Residential Applications Research Articles

Dynamic modelling and sensitivity analysis of parameters impacting the performances of a liquid piston-based energy conversion system

The present work deals with the dynamic modelling of a small-scale thermo-hydraulic engine, designed for residential application. Comparing to Organic Rankine systems, the CAPILI cycle uses a hydraulic motor instead of a turbine. The solar activated CAPILI engine produces electricity through a liquid piston oscillating between two reservoirs connected alternatively to a high pressure evaporator and a low pressure condenser. The heat rejected by the condenser is discharged in the ground through geothermal probes at 13 °C while the solar panels provide heat at about 70 °C. The liquid piston drives a hydraulic motor coupled to an electrical generator to produce electricity. Based on these temperature conditions, the dynamic modelling approach undertaken in the study enables a sensitivity analysis of the most impacting parameters of the CAPILI system. In particular, the study focuses on the volume capacity and the filling ratio of transfer cylinders, the switching -balancing- volume of the cycle as well as the electrical load. The results highlight the effects of each investigated parameters on the whole behaviour of the simulated CAPILI system. The best performance of the investigated CAPILI system operating under the given operating conditions, highlights a thermal efficiency of 9.14 % and almost 55 % for the exergy efficiency.

Alcohol-free synthesis, biological assessment, in vivo toxicological evaluation, and in silico analysis of novel silane quaternary ammonium compounds differing in structure and chain length as promising disinfectants

Quaternary ammonium compounds (QACs) are commonly used as disinfectants for industrial, medical, and residential applications. However, adverse health outcomes have been reported. Therefore, biocompatible disinfectants must be developed to reduce these adverse effects. In this context, QACs with various alkyl chain lengths (C12–C18) were synthesized by reacting QACs with the counterion silane. The antimicrobial activities of the novel compounds against four strains of microorganisms were assessed. Several in vivo assays were conducted on Drosophila melanogaster to determine the toxicological outcomes of Si-QACs, followed by computational analyses (molecular docking, simulation, and prediction of skin sensitization). The in vivo results were combined using a cheminformatics approach to understand the descriptors responsible for the safety of Si-QAC. Si-QAC-2 was active against all tested bacteria, with minimal inhibitory concentrations ranging from 13.65 to 436.74 ppm. Drosophila exposed to Si-QAC-2 have moderate-to-low toxicological outcomes. The molecular weight, hydrophobicity/lipophilicity, and electron diffraction properties were identified as crucial descriptors for ensuring the safety of the Si-QACs. Furthermore, Si-QAC-2 exhibited good stability and notable antiviral potential with no signs of skin sensitization. Overall, Si-QAC-2 (C14) has the potential to be a novel disinfectant.

Smart Irrigation Controllers in Residential Applications and the Potential of Integrated Water Distribution Systems

Smart Irrigation Controllers in Residential Applications and the Potential of Integrated Water Distribution Systems

Experimental investigation and modelling of a Solid Oxide Fuel Cell (SOFC) used in residential cogeneration applications

Experimental investigation and modelling of a Solid Oxide Fuel Cell (SOFC) used in residential cogeneration applications

Prototype Development for Solar Energy Tracking Based on Arduino in QUEST Campus Larkana

The utilization of solar energy has become increasingly popular due to its renewable and sustainable nature. However, one of the primary challenges in solar energy harvesting is the optimization of the amount of energy that can be captured from the sun. The implementation of solar trackers is an effective solution that enables the automatic adjustment of the solar panel's position to face the sun throughout the day. In this project, an Arduino-based solar tracker prototype was designed and implemented to optimize the solar energy harvesting process. The system employs Light-Dependent Resistors (LDRs) to detect sunlight intensity and a servo motor to adjust the position of the solar panel accordingly. The system was programmed using the Arduino programming language and was tested using a small-scale solar panel. The increasing demand for cost-effective and easy-to-install renewable energy systems has led to a growing interest in photovoltaic solar energy for residential use. To optimize energy production, a two-axis photovoltaic solar tracker that orients the solar panel toward the maximum solar radiation is proposed in this study. The use of Free Computer Aided Design (CAD) 0.15 for the prototype's design, combined with Arduino technology, provides an affordable solution for mounting the solar tracker on flat roofs and other horizontal building elements. The performance of the solar tracker was evaluated under various testing conditions, showcasing an enhanced level of accuracy and energy production when compared to traditional fixed systems. The prototype's successful demonstration represents a significant advancement in the field, providing a practical solution for small-scale and residential solar energy applications. This research prototype was developed and installed on the roof of the Electrical department of QUEST, Campus Larkana, and validated through simulation results.

Breached and Denied: The Cost of Data Breaches on Individuals as Mortgage Application Denials

While a large body of the information systems (IS) literature has investigated the antecedents and consequences of data breaches in organizations, we do not have a good understanding of whether a data breach has a material impact on individuals whose private information is compromised and how much damage it causes. We overcome empirical challenges in investigating the impact of data breaches on individual victims by utilizing a unique natural experimental setting that allows us to credibly identify treated and controlled populations—the breach of South Carolina (SC) taxpayer records in 2012. With residents in SC as the treatment group and those in Georgia and North Carolina as the control group, our difference-in-differences estimations find that after the breach to the SC Department of Revenue, there was a significant increase in denials to SC residents’ residential mortgage applications for refinance and home improvement. We also find that the adverse impact of the breach was more profound for Black and Hispanic residents. Our study provides significant theoretical and policy implications with respect to the harm and costs of a large-scale data breach.

Non-intrusive Load Monitoring Based on Graph Total Variation for Residential Appliances

Non-intrusive Load Monitoring Based on Graph Total Variation for Residential Appliances

Nano-enabled antimicrobial thin films: design and mechanism of action.

Antimicrobial thin films are types of protective coatings that are applied to surfaces such as medical devices, food packaging materials, water-resistant coatings, and other systems. These films prevent and reduce the spread of microbial organisms, including bacteria, fungi, and viruses. Antimicrobial thin films can be prepared from a variety of nanostructured materials including metal nanoparticles, metal oxides, plant materials, enzymes, bacteriocins and polymers. Their antimicrobial mechanism varies mostly based on the types of active agents from which the film is made of. Antimicrobial thin films are becoming increasingly popular microbial treatment methods due to their advantages such as enhanced stability, reduced toxicity levels, extended effectiveness over time and broad spectrum antimicrobial action without side effects on human health or the environment. This popularity and enhanced performance is mainly due to the extended possibility of film designs. Thin films offer convenient formulation methods which makes them suitable for commercial practices aiming at high turnover rates along with residential applications requiring frequent application cycles. This review focuses on recent developments in the possible processing methods and design approaches for assembling the various types of antimicrobial materials into nanostructured thin film-based delivery systems, along with mechanisms of action against microbes.

Dynamic study of hydrogen optimization in the hybrid boiler-fuel cells MCHP unit for eco-friendly house

This paper investigates an innovative study on the performance of a hybrid condensing boiler-fuel cell micro-cogeneration system for single residential applications. It combines experimental and dynamic numerical investigations including renewable energy for green hydrogen production and solid storage. Basing on the hourly measurements for a typical winter day, a dynamic model was developed and validated against different home heating need. Highlighting the influence home energy needs on fuel cell operating mode, it shows that single homes with low energy demand led to reduce the fuel cell's yearly operation below 50 %. In low-energy homes, a reduction in fuel cell size led to an increase in yearly operation to 60-70 % and achieved a 55 % electrical coverage rate. The integration of metal hydride hydrogen solid storage, powered by renewable sources, is emphasized. This setup increases heat demand, influencing fuel cell operation. In winter season, fuel cell operated for an average of 611 h, compared to 61 h in summer. System efficiency averaged 91 % annually, peaked at 95 % in summer, and sustained 93 % when both FC and condensing boiler were switched on.

Comprehensive modeling of ventilation systems for Nearly Zero Energy Buildings

In the present work, a lumped-parameter model of a multifunctional ventilation unit for residential applications was developed in the Simulink environment, also relying on the Simscape toolbox with Moist Air and Two-Phase fluid libraries. A simple, yet effective method to analyze and optimize the efficiency of the combined HVAC – air distribution system is proposed. To investigate the impact of boundary conditions on system performance, a parametric study of different installation conditions was also carried out, including outdoor air and indoor air temperature, humidity, static pressure, filter fouling, pressure drop in the intake and distribution ducts. The model highlights a strong decrease in the useful cooling/heating heat flow rate produced by the system as the installation and maintenance conditions become more challenging.

Review on Non-Isolated Multiport Converters for Residential DC Microgrids

Nowadays, energy sustainability needs drive the development of novel power system architectures that efficiently harvest and deliver green energy. Specifically, DC Microgrids (DC-MG) have emerged as promising bases for distributed power generation, especially in residential applications. The pivotal role of power conversion and the need for more affordable and compact converters has led to an increasing research interest. MultiPort Converters (MPCs) exhibit beneficial operational characteristics for these applications and, therefore, a plethora of different topologies is suggested in the literature. Even though there have been some attempts to organize and review the field status, the categorization is based on the existence or not of isolation between the converter’s ports, without providing insight on the topology conception. In this article, a literature review is conducted to specify the most suitable non-isolated MPC topologies for residential DC-MGs. Converters with a power rating ranging from 0.1 to 1 kW are compared based on technical features and categorized according to their topology derivation process. This procedure is performed separately for MPCs suitable for unipolar and bipolar DC Buses. The selected approach highlights the design basis for each MPC in a structured manner, facilitating further development of original converters by both new and experienced researchers.

Power Quality Gain of Self-Lift Luo Converter used for Hybrid Renewable Power System with Battery Grid Integration

The renewable power sources such as wind as well as photovoltaic (PV) energy are fashionable for residential and commercial applications. For the reason, that eco friendlessness plus expenditure are effective. This paper intends a Self-Lift Luo converter integrated with solar photovoltaic system to the utility grid along with its Adaptive Neuro-Fuzzy Inference System (ANFIS) and Recurrent Neural Network (RNN) control strategies are proposed. By achieve an energy management for the proposed system using Bidirectional Battery converter along with battery system. Power supervision move towards is suggested to control the DC bus voltage by way of Self-Lift Luo converter. The wind power with Doubly Fed Induction Generator (DFIG) based grid integration with a PI controller. Under this work, DSTATCOM has been used to improve the quality of power under different load conditions. The obtained results designate that the proposed approach delivers recovered performance with enhanced efficiency and nominal harmonics. The intact system is validated through a MATLAB simulation.

Non-Intrusive Load Identification of Residential Appliances Using Improved Dictionary Learning Technique

With the advent of time, the demand for power in the residential sector is increasing. Along with supply-side management, the demand side is also used to balance electricity and supply demand. To apply different demand-side management techniques, the energy disaggregation on metered data is used to retrieve information related to available demand. Non-intrusive load monitoring is a technique that separates the total power consumption into appliance loads with minimum invasion of privacy. Non-intrusive load monitoring covers the methods of Stochastic finite state machines, Neural Networks and Sparse Coding. Developing an efficient algorithm for NILM is a key challenge in maximizing energy conservation. Recently, a new deep learning technique called dictionary learning has been developed for energy disaggregation. Smart meters provide the whole house data, and the Dictionary technique is trained to predict an appliance's power or ON/OFF based on its power consumption. This research proposes the event-based dictionary learning technique, which can disaggregate multiple appliances through orthogonal matching pursuit (OMP) and kernel-singular value decomposition (K-SVD). The sparse matrix is predicted through OMP, and K-SVD predicts the dictionary matrix. The training, testing and validation are done on the ECO dataset. The results of this research are noticeable and show the validity of the proposed methodology for energy disaggregation.

A comprehensive comparison study on household solar-assisted heating system performance in the hot summer and cold winter zone in China

Distributed solar heating systems have high energy-saving potential as clean and energy-efficient production units in residential building applications. Solar energy resources are weak in hot summer and cold winter zone in China, which makes it difficult to completely rely on solar energy to heat residential buildings. A critical challenge is the lack of a theoretical basis for how to choose the solar-assisted heating system form. In this paper, seven solar-assisted heating systems are modeled and their performances are evaluated in six cities by using TRNSYS software. In terms of performance indicators, the solar fraction, the season performance factor, and the heat efficiency are used to thoroughly discuss the viability of using solar heating technologies in this zone. Based on the results, the average indoor air temperature was maintained between 16 °C and 20 °C, and the lowest solar fraction obtained was 10.1%. The carbon emission reduction in each city ranged from 60 kg to 400 kg, yielding good environmental benefits. According to the comprehensive comparison of the six evaluation indexes considered, the parallel or dual-source solar-assisted air source heat pump system can be used in a zone with medium solar energy resources. It is more suitable to use a dual-source solar-assisted air-source heat pump system in a zone with poor solar energy resources. The findings of this work can guide and promote the widespread application of distributed solar heating in household residential buildings in the hot summer and cold winter zone in China.

Analysis of the Main Architectural and Structural Design Considerations in Tall Timber Buildings

Tall timber buildings represent an emerging and highly promising sector due to their potential to yield significant environmental and economic advantages throughout their entire life cycles. Nonetheless, the existing body of literature lacks a comprehensive exploration of the primary architectural and structural design considerations for such sustainable towers. To address this gap and to enhance our understanding of emerging global trends, this study scrutinized data from 49 tall timber building case studies from around the world. The key findings revealed the following: (1) Europe stood out as the region boasting the highest number of tall timber buildings, with North America and Australia following behind; (2) residential applications were the most preferred function for tall timber buildings; (3) central cores were the predominant choice for core configuration; (4) prismatic forms were the most prevalent design preferences; (5) composite materials were notably widespread, with timber and concrete combinations being the most prominent; (6) structural systems primarily featured shear–frame systems, especially shear-walled frames. By unveiling these contemporary characteristics of tall timber buildings, this research is expected to provide valuable insights to architects, aiding and guiding them in the design and execution of future sustainable projects in this field.

Smart and optimization-based operation scheduling strategies for maximizing battery profitability and longevity in grid-connected application

Lithium-ion battery storage has emerged as a promising solution for various energy systems. However, complex degradation behavior, relatively short lifetime, high capital, and operational costs, and electricity market volatility are critical factors that challenge its practical viability. Thus, to ensure sustained profitability of Lithium-ion batteries in real-life applications, a smart and optimal management strategy considering key influencing factors is imperative for achieving efficient battery utilization.This study proposes two day-ahead battery-behavior-aware operation scheduling strategies to maximize profitability and longevity in residential grid-connected applications with dynamic electricity pricing. Each scenario employs unique approaches to make optimal decisions for optimal battery utilization. The first scenario optimizes short-term profitability by prioritizing revenue gains under three charge/discharge rates (high, moderate, low), considering daily charge and discharge timings as decision variables. Conversely, the second scenario proposes a smart strategy capable of making intelligent decisions on a wide range of variables to simultaneously maximize revenue and minimize degradation costs, ensuring short-term and long-term profitability. Decision variables include the cycle frequency for each specific day, timings as well as durations for charging and discharging per cycle. To ensure effective long-term assessment, both scenarios accurately estimate battery performance, calendric and cyclic capacity degradations, remaining-useful-lifetime, and internal states under real operational conditions until battery reaches its end-of-life criteria. The scenarios are assessed economically using various indicators. Furthermore, the impact of battery price and size on optimization outcomes are examined.The key findings indicate that, among the first set of scenarios, the strategy with low charge/discharge rate extends the battery lifetime most efficiently, estimated at 14.8 years. However, it proved to be the least profitable, resulting in negative profit of −3€/kWh/yr. On the other hand, strategies with high and moderate charge/discharge rates resulted in positive profit of 8.3 €/kWh/year and 9.2 €/kWh/year, despite having shorter battery lifetimes, estimated at 10.1 years and 13.6 years, respectively. Furthermore, from a payback perspective, the strategy with fast charge/discharge capability led to 1.5 years shorter payback period than that of the moderate rate strategy. The findings highlight that the first set of scenarios limits the strategy’s flexibility in achieving both sustainability and profitability. In contrast, the second scenario achieves impressive profit (18 €/kWh/yr), shortest payback period (7.5 year), a commendable lifespan (12.5 years), contrasting revenue-focused scenarios, emphasizing the importance of striking optimal balance between revenue gain and degradation costs for charging/discharging actions, ensuring sustained profitability. The findings offer valuable insights for decision-makers, enabling informed strategic choices and effective solutions.

A data-driven framework for thermal comfort assessment method based on user interaction

The rapid development of smart home systems requires a transition of thermal comfort studies. A feasible, user-friendly, consumer-oriented thermal comfort assessment method for large-scale residential applications is extremely urgent. However, most studies of thermal comfort models have focused on large commercial buildings. The application and deployment of such methods often rely on multiple prerequisites like relatively steady thermal conditions, regular energy consumption schedule, and additional sensor information. While situations are different in residential scenarios. In this paper, over 100 thousand air conditioner users were analyzed and a fundamental but overlooked question in thermal comfort research was established. In the household environment, the thermal condition is more complicated. Difference in age, gender, and usage preference leads to diversity in individual thermal comfort. Furthermore, introducing more sensors for better comfort prediction performance is not acceptable both from the cost perspective and the user perspective. To bridge the above missing gap, a novel thermal comfort assessment framework combining user interaction and metric learning was constructed. The proposed framework can be used to construct thermal comfort assessment systems by exploiting user interaction actions, which is a low-cost alternative and complementary to the traditional methods based on thermal equilibrium. The ease of construction makes the framework easy to integrate into smart home systems, addressing the difficulty of applying thermal comfort studies in residential scenarios.

Solar flat plate collector's heat transfer enhancement using grooved tube configuration with alumina nanofluids: Prediction of outcomes through artificial neural network modeling

Solar thermal systems are far more important than solar PV systems in residential and commercial applications. Improving the efficiency of solar thermal technology is a major challenge. Several researchers separately studied the effects of turbulence enhancers and nanofluids to enhance heat transfer of solar flat plate collectors (SFPC). The current research focuses on the synergic effect of an internally grooved absorber tube and Al2O3-WEG-based nanofluid on SFPC performance. The experimental investigation used various concentrations of nanoparticles (0.01 %, 0.05 %, 0.1 %, and 0.2 %) and mass flow rates (MFR) (0.024 kg/s, 0.036 kg/s and 0.048 kg/s). The outcomes of Al2O3-WEG based nanofluid and plain working fluid were compared. MFRs of 0.036 kg/s and 0.2 % vol. Showed the highest efficiency for SFPC models 1 and 2. The efficiency enhancement of model 2 over model 1 of plain fluid increased in an order of 46.37 %, 54.13 %, and 33.83 % for MFRs of 0.024, 0.036, and 0.048 kg/s, respectively. The maximum efficiency enhancement of model 2 over model 1 was 54.1 % for a MFR of 0.036 kg/s with 0.2 % vol. The created ANN models predicted the output values of the SFPC experiment accurately in real-time.

AI-Driven Urban Energy Solutions—From Individuals to Society: A Review

This paper provides a comprehensive review of solutions based on artificial intelligence (AI) in the urban energy sector, with a focus on their applications and impacts. The study employed a literature review methodology to analyze recent research on AI’s role in energy-related solutions, covering the years 2019 to 2023. The authors classified publications according to their main focus, resulting in two key areas of AI implementation: residential and individual user applications, and urban infrastructure integration for society. The objectives of this review of the literature are the following: O1: to identify trends, emerging technologies, and applications using AI in the energy field; O2: to provide up-to-date insights into the use of AI in energy-related applications; O3: to gain a comprehensive understanding of the current state of AI-driven urban energy solutions; O4: to explore future directions, emerging trends, and challenges in the field of AI-driven energy solutions. This paper contributes to a deeper understanding of the transformative potential of AI in urban energy management, providing valuable insights and directions for researchers and practitioners in the field. Based on the results, it can be claimed that AI connected to energy at homes is used in the following areas: heating and cooling, lighting, windows and blinds, home devices, and energy management systems. AI is integrating into urban infrastructure through the following solutions: enhancement of electric vehicle charging infrastructure, reduction in vehicle emissions, development of smart grids, and efficient energy storage. What is more, the latest challenges associated with the implementation of AI-driven energy solutions include the need to balance resident comfort with energy efficiency in smart homes, ensuring compatibility and cooperation among various devices, preventing unintended energy consumption increases due to constant connectivity, the management of renewable energy sources, and the coordination of energy consumption.

Hydrogen Fuel Cell Integration: Automotive, Residential Power Generation & Portable Devices

Hydrogen fuel has emerged as a promising element in the quest for sustainable energy solutions across diverse sectors. This abstract distils the findings and insights from extensive research into hydrogen fuel integration, focusing on its applications in the automotive industry, residential power generation, and portable devices. In the automotive sector, hydrogen fuel cell vehicles (FCVs) offer a zero-emission alternative with extended driving ranges and rapid refuelling times, addressing some of the limitations of battery electric vehicles (BEVs). However, the successful integration of hydrogen as a transportation fuel hinges on the development of a robust refuelling infrastructure, cost reductions in fuel cell technology, and the optimization of energy-intensive hydrogen production processes. In residential power generation, hydrogen shows promise as a versatile energy carrier, capable of powering homes through fuel cells or combined heat and power (CHP) systems. To ensure sustainable residential hydrogen power, research efforts should continue to focus on efficient hydrogen production methods, such as advanced electrolysis powered by renewable energy sources. Furthermore, the integration of hydrogen in portable devices, including backup power systems and mobile electronics, is being explored. Overcoming challenges related to safe hydrogen storage, efficient energy conversion, and addressing energy density limitations are critical for expanding the utility of hydrogen in this domain. To drive further advancements, key research directions include the development of lightweight and high-capacity hydrogen storage materials, improvements in energy conversion efficiency, and enhanced safety measures for hydrogen-powered portable devices. Moreover, cross-sector collaboration between automotive, residential, and portable device applications is vital to optimize hydrogen production and utilization. Regulatory support and incentives play a pivotal role in promoting the adoption of hydrogen technologies, along with comprehensive life-cycle assessments to quantify their environmental impact.