 kW of cooling load, and producing 5.39 kg/h of hydrogen. In the exergy analysis, Evaporator1 is identified as the primary contributor to exergy loss, representing 34 % of the total exergy destruction. This is followed by the electrolysis unit, the condenser, and the ejector refrigeration cycle, which contribute 18 %, 14 %, and 12 %, respectively. The system achieves optimal efficiency at an organic Rankine cycle turbine1 inlet temperature of 387 K, yielding a power generation of 885.4 kW and an exergy efficiency of 26.7 %. Beyond this temperature, any further increase leads to a decline in power output due to operational disturbances. A multi-criteria optimization using genetic algorithm is applied, resulting in an optimized system with a cost rate of 18.13 $/h and an exergy efficiency of 38.96 %.

Design and experimental characterization of a propane-based reversible dual source/sink heat pump

The current paper presents the design and energy performance analysis of a propane-based reversible Dual Source/Sink Heat Pump (DSHP). DSHPs offer an alternative to conventional water to water and air to water heat pumps, leveraging the strengths of both technologies in an efficient manner. The developed prototype incorporates an innovative Dual Source/Sink Heat eXchanger (DSHX), enabling the unit operating in various modes, including space heating, space cooling, and domestic hot water production using brine, air or both simultaneously as a source/sink. The DSHX serves as as both a condenser or an evaporator, directly rejecting or absorbing heat from air and/or brine. By eliminating secondary loops and defrost cycles, the DSHX minimizes energy losses. The main novelty of this work lies in the DSHX that integrates external units typically duplicated in DSHPs into a single component, eliminating the need for split refrigerant flow rates, thus avoiding maldistribution, refrigerant charge increase and draining valves. A steady state experimental campaign was conducted in a climatic chamber to characterize the DSHP prototype and validate the DSHX performance models. Heating capacity up to 11.2 kW and COP values up to 4.7 were achieved at nominal compressor speed by supplying hot water at 35 °C with an ambient temperature of 7 °C. Similarly, when producing cold water at 7 °C, cooling capacity and EER reached 9.8 kW and 3.6, respectively, at nominal compressor speed using air as heat sink at 35 °C. The effects of various operating parameters on the overall coefficient of performance and heat duty in both heating and cooling modes, considering air or brine as heat source/sink are analyzed in detail. Results demonstrate enhancements of approximately 15 % in capacity and efficiency compared to earlier work. Moreover, four deterministic models were created in order to predict the behaviour of the DSHX and validated against experimental results, reaching deviation values below 15 %.

Performance assessment of new reliability index of energy in water distribution networks equipped with PATs based on component simultaneous failure scenarios

For a water distribution network (WDN) equipped with pump as turbines (PATs), when a pipe failure scenario occurs, the network performance in renewable energy supply is very important by issues in pressure supply, leakage control, and quality of water. Due to the importance for both water and energy approaches in WDNs equipped with PAT, a reliability of networks performance under pipe failure is evaluated by a novel reliability index with the nature of energy called ERI for the two cases studies as 25-node network (case 1) and the network connected to reservoir No. 23 in Tehran (case 2) in this study. To increase the accuracy and to make the more realistic results for examining higher-order simultaneous failure scenarios given from one to three pipes, the multidimensional performance is considered by energy, water equity, water adequacy and their combinations in ERI. The ERI provided a correlation of the energy assessment for studied networks as 0.99 for case 1 and 0.98 for case 2. The results of the energy performance analysis in case 1 introduced that pipes number 2 and 36 are the most critical pipes, similarly by performance for Case 2, pipes number 2, 4, 31, and 55 are the most critical pipes for repair and maintenance. The loss energy due to worst failure scenario showed that the simultaneous failure of pipes 2-12-21 in case 1 and pipes 2-4 in case 2 can be provided a completely loss energy produced by PATs.

Hybrid building energy modeling method with parameterized prototype models and rapid calibration

Building energy models were widely used in building energy performance analysis and efficiency improvement, such as building demand response assessment and energy system optimization. However, building energy modeling was a time-consuming and complex process. Therefore, this paper proposed a hybrid building energy modeling method based on parameterized prototype models and rapid calibration. The main feature of the method was the rapid generation of target building energy models using the prototype building energy performance database. The parameterized prototype building energy model considered 13 uncertainty parameters. Based on the range of 13 uncertainty parameters, such as wall U-value and solar heat gain coefficient, 1000 simulations were performed by Monte Carlo sampling to generate the prototype building energy performance database. The target building energy model was quickly calibrated by learning from this database. It filtered the models that met the requirements based on the actual building measurement data. Based on this hybrid modeling method, the rapid modeling tool AutoBPS-Hybrid was developed in a ruby environment. Shopping mall buildings located in three different climate zones were selected as case studies for this study. The results showed that if only one building energy model meeting the percentage errors was needed, only 3–4 simulations were required. If it was necessary to match the real uncertainty parameter distributions, an average of about 53 simulations was needed. The building energy models were applied to plug load and lighting control in buildings. The shopping mall buildings in Harbin, Beijing and Chengdu could reduce energy consumption by 10.18–13.33 kWh/m2, 14.43–18.15 kWh/m2 and 11.54–14.69 kWh/m2 per year, respectively.

Evaluating Synergies between Electric Vehicles and Photovoltaics: A Comparative Study of Urban Environments

Electric vehicles (EVs) and photovoltaics (PVs) are expected to be broadly adopted in future power systems. However, the temporal variability of EV load and PV production presents challenges for integrating them into the power grid. This study evaluates and assesses the synergies between EVs and PV systems to maximize solar energy utilization for EV load coverage. The configurations studied include EV charging via the national grid as a reference case (Case 1) and two solar energy harvesting options: EVs powered directly by vehicle-mounted PVs (Case 2) and EV chargers connected to residential PV installations (Case 3). These cases are evaluated across different urban environments with large EV fleets and dissimilar weather conditions: Berlin and Los Angeles. A customized operation profile based on the worldwide harmonized light-duty test cycle (WLTC) and a charge-right-away (CRA) strategy is used. Energy performance analysis is conducted through dynamic simulations using the Modelica language, with environmental and economic indices derived. Key findings highlight the superior performance of residential PV systems in both cities compared to current solar EV technologies, with both solutions offering significant benefits over the reference case. Cases 2 and 3 result in a 44% and 59% reduction in annual energy consumption, greenhouse gas emissions, and charging costs in Berlin, while in Los Angeles, the reductions are 67% and 98%. The average daily solar driving range reaches 20.3% in Berlin and 30.4% in Los Angeles.

Energy performance analysis of multi-chiller cooling systems for data centers concerning progressive loading throughout the lifecycle under typical climates

AbstractThe increasing demand for cooling energy in data centers has become a global concern. Existing studies lack a comprehensive analysis of the energy performance of widely used multi-chiller cooling systems in air-cooled data centers throughout their lifecycle, especially concerning progressive loading. To bridge this gap, this study conducts a thorough assessment of the energy performance of multi-chiller cooling systems throughout the entire lifecycle. Additionally, the impact of climate conditions on the energy efficiency of the cooling systems is analyzed, considering design variations for typical climates. Multi-chiller cooling system models are developed using the test data of cooling equipment and typical control algorithms. The energy performance of the cooling system is thoroughly analyzed under full-range cooling loads and climate conditions. Results show that free cooling time could differ up to 1442 hours at different part load ratios in the same location. Furthermore, the cooling system’s coefficient of performance (COP) varies significantly, by up to 6, at different part load ratios, corresponding to a difference in power usage effectiveness (PUE) up to 0.14. Notably, the average cooling system COP throughout the lifecycle loading is found to be only 11.7, 2.9 lower than the design system COP.

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.

Analysis of energy performance and load matching characteristics of various building integrated photovoltaic (BIPV) systems in office building

Building Integrated Photovoltaic (BIPV) is a key technology for achieving zero-energy buildings by generating electricity and reducing energy consumption. Although many studies have analyzed the impact of BIPV on building energy efficiency, there is a lack of comprehensive comparative analysis of various BIPV systems. This study compared the impact of various BIPV systems on office building energy performance and provided optimal solutions for different climate zones. Simulation models for PV rooftop, PV window, and PV shading systems were developed and validated in EnergyPlus. The energy performance of BIPV systems in different Chinese climates was evaluated using these models. The results show that the PV window and PV shading have the most power generation capability in Beijing, and the PV rooftop has the most power generation capability in Kunming. Energy savings in Kunming are the highest with PV rooftop, PV windows, and PV shading at 111.78 %, 39.36 %, and 44.43 %, respectively. Finally, the study calculated the self-sufficiency rate (SSR) and self-consumption rate (SCR), and their ratio, along with the load matching ratio, were used to assess loading matching. Optimal BIPV schemes were identified for each climate zone, revealing that the PV rooftop combined with the PV shading system achieved the best load matching in Kunming, Guangzhou, Changsha, Beijing, and Harbin, with ratios of 82.00 %, 69.38 %, 70.88 %, 74.78 % and 67.27 %, respectively. These results provide a valuable reference for implementing the BIPV system to achieve zero energy consumption in office buildings under different climatic conditions in China.

The Impact of Building Usage Profiles on Energy Performance Analysis Results In ECO2 Program

The Impact of Building Usage Profiles on Energy Performance Analysis Results In ECO2 Program

Energy efficiency and indoor thermal comfort of railway carriages: Development of an innovative passenger-centric-control framework for HVAC systems

The railway sector's energy impact is increasing, and this trend is expected to persist over the next decade. Particularly, the energy consumption of Heating Ventilation, and Air Conditioning (HVAC) systems is significant among various services provided on board (30 % of total energy requirements) due to the rising attention to passengers' thermal comfort. In this framework, this research proposes an innovative method for enhancing indoor thermal comfort while also studying the associated energy consequences. It consists of an advanced passenger-centric-control framework for HVAC systems that prioritizes comfort, utilising optimized indoor air setpoints, which surpasses the rule-based control logic proposed by the existing standards. To analyse the proposed control framework, a novel mathematical model for the energy, economic, and environmental performance analyses of train HVAC systems, which can incorporate weather data associated with actual railway paths, is developed and validated. To prove the potential of the proposed method, a proof-of-concept analysis is conducted. In particular, for an existing railway coach operating in Italy, the standard and the innovative control logic are tested and compared. The results show an interesting thermal comfort hours increase (≃+1000 h) and energy savings (−27 % yearly), proving the benefits potentially achievable by adopting the proposed method.

Thermodynamic and economic analysis of multi-generation system based on LNG-LAES integrating with air separation unit

LNG consumption is rising globally, releasing significant cold energy during regasification. Coupling LNG vaporization with liquid air energy storage (LAES) maximizes this cold energy recovery, enhancing LAES efficiency. However, current LNG-LAES systems face issues like insufficient high-grade cold energy use and high liquid air temperatures. LAES's inability to recover LNG cold energy during energy release necessitates cold storage fluid, increasing costs. Safety concerns also arise from LNG and air coexisting in the same heat exchanger, and LNG vaporization fluctuations can destabilize LAES operations. This study proposes a multi-generation system (LNG-LAES-ASU) incorporating an air separation unit (ASU) to address these challenges. The ASU recovers LNG cold energy during energy release, adapts to LNG vaporization fluctuations, and reduces ASU energy consumption. Energy, economic, and peak-shaving performance analyses show the system achieves a 91.07 % round-trip efficiency (RTE). The ASU's average energy consumption is 0.1356–0.1506 kWh/Nm³ O₂, much lower than a standalone ASU's 0.4 kWh/Nm³ O₂. Over 30 years, the system yields a net present value (NPV) of $56,111,291 and a dynamic payback period of 3.23 years. Its peak-shaving capacity is 2.47–2.57 times greater than LNG-LAES alone. This research offers valuable insights into efficient LNG cold energy utilization.

Construction and optimization of a waste heat and off-peak operation-assisted absorption carbon capture system

ABSTRACT Carbon capture and storage can reduce the carbon emission directly and effectively. Absorption carbon capture (ACC) is currently the most promising way to remove CO2 from coal-fired power plant, yet the main drawback is the excessive thermal energy consumption for the regeneration process. In this study, a new ACC system that utilizing the low-grade waste heat to generate steam has been proposed, in which system the steam is compressed to increase the saturation temperature to satisfy the thermal energy grade demand of the absorbent regeneration. Heat pump is introduced to increase the inlet pressure and enhance the energy and economic effect of vapor compression and R245fa is found suitable for the system. The vapor generating work can be controlled below 200 kWh t−1 when T wh is higher than 60°C, and COPvg can be higher than 3.5 for situations of T tag,sat not exceeding 130°C. The energy performance and economic analysis of the proposed ACC system driven by the new vapor generation method is analyzed. Off-peak operation by ASS shows good economic effect, the operating cost for the regeneration process of carbon capture is only 69.70 CNY t−1 CO2 under the worst condition and far below the traditional heating method. The new heat supply method for carbon capture presents reasonable energy and economic performance, which is shown suitable for peak shifting of the power grid.

Volumetric Add-On Retrofit Strategy with Multi-Benefit Approach toward Nearly Zero Energy Buildings Target

Around 35% of the total housing stock of the European Union is more than half a century old. The shortage of funds for new construction, combined with rapidly changing economic, social, and technological factors, has led to significant obsolescence. Additionally, this situation makes it difficult to satisfy the owners’ energy, functional, and socio-economic needs. This research aims to develop an innovative retrofit approach that brings multiple benefits to assessing retrofit designs for social housing, with specific emphasis on volumetric envelope additions toward the nearly zero energy buildings target (nZEBs). To achieve the purpose of this study, the research through design methodology was chosen. The research methodology consisted of two phases: design and simulation. First, the design phase focused on re-designing and retrofitting social housing to address various aspects of the functional requirements in developing rational solutions. Second, the simulation phase focused on computational modeling and analysis of energy performance to assess the nZEBs target. The results show that the use of high-efficiency Heating, Ventilation, and Air Conditioning (HVAC) systems and improved material envelopes cut electricity consumption use by 43% and primary energy use by 40% compared to the base case. Photovoltaics (PV) production can meet the total electricity demand for six months. This approach can encourage residents and tenants to actively participate in the retrofit process and increase the real estate value of buildings through improvements in energy efficiency and housing function.

BIM Integration with XAI Using LIME and MOO for Automated Green Building Energy Performance Analysis

Achieving sustainable green building design is essential to reducing our environmental impact and enhancing energy efficiency. Traditional methods often depend heavily on expert knowledge and subjective decisions, posing significant challenges. This research addresses these issues by introducing an innovative framework that integrates building information modeling (BIM), explainable artificial intelligence (AI), and multi-objective optimization. The framework includes three main components: data generation through DesignBuilder simulation, a BO-LGBM (Bayesian optimization–LightGBM) predictive model with LIME (Local Interpretable Model-agnostic Explanations) for energy prediction and interpretation, and the multi-objective optimization technique AGE-MOEA to address uncertainties. A case study demonstrates the framework’s effectiveness, with the BO-LGBM model achieving high prediction accuracy (R-squared > 93.4%, MAPE < 2.13%) and LIME identifying significant HVAC system features. The AGE-MOEA optimization resulted in a 13.43% improvement in energy consumption, CO2 emissions, and thermal comfort, with an additional 4.0% optimization gain when incorporating uncertainties. This study enhances the transparency of machine learning predictions and efficiently identifies optimal passive and active design solutions, contributing significantly to sustainable construction practices. Future research should focus on validating its real-world applicability, assessing its generalizability across various building types, and integrating generative design capabilities for automated optimization.

Renewable Energy Distributed Energy System Optimal Configuration and Performance Analysis: Improved Zebra Optimization Algorithm

The use of distributed energy systems (DES) can utilize local resources to achieve flexible and efficient energy production and supply. However, this aspect of pollutant emission reduction has not been sufficiently investigated in current related studies. On this basis, this study establishes a DES system that integrates a ground-source heat pump, a gas turbine, a photovoltaic device and an energy storage device. An Improved Zebra Optimization Algorithm (IZOA) is proposed for optimizing the capacity of DES devices and the energy supply ratio of the ground-source heat pump. Using the economic cost saving rate (ECSR), pollutant emission reduction rate (PERR) and energy saving rate (ESR) as the optimization objectives, the study builds a DES configuration optimization model. By analyzing the arithmetic example of a large hotel building, the study verifies the effectiveness of the IZOA algorithm in solving the DES configuration optimization problem. This study provides useful research ideas in promoting the development of distributed energy systems, environmental protection and energy conservation.

Comprehensive analysis and identification of energy performance and unsteady two-phase flow patterns based on experiments and comparison between two distinct multiphase flow models

ABSTRACT In the petroleum sector, electrical submersible pumps (ESP) face numerous challenges when handling multiphase flow of gas and liquid. The primary challenge is from the build-up of the gas-bubbles within the impellers of ESPs, leading from moderate to severe deterioration in pump efficiency. Consequently, a comprehensive investigation is conducted, involving a combination of experimental and numerical analyses, to thoroughly explore the effects of gas entrainment on the performance and intricate internal flow mechanisms of a five-stage mixed-flow ESP. All these analysis was carried out under both design (Qd ) and off-design conditions (0.8Qd , and 1.2Qd ). For unsteady numerical calculations, two widely used multiphase-models: The volume of fluid (VOF) and The Euler-Euler model are employed and compared to investigate the versatility/validity of these models in predicting multiphase performance of ESP. The comparison between tests, Eulerian, and VOF models demonstrated that the Eulerian model aligns well with the experimental results. and shows higher-adaptability pattern with the test results. This reveals its best capability/versatility in predicting two-phase performance and internal-flow results for ESP. Moreover, it can more accurately capture the phase slippage inside ESP under two-phase flow. Additionally, this work provides a vision to the broad-applicability of Eulerian-model for complicated machinery such as ESP.

Fuel cells for multirotor unmanned aerial vehicles: A comparative study of energy storage and performance analysis

Hydrogen fuel cells and the economics of unmanned aerial vehicles (UAVs) are gaining global attention. With higher energy densities, fuel cells can overcome the range limitations of lithium battery-powered aircraft. This paper is to address two important issues often overlooked in research on fuel cell UAVs. It innovatively quantified the ranges within which fuel cells remain a better option and originally focused on the impact of altitudes on the power demand. A detailed literature review was conducted to determine the flight profile. Environment models, power demand models, and other models were established using MATLAB to analyse the impact of altitude on performance. Some parameters were obtained through fluid field simulations using Ansys. The study shows that using air-cooled fuel cells in a 3.5 kW UAV is a superior solution compared to lithium batteries when the energy demand exceeds 2.8 kWh. Furthermore, the power demand increases by 3.5 % per kilometre in altitude, and the maximum flight altitude is reduced by approximately 266 m per kilogram of take-off mass. It also emphasizes that solely increasing the air stoichiometric ratio cannot always enhance performance. Through sensitivity analysis, it was found that improving the stack's power density has the highest relative gain.

Energy Performance and Life-Cycle Analysis of Building Retrofits: A Case Study in Abu Dhabi

Highly developed nations worldwide encounter a notable energy demand as their main obstacle. Furthermore, the building sector plays a significant role in contributing to carbon emissions and climate change. In the UAE, buildings consume the largest portion of energy due to the improper selection of design parameters during the building's design phase, which are specifically tailored for the remarkably hot climate in the country. As a result, various studies, initiatives, and policies are focused on enhancing the energy efficiency of buildings. Additionally, retrofitting existing buildings has emerged as a crucial approach to achieving energy efficiency, resulting in several benefits such as reduced costs for operation and maintenance. This research performed an analysis of a commercial building in Abu Dhabi using DesignBuilder, based on energy modeling and simulation. Five main retrofits were examined, accompanied by a cost analysis to determine the most appropriate retrofit for future investments. The results demonstrate that increasing the cooling set point temperature by 4 degrees led to a 19.53% decrease in the annual cooling load. Additionally, retrofitting the chiller resulted in a 16.11% reduction in the annual cooling load, whereas wall insulation had the least impact as a retrofit. It was observed that improving the chiller's coefficient of performance (COP) offered significant advantages, with a payback period of around 5 years, making it the most favorable retrofit for investment. However, the glazing and wall insulation retrofits were considered less beneficial due to their high initial costs and long payback periods.

Renovation Analysis of a Socialist Modernism Office Building–Case Study

Socialist modernist architecture in the Balkan has left a valuable legacy of remarkable buildings from this century, which brought a mixture of new experiences and local traditions. Unfortunately, after the 1990s, many of these buildings have been neglected, improperly treated, or abandoned. This paper focuses on the iconic socialist modernist office building “Rilindja” in Prishtina, Kosovo, which was built in 1979. In 2010, the building envelope was changed in the name of revitalization, without considering the energy aspect. The study aims to present energy performance analysis through cost-optimal renovation measures of the building envelope while restoring the architectural values before the last renovation. Using Archicad and EcoDesigner STAR, a BIM model was created, and energy analysis was conducted. The findings indicate that eighteen proposed energy efficiency measures can achieve a reduction in energy consumption for heating and cooling of more than 80% over the life cycle period of 20 years. The comparison before and after renovation considering restoring and preserving the inherent values, while integrating energy efficiency measures was necessary, as there is a lack of such studies in the general literature. Finally, the potential of restoring the collective memory through cost-optimal analysis is emphasized as an approach for similar cases.

Energy and exergo-environmental performance analysis of a Stirling micro-fridge with imperfect regenerator

In search of very small and ecological refrigeration machines, Stirling chillers are studied on a micro-scale. This article analyzes the performance of a Stirling microcooler using a new modeling approach. This micro-cooler consists of a pillar network as regenerator, a compression and expansion chamber suitable for batch manufacturing, Alpha configuration with helium as working fluid. The Schmidt model with imperfect regeneration is used with consideration of work losses due to gas spring hysteresis. The equations solved analytically using the laws of thermodynamics are used to evaluate the energy and exergy performance of the microcooler. The parameters like height and internal width of the regenerator, phase angle, temperature ratio, swept volume ratio, cooling pressure, dead volume ratio are studied. A numerical code is developed in Matlab. Results show that optimal parameters develop a cooling capacity of 18.99 mW at a phase angle of 45°, a coefficient of performance of 1.104 at an internal height of the regenerator of 0.85 mm, an ecological coefficient of performance of 10.9 mW, an exergy yield of 6.13%, a destroyed exergy of 0.66 mW. The comparison between the present work and those in the literature shows that the current micro-cooler explores a COP improvement of 35%.