Residential Applications Research Articles

Development of a Test Bench for Biogas-fueled Internal Combustion Engines Working in Cogeneration Mode for Residential Applications

The aim of this paper is the presentation of a test bench developed and installed at the Laboratory of the University of Bologna: the test bench has been developed for internal combustion engines, working as cogeneration units and fueled with biogas. In this perspective, the test bench purpose is to experimentally test and optimize the operation of cogenerative internal combustion engines on varying the boundary conditions, in terms of both biogas composition and electric and thermal load. Other main components are the anaerobic digester, a multi-fuel internal combustion engine, the electric load and a heat exchanger for the heat recovery from the exhaust gases and connected to a water circuit representing the thermal user. The test bench has been equipped with the opportune measurement devices, as well as with a specifically developed data acquisition system. First experimental tests, carried out on varying the methane content within the CH4-CO2 blend and the electric load allowed to optimize the test bench in terms of heat recovery section and air supply to the engine.

A Polygeneration System Based on Desiccant Air Conditioning Coupled with an Electrical Storage

This study presents an extension of a previous paper recently published by the authors. In particular, the current paper focuses on adding electrical storage to a polygeneration system developed for residential applications. Different from the previous work, it aims to design an off-grid facility. The polygeneration plant provides electricity, space heating and cooling, domestic hot water, and freshwater for a single-family dwelling in Almería, Spain. The main system technologies are photovoltaic/thermal collectors, reverse osmosis, and desiccant air conditioning. Lead-acid battery storage was added as a backup for the electrical system. The system was performed in the TRNSYS simulation environment for one year with a 5-min time step. A parametric study was carried out to investigate the grid dependence according to the number of batteries installed. Design optimization was also performed to provide the optimal system configuration for the off-grid case. A solar collector efficiency of 0.55 and a desiccant air-conditioning coefficient of performance of 0.42 were obtained. All demands were fully supplied, and the primary energy saving and CO2 saving achieved 100%. A minimum battery state of charge of 30% was reached for a few hours all year long.

Optimization of silver/water-based porous wavy direct absorption solar collector

Direct Absorption Solar Collectors (DASCs) are a widely utilized technology in residential applications. However, having known the limitation in DASC size, the efficiency must be enhanced by applying effective modifications and optimizing design parameters. In this study, the performance of a wavy bottom-shaped collector filled with an aluminum porous medium was investigated and the most influential characteristic parameters are specified. Then a design for DASC using Polyvinylpyrrolidone-coated silver nanofluid is proposed and characteristic parameters are optimized based on the full factorial design of the experiment methodology. The model consists of four primary factors, including nanofluid volume concentration (C=0.025%,0.05%,0.1%), porosity (ε=0.8,0.88,0.95), bottom wave amplitude (A=2.5,5,7.5mm), and bottom wavenumber (λ=15,30,60m−1). The results indicated that lowering porosity and increasing nanofluid concentrations improves collector efficiency, whereas rising the wave amplitude and wavenumber causes a higher pressure drop. Additionally, by employing the full factorial design, the main and interaction effects of factors on the efficiency and pressure drop of DASC as the response variables are evaluated. Thus, an optimum value is observed for wave amplitude to reach maximum efficiency and minimize pressure drop. By integrating a porous medium and a wavy bottom with nanofluid, the efficiency of DASC is enhanced from 52 to 93.7%, paving the way for their use in residential applications.

Artificial Intelligence Algorithms for Detecting and Classifying MQTT Protocol Internet of Things Attacks

The Internet of Things (IoT) grew in popularity in recent years, becoming a crucial component of industrial, residential, and telecommunication applications, among others. This innovative idea promotes communication between physical components, such as sensors and actuators, to improve process flexibility and efficiency. Smart gadgets in IoT contexts interact using various message protocols. Message queuing telemetry transfer (MQTT) is a protocol that is used extensively in the IoT context to deliver sensor or event data. The aim of the proposed system is to create an intrusion detection system based on an artificial intelligence algorithm, which is becoming essential in the defense of the IoT networks against cybersecurity threats. This study proposes using a k-nearest neighbors (KNN) algorithm, linear discriminant analysis (LDA), a convolutional neural network (CNN), and a convolutional long short-term memory neural network (CNN-LSTM) to identify MQTT protocol IoT intrusions. A cybersecurity system based on artificial intelligence algorithms was examined and evaluated using a standard dataset retrieved from the Kaggle repository. The dataset was injected by five attacks, namely brute-force, flooding, malformed packet, SlowITe, and normal packets. The deep learning algorithm achieved high performance compared with the developing security system using machine learning algorithms. The performance accuracy of the KNN method was 80.82%, while the accuracy of the LDA algorithm was 76.60%. The CNN-LSTM model attained a high level of precision (98.94%) and is thus very effective at detecting intrusions in IoT settings.

Lithium ion battery energy storage systems (BESS) hazards

There has been an increase in the development and deployment of battery energy storage systems (BESS) in recent years. In particular, BESS using lithium-ion batteries have been prevalent, which is mainly due to their power density, performance, and economical aspects. BESS have been increasingly used in residential, commercial, industrial, and utility applications for peak shaving or grid support. As the number of installed systems is increasing, the industry has also been observing more field failures that resulted in fires and explosions. Lithium-ion batteries contain flammable electrolytes, which can create unique hazards when the battery cell becomes compromised and enters thermal runaway. The initiating event is frequently a short circuit which may be a result of overcharging, overheating, or mechanical abuse. During the exothermic reaction process (i.e., thermal runaway), large amounts of flammable and potentially toxic battery gas will be generated. The released gas largely contains hydrogen, which is highly flammable under a wide range of conditions. This may create an explosive atmosphere in the battery room or storage container. As a result, a number of the recent incidents resulted in significant consequences highlighting the difficulties on how to safely deal with the hazard. This paper identifies fire and explosion hazards that exist in commercial/industrial BESS applications and presents mitigation measures. Common threats, barriers, and consequences are conceptually shown and how they would be identified in a hazard mitigation analysis (HMA). Mitigation measures that can be implemented to reduce the risk of a fire or an explosion are discussed. The presented information is intended to provide practical information to professionals and authorities in this fairly new industry to assure that prevention and mitigation strategies can be effectively implemented and that the regulatory requirement of the HMA can be met.

Overview of Natural Gas Boiler Optimization Technologies and Potential Applications on Gas Load Balancing Services

Natural gas is a fossil fuel that has been widely used for various purposes, including residential and industrial applications. The combustion of natural gas, despite being more environmentally friendly than other fossil fuels such as petroleum, yields significant amounts of greenhouse gas emissions. Therefore, the optimization of natural gas consumption is a vital process in order to ensure that emission targets are met worldwide. Regarding residential consumption, advancements in terms of boiler technology, such as the usage of condensing boilers, have played a significant role in moving towards this direction. On top of that, the emergence of technologies such as smart homes, Internet of Things, and artificial intelligence provides opportunities for the development of automated optimization solutions, which can utilize data acquired from the boiler and various sensors in real-time, implement consumption forecasting methodologies, and accordingly provide control instructions in order to ensure optimal boiler functionality. Apart from energy consumption minimization, manual and automated optimization solutions can be utilized for balancing purposes, including natural gas demand response, which has not been sufficiently covered in the existing literature, despite its potential for the gas balancing market. Despite the existence of few research works and solutions regarding pure gas DR, the concept of an integrated demand response has been more widely researched, with the existing literature displaying promising results from the co-optimization of natural gas along with other energy sources, such as electricity and heat.

3-E feasibility analysis on photovoltaic/thermal application for residential buildings: a case study of Sub-Saharan Africa

ABSTRACT This study was driven by the need to comprehend and give long-term answers to Nigeria’s ongoing energy crises and energy famine, despite the country’s tremendous endowment of renewable energy. The first step toward proffering such solutions is to present the potential benefits of solar-driven technology for residential applications. This study simulates the performance of a photovoltaic/thermal system for electricity and hot water production for a typical four-person residential settlement in different regions in Nigeria. This study computes the economic feasibility, as well as the environmental implications of the proposed PVT system on the considered geopolitical zones in Nigeria. The performance of the system were assessed on a technical, economic and environmental basis. Final system yield, performance ratio, electrical efficiency, and solar fraction were used for technical assessments, and cost savings was used for economic analysis. The relevant finding revealed that the maximum final yield (in this study) of 159kWh/kWp is retrieved in Maiduguri, while the least final yield of 75.8kWh/kWp is retrieved in Port Harcourt. The northeast (Maiduguri) showed the best annual final yield of 1735kWh/kWp. Onitsha and Port Harcourt showed a maximum performance ratio of 76.3%, and 76.2% respectively. The value of LCOE obtained in this study is in the range of 0.2518$/kWh-0.3838$/kWh, with an average of 0.3056$/kWh

Adaptation of residential solar systems for domestic hot water (DHW) to hybrid organic Rankine Cycle (ORC) distributed generation

Among the portfolio of energy systems for local power generation, Organic Rankine cycles (ORCs) for residential applications are an opportunity for local cogeneration based on synergies with existing thermal heating and storage systems. They can be highly competitive for isolated installations and the refurbishment of existing solar heating installations based on solar domestic hot water. This article evaluates the potential for hybrid solar ORC integration in residential buildings. The analyses focus on the annual yields of a domestic 1 kW ORC cycle to assess the advantages and disadvantages of the variation of demand and the availability of solar resources. The models are developed, integrating TRNSYS and EES to allow a detailed evolution characterisation. Performance and impact of CHP adaptation are considered based on demand, storage volume-collectors area ratio, and production strategies. The analysis is completed with a thermo-economic analysis under different ranges of thermodynamic parameters. Positive IRR results of 8.61% are obtained for the installation located in Seville, Spain, operating the ORC 15% of the year. It also reduces the overheating associated with the lack of heat demand and excess solar irradiation in the solar system for the warm months by 20%.

Compact Thermal Storage with Phase Change Material for Low-Temperature Waste Heat Recovery—Advances and Perspectives

The current interest in thermal energy storage is connected with increasing the efficiency of conventional fuel-dependent systems by storing the waste heat in low consumption periods, as well as with harvesting renewable energy sources with intermittent character. Many of the studies are directed towards compact solutions requiring less space than the commonly used hot water tanks. This is especially important for small capacity thermal systems in buildings, in family houses or small communities. There are many examples of thermal energy storage (TES) in the literature using the latent heat of phase change, but only a few are commercially available. There are no distinct generally accepted requirements for such TES systems. The present work fills that gap on the basis of the state of the art in the field. It reviews the most prospective designs among the available compact latent heat storage (LHS) systems in residential applications for hot water, heating and cooling and the methods for their investigation and optimization. It indicates the important characteristics of the most cost- and energy-efficient compact design of an LHS for waste heat utilization. The proper design provides the chosen targets at a reasonable cost, with a high heat transfer rate and effective insulation. It allows connection to multiple heat sources, coupling with a heat pump and integration into existing technologies and expected future scenarios for residential heating and cooling. Compact shell-tube type is distinguished for its advantages and commercial application.

Residential Appliance Identification Using 1-D Convolutional Neural Network Based on Multiscale Sinusoidal Initializers

Appliance identification and classification are primary requirement for successful deployment of demand side management in smart grid. Traditionally, load identification is carried out after extracting handcrafted features from electrical signals followed by classification algorithms, which is laborious and time consuming. To nullify the abovementioned shortcomings, this article proposes a 1-D convolutional neural network (CNN) with sinusoidal kernel initializers for classification of domestic appliances operating individually or in combination with other devices. For efficient operation, 15 primary and 225 multiscale sinusoidal kernels (MSK) are formed and included in the CNN architecture for extracting important discriminative features from the current signals. Classification accuracy of the proposed CNN module, named as MSK-CNN, is further improved by adding a new nonlinear activation function (AF), SL-ReLU, having an adjustable logarithmic function along with softsign and ReLU functions. The efficacy of MSK-CNN is tested on a practical dataset, created by the authors, consists current signals of different real life residential appliances. It is showed that MSK-CNN can successfully distinguish 18 single and 12 appliance combinations, and can attain an accuracy of 98.61%. The experimental outcomes reveal superiority of the MSK-CNN over classical CNN modules with other kernel initializers and AFs in terms of classification accuracy and training convergence.

PV-EV integrated home energy management using vehicle-to-home (V2H) technology and household occupant behaviors

The Vehicle-to-Home (V2H) topic is considered a promising and potential field of research due to its ability to address a variety of issues related to smart household electricity consumption and consumer energy demand. Therefore, as the population grows and their habits change, so does the need for domestic energy. Consequently, the provision of electricity poses increasingly difficult problems. To this end, the Home Energy Management System (HEMS) is being implemented to avoid similar problems. To maximize the utilization of various home appliances under energy demand and a predetermined timetable, we propose a precise Home Centralized Photovoltaic (HOCP) System, which includes V2H technology, Solar Photovoltaic (SPV), and a Green Electric Vehicle (GEV). The suggested design is aimed at reducing residential energy demand by providing for optimal automation of appliances. The recommended HOCP design will cover household electricity demand under sunny and rainy conditions without requiring additional electricity. On the other hand, the combination of electricity transmission SPV and V2H is sufficient to meet the demand for residential load in cloudy and sunny conditions. In this vein, HEMS with various constraints is implemented to perform proper system operations and satisfy load demand. The proposed algorithm attempts to characterize and perceive the situation of sources through the use of energy demand. The results show that H2V in combination with a renewable energy source can effectively reduce energy use and future residential applications during peak periods.

Thermal analysis of hybrid photovoltaic-thermal water collector modified with latent heat thermal energy storage and two side serpentine absorber design

The most popular renewable energy source is solar energy, which characterises as free, clean, and environmentally friendly. Photovoltaics (PV) generate electricity from daylight, becoming increasingly popular in residential and other applications. The potential energy delivery from a photovoltaic module is a function of solar radiation falling on the front surface and module operating temperature. However, these systems are modified to improve energy generation by placing an absorber on the bottom side of the module termed a Photovoltaic Thermal (PVT) system to reduce module temperature. The current study aims to investigate the experimental heat transfer efficiency for the fabricated PVT system employing two-sided serpentine flow thermal absorber and phase change material (PCM). PCM discharge the latent heat during off-sunshine hours to provide additional hot water. The experiment setup was tested with water as a working fluid in the flow rate range of 0.0085–0.067 kg/s. The optimal flow rate at which maximum heat gain of 757 W was obtained 0.033 kg/s with an average energy-saving efficiency of 69 %. The results confirm enhanced energy delivery of 3–5 % by PVT-PCM system compared to reference PV module for the same ambient operating conditions. Furthermore, the study reveals that overall efficiency of the PVT setup augment with the use of a thermal absorber and PCM, while the thermal efficiency is a factor that depends on the working fluid properties.

Using Household Electricity Metrics in Identifying Trends in Residential Appliances Usage in Selected Ghanaian Homes

Using Household Electricity Metrics in Identifying Trends in Residential Appliances Usage in Selected Ghanaian Homes

An in vitro alveolar model allows for the rapid assessment of chemical respiratory sensitization with modifiable biomarker endpoints

Diisocyanates are commonly used in polyurethanes where use includes industrial, commercial, and residential applications and can exist as respirable contaminants. These respirable contaminants exist in the air we breathe. Yet, there is no rapid assay available to test for potential respiratory sensitizers. To assess these hazards, as well as to decrease animal numbers used in testing, investigations that lead to verifiable in vitro methods are needed. We describe an easy, reliable, verified cell culture model that can be adopted by any lab capable of performing molecular toxicology. The architecturally relevant alveolar model consists of epithelial cells, macrophage cells, and dendritic cells in a simply maintained submerged system ideal for high-throughput testing. Exposures to contaminants that verify biomarker identification include a known pulmonary sensitizer (isophorone diisocyanate) and a positive control for cellular activation (phorbol 12-myristate 13-acetate/ionomycin). The mitochondrial reactive oxygen species generation and cytostructural changes were assessed with confocal laser scanning microscopy; cell morphology was assessed with scanning electron microscopy; biochemical reactions were assessed via protein arrays; genetic alterations were assessed via gene arrays; and cell surface activation markers were assessed via flow cytometry. Results showed that compared to untreated cultures, isophorone diisocyanate increased markers for dendritic cell activation, trafficking, and antigen presentation; number and length of dendritic protrusions; oxidative stress; and genetic and cytokine expression of neutrophil chemoattractants. The chemokines and cytokines CCL7, CXCL5, IL-6, and IL-8 were identified as biomarkers indicative of respiratory sensitization. By including multiple methods to assess endpoints, the in vitro model described can serve as a high-throughput assay to identify substances which may lead to respiratory sensitization.

Solid Oxide Fuel Cell-Based Polygeneration Systems in Residential Applications: A Review of Technology, Energy Planning and Guidelines for Optimizing the Design

Solid oxide fuel cells are an emerging energy conversion technology suitable for high-temperature power generation with proper auxiliary heat. Combining SOFCs and polygeneration has produced practical applications for modern energy system designs. Even though many researchers have reviewed these systems’ technologies, opportunities and challenges, reviews regarding the optimal strategy for designing and operating the systems are limited. Polygeneration is more complicated than any other energy generation type due to its ability to generate many types of energy from various prime movers. Moreover, integration with other applications, such as vehicle charging and fueling stations, increases the complication in making the system optimally serve the loads. This study elaborates on the energy planning and guidelines for designing a polygeneration system, especially for residential applications. The review of polygeneration technologies also aligns with the current research trend of developing green technology for modern and smart homes in residential areas. The proposed guideline is expected to solve the complication in other applications and technologies and design the polygeneration system optimally.

Highly Selective Multiple Gases Detection Using a Thermal-Conductivity-Based MEMS Resonator and Machine Learning

There is an urgent need to develop innovative and highly selective gas sensors for environmental, residential, and industrial applications. Here, we propose a highly selective multiple gases detection system using an electro-thermally heated silicon micro-resonator and machine- learning algorithms. The device is based on the cooling/heating effect of gases on the thermal stresses of a resonating structure. As a case study, we demonstrate sensitive and selective responses toward He, Ar, and CO2. To generate the unique signature markers for each gas, multiple datasets are collected at three different concentration levels (4%, 10%, and 25%). A principal component analysis (PCA) is conducted using seven customized highly significant and unique signature markers. The markers are obtained through data processing from the response of all gases. Quadratic discriminant and medium Gaussian support vector machines (SVMs) are used for training based on the seven customized features, which yield a high classification accuracy of 100 %. The proposed gas- sensing approach can be promising for the development of intelligent and highly selective compact size sensing platforms without the need for special materials for coating and functionalization.

A proton-exchange membrane fuel cell and ultra-capacitor system model for stand-alone residential applications

Energy consumption by sector in Malaysia is rising significantly, especially for residential and commercial sectors, and is expected to continue to increase in the upcoming years. The existing power generated from a proton-exchange membrane fuel cell (PEMFC) system may be insufficient to sustain peak load demands during peak periods in stationary residential applications. The presence of an ultra-capacitor (UC) bank would be beneficial as a support as it can supply a large burst of power. The integration of PEMFC and UC has the potential to provide an effective way to supply power demands, has better energy efficiency, and is also economically friendly. In this research, we demonstrate a proposed combined PEMFC and UC bank that operates in parallel. A novel design methodology and dynamic model for both PEMFC and UC systems as energy sources have been developed for stand-alone residential applications. The simulation results are shown in Matlab Simulink. These results are based on mathematical and dynamic models of the system being shown.

Experimental Assessment of Rotary Solid Desiccant Dehumidifier Assisted Hybrid Cooling System

"The prime objective of the present investigation is to assess the performance evaluation of rotary solid desiccant dehumidifier integrated vapor-compression integrated hybrid thermally cooling system by experimental investigation for the transient humid conditions. The experimental test set up is precisely designed and practically fabricated so as to obtain the consistent experimental data during performance testing. The main aim of the experimental investigation is to measure the overall system performance of the rotary solid desiccant assisted hybrid dehumidification and cooling system in terms of COP by measurement at various ambient conditions, air stream flow rates and different regeneration temperatures. The desiccant integrated hybrid thermally cooling system (DAHCS) is primarily the environmental protection technique for indoor comfort cooling purpose of the various residential and commercial building applications. This system also reduces the CFC level in the environment because it minimizes the use of conventional refrigerant. It is found that the rotary solid desiccant dehumidifier assisted hybrid cooling system (DAHCS) is alternate suitable option against vapor compression integrated conventional cooling system in transient humid climates. The desiccant assisted hybrid cooling system (DAHCS) has proven their feasibility and energy saving in the field of built environment. It is concluded that this innovative cooling technology is feasible and demand low energy for comfort cooling. This study is very useful in enhancing opportunities to extend further innovation and core research in different areas of desiccant integrated hybrid thermally cooling system.

Thermal performance assessment and control optimization of a solar-driven seasonal sorption storage system for residential application

The present paper analyzed the thermal performance and control optimization of a solar system based on seasonal sorption storage for domestic applications. The system control, which could choose between 41 operational modes, was optimized based on operational costs and maximization of sorption system use. The system was composed by 17.5 m2 of evacuated tube collectors, 3.6 m3 of composite sorbents based on lithium chloride and a stratified water tank. High efficiency of a sorption storage system was obtained when continuous charges or discharges occur, which, in this study, depended on weather conditions (ambient temperature and solar irradiation). The operational economic benefits were maximized using a sorption system with 9% less capacity and, therefore, less storage volume. The sorption thermal energy storage system obtained energy densities of 90 and 106 kWh/m3. The whole system could supply 35% of the total thermal demand of a single family house in Nuremberg. The study concluded that the control optimization of a seasonal sorption system is a key factor to make the technology competitive, define its optimal size and, therefore, maximize its energy density in further designs.

Archimedes Spiral Wind Turbine performance study using different aerofoiled blade profiles: Experimental and numerical analyses

Wind power is one of the most quickly expanding forms of clean energy. A novel horizontal axis wind turbine type, the Archimedes Spiral Wind Turbine (ASWT), is built for residential applications. The influence of the rotor pitch to diameter ratio (2s/D) and the aerofoil blade profile on the productivity of ASWT is investigated using experimentation and computer simulation. To fulfill the validation of the experimental work, the ANSYS Fluent solver provides the numerical solution. The tests are performed on a modified ASWT with a nominal blade thickness and blade angles of α1 = 25°, α2 = 50°, and α3 = 60° for the first, middle, and third blades. Wind speeds of 8 and 10 m/s were used. The NACA4401 ASWT with (2s/D) = 0.30 is the best-studied design. At a wind speed of 10 m/s, the maximum CP of the conventional, modified, and aerofoiled ASWTs is 0.243, 0.286, and 0.3045, respectively, at tip speed ratios (λ) of 1.5, 2, and 2. Compared to the conventional and modified ASWT, the aerofoiled ASWT exhibits a 26.88% and 6.47% improvement in the peak CP.