Search Results (11)

Appliance recognition from aggregate household measurements is challenging under real deployment conditions, where multiple devices operate concurrently and sensor data are affected by imperfections such as noise, missing samples, and nonlinear meter response. In contrast to many studies that rely on curated or idealized datasets, this work investigates appliance recognition using real multimodal utility data (electricity, water, gas) collected at the building entry point, in the presence of substantial uninstrumented background activity. We present a case study evaluating transparent, rule-based detectors designed to exploit characteristic temporal dependencies between modalities while remaining interpretable and robust to sensing imperfections. Four household appliances—washing machine, dishwasher, tumble dryer, and kettle—are analyzed over six weeks of data. The proposed approach achieves reliable detection for structured, water-related appliances (22/30 washing cycles, 19/21 dishwashing cycles, and 23/27 drying cycles), while highlighting the limitations encountered for short, high-power events such as kettle usage. The results illustrate both the potential and the limitations of conservative rule-based detection under realistic conditions and provide a well-documented baseline for future hybrid systems combining interpretable rules with data-driven adaptation. Full article

Load disaggregation has emerged as an effective tool for enabling smarter energy management in residential and commercial buildings. By providing appliance-level energy consumption estimation from aggregate data, it supports energy efficiency initiatives, demand-side management, and user awareness. However, several challenges remain in improving the accuracy of energy disaggregation methods. For instance, the amount of noise in energy consumption datasets can heavily impact the accuracy of disaggregation algorithms, especially for low-power consumption appliances. While disaggregation performance depends on hyperparameter tuning, the influence of data characteristics, such as noise, on hyperparameter selection remains underexplored. This work investigates the hypothesis that appliance-specific noise information can guide the selection of algorithm hyperparameters, like the input sequence length, to maximize disaggregation accuracy. The appliance-to-noise ratio metric is used to quantify the noise level relative to each appliance’s energy consumption. Then, the selection of the input sequence length hyperparameter is investigated for each case by inspecting disaggregation performance. The results indicate that the noise metric provides valuable guidance for selecting the input sequence length, particularly for user-dependent appliances with more unpredictable usage patterns, such as washing machines and electric kettles. Full article

The purpose of this investigation was to utilize pulsed electric field (PEF) technology to make sweet potato kettle chips (SPKC) healthier by lowering the amount of oil absorbed and reducing the amount of acrylamide formed during frying. Sweet potatoes were treated continuously in an Elea PEF Advantage Belt One system and prepared as SPKC, without peeling and sliced to a thickness of 1.7 mm. The specific energy for PEF application was set to either low (1.5 kJ/kg) or high (3.0 kJ/kg) with a field strength of 1.0 kV/cm and a pulse width of 6 μm. Batches of 500 g unrinsed potato slices were fried in canola oil at 130 °C for 360 s. The oil content in 3.0 g of fried SPKC was 1.39 g or 46.3%, whereas the oil content was 37.9% for high and 37.7% for low PEF-treatment conditions. Acrylamide (AA) in the fried SPKC was quantified by mass spectrometry to be 0.668 μg/g in the non-PEF control and 0.498 μg/g for low and 0.370 μg/g for high PEF treatment. The results of this study support the use of PEF in SPKC processing to reduce oil absorbance during frying by up to 9% and lower AA by up to 45%. Full article

Rising environmental consciousness has prompted increased scrutiny of the environmental impact of everyday activities, such as barbecuing—a popular summertime activity in Germany. This study aimed to explore the environmental impacts of three grilling techniques, charcoal (including reusable types such as swivel, round, and kettle grills, as well as disposable charcoal grills), gas, and electric grills, utilizing a life cycle assessment (LCA) approach including the manufacturing of grills, consumption of energy sources and grilling ingredients, as well as the end-of-life of the grills. Five impact categories were considered: global warming potential (GWP), acidification potential (AP), eutrophication potential (EP), abiotic depletion potential fossil (ADP), and land use (LU) according to the CML2016 and ReCiPe 2016 methodology. This study found that a barbeque event for four people results in GWP, AP, EP, ADP, and LU values ranging from 18 to 20 kg CO₂-eq., 174 to 179 g SO₂-eq., 166 to 167 g PO₄-eq., 102 to 138 MJ, and 36 to 38 m² annual crop-eq., respectively, across different types of grills. Furthermore, the ingredients proved to be the most significant contributor, surpassing 70% in all impact categories. Among the three types of grills, the electric grill emerged as the most environmentally friendly, while the disposable grill had the greatest environmental impact across the majority of categories. Lastly, the environmental impacts of varying consumer behaviors were evaluated to potentially assist consumers in adopting more sustainable grilling practices. Full article

With the massive, worldwide, smart metering roll-out, both energy suppliers and users are starting to tap into the potential of higher resolution energy readings for accurate billing, improved demand response, improved tariffs better tuned to users and the grid, and empowering end-users to know how much their individual appliances contribute to their electricity bills via nonintrusive load monitoring (NILM). A number of NILM approaches, based on machine learning (ML), have been proposed over the years, focusing on improving the NILM model performance. However, the trustworthiness of the NILM model itself has hardly been addressed. It is important to explain the underlying model and its reasoning to understand why the model underperforms in order to satisfy user curiosity and to enable model improvement. This can be done by leveraging naturally interpretable or explainable models as well as explainability tools. This paper adopts a naturally interpretable decision tree (DT)-based approach for a NILM multiclass classifier. Furthermore, this paper leverages explainability tools to determine local and global feature importance, and design a methodology that informs feature selection for each appliance class, which can determine how well a trained model will predict an appliance on any unseen test data, minimising testing time on target datasets. We explain how one or more appliances can negatively impact classification of other appliances and predict appliance and model performance of the REFIT-data trained models on unseen data of the same house and on unseen houses on the UK-DALE dataset. Experimental results confirm that models trained with the explainability-informed local feature importance can improve toaster classification performance from 65% to 80%. Additionally, instead of one five-classifier approach incorporating all five appliances, a three-classifier approach comprising a kettle, microwave, and dishwasher and a two-classifier comprising a toaster and washing machine improves classification performance for the dishwasher from 72% to 94% and the washing machine from 56% to 80%. Full article

In this paper, an inductive power transfer (IPT) system without compensation elements is presented for small house appliances. The proposed system’s transmitter side is an independent induction heating cooktop. IPT can be achieved when the kettle with the receiving coils is placed on the transmitter coil. The coils are designed with a high coupling coefficient. The magnetic system model consisting of aligned transmitter and receiver coils is created in the Maxwell program. In the created model, the analysis depends on the air gap and frequency, which are the variables that affect the wireless power transfer. The electronic circuit simulation uses the coil model to examine the system’s dynamic behavior. The design of the transmitter/receiver coils of the IPT system is made with a cylindrical coil with a diameter of 145 mm, taking into account that it is compatible with the dimensions of the existing kettle and induction heating cooktops coil. A half-bridge series resonant converter circuit is used to adjust the power transferred to the load. To verify the simulation results and test the designed system, an experimental circuit using a 2200 W kettle is carried out. In the experiments, the air gap between the coils is kept constant at 7 mm, and measurements are taken for different powers. Experimental results confirm the magnetic model and simulation results. As a result, wireless power transfer is realized in a wide range without loss of performance in the kettle. System efficiency is greater than the 90% specified in the Ki cordless kitchen standard, and the harmonic currents drawn from the mains are lower than the values determined by the IEC 61000-3-2 standard. Full article

Electric kettles are found in almost every household in the European Union. Within the preparatory study to establish the Ecodesign Working Plan 2015–2017, the electricity consumption of this product group in Europe was estimated at 20 to 33 TWh in 2012, with an energy-saving potential of more than 20%. This led to an Ecodesign preparatory study on kettles in 2020 to analyse the potential role of environmental policy-making for electric kettles in Europe in more detail. Based on elements from this study, this paper reviews worldwide policies covering this product group, methods to assess its energy efficiency and analyses of the potential of technical improvements to enhance energy efficiency. A method is suggested for measuring the power of kettles, and corresponding power-temperature measurements of selected kettles are presented. Overall, the findings indicate that technical optimization alone has a limited potential to improve the energy efficiency of kettles and to highlight the absence of a standard for measuring the energy consumption of electric kettles. However, user-related aspects of operating kettles offer a substantial saving potential. Heating too much water or at higher than required temperatures increase the energy consumption and related energy costs of private households. This could provide leverage for policy makers to improve the market and to reduce the environmental impact of this product group beyond mere technical optimization of energy efficiency, including aspects related to circular economy and energy sufficiency. Full article

Narrowband power-line communication seems to be a suitable communication technology designed for off-grid renewable energy solutions. Existing electrical installations can be designed both for the transmission of electricity and for the communication of electrical equipment operating inside such an installation. This study presents an implementation of the above-mentioned off-grid communication system and examines the basic problems related to its exploitation. The authors of this article focused their attention primarily on examining the disturbance of the communication channel caused by the use of typical electrical devices, such as: a light bulb, a kettle, etc. used in a household. The aim of the research was also to find the impact of switching on individual devices and their combinations on the disturbances during data transmission. Measurements of incorrectly transmitted data packets were carried out and then the test results were referred to the error measures. Moreover, the influence of the carrier frequencies on the signal attenuation and the method of eliminating the existing interferences were also discussed. Full article

The measurement of the energy consumption of electrical appliances, where the meter is installed at a single point on the main input circuit of the building, is called non-intrusive load monitoring (NILM). The NILM method can distinguish the loads that are currently active and break down how the loads consume electricity. A microcontroller with embedded software was selected to read the data into the NILM method process at a low sampling rate every 1 s or 1 Hz. The measured data and the data obtained by the NILM algorithm were displayed via an internet platform. This article presents an alternative low-cost embedded NILM system for household energy conservation with a low sampling rate, which could identify electrical appliances such as an air conditioner, refrigerator, television, electric kettle, electric iron, microwave oven, rice cooker, and washing machine. Four features of symmetry pattern were extracted, containing information on the value of active power change, the value of reactive power change, the number of intersection points between the active power data and the reference line, and an estimation of an equation for the starting characteristics of the electrical equipment. The proposed NILM system was tested in a selected test house that used a single-phase power system. A typical meter was also installed to compare the results with the proposed NILM. The validity of the tests was checked for 1 month in 3 houses to analyze the results. The proposed method was able to detect 91.3% of total events. The accuracy of the average ability of the system to disaggregate devices was 0.897. The accuracy value for total power consumption was 0.927. The continuous data recording of the NILM method provides information on the behavior of electrical appliances that can be used for maintenance and warnings. Full article

The natural gas hydrate (NGH) reservoir in China is mainly distributed in the continental shelf with water depths ranging from 600–1500 m, about 90% of which is stored in the shallow area of the deep sea, with weak cementation and non-diagenetic characteristics. In order to test and study this type of NGH, samples must be prepared in situ, in large quantities, and at fast speed. At present, there are problems with the common stirring, spraying, and bubbling preparation techniques available, such as slow generation rate, low gas storage density, and lack of rapid preparation. Therefore, the rapid preparation of large samples of non-diagenetic natural gas hydrate has received extensive attention at home and abroad. In view of this technical bottleneck, Southwest Petroleum University innovatively established a rapid preparation kettle of 1062 L. In this paper, the preparation experiment of natural gas hydrate in the South China Sea (the pressure of the preparation kettle was reduced from 7 MPa to 3.3 MPa) was carried out in the preparation method of the ‘three-in-one’ (stirring method, spraying method, bubbling method) and experimental test method. In the process of preparation of non-diagenetic gas hydrate, the data of dynamic image, temperature, pressure, electrical resistivity, and reaction time are tested. During the preparation of natural gas hydrate, temperature, pressure, and electrical resistivity curves in four preparation methods were made, respectively. Through the experimental data analysis of different preparation methods of natural gas hydrate, it has been found that the preparation time of natural gas hydrate using the stirring method, the spraying method, and the bubbling method alone require a longer preparation time. However, when the three-in-one method is used to prepare natural gas hydrate, the preparation cycle of natural gas hydrate is obviously shortened. The preparation time of the single method of stirring method, spraying method, and bubbling method is respectively about 5.13, 3.59, and 3.37 times as long as that of three-in-one method. The three-in-one method for preparing natural gas hydrate greatly improves the preparation efficiency, which has a great significance to the scientific and technological progress of experimental research and evaluation methods of natural gas hydrate. Full article

Organic Rankine Cycles (ORCs) are nowadays a valuable technology to produce electricity from low and medium temperature heat sources, e.g., in geothermal, biomass and waste heat recovery applications. Dynamic simulations can help improve the flexibility and operation of such plants, and guarantee a better economic performance. In this work, a dynamic model for a multi-pass kettle evaporator of a geothermal ORC power plant has been developed and its dynamics have been validated against measured data. The model combines the finite volume approach on the tube side and a two-volume cavity on the shell side. To validate the dynamic model, a positive and a negative step function in heat source flow rate is applied. The simulation model performed well in both cases. The liquid level appeared the most challenging quantity to simulate. A better agreement in temperature was achieved by increasing the volume flow rate of the geothermal brine by 2% over the entire simulation. Measurement errors, discrepancies in working fluid and thermal brine properties and uncertainties in heat transfer correlations can account for this. In the future, the entire geothermal power plant will be simulated, and suggestions to improve its dynamics and control by means of simulations will be provided. Full article