Energy Efficiency Of System Research Articles

Reshaping the World with Computer Technologies and Their Impact on the Development of Processes in the Field of Real Estate Trading

Purpose: This study examines artificial intelligence (AI) impact on real estate, highlighting its role in improving processes, enhancing customer experiences, and ensuring competitiveness while prioritising data protection and security. Methodology/Approach: A comprehensive literature review compared AI technologies in real estate, including drones, the Internet of Things (IoT), cloud computing, big data, 3D scanning, wearables, virtual and augmented realities, and robotics. It examines their impact on operations, focusing on AI in Heating, Ventilation and Air Conditioning (HVAC) systems for energy efficiency and comfort. Findings: AI enhances real estate development by optimising operations, transforming customer relationships, and improving energy efficiency and comfort with AI-controlled HVAC systems. Benefits include automated data processing, better decision-making, and optimised marketing strategies. Research Limitation/Implication: AI has great potential, but its implementation is in the early stages, including in real estate. Challenges include data protection, security, costs, and new hardware for HVAC systems. Broader real-case testing is needed. Originality/Value of paper: This paper broadens the perspective on AI's impact on real estate, showing how to implement AI in various processes. It improves performance and transforms customer experiences, setting new standards for property management.

Optimizing domestic energy management with a wild Mice colony-inspired algorithm: Enhancing efficiency and coordination in smart grids through dynamic distributed energy storage

Energy management (EM) is a critical strategy that spans the production and consumption of electricity, enhancing the stability of the electricity network. Smart grid technology significantly improves the electrical system's energy efficiency (EE), facilitating a transformation from a conventional power grid (PG) to a smart PG. This paper presents a key strategy for modeling the EE of the smart grid tailored to domestic demand, establishing smart coordination between domestic demand, energy production, and storage to reduce energy waste and costs. Our model integrates various energy sources, including renewable energy (RE), photovoltaic (PV) systems, wind power, and an energy storage system (ESS), interconnected with the PG. The model's structure ensures the coordinated flow of electricity in a residential house through an optimal control method (OCM). To develop a robust closed-loop control model, we employ Demand Response (DR) schemes within the Real-Time Electricity Pricing (RTEP) framework. We construct a dynamic model of the ESS to compute the System Performance Index (SPI), corresponding to energy costs. To enhance our model, we introduce a Dynamic Distributed Energy Storage Strategy (DDESS). Additionally, we introduce a novel optimization algorithm inspired by the behavioral patterns of wild mice, called the Wild Mice Colony (WMC). By analyzing the targeted and advantageous behaviors of wild mice in colonies, we propose that these behaviors can serve as a model for addressing complex, uncertain problems. This strategy is highly advantageous, capable of reducing total energy consumption (EC) from the main grid by over 100 % of the load demand, optimizing the energy system, and ensuring synchronization. The performance of DDESS optimizes energy flow (EF) during the repayment plan, leading to minimized EC costs from the PG.

Ultrasonic destruction of surfactants

This study investigates the effectiveness of ultrasonic (US) treatment in removing and mineralizing surfactants in wastewater. It examines the complex mechanisms and variables (acoustic conditions, solution temperature, initial dose, etc.) that affect sonolytic processes. The effect of water matrix components (such as salts and the presence of secondary pollutants) on process performance is thoroughly investigated. Various treatments are analyzed through a detailed comparison of synergistic hybridization processes. The study also provides a comprehensive review of current environmental applications and explores potential directions for surfactant degradation using ultrasound. Insightful information is presented to advance sustainable wastewater treatment techniques. The literature review clearly reveals the promising future of sonotreatment for degrading various surfactants under different conditions. The use of multifrequency mechanisms and the integration of other advanced oxidation processes (AOPs) with the US process have significantly enhanced the energy efficiency of the sonochemical system. Additionally, the results highlight the need to focus on developing new sonoreactor designs, identifying degradation intermediates, and hybridizing the sonochemical system under innovative operating conditions.

Analyzing energy transition for industry 4.0-driven hybrid energy system selection with advanced neural network-used multi-criteria decision-making technique

This study aims to select the appropriate renewable energy alternatives for the efficiency of hybrid energy systems to increase energy transition performance. For this purpose, a novel neural network (NN)-based fuzzy decision-making model is constructed that has three different stages. In the first stage, NN-based fuzzy decision matrix is created. Secondly, 6 different variables based on industry 4.0 are weighted with the sine trigonometric Pythagorean fuzzy entropy technique. Additionally, another calculation has been implemented with criteria importance through intercriteria correlation (CRITIC) to identify the consistency of the results. Furthermore, in the third stage, considering 5 different renewable energy alternatives, 10 different combinations are identified for hybrid energy systems. The most effective alternatives are defined by the sine trigonometric Pythagorean fuzzy ranking technique by geometric mean of similarity ratio to optimal solution (RATGOS) method. Moreover, to test the validity of these results, another analysis is conducted using the additive ratio assessment (ARAS) technique. The main contribution of the study is that the optimal renewable energy combination required for an efficient hybrid energy system is determined by performing a priority analysis between the variables. This situation has a significant guiding feature for investors. Similarly, the development of the RATGOS technique both increases the methodological originality of the study and enables more accurate alternative ranking. It is identified that the results of all methods are similar. Therefore, this situation gives information about the coherency and validity of the findings. It is concluded that the most important criterion is real-time capability. It is also denoted that the best combination for hybrid energy systems is Solar-Wind.

LAAN LUNDUYAN: A Volcanic Disaster Resilient Conservation Complex in Albay Biosphere Reserve Through Bionic Architecture

Albay Biosphere Reserve (ABR) aims to conserve biodiversity, support research and recreation, and promote sustainable economic development. However, threats and challenges are present, including a lack of institutionalized biodiversity monitoring systems, a low level of community awareness of ABR, and the looming threat from Mt. Mayon. This research aims to explore the role of bionic architecture in ABR management, while considering biodiversity conservation, addressing the vulnerability of structures in volcanic disasters, and the potential of tourism. To answer this, a descriptive research design with a mixed-method approach was employed to analyze the data gathered from selected barangays in the Mayon Unit of Ligao City. Research findings reveal the potential of bionic architecture for creating a design framework for guiding the development of a volcanic disaster- resilient conservation complex. The framework employs the principle of bionic architecture of incorporat ing the natural ways and processes in biological systems studied in coconut trees towards efficiency, resilience, and adaptability, using its six dimensions: role and patterns, materials, structure, form, function, and process. This proposes architectural features, including energy-efficient and resilient systems, materials such as Albay black sand, and coconut-based products, and key facilities contributing to conservation, and tourism development.

A Cooperative Operation Strategy for Multi-Energy Systems Based on the Power Dispatch Meta-Universe Platform

To meet the challenges of renewable energy consumption and improve the efficiency of energy systems, we propose an intelligent distributed energy dispatch strategy for multi-energy systems based on Nash bargaining by utilizing the power dispatch meta-universe platform. First, the operational framework of the multi-energy system, including wind park (WP), photovoltaic power plant (PVPP), and energy storage (ES), is described. Using the power dispatch meta-universe platform, the models of WP, PVPP, and ES are constructed and analyzed. Then, a Nash bargaining model of the multi-energy system is built and transformed into a coalition profit maximization problem, which is solved using the alternating direction multiplier method (ADMM). Finally, the effectiveness of the proposed strategy is verified. The results show that the strategy greatly improves the consumption of renewable energy sources and the profit of the overall system.

3D Numerical Modeling to Assess the Energy Performance of Solid–Solid Phase Change Materials in Glazing Systems

This research investigates the energy efficiency of a novel double-glazing system incorporating solid–solid phase change materials (SSPCMs), which offer significant advantages over traditional liquid–solid phase change materials. The primary objective of this study is to develop a 3D numerical model using the finite volume method, which will be followed by a parametric study under real climatic boundary conditions. A proposed double-glazing setup featuring a 2 mm layer of SSPCM applied on the inner glass pane within the air gap is modeled and analyzed. The simulations consider various transient temperatures and ranges of the SSPCM to evaluate the energy performance of the system under different weather conditions of Miami, FL during the coldest and hottest days of the year, both in sunny and cloudy conditions. The results demonstrate a notable improvement in energy performance compared to standard double-glazing windows (DGWs), with the most efficient SSPCM configuration exhibiting a phase transition temperature and range of 25 °C and 1 °C, respectively. This configuration achieved energy savings of 24%, 26%, and 23% during summer sunny, winter sunny, and winter cloudy days, respectively, relative to DGWs during cooling and heating degree hours. However, a 3% energy loss was observed during summer cloudy days. Overall, the findings of this study have shown the potential for energy savings by incorporating SSPCM with suitable thermophysical properties into double-glazing systems.

Impact on Annual Energy Cost due to Air-Conditioner selection for Hotel Business setup in North India

Energy consumption is a critical factor in determining the overall cost and profitability of a hotel. High energy consumption can significantly increase operating costs, which directly impacts the overall financial performance of a hotel (Filimonau et al., 2011). By reducing energy consumption, hotels can effectively lower their operating costs and increase profitability. This can be achieved through various measures such as implementing energy-efficient lighting systems, optimizing HVAC systems, using smart technologies for better control and monitoring of energy usage, and adopting energy-saving practices in areas such as heating, cooling, and ventilation. Implementing these energy-saving measures can not only reduce the hotel's carbon footprint but also improve its competitiveness in the market (Čingoski & Petrevska, 2018). Additionally, promoting energy conservation in a hotel can also contribute to enhancing its reputation and attracting environmentally conscious guests (Filimonau et al., 2011). Overall, the impact of energy consumption on the cost and profit of a hotel is significant. Keywords Energy consumption, Air-Conditioner Selection, Advance Technologies, Energy Saving, AC Star Rating, Five Star AC, Inverter AC, Split AC, Window AC.

FEATURES OF ARCHITECTURAL FORM FORMATION OF ENERGY-EFFICIENT MULTISTORY BUILDINGS

Problem statement. The active use of renewable energy sources and the introduction of energy-efficient systems in all spheres of life today is the most important component of future development, which can change the life and comfort of every person. And it is very important to determine the place of architecture in this process. Analyzing the global experience of architectural activity in recent decades, especially in economically developed countries, it can be noted that engineering and technological systems of alternative energy are becoming an integral part of various types of buildings and complexes, both residential (low-rise, high-rise) and public (business, retail, cultural, multifunctional complexes, etc.). Alternative energy is becoming one of the factors influencing the layout and appearance of a building, the choice of materials and decorative finishing, and significantly influencing the formation of objects of new “innovative” architecture. Purpose of the article. To explore the features of the architectural form formation of energy-efficient multi-storey buildings as a result of the interdependence of architecture and energy-efficient technological systems using the example of modern architectural objects in the world. Conclusion. Engineering and technological systems of alternative energy for multi-storey buildings, based on renewable energy sources, provide such characteristics of buildings as: environmental friendliness, autonomy, self-sufficiency, profitability, energy efficiency and a high level of living comfort, architectural individuality and freedom of architectural form formation, unusual volumetric and compositional architectural solutions objects.

Primarily experimental study of the energy performances of a humidification-dehumidification seawater desalination system coupled with a heat pump

The study presented in this article explores a comprehensive analysis of a humidification-dehumidification (HDH) seawater desalination system integrating a heat pump for heating seawater intended for distillation, and incorporates additional condensation plates supplied with cold seawater. This system was the subject of an experimental investigation to simultaneously evaluate the energy performance of the heat pump and the thermal behavior of the desalination unit, focusing on seawater and condensation wall temperatures, as well as the stratification of temperatures of humid air inside the unit compared to the evaporation surface. Experimental results showed an average daily production of distilled water of approximately 32.75 kg/m² per day, with an electrical consumption of 37.68 kWh/day, which was reduced to 26.72 kWh/day through the integration of photovoltaic solar energy. Based on heat and mass balance equations of all the system’s components, the study used a detailed thermodynamic model. The system's energy performance was analyzed by calculating the coefficient of performance (COP), the specific energy consumption (SEEC), and the gain output ratio (GOR), reflecting the overall energy efficiency of the HDH system coupled with the heat pump, as well as the recovery ratio (RR), indicating the proportion of the recovered water compared to the input water.

Design and investment strategy optimization of district cooling system during the ramp-up phase

District Cooling (DC) systems, known for their efficiency and integration of renewable energy sources, encounter substantial design and investment complexities during the initial ramp-up phase. This critical phase is characterized by increasing cooling demand, necessitating a scientific approach to equipment selection and sizing that spans multiple temporal scales. A key yet frequently underestimated element in DC systems is the inclusion of backup chiller. While traditionally reserved to emergency use, its proactive interactions with regular system operations can significantly diminish operational expenses, despite the inherent complexities. Our study presents an innovative mixed-integer linear programming (MILP) optimization framework. This framework is designed to manage and optimize the intricate DC system design and investment strategy during the ramp-up phase, with a particular focus on the strategic inclusion of backup chillers. To demonstrate this framework, our research undertakes a comprehensive analysis of a real-world DC project in Kuala Lumpur. The findings show that the MILP optimization delivers substantial reductions in Life Cycle Costs (LCC) up to 3.33% across various system configurations. This is of significant value for energy efficiency and sustainable urban energy systems.

Computational Fluid Dynamics Analysis of Slip Flow and Heat Transfer at the Entrance Region of a Circular Pipe

In the era of sustainable development goals (SDGs), energy efficient heat transfer systems are a must. Convective heat transfer within circular pipes is an important field of research on a rarely addressed limitation of fluid flows. Vacuum solar tubes is one of many applications that could benefit from the existence of nanoparticles, Al2O3, for example, to enhance the heating of air or water steam. The current research investigates the impacts of the Reynolds number (Re), Prandtl number (Pr), Knudsen number (Kn), aspect ratio (x/Dh), and volume fraction of Al2O3 nanoparticles (ϕ) on the Nusselt number (Nu) under constant wall heat flux conditions. An axisymmetric computational fluid dynamics (CFD) analysis of the nanofluid flowing at the entrance region of a circular pipe was conducted under a slip flow at steady-state developing laminar conditions using the Ansys-Fluent 2018 software package. A mesh sensitivity analysis was conducted, and a proper number of mesh elements was selected. The results showed that an increasing Re and/or ϕ would result in an increasing Nu. The dependance of Nu on Kn was strong due to the high slip values and temperature jump. An increasing x/Dh ratio resulted in reduced Nu values. The major impact was due to Kn, which caused a reduction of up to 40% in the Nu value due to slip conditions. However, there was an enhancement of 2.5% in the heat transfer due to the addition of nanoparticles, which was found at Re = 250, Kn = 0.1, and ϕ = 0.1 (Pr = 0.729). Finally, Nuavg, Nux, U/Um, and ReCf were corelated with Kn, Pr, Re, and x/Dh with proper coefficient of determination (R2) values.

Characteristics of thermo‐hydraulic flow inside corrugated channels: Comprehensive and comparative review

AbstractPrevious works that investigated the characteristics of heat transfer and fluid flow in channels with corrugated walls have been extensively reviewed in this study. In accordance with the fast increase in power consumption requirements, many researchers have investigated a new approach for cooling techniques that can enhance the cooling performance of devices without consuming more power. To improve the efficiency of energy systems, many investigators and engineers implement promising techniques such as surface optimization and additives as passive methods to augment the rates of heat transfer. Researchers investigated different corrugation profiles along with various working fluids as well as external power devices to further improve the heat exchange process of thermal systems. The aim of this article is to give a clear preview of the effects of different parameters such as wave parameters, Reynolds number, type of working fluid, and pulsating flow condition on the average and local Nusselt number, the pressure drop, the performance factors, and irreversibility. The main findings are listed in tables and depicted in figures, the matter that helps engineers and researchers to choose a suitable channel shape for their applications.

Energy-efficiency optimization for heterogeneous computing-assisted NOMA-MEC edge AI tasks

Edge artificial intelligence (AI) is an emerging paradigm that leverages edge computing to pave the last-mile delivery of AI. To satisfy the increasing demand for high-performance computing and low latency of edge service, heterogeneous computing accelerators, especially Neural Processor Units (NPUs), are widely deployed on edge nodes. However, the edge AI heterogeneous computing system encounters the challenge of energy constraints. In this paper, we investigate the energy efficiency (EE) optimization problem in heterogeneous computing-assisted non-orthogonal multiple access mobile edge computing (NOMA-MEC) network model. Edge devices are configured with CPU-NPU heterogeneous computing processors to improve the AI task processing, and NOMA is applied to edge task offloading to enable massive connectivity. The system-centric energy efficiency maximization problem is studied. We formulate a system-centric energy efficiency maximization problem. To solve this problem, we decouple the original problem into two subproblems, i.e., the optimization problems of heterogeneous computing workload splitting and task offloading. A heuristic algorithm and binary search algorithm are proposed to optimize NOMA user pairing and task offloading delay, respectively. Furthermore, we propose a multi-objective alternative iterative algorithm to optimize system energy efficiency. Numerical results show that the proposed scheme can significantly improve the energy efficiency of heterogeneous computing-assisted NOMA-MEC networks compared to the existing baselines.

Joint 3D trajectory and phase shift optimization via deep reinforcement learning for RIS-assisted UAV communication systems

Unmanned aerial vehicle (UAV) can be deployed as aerial base station to provide communication services for the user equipments (UEs). However, in urban environments, the links between UAV and UEs might be frequently blocked by obstacles, leading to severely adverse effects on the quality of service (QoS) of UEs. Additionally, due to the limited energy of the UAV, it might not always be feasible to re-establish the line-of-sight (LoS) links by frequently adjusting the positions of the UAV. In this context, the reconfigurable intelligent surface (RIS) is utilized to enhance the transmission range of UAV-UE links by reflecting incident signals to UEs. In this paper, we investigate the RIS-assisted UAV communication systems with the goal of maximizing the energy efficiency of the UAV through a joint optimization of the UAV’s trajectory and the RIS’s phase shift. The formulated optimization problem is non-convex, and challenging to solve in a polynomial time. Therefore, an effective deep reinforcement learning (DRL)-based solution, named Dueling DQN-PER is proposed, which combines the Dueling DQN algorithm with the prioritized experience replay (PER) technique. To ensure the fairness among all UEs, we design a service fairness index, and integrate it into the reward function when designing the proposed algorithm. Numerical results demonstrate that: 1) the proposed Dueling DQN-PER algorithm is capable of improving the system energy efficiency and has a better training performance than benchmark schemes; 2) by devising the service fairness index, the fairness among all UEs is ensured while enhancing the system performance in energy efficiency; 3) the RIS-assisted UAV communication systems benefit from significant energy efficiency gain over the systems without RIS.

Enhancing energy efficiency in HVAC systems through precise heating load forecasting and advanced optimization algorithms

Enhancing energy efficiency in HVAC systems through precise heating load forecasting and advanced optimization algorithms

Power-Efficient Resource Allocation for Active STAR-RIS-Aided SWIPT Communication Systems

Simultaneous wireless information and power transfer (SWIPT) has emerged as a pivotal technology in 6G, offering an efficient means of delivering energy to a large quantity of low-power devices while transmitting data concurrently. To address the challenges of obstructions, high path loss, and significant energy consumption associated with long-distance communication, this work introduces a novel alternating iterative optimization strategy. The proposed approach combines active simultaneous transmission and reflection of reconfigurable intelligent surfaces (STAR-RIS) with SWIPT to maximize spectrum efficiency and reduce overall system energy consumption. This method addresses the considerable energy demands inherent in SWIPT systems by focusing on reducing the power output from the base station (BS) while meeting key constraints: the communication rate for information receivers (IRs) and minimum energy levels for energy receivers (ERs). Given complex interactions between variables, the solution involves an alternating iterative optimization process. In the first stage of this approach, the passive beamforming variables are kept constant, enabling the use of semi-definite relaxation (SDR) and successive convex approximation (SCA) algorithms to optimize active beamforming variables. In the next stage, with active beamforming variables fixed, penalty-based algorithms are applied to fine-tune the passive beamforming variables. This iterative process continues, alternating between active and passive beamforming optimization, until the system converges on a stable solution. The simulation results indicated that the proposed system configuration, which leverages active STAR-RIS, achieves lower energy consumption and demonstrates improved performance compared to configurations utilizing passive RIS, active RIS, and passive STAR-RIS. This evidence suggests that the proposed approach can significantly contribute to advancing energy efficiency in 6G systems.

Energy-efficient solar heat supply system based on hybrid photovoltaic collector

Following the commitments made under the Paris Climate Agreement, the scientific community has initiated a strategic increase in the share of renewable energy sources while gradually reducing dependence on traditional carbon fuels. Priority is given to the acceleration of the development of the photovoltaic industry, which has shown a constant increase in capacity over the past decades. According to the energy and climate strategies of the European Union, a significant increase in the amount of energy generation due to solar sources is planned. Therefore, the article is devoted to the development of a solar heat supply system based on a hybrid thermal photovoltaic solar collector with an improved design and analysis of the main characteristics of its operation using computer modeling. The authors have developed a 3D computer model of the proposed hybrid system with a solar collector by using SolidWorks software. The change in the temperature of the heat carrier in the hybrid thermal photovoltaic solar collector under constant solar radiation was analyzed. The temperature change of the coolant in the thermal accumulator of the system was also investigated. The results of the simulation of thermal processes revealed the key regularities of the temperature increase during the computer experiment, both in the hybrid thermal photovoltaic solar collector and in the thermal accumulator. The change in the instantaneous specific heat capacity of the developed solar collector was analyzed, and its average efficiency was estimated. The trends of changes in the thermal efficiency of the developed heat supply system during the computer experiment were determined. The novelty of the study is that the design of the hybrid thermophotoelectric solar collector has been improved, its 3D computer model has been developed, and the main thermal characteristics of the developed heat supply system with constant solar radiation have been obtained, which will contribute to the development of calculation methods for such heat supply systems with hybrid solar collectors in the future.

Energy, exergy, economic, and environmental analyses and optimization of a multigeneration system considering high-temperature island environment

Renewable energy based multigeneration systems help satisfy the diverse demand for marine resources exploration in off-grid island area, where the storage of fluctuating renewable energy for continuous power supply becomes necessary. Therefore, this paper proposes a solar-driven multigeneration system for island environment integrated with energy storage and production of electricity, cooling, heating, and freshwater. The system comprises an ejector power subsystem, a multiple-effect distillation subsystem, and a CO2 binary mixture-based compressed gas energy storage subsystem. The system performance from the perspectives of energy, exergy, economics, and environment, as well as the impact on performance of the working fluid and several key system parameters, are investigated in this paper. According to the results, an increase in the mass fraction of organic in the CO2 mixture leads to an improvement in system energy efficiency and exergy density at the cost of lower system power efficiency. Increasing the high-pressure tank pressure enhances system performance except for system power efficiency. Increased low-pressure tank pressure leads to improved system energy efficiency and exergy density, accompanied by lower system power efficiency and exergy efficiency. When the ambient temperature increases from 298 K to 303 K, the system energy efficiency noticeably decreases, whereas an increase in direct normal irradiance improves various system performance indicators. Among several mixtures, CO2/R32 mixture was chosen for further analysis and optimization for its wider operating range with R32 mass fraction and better system performance. The optimal operating point had system energy efficiency, exergy density, and modified levelized cost of energy of 1.281, 22.216 kWh/m3, and 0.131 $/kWh, respectively. The proposed system in this research is proven to be a novel technical solution to meet the diverse energy demands on unique island environments.

Energy efficiency and interoperability through O-RAN Rapid Transition Protocol (ORTP)

Mobile network traffic is increasing accompanied by increased energy consumption. Traditional Radio Access Networks (RANs) have been used for decades as the foundation of mobile communications, providing mobile customers with reliable voice and data services. However, they encounter obstacles in terms of scalability, adaptability, and cost-effectiveness. Next-generation wireless networks need efficient Radio Access Network (RAN) solutions to achieve low latency and high throughput. The Open RAN (O-RAN) architecture is a potential solution for 5G and beyond networks due to its open interfaces, disaggregated network entities and services, network hardware and software virtualization, and intelligent control. Traditionally standard RAN accounts for the bulk of mobile network energy consumption, leading towards higher Operational expenditure (OPEX) costs. In the context of cellular networks. Handover strategies need careful development to cater for efficient resource usage as well as overall system energy efficiency. O-RAN Rapid Transition Protocol (ORTP) presented in this paper employs minimum value of handover margin (HOM) and is aimed at increased energy efficiency. 5G based System level simulations have been performed to investigate the efficacy of ORTP for key performance indicators including handover probability, Radio Link Failure, connection density, ping pong effect and dynamic power consumption. It is found that the usage of lower HOM values provide noticeable achievement in terms of power consumption, thereby rendering ORTP around 20 % more efficient compared to 5G networks, while keeping it interoperable.