Energy Efficiency Perspective Research Articles

The impact of trees on the peak cooling load of detached rural residences

Trees can reduce heat radiation for adjacent farmhouses, achieving cooling and energy-saving effects in summer. However, there is still a lack of research on the quantitative influence of trees’ parameters and their spatial orientation on the cooling load of farmhouses. This knowledge gap hampers the scientific greening of residences from an energy-efficiency perspective and leads to wasted ecological benefits. Taking Gao Hong Town’s residences in China as an example, by comprehensively applying remote sensing technology, frequency statistics, and numerical simulation, the representative tree-farmhouse information model was constructed. The ENVI-met software was used to simulate and extract the temperatures of external walls under 54 scenarios. The Radiant Time Series Method (RTSM) was then used to calculate peak cooling load with trees under different scenarios. Sensitivity analysis indicates that trees on the south side have the most significant impact on the disturbance rate of peak cooling load of trees to farmhouses (PCLTD), reaching up to 4.4 %, followed by the west, east, and north sides with PCLTD of 1.6 %, 1.1 %, and 0.8 %, respectively. According to the sensitivity of the minimum distance between wall and tree canopy (DW-T) to PCLTD, the 1 m-5 m range of DW-T can be divided into three zones: high-sensitivity (1 m-2 m), medium-sensitivity (2 m-4 m), and low-sensitivity (4 m-5 m).For trees on the south side with leaf area density (LAD) of 1 m2/m3, 2 m2/m3, and 3 m2/m3, the corresponding PCLTD are 3.4 %, 4.4 %, and 4.9 %; for Diameter of Tree Canopy (DC) of 5 m, 7 m, and 9 m, the respective PCLTD are 4.4 %, 6.2 %, and 8.3 %.To maximize the energy-saving effects of trees on farmhouses, it is recommended that the DW-T for trees on the south be less than 3 m, and for trees on the west and east, less than 2 m.These findings support optimizing tree planting strategies adjacent to rural residences in China from an energy-saving perspective, contributing to the improvement of thermal environments and the assessment of energy efficiency.

PhotoROMP: The Future Is Bright.

Since the earliest investigations of olefin metathesis catalysis, light has been the choice for controlling the catalyst activity on demand. From the perspective of energy efficiency, temporal and spatial control, and selectivity, photochemistry is not only an attractive alternative to traditional thermal manufacturing techniques but also arguably a superior manifold for advanced applications like additive manufacturing (AM). In the last three decades, pioneering work in the field of ring-opening metathesis polymerization (ROMP) has broadened the scope of material properties achievable through AM, particularly using light as both an activating and deactivating stimulus. In this Perspective, we explore trends in photocontrolled ROMP systems with an emphasis on approaches to photoinduced activation and deactivation of metathesis catalysts. Recent work has yielded a myriad of commercial and synthetically accessible photosensitive catalyst systems, although comparatively little attention has been paid to achieving precise control over polymer morphology using light. Metal-free, photophysical, and living ROMP systems have also been relatively underexplored. To take fuller advantage of both the thermomechanical properties of ROMP polymers and the operational simplicity of photocontrol, clear directions for the field are to improve the reversibility of activation and deactivation strategies as well as to further develop photocontrolled approaches to tuning cross-link density and polymer tacticity.

Enhancing Occupant Comfort and Building Sustainability: Lessons from an Internet of Things-Based Study on Centrally Controlled Indoor Shared Spaces in Hot Climatic Conditions.

It is well known that buildings have a sizeable energy and environmental footprint. In particular, in environments like university campuses, the occupants as well as occupancy in shared spaces varies over time. Systems for cooling in such environments that are centrally controlled are typically threshold driven and do not account for occupant feedback and thus are often relying on a reactive approach (fix after identifying problems). Therefore, having a fixed thermal operating set point may not be optimal in such cases-both from an occupant comfort and well-being as well as an energy efficiency perspective. To address this issue, a study was conducted which involved development and deployment of an experimental Internet of Things (IoT) prototype system and an Android application that facilitated people engagement on a university campus located in the UAE which typically exhibits hot climatic conditions. This paper showcases data driven insights obtained from this study, and in particular, how to achieve a balance between the conflicting goals of improving occupant comfort and energy efficiency. Findings from this study underscore the need for regular reassessments and adaptation. The proposed solution is low cost and easy to deploy and has the potential to reap significant savings through a reduction in energy consumption with estimates indicating around 50-100 kWh/day of savings per building and the resulting environmental impact. These findings would appeal to stakeholders who are keen to improve energy efficiency and reduce their operating expenses and environmental footprint in such climatic conditions. Furthermore, collective action from a large number of entities could result in significant impact through this cumulative effect.

Energy-Efficient BWP Configuration for Multi-Slice Users.

Fifth Generation (5G) mobile networks introduce the concept of slicing to ensure isolation among the various supported heterogeneous services. The User Equipment (UE) can be connected to multiple slices simultaneously. Additionally, the notion of a Bandwidth Part (BWP) was also instigated to reduce power consumption. A BWP is a small chunk of the bandwidth scanned by the UE to retrieve its service data. Therefore, a UE connected to multiple services can be configured with multiple BWPs each associated with a given service. Such UEs find themselves scanning multiple BWPs, which can be time consuming and highly energy intensive. Hence, it is paramount to study the appropriate choice of the BWP configuration from an energy-efficiency perspective for multi-slice users depending on their battery level. In this paper, two energy-efficient BWP selection solutions are proposed for users connected to multiple slices. The first solution is based on a centralized approach where UEs are stirred optimally to the best BWP configuration, while the second solution relies on a user-centric distributed approach using non-cooperative game theory. The proposed schemes take into account the users' battery level and their sojourn time in the network as well as the scanned BWP size. Both solutions are compared with one another and against the legacy solution. Intensive simulation results demonstrate the efficiency of our proposition in terms of users' energy efficiency and quality of service.

The impact of varying trolley case usage modes and weights on body posture

ObjectiveTo study the body posture characteristics when walking with trolley case, and to explore the effects of different usage methods and weights of trolley case on body posture characteristics. MethodsFifteen subjects pushed and pulled(Condition 1 and 2) the case with three load weights of 10 %, 20 % and 30 % of their own body weight with 0 % no load as baseline for both conditions. The basic gait parameters, kinematic and kinetic data were collected using the VICON infrared motion capture system and a 3D force platform. Two repeated measures factor (condition×weight) analysis of variance was used for statistical analysis of the gait temporal and spatial parameters, as well as trunk angle, kinetic ground reaction force, shoulder joint force, and trunk moment. ResultsSignificant condition*weight interactions were detected in DLST (Double Limb Stance Time) (F=5.341，P = 0.006), GRF (Ground Reaction Force) in frontal plane (F=10.507, p < 0.001) and vertical plane (F=3.751, p = 0.021), shoulder joint force in sagittal plane (F=21.129, p < 0.001), and flexion-extension angle of the trunk in the sagittal plane (F=4.888, p < 0.010). Significant main effects were detected in walking speed (F=35.842, p < 0.001), right support time (F=12.156, p < 0.001), left swing time (F=8.506, p < 0.001), left support time (F=1.122, p < 0.001), right step length (F=33.900, p < 0.001), and left step length (F=14.960, p < 0.001) under different weights. A significant main effect was detected in sagittal GRF (F=11.77, p < 0.001), trunk rotation angle (F=4.124, p = 0.016), amplitude of COM (F=2.993, p = 0.046), under different weights. ConclusionWhen the weight of the case exceeds 20 % of the body weight, from the perspective of energy efficiency, the push method is more advantageous than the pull method. When walking with luggage, people tend to maintain the stability of their trunk posture by adjusting the force on their arms more often.

Energy Flow Modeling and Low Carbon Analysis of Processoriented Production Line

Nowadays, energy and environmental problems are becoming more and more prominent, and the energy-based manufacturing industry also needs to face huge energy consumption problems. Therefore, production processes need to be investigated from an energy efficiency perspective at an early design stage so that maximum benefits can be obtained at low cost, low time and low risk. This process industry carbon emissions system does not calculate the consumption of raw materials and electricity in a generalized way at the boundaries of the plant. Rather, we delve into each step of the process and perform mathematical modeling of the process through a graphical approach, incorporating each link and factor that constitutes and influences the change in carbon emissions, and performing an aggregation of carbon emissions for the entire production line. It facilitates the subsequent improvement and optimization of the entire process-based production line, providing the basis for implementing and establishing the best energy-saving system.

RIS-NOMA Integrated Low-Complexity Transceiver Architecture: Sum Rate and Energy Efficiency Perspective

RIS-NOMA Integrated Low-Complexity Transceiver Architecture: Sum Rate and Energy Efficiency Perspective

Improving agricultural sustainability through farm mergers: an energy efficiency perspective

ABSTRACT The aim of this paper is to investigate agricultural sustainability as a collective issue involving multiple rather than individual farms. Through the utilization of energy consumption as a proxy, we propose a novel methodology that evaluates the impact of farm consolidations on agricultural sustainability while accounting for resource preferences. Our approach incorporates the ordered weighted averaging (OWA) operator within an inverse data envelopment analysis (IDEA) model to identify post-merger farms that meet preset efficiency targets. We employ a DEA cross-efficiency (DEA-CE) procedure to select merger plans that maximize agricultural sustainability for each preference scenario. By analysing a case study of 43 tomato greenhouse farms in Biskra, northern Algeria, our findings demonstrate that mergers can significantly enhance agricultural sustainability, surpassing the potential of individual farms by a factor of over 15. Additionally, the adoption of the most sustainable merger plan can lead to energy savings of more than 69%. Irrespective of the preference scenario, substantial energy savings in machinery, fertilizers, diesel, and electricity ranging from 22.92% to 73.73% were observed. These results emphasize the strategic role of merger processes in promoting agricultural sustainability and optimizing resource utilization.

A Thermodynamics Model for the Assessment and Optimisation of Onboard Natural Gas Reforming and Carbon Capture

The paper examines pre-combustion carbon capture technology (PreCCS) for liquefied natural gas (LNG) propelled shipping from thermodynamics and energy efficiency perspectives. Various types of LNG reformers and CCS units are considered. The steam methane reformer (SMR) was found to be 20% more energy efficient than autothermal (ATR) and methane pyrolysis (MPR) reactors. Pressure swing adsorption (PSA) had a lower energy requirement than membrane separation (MEM), cryogenic separation (CS), and amine absorption (AA) in pre-combustion carbon capture, with PSA needing 0.18 kWh/kg CO2. An integrated system combining SMR and PSA was proposed using waste heat recovery (WHR) from the engine, assuming similar efficiency for LNG and H2 operation, and cooling and liquefying of the CO2 by the LNG. The SMR-PSA system without WHR had an overall efficiency of 33.4% (defined as work at the propeller divided by the total LNG energy consumption). This was improved to 41.7% with WHR and gave a 65% CO2 emission reduction. For a higher CO2 reduction, CCS from the SMR heater could additionally be employed, giving a maximum CO2 removal rate of 86.2% with 39% overall energy efficiency. By comparison, an amine-based post-engine CCS system without reforming could reach similar CO2 removal rates but with 36.6% overall efficiency. The advantages and disadvantages and technology readiness level of PreCCS for onboard operation are discussed. This study offers evidence that pre-combustion CCS can be a serious contender for maritime propulsion decarbonization.Graphical

Modeling uncertainty in positive energy districts through a non-probabilistic approach

Positive Energy Districts (PEDs) transcribe an emerging energy transition paradigm for rapid upscaling of building energy efficiency programs to match the urgency of climate mitigation and adaptation. PEDs facilitate pro-active sharing of information and experiences, responsive learning and dissemination, and cooperation across sectors and disciplines. The rapid evolution of technologies for energy efficiency and integration of renewable energy in buildings requires a research-to-design approach. Therefore, it is imperative that a designer makes informed decisions at an early stage of design from an energy-efficiency perspective. However, since PED design involves a significant number of stakeholders, the design parameters could be highly uncertain, which eventually affect the quality of the design solution space. This study uses a bilateral process workflow to quantify risks using a nonprobabilistic technique and a PED roadmap structure. The workflow evaluates different PED scenarios and quantifies the PED potential for the city of Sint-Niklaas in Belgium. The results indicate that risk quantification significantly improves PED decision-making when evaluating collective solutions (district heating) for a district.

Modeling an Optimal Environmentally Friendly Energy-Saving Flexible Workshop

From the perspective of energy efficiency and environmental sustainability, the scheduling problem in a flexible workshop with the utilization of automated guided vehicles (AGVs) was investigated for material transportation. Addressing the dual-constrained integrated scheduling challenge involving machining machines and AGVs, a scheduling optimization model was established with makespan, workshop energy consumption, and processing quality as the optimization objectives. To effectively solve this model, an enhanced whale optimization algorithm (IWOA) was proposed. Specifically, nonlinear convergence factors, adaptive inertia weights, and improved helix positions were introduced into the standard whale optimization algorithm to update the model. Furthermore, a loss function was constructed based on fuzzy membership theory to obtain the optimal compromise solution of the multi-objective model. The research results indicate that: (1) The IWOA obtained the optimal solutions on benchmark instances MK01, MK02, MK04, MK07, and MK08; (2) The IWOA outperformed the WOA(1), WOA(2), WOA-LEDE, and NSGA-II algorithms in the two instances provided in this paper, demonstrating strong robustness of the model; (3) Although the multi-objective model constructed in this paper could not surpass the single-objective optimal solution in individual objectives, it achieved compensation in other objectives, effectively balancing the trade-offs among the makespan, workshop energy consumption, and processing quality of the three objectives. This research offers an effective practical approach to address green flexible workshop scheduling with AGV transportation.

Symbiotic Backscatter Communication Underlying a Cell-Free Massive MIMO System

In ambient backscatter communications, backscatter devices (BDs) utilize ambient “legacy” radio signals as both a harvested energy source and a carrier on which to modulate data. Symbiotic radio, a subtype in which the legacy system assists both its own users and underlaid BDs, has attracted much research interest recently. Furthermore, cell-free massive multiple-input multiple-output (CF mMIMO) systems are promising for beyond-5G networks from both spectral and energy efficiency perspectives. To reap the benefits of both, we consider a primary CF mMIMO system where the access points (APs) aid an underlaid BD layer to both harvest energy and reflect information toward the primary receivers (which receive data from both layers). To acquire separate channel state information (CSI) of the direct and backscattered channels at the APs, a two-phase uplink pilot training method is proposed, with the effects of pilot contamination and spatial correlation between antennas accounted for. However, the receivers are assumed to only have partial CSI (statistical knowledge plus instantaneous phase information for partially-coherent reception). Assuming uplink/downlink radio channel reciprocity, the CSI is used to design downlink precoding vectors for the APs such that channel hardening is enhanced and both primary receivers and BDs benefit. We derive expressions for the average signal-to-interference-plus-noise ratios of both primary and backscatter signals, accounting for the effects of imperfect CSI, spatial correlation, pilot contamination, and channel hardening. Furthermore, the average power harvested in the BDs is derived. Simulation results demonstrate that the performance of the proposed scheme is much more uniform across all devices with CF mMIMO than with conventional co-located mMIMO. The use of CF mMIMO also largely removes the need for special consideration of the BD layer in the symbiotic system, which is not the case with co-located mMIMO.

Separation of a two binary-azeotrope acetonitrile-cyclohexane-toluene ternary mixture via continuous triple column extractive distillation with heat integration: design, simulation, and multi-objective genetic-algorithm (MOGA) optimization

ABSTRACT Using a sustainable method for separating azeotropic mixtures, such as extractive distillation, is crucial for environmental and resource sustainability. Cyclohexane, acetonitrile, and toluene are essential solvents in different chemical processes. This ternary mixture has two binary azeotropes between cyclohexane-acetonitrile and acetonitrile-toluene at atmospheric pressures. Using residue curve maps and a uni-volatility line, n-butylbenzene was selected as a viable entrainer for extractive distillation, among other possibilities. Unlike conventional designs, the recycled entrainer was only sent to the first column in this simulation. The wasted energy from the recycled entrainer was used to supply reboilers duty through integration. A 3-D material balance was performed to understand the separation procedures better. High-purity acetonitrile, cyclohexane, and toluene will also be obtained from the first, second, and third columns. Finally, a multi-objective genetic algorithm with 14 key decision variables was utilized to reduce total annual cost (TAC) and CO2 emissions and improve thermodynamic efficiency as objective functions from economic, environmental, and energy efficiency perspectives. Optimized results reveal that a heat-integrated design reduces almost 25% TAC and 46% CO2 emissions compared to conventional extractive distillation and does not significantly affect thermodynamic efficiency. This research could be valuable for separating azeotrope systems from other ternary mixtures.

Network-Assisted Full-Duplex Cell-Free Massive MIMO: Spectral and Energy Efficiencies

We consider network-assisted full-duplex (NAFD) cell-free massive multiple-input multiple-output (CF-mMIMO) systems, where full-duplex (FD) transmission is virtually realized via half-duplex (HD) hardware devices. The HD access points (APs) operating in uplink (UL) mode and those operating in downlink (DL) mode simultaneously serve DL and UL user equipments (UEs) in the same frequency bands. We comprehensively analyze the performance of NAFD CF-mMIMO from both a spectral efficiency (SE) and energy efficiency (EE) perspectives. Specifically, we propose a joint optimization approach that designs the AP mode assignment, power control, and large-scale fading (LSFD) weights to improve the sum SE and EE of NAFD CF-mMIMO systems. We formulate two mixed-integer nonconvex optimization problems of maximizing the sum SE and EE, under realistic power consumption models, and the constraints on minimum individual SE requirements, maximum transmit power at each DL AP and UL UE. The challenging formulated problems are transformed into tractable forms and two novel algorithms are proposed to solve them using successive convex approximation techniques. More importantly, our approach can be applied to jointly optimize power control and LSFD weights for maximizing the sum SE and EE of HD and FD CF-mMIMO systems, which, to date, has not been studied. Numerical results show that: (a) our joint optimization approach significantly outperforms the heuristic approaches in terms of both sum SE and EE; (b) in CF-mMIMO systems, the NAFD scheme can provide approximately 30% SE gains, while achieving a remarkable EE gain of up to 200% compared with the HD and FD schemes.

A closed loop case study of decentralized food waste management: System performance and life cycle carbon emission assessment

Food waste (FW) has become a worldwide issue, while anaerobic digestion (AD) has appeared as a widely adopted technology to recover energy and resources from FW. Compared to many existing case studies of centralized AD system, the comprehensive study of decentralized micro-AD system from both system energy efficiency and carbon emission perspective is still scanty, particularly system operated under ambient temperature conditions. In this study, an actual decentralized micro-AD system with treating capacity of 300 kg FW/d for a local hawker center in Singapore was reported and evaluated. The results showed that 1894.5 kg of FW was treated and 173 m3 biogas with methane content of 53 % was produced during the experimental period of 75 days. The methane yield results showed a high FW degradation efficiency (87.87 %). However, net energy consumption and net carbon emission were observed during the experimental period. Nevertheless, energy self-efficiency and carbon neutrality, even net energy output and carbon reduction, can be achieved by increasing daily FW loading and biogas engine efficiency. Specifically, the FW loading for system energy self-efficiency was identified as 159 kg/d for engine efficiency of 35 % at a high kitchen waste/table waste ratio (63 %/37 %, with covid-19 dine-in restrictions); while they were 112 and 58 kg/d for engine efficiency of 25 % and 35 %, respective, at a low kitchen waste/table waste ratio (31 %/69 %, without covid-19 dine-in restrictions). The carbon emission ranged from 156.08 kg CO2-eq/t FW to −77.35 kg CO2-eq/t FW depending on the FW loading quantity and engine efficiency. Moreover, the sensitivity analysis also showed that the used electricity source for substitution influenced the carbon emission performance significantly. The obtained results imply that the decentralized micro-AD system could be a feasible FW management solution for energy generation and carbon reduction when the FW loading and engine electrical efficiency are carefully addressed.

Ensuring Data Freshness in Wireless Monitoring Networks: Age-of-Information-Sensitive Coverage and Energy Efficiency Perspectives

With the development of IoT, the sensor usage has been elevated to a new level, and it becomes more crucial to maintain reliable sensor networks. In this paper, we provide how to efficiently and reliably manage the sensor monitoring system for ensuring data freshness. A sensor transmits its sensing information regularly to the data center (DC), and the sensed information generally has the correlation over the space and the time. Hence, the accuracy of the estimated information from the sensed information decreases as the target location for information estimation is further away from the sensor or the AoI, the elapsed time from the information generation, increases. Therefore, by considering the effect of the AoI and the distance from the sensor on the estimation error, we newly define an error-tolerable sensing (ETS) coverage as the area that the estimated information at the DC is with smaller error than the target value. To analyze the impact of the AoI on the ETS coverage, we derive the η-coverage probability, which is the probability that the ETS coverage is greater than η ratio of the maximum sensor coverage, and the average ETS coverage. We also provide the optimal transmission power of the sensor, which minimizes the average energy consumption while guaranteeing certain level of the η-coverage probability. Numerical results validate the theoretical analysis and show the tendency of the optimal transmission power according to the maximum number of retransmissions. This paper can pave the way to efficient design of the AoI-sensitive sensor networks.

The optimal electrode pore size and channel width in electrochemical flow cells

Microfluidic fuel cells, electrolyzers, and redox flow batteries utilize laminar flow channels to provide reactants, remove products and avoid their crossover. These devices often also employ porous flow-through electrodes as they offer a high surface area for the reaction and excellent mass transfer. The geometrical features of these electrodes and flow channels strongly influence energy efficiency. We derive explicit analytical relations for the optimal flow channel width and porous electrode volumetric surface area from the perspective of energy efficiency. These expressions are verified using a two-dimensional tertiary current distribution and porous electrode flow model in COMSOL and are shown to be able to predict optimal parameters in commonly used flow-through and interdigitated flow fields. The obtained analytical models can dramatically shorten modelling time and expedite the industrial design process. The optimal channel width and pore sizes we obtain, in the order of 100 microns and 1 micron respectively, are much smaller than those often used. This shows that there is a significant room for improvement of energy efficiency in flow cells that can sustain the resulting pressure drop.

Wireless Multi-Interface Connectivity with Deep Learning-Enabled User Devices: An Energy Efficiency Perspective

Undoubtedly, future Beyond 5G (B5G) and 6G networks will be empowered by AI and Machine Learning (ML) technologies. However, current Deep Learning methods consume tremendous power, making them unsuitable to be deployed at edge Access Points (AP) or user devices. As energy efficiency will become one of the major Key Performance Indicators in 6G, there is an urge for realizing lowpower yet highly efficient Deep Learning at user devices, the most severely battery-limited entities. We analyze this issue through the problem of distributed user-to-multiple APs association optimization in B5G networks that integrate diverse wireless interfaces such as Sub-6GHz and mmWave bands. In the proposed Deep Reinforcement Learning (DRL) framework, each device is equipped by a light-weight Deep Q-Network (DQN), which enables it to self-optimize its APs and interfaces association to fulfill the stringent Quality of Service (QoS) requirements of its various applications. We analyze the energy consumption of the device DQN, and investigate key performance trade-offs in terms of sum-rate, user outage and energy efficiency, while disclosing the major power consuming elements of user DQN. Finally, crucial open research issues are identified for realizing energy-efficient AI at all network levels.

Thermal performance enhancement of a modified pyramid distiller using different modifications with low-cost materials

This study seeks to enlarge the yield and thermal performance and reduce the cost of the conventional pyramid distiller. Three modified pyramid distiller systems have been proposed, and their effects on the thermo-economic performance have been investigated. The first proposed system uses v-corrugated aluminum basin, black cotton fabric (wick material), and paraffin wax as PCM. In contrast, the second one uses the same parts as the first one, but the carbon black nanofluid is used instead of base water. The last modification was like the second one, but with the addition of CB nanoparticles to the paraffin wax to increase its absorptivity and heat transfer rate. Thermal analysis has been conducted to evaluate their thermal performance from the perspective of exergy and energy efficiency compared to the conventional system. Moreover, an economic investigation has been undertaken to evaluate yield's cost per one liter in each case. According to the results, it was found that the three established systems performed well from a thermo-economic point of view when compared to the conventional one. Compared to the conventional system, it is found that the third system yield has been enhanced by 76.9%, while its thermal efficiency has been increased by 101.5%, and the exergy efficiency has been improved by 109.7%. Finally, the save in the total yield's cost per liter is 29.7% when using the last system compared to the conventional one.

Thermoeconomic performance assessment of a novel solar-powered high-temperature heat pump/adsorption cogeneration system

This study presents a theoretical thermoeconomic performance assessment of a novel solar-powered high-temperature heat pump (HTHP)/adsorption cogeneration system for simultaneous electricity production and cooling. Photovoltaic/thermal (PVT) solar collectors are used to capture solar thermal energy and generate electricity that is partially used to drive the HTHP compressor. The HTHP is mainly used to absorb the captured solar thermal energy through its evaporator coils to keep the collectors at lower operating temperatures for better electricity generation. Then through the HTHP compressor, the thermal energy is amplified to produce higher-temperature hot water to drive the adsorption chiller for improved cooling production. The performance of the proposed system (PVT-HTHP) is compared to the performance of the PVT-only, and evacuated tube collectors (ETC-only) powered adsorption chiller for the same solar collector area. A parametric study with different operating HTHP conditions has been performed to determine the optimal operational scenario for the proposed system. A low-GWP refrigerant R1234ze(Z) is considered for the HTHP and compared against the conventional high-GWP R134a option. A complete dynamic mathematical model is developed for the studied systems and solved by MATLAB software. Under the summer conditions of Alexandria, Egypt, the average cooling capacity is improved substantially from 3.91 kW for PVT-only to 8.6 kW for ETC-only and 10.21 kW for proposed PVT-HTHP configuration with R1234ze(Z) and operating evaporator and condenser temperatures of 35 °C and 90 °C, respectively. The best-performing configuration from the energy efficiency perspective is the proposed PVT-HTHP with R1234ze(Z) refrigerant at a value of 46.8% when the operating HTHP evaporator and condenser saturation temperatures of 35 °C and 80 °C, respectively. The economic assessment of the proposed PVT-HTHP system proves that the system can be applied feasibly with a payback period (PBP) of 7.5 years.