Residential Applications Research Articles

Review of microbial fuel cell from a techno-economic perspective

This review presents a techno-economic analysis of microbial fuel cells (MFCs) in the domain of generating sustainable energy and treating wastewater with the aim of attracting investors through research and development for residential and commercial applications. The operation principles and various MFC types, along with their advantages and disadvantages, are thoroughly considered. The efficiency of various MFC types is considered to present appropriate options for commercial applications. However, large-scale integrations face substantial financial limitations owing to the reluctance of investors. This review explores the cost-benefit balance associated with the operation of an MFC system. For encouraging investors, different cost variables, such as the initial investment, operating costs, potential electricity generation, and waste treatment capacity, are thoroughly considered. These variables are placed on the spectrum of a cost-benefit analysis to vitalize the economic feasibility of the MFC technology in various scenarios, considering an order of financial variables. MFC development at an optimized cost is the pivotal pre-requisite to secure a competitive advantage over conventional sources of energy with carbon emissions. Thus, this study is expected to prompt decision-makers to adopt the MFC technology at the commercial level.

Hydrogen energy system for cooling habitation located in Ghardaïa using TRNSYS 16

Hydrogen system is mainly based on the Proton Exchange Membrane PEMFC technology (cogeneration), using hydrogen and air, respectively, as fuel and oxidant. The heat exhaust is evacuated to the Thermal Storage Tank (TST) which is using in LiBr/H2O single effect absorption system for residential system cooling. Absorption system is based on evaporation of the refrigerant (water) in the evaporator in low pressure. Numerical simulation of the absorption cooling system using the thermal energy of the Proton Exchange Membrane Fuel Cell (PEMFC) for residential application situated in the Unit of Applied Research in Renewable Energy in Ghardaïa (southern Algeria) has been made and performances was analysed, we have determine the quantity of electrical and thermal energy generated by the PEMFC. TRNSYS 16 is used to plot initial and final residence temperatures before and after cooling. The results showed the feasibility of using PEMFC for cooling.

Impact of Solar Radiation on Luminaires and Energy Efficiency in Isolated Residential Photovoltaic Systems

This research centers on the implementation of photovoltaic systems in residential applications, coupled with battery-based energy storage, and evaluates their efficiency in generating energy, specifically for lighting in buildings. The methodology hinges on detecting interharmonic signals to characterize potentially disruptive frequencies and identify the origins of various failures. Multiple case studies are presented to validate the method’s efficacy, including one involving fluorescent lamp circuits and another examining variations in solar radiation during the summer season. Real-world experiments are conducted in a residential setting, and the results are thoroughly analyzed. Various types of interharmonic generation behaviors are demonstrated, which are influenced by fluctuations in solar radiation and the appropriate installation of solar panels. The findings reveal that the absence of solar radiation below 300 W/m2 in a photovoltaic system relying on energy storage adversely affects interharmonics in luminaires installed within a residential space.

Cascading approach can supply nuclear-powered heat to diverse industrial, residential applications

Expanding the range of needs met by nuclear-renewable integrated energy systems increases their viability and adoption.

An Internet of Things based Solar Power Monitoring System using Node MCU

Solar power systems are increasingly being adopted as a renewable energy solution worldwide. However, effective monitoring and management of these systems are crucial for optimizing their performance and ensuring their reliable operation. In this research paper, we propose a solar power monitoring system using NodeMCU, an open-source IoT platform. Our system collects, processes, and visualizes real-time data from solar panels, batteries, and other qsystem components, providing comprehensive monitoring capabilities for solar power system owners. The system is designed to be cost-effective and scalable, making it suitable for both residential and commercial applications. Through our research, we demonstrate the feasibility and effectiveness of our solar power monitoring system using NodeMCU. The findings contribute to the field of renewable energy management by offering an innovative approach to monitor and optimize solar power systems, promoting the wider adoption of renewable energy sources for a sustainable future.

Evaluating the Technical, Economic, and Environmental Performance of Solar Water Heating System for Residential Applications–Comparison of Two Different Working Fluids (Water and Glycol)

The use of solar water heaters (SWH) in both residential and commercial facilities is one of the possible ways to reduce electricity bills and the release of greenhouse gases (GHG). This study assessed the technical, economic, and environmental performance of a SWH system at six different locations in China (i.e., Lhasa, Lauchang, Wuhan, Kashi, Yumen, and Harbin). A comparison between two different working fluids (i.e., water and glycol) were modeled in the System Advisor Model in all six cities. A sensitivity analysis was conducted on some key technical and economic parameters to assess the impact of such parameters on the performance of SWH systems in the country. According to the results, Lhasa recorded the highest capacity factor of 11% and 10.70% using water and glycol as the working fluid, respectively. Lhasa was identified as the best location among the studied locations due to its high solar irradiation. The optimization study indicates that the optimum azimuth for China is 190°. It was also found that a 25% reduction in the outlet set temperature of the water can reduce the capacity factor from 11% to about 9.2%. Using the SWH as simulated in this study can reduce carbon dioxide emissions from 1252.87–2014.85 kg per year to 138.20–330.23 kg per year; the extent of reduction depends on the location of the SWHS, and the solar energy available at the area. Net electricity bill savings of $156–296 could be obtained if SWH systems were installed and used at the studied locations.

A Simplified Design Method for Quasi-Resonant Inverter Used in Induction Hob

Induction heating (IH) technology is widely recognized and utilized in residential applications due to its high efficiency and safe operating characteristics. Resonant inverter circuits are widely used in IH systems because of their high efficiency and ability to perform soft switching. Among the various resonant inverters used in IH systems, the single-switch quasi-resonant (SSQR) inverter topology is typically preferred for low-cost and low-output-power applications. Despite its cost advantage, the SSQR topology has a relatively narrow soft-switching range, which can be unstable depending on the electrical parameters of the load and the resonant converter circuit. Accurately determining the capacitance value of the resonant capacitor and the inductance value of the induction coil, which are the key circuit elements of the SSQR induction cooker, is crucial for designing a reliable, efficient, and durable cooking system. In other words, there exists a critical relationship between the resonant converter circuit parameters, load characteristics, and safe operating conditions. Additionally, when considering closed-loop control methods used for power control and safety, selecting appropriate resonant circuit elements becomes vital in ensuring both reliable and efficient operation. This paper focuses on a novel and simplified design method for the SSQR inverter utilized in household appliances. The proposed method and its advantages in terms of the safe operating area of the switch are theoretically investigated and verified through simulations and prototype circuits.

Day Ahead Solar Generation Forecasting in Smart Grids to Minimize Electricity Bill

Abstract: In order to meet the increasing growth of energy demand, integration of renewable resources into residential applications appears to be a viable solution. In the proposed model,a residential house is considered where the consumer is able to generate his own energy from a microgrid consisting of solar panels and wind turbines. In this study, an optimization method is employed to minimize the overall electricity bill of a residential home over a periodof 24 hours. In smart grids, energy management is imperative in reducing the electricity cost of consumers under a real time pricing approach. Nowadays, learning-based modeling methods are utilized to build a precise forecast model for renewable power sources. In this paper, we propose a long short-term memory (LSTM) recurrent neural network-based framework, which is one of the most popular techniques of deep learning. This technique predicts day ahead solar irradiation and wind speed data. We also consider an energy storage system (ESS) for efficient energy utilization. Optimization is done and from the obtained results a substantial reduction in electricity bill is observed

A smart green mashrabiyya-shutter design for residential applications in Egypt

ABSTRACT The revival of traditional latticework mashrabiyya is continually urged in the Middle East and North Africa to address conflicting needs since it optimally balances environmental, social, and aesthetic functions. However, its material and craftsmanship costs and inflexibility are significant barriers. This study aims to provide a preliminary design for a green, smart mashrabiyya-like shutter responsive to climatic conditions and privacy needs in Egypt, manufactured with palm midribs, a waste material available in the MENA region due to annual trimming. The simple, yet responsive and traditional design outlined in this study has a considerable potential for residential applications not only in Egypt, but also in similar socio-environmental contexts. The design generation is based on three steps: 1) constructing a static model that maintains the basic socio-environmental needs, manufactured with palm midrib patterns, 2) modeling dynamic functions, using Grasshopper/Ladybug, through standardizing slats and deciding upon visibility and adjustable parts, and 3) integrating smart controls based on comfort indexes and indoor climatic readings. Using a simple circuit fitted with sensors, actuators, and a microcontroller, the design of a latticework shutter responsive to climate and privacy was generated. The concept depends on computing indoor weather data and comparing them to thermal, daylight, and wind comfort indexes. Consequently, automated decisions could be made to regulate the shutter parts in two ways: 1) its opening angle and 2) openness between the slats. Ultimately, the operating concept of the smart shutter in a room and automated flowcharts that make decisions in daytime and nighttime modes were proposed.

Comparison of Wireless Data Transmission Protocols for Residential Water Meter Applications

Comparison of Wireless Data Transmission Protocols for Residential Water Meter Applications

Atomic Orbital Search Algorithm for Efficient Maximum Power Point Tracking in Partially Shaded Solar PV Systems

The efficient extraction of solar PV power is crucial to maximize utilization, even in rapidly changing environmental conditions. The increasing energy demands highlight the importance of solar photovoltaic (PV) systems for cost-effective energy production. However, traditional PV systems with bypass diodes at their output terminals often produce multiple power peaks, leading to significant power losses if the optimal combination of voltage and current is not achieved. To address this issue, algorithms capable of finding the highest value of a function are employed. Since the PV power output is a complex function with multiple local maximum power points (LMPPs), conventional algorithms struggle to handle partial shading conditions (PSC). As a result, nature-inspired algorithms, also known as metaheuristic algorithms, are used to maximize the power output of solar PV arrays. In this study, we introduced a novel metaheuristic algorithm called atomic orbital search for maximum power point tracking (MPPT) under PSC. The primary motivation behind this research is to enhance the efficiency and effectiveness of MPPT techniques in challenging scenarios. The proposed algorithm offers several advantages, including higher efficiency, shorter tracking time, reduced output variations, and improved duty ratios, resulting in faster convergence to the maximum power point (MPP). To evaluate the algorithm’s performance, we conducted extensive experiments using Typhoon HIL and compared it with other existing algorithms commonly employed for MPPT. The results clearly demonstrated that the proposed atomic orbital search algorithm outperformed the alternatives in terms of rapid convergence and efficient MPP tracking, particularly for complex shading patterns. This makes it a suitable choice for developing an MPP tracker applicable in various settings, such as industrial, commercial, and residential applications. In conclusion, our research addresses the pressing need for effective MPPT methods in solar PV systems operating under challenging conditions. The atomic orbital search algorithm showcases its potential in significantly improving the efficiency and performance of MPPT, ultimately contributing to the optimization of solar energy extraction and utilization.

A non-intrusive method of industrial load disaggregation based on load operating states and improved grey wolf algorithm

As for the internal load of electricity users, it can be determined by non-intrusive load monitoring (NILM), which is conducive to peak-load shift in the power grid. At present, the research on NILM focuses mainly on residential appliances, while industrial loads that consume large amounts of electricity may have more effective regulation capabilities in the face of large fluctuations in grid power brought about by a great deal of new energy connected to the grid, however, there is still little research conducted on the non-intrusive monitoring of industrial loads. In this paper, our consideration is given to the fact that industrial loads, compared to residential loads, operate steadily in the same state for a long time. Then, a non-intrusive industrial load disaggregation method is proposed on the basis of load operating states and improved grey wolf algorithm. On the one hand, this method takes into account the different times of load operation in different states, with the expanded label method proposed to improve the initialization of the population. On the other hand, median filtering is performed to process the results of first-generation load disaggregation in two times. Moreover, a strategy is proposed for multiple disaggregation of a single power according to this method. In addition, the search mechanism of the grey wolf algorithm is improved through the beta distribution of the three-point estimate and the genetic algorithm. According to the experimental results, the proposed method is effective in improving the accuracy of load disaggregation, the impact of high-power load on low power load disaggregation is mitigated to a certain extent, and the accuracy of each load reaches a minimum of 90%.

A novel renewable energy system designed with Mg–Cl thermochemical cycle, desalination and heat storage options

In this paper, a novel multigenerational integrated system that is able to produce five useful commodities, such as freshwater, space heating, hot water, power and hydrogen for a community, is proposed and investigated. The system uniquely covers heat storage by molten salt heat storage along with hydrogen production by magnesium-chlorine (Mg–Cl) based thermochemical cycle. Additionally, the present system has a multi-effect desalination plant to provide freshwater community needs. A solar power tower is offered due to its capability of harvesting high energy levels. The heat recovered by the solar power receiver is passed through an organic Rankine cycle (ORC) to meet the need for the high-temperature level that is required for the thermochemical cycle. The molten salt storage tanks are used to offset the mismatch between demand and supply for the necessary energy to run the system in case of the absence of solar irradiation. The suggested system is intended to leverage solar and geothermal energy sources to generate practical necessities like power, heat, and hot water for residential applications of a projected community. The system is then analyzed in detail thermodynamically in the context of exergy and energy approaches. In addition, the subsystems are analyzed parametrically to study the performance of the overall system to observe how the ambient and working conditions change the system efficiencies. The city of Vancouver in Canada is selected as the potential location where the system performance assessment is carried out accordingly. As a result of the present thermodynamic analysis, the energetic and exergetic efficiencies for the system are obtained as 45.45% and 52.32%. The total exergy destruction rate is another exergy metric to compare both versions, where the rate of 163967.39 kW exergy destruction is obtained for the overall system.

Thermo-hydraulic performance augmentation in residential heating applications using a novel multi-fluid heat exchanger with helical coil tube insertion

This study proposes a heat transfer augmentation technique using a brazed helix tube (BHT) fabricated from a helical tube with precision brazing between coil turns in a novel multi-fluid heat exchanger (NMFHE) for simultaneous heating of water and air using solar energy. The thermo-hydraulic performance of the present NMFHE for residential heating of water (CW) and air (CA) using hot water (HW) is tested experimentally. Nusselt number and friction factor for fluid flow inside the NMFHE are calculated as the thermo-hydraulic measure relating to variations in flow rate, inlet temperature, and flow configuration. Optimal flow parameters for overall optimized performances that is, maximum heat transfer and minimum pressure drop in NMFHE are determined using the Taguchi Grey relational approach. NMFHE performs efficiently in the Counterflow (cold water reverse) flow configuration with HW flow rate of 100 LPH, CW flow rate of 200 LPH, and HW inlet temperature of 70°C. The CW flow rate has the greatest impact on both the Nusselt number and friction factor, with a contribution of 82.37% and 93.42%, respectively. A confirmation test has been conducted to validate the findings, revealing a significant performance improvement of 32.19% when using the Grey relational grade model.

Performance Evaluation of a Fuel Cell mCHP System under Different Configurations of Hydrogen Origin and Heat Recovery

Motivated by the growing importance of fuel cell systems as the basis for distributed energy-generation systems, this work considers a micro-combined heat and power (mCHP) generation system based on a fuel cell integrated to satisfy the (power and thermal) energy demands of a residential application. The main objective of this work is to compare the performance of several CHP configurations with a conventional alternative, in terms of primary energy consumption, greenhouse gas (GHG) emissions and economic viability. For that, a simulation tool has been developed to easily estimate the electrical and thermal energy generated by a hydrogen fuel cell, and all associated results related to the hydrogen production alternatives: excess or shortfall of electrical and thermal energy, CO2 emission factor, overall performance, operating costs, payback period, etc. A feasibility study of different configuration possibilities of the micro-CHP generation system has been carried out considering different heat-to-power ratios (HPRs) in the possible demands, and analyzing primary energy savings, CO2 emissions savings and operating costs. An extensive parametric study has been performed to analyze the effect of the fuel cell’s electric power and number of annual operation hours as parameters. Finally, a study of the influence of the configuration parameters on the final results has been carried out. Results show that, in general, configurations using hydrogen produced from natural gas save more primary energy than configurations with hydrogen production from electricity. Furthermore, it is concluded that the best operating points are those in which the generation system and the demand have similar HPR. It has also been estimated that a reduction in renewable hydrogen price is necessary to make these systems profitable. Finally, it has been determined that the most influential parameters on the results are the fuel cell electrical efficiencies, hydrogen production efficiency and hydrogen cost.

Study of the Influences of Fuel Utilization on Efficiency and Anode Safety at Different Fuel Flow Rates for Industrial-Size Solid Oxide Fuel Cell

Solid oxide fuel cell (SOFC) is regarded as a promising energy conversion technology that can directly produce electricity from chemical fuels without combustion. Commercialization of SOFC systems has already started with residential and industrial applications, and demonstrations for a broader range of uses have been carried out. However, the widespread commercialization of SOFC systems requires further improvements both in efficiency and durability. The efficiency of a single cell is affected by fuel utilization and voltage. In addition, high fuel utilization may cause an increase in concentration polarization or lead to local Ni oxidation of cell anode. Therefore, it is imperative to study the influence of fuel utilization on the cell's performance, efficiency, and anode safety. In this work, I-V curves at different fuel flow rates were tested. The fuel utilization and voltage corresponding to the peak power density at different flow rates were determined. Based on the gas conversion and diffusion resistance models, the area specific resistance behavior and the fuel utilization corresponding to the beginning of the concentration polarization zone were investigated. Besides, the effects of fuel utilization and cell voltage on local Ni oxidation were also studied. The results indicated that at a low fuel flow rate of 0.1-0.3 L/min, the fuel utilization corresponding to the peak power density condition (which is also the condition of maximum efficiency) was about 90%. Although a significant increase in concentration polarization occurred under such high fuel utilization, no Ni oxidation occurred due to the high voltage. However, at a high fuel flow rate of 0.8-1.0 L/min, the fuel utilization corresponding to the peak power density condition was about 70%. The low voltage led to local Ni oxidation before entering the concentration polarization zone. This finding provides an idea for choosing fuel utilization at different fuel flow rates to realize high efficiency and anode safety.

Easy-to-install battery storage based residential power supply with contactless power transfer

Solar energy with battery storage has enormous potential for residential power supply applications. However, the installation is often complicated with lots of wiring. The wireless power transfer (WPT) interface can greatly reduce the complicated wiring part, facilitating easier installation, with additional benefits like electrical isolation, lower maintenance cost, better reliability. However, rigorous proof-of-concept of WPT for LV household power supply still remains to be largely unexplored. This work fills the research gap by presenting application of contactless power transfer system with battery storage for the solar-powered low-voltage (LV) power supply. Various resonant topologies for inductive power transfer (IPT) are studied, and a complete theoretical model of an LCL compensated IPT system integrated with a battery energy storage system is presented. The voltage and current characteristics are investigated to understand the operation of the proposed integrated IPT system at LVDC level. The setup is first realized and analysed in details in simulation using MATLAB/Simulink. Hardware experiments proves the feasibility of the contactless power transfer capability at the high efficiency of the integrated IPT battery system. The results show that the proposed system can maintain a constant load voltage of 48 V for a load variation of around 25%, with an efficiency of 92% at 85 kHz switching frequency.

Assessing techno-economic feasibility of cogeneration and power to hydrogen plants: A novel dynamic simulation model

Green hydrogen technologies are crucial for decarbonization purposes, while cogeneration offers efficient heat and power generation. Integrating green hydrogen and cogeneration brings numerous benefits, optimizing energy utilization, reducing emissions, and supporting the transition to a sustainable future. While there are numerous studies examining the integration of combined heat and power with Power to Gas, certain aspects still requires a more detailed analysis, especially for internal combustion engines fuelled by natural gas, due to their widespread adoption as one of the primary technologies in use. Therefore, this paper presents a comprehensive numerical 0-D dynamic simulation model, implemented within the TRNSYS environment, considering internal combustion engines fuelled by natural gas. Specifically, the study focuses on capturing CO2 from exhaust gases and producing green hydrogen from electrolysis. Based on these considerations, two configurations are proposed: the first involves the methanation reaction, while the second entails the production of a hydromethane mixture. The aim is to evaluate the technical and economic feasibility of these configurations and compare their performance within the Power to Gas framework. Self-sufficiency from the national electricity grid has been almost achieved for the two configurations, considering an industrial case. The production of hydromethane allows smaller photovoltaic plant (81 kWp) compared to the production of synthetic methane (670 kWp) where a high quantity of hydrogen is required, especially if all the carbon dioxide captured is used in the methanation process. Encouraging economic results with payback times below ten years have been obtained with the use of hydromethane. Moreover, hydromethane shows potential residential applications, with small required photovoltaic sizes.

Analysis of optimal expansion dynamics in a reciprocating drive for a micro-CAES production system

This paper presents the unique design and processing conditions of a micro-CAES device that generates, stores and delivers electrical energy with highly efficient total energy conversion. The micro-CAES installation is divided into six parts, where air, the energy carrier, is compressed, stored, heated and expanded in appropriate sections. We focus mainly on the post-preparation section, where the air mass flow is pulse heated and controlled by Pulse Width Modulation (PWM), and the expansion section, where multiple piston drives are used to achieve maximum energy conversion efficiency or the required amount of electricity to be fed into the grid. We discover that the controllability of expansion process performance is improved by exploiting the inertia of the following elements in multiple reciprocating engines: piston, piston rod, connecting rod, crank, and crankshaft, connected with air injection dynamics and pulse heating by Thermal Energy Storage (TES). Furthermore, we investigate the efficiency using our own zero-dimensional mathematical model illustrating the complex dynamics of air processing. The mathematical model was compared with experimental data for the single-drive air expander, showing qualitatively and quantitatively satisfying model reliability. Moreover, we performed a sensitivity analysis to determine the best number of reciprocating drives involved in the expansion section and the best operating conditions. The use of the PWM function of mass flow of air supplied the expander with an index of 0.5 together with pulsating air heating in the expander installation, including three- reciprocating drives, allows a maximum total energy conversion efficiency of 81%. The presented piston drive expander seems to be a promising solution for micro-CAES in residential and industrial applications, especially where additional low-temperature waste heat is available, and an intermittent control strategy is implemented.

Efficient Techniques for Residential Appliances Scheduling in Smart Homes for Energy Management Using Multiple Knapsack Problem

The evolution of the smart grid has enabled residential users to manage the ever-growing energy demand in an efficient manner. The smart grid plays an important role in managing this huge energy demand of residential households. A home energy management system enhances the efficiency of the energy infrastructure of smart homes and provides an opportunity for residential users to optimize their energy consumption. Smart homes contribute significantly to reducing electricity consumption costs by scheduling domestic appliances effectively. This residential appliance scheduling problem is the motivation to find an optimal appliance schedule for users that could balance the load profile of the home and helps in minimizing electricity cost (EC) and peak-to-average ratio (PAR). In this paper, we have focused on appliance scheduling on the consumer side. Two novel home energy management models are proposed using multiple scheduling options. The residential appliance scheduling problem is formulated using the multiple knapsack technique. Serial and parallel scheduling algorithms of home appliances namely MKSI (Multiple knapsacks with serial implementation) and MKPI (Multiple knapsacks with parallel implementation) are proposed to reduce electricity cost and PAR. Price-based demand response techniques are incorporated to shift appliances from peak hours to off-peak hours to optimize energy consumption. The proposed algorithms are tested on real-time datasets and evaluated based on time of use pricing tariff and critical peak pricing. The performance of both the algorithms is compared with the unscheduled scenario and existing algorithm. Simulations show that both proposed algorithms are efficient methods for home energy management to minimize PAR and electricity bills of consumers. The proposed MKSI algorithm achieves cost reduction of 20.26% and 42.53% for TOU and CPP, respectively as compared to the unscheduled scenario while PAR is reduced by 45.07% and 39.51% for TOU and CPP, respectively. The proposed MKPI algorithm achieves 22.33% and 46.36% cost reduction compared to the unscheduled case for TOU and CPP while the PAR ratio is reduced by 46.47% and 41.16% for TOU and CPP respectively.