Individual Energy Consumption Research Articles

Evaluation of the results of the study of individual indicators of physical development, special physical fitness and sports nutrition "Power Pro" of graduates of higher education with specific training conditions, engaged in mixed martial arts

Evaluation of the results of the study of individual indicators of physical development, special physical fitness and sports nutrition "Power Pro" of graduates of higher education with specific training conditions, engaged in mixed martial arts and law enforcement officers In order to achieve and maintain a high level of functional and physical fitness, high sports results, and maintaining the health of those who practice, a number of pedagogical, methodical, psychological, and medical-biological aspects are necessary. Therefore, the introduction of specialized sports nutrition is expedient. With the rational development of nutrition schemes, it is possible to increase the performance of athletes, improve all necessary indicators and planned results. The purpose of the article is to develop a program and recommendations for optimizing sports nutrition "Power Pro" and research the impact of specialized nutrition on individual anthropometric, indicators of general and special physical fitness of graduates of higher education with specific training conditions, engaged in mixed martial arts and law enforcement officers. The experiment involved young men (average age 19.10±0.74), high school graduates with specific training conditions, engaged in mixed martial arts and law enforcement officers (Dnipropetrovsk State University of Internal Affairs), who were divided into 2 groups – control (n= 15) and experimental (n=15). The purpose of using specialized sports nutrition was as follows: 1. Increasing both general and special fitness (training and competition). 2. Preventive action of possible injuries and disruption of adaptation. 3. Timely and correct recovery of the body of those who are engaged, after a state of overstrain. 4. Providing the body of those who are struggling with food substances, taking into account individual energy consumption. To test the developed program for the introduction of specialized sports nutrition, before and after the experiment, the following parameters were studied: height, weight, dynamometers, VL, impact force. We have developed and implemented schemes for the ratio and combination of food substances: whey protein, BCAA (branched chain amino acids), creatine, taurine, a complex of vitamins and minerals. When developing the program of specialized sports nutrition "Power Pro" for the experimental group, the main factors such as age characteristics and body weight, gender of the test subjects, as well as individual characteristics of their physical development, specifics of the sport were directly analyzed. The obtained results of the study showed a statistically significant improvement of individual anthropometric and indicators of special physical fitness in the experimental group (p<0.05). This makes it possible to draw conclusions about the positive dynamics of the implemented program of specialized sports nutrition on the monitored indicators, which are basic for athletes specializing in mixed martial arts.

Comparative Analysis of Machine Learning Techniques for Non-Intrusive Load Monitoring

Non-intrusive load monitoring (NILM) has emerged as a pivotal technology in energy management applications by enabling precise monitoring of individual appliance energy consumption without the requirements of intrusive sensors or smart meters. In this technique, the load disaggregation for the individual device is accrued by the recognition of their current signals by employing machine learning (ML) methods. This research paper conducts a comprehensive comparative analysis of various ML techniques applied to NILM, aiming to identify the most effective methodologies for accurate load disaggregation. The study employs a diverse dataset comprising high-resolution electricity consumption data collected from an Estonian household. The ML algorithms, including deep neural networks based on long short-term memory networks (LSTM), extreme gradient boost (XgBoost), logistic regression (LR), and dynamic time warping with K-nearest neighbor (DTW-KNN) are implemented and evaluated for their performance in load disaggregation. Key evaluation metrics such as accuracy, precision, recall, and F1 score are utilized to assess the effectiveness of each technique in capturing the nuanced energy consumption patterns of diverse appliances. Results indicate that the XgBoost-based model demonstrates superior performance in accurately identifying and disaggregating individual loads from aggregated energy consumption data. Insights derived from this research contribute to the optimization of NILM techniques for real-world applications, facilitating enhanced energy efficiency and informed decision-making in smart grid environments.

ELEKTRA: Empowering prosumers with distributed prosumer grouping and game-theoretic energy procurement

In this paper, the ELEKTRA framework is introduced, a novel community energy management system that organizes the prosumers into autonomous communities and determines the prosumers’ optimal energy procurement in a distributed manner. Our motivation stems from the increasing complexity of the energy procurement for prosumers and the need for more efficient and decentralized approaches to optimize their energy consumption. The first element of the ELEKTRA framework implements an autonomous hedonic game-theoretic model at the prosumers’ home energy management controllers, considering the prosumers’ individual energy consumption and generation patterns, as well as the utility-provided rewards for proactive participation. Specifically, the prosumer grouping is modeled as a hedonic game, demonstrating the existence of a Nash-stable and individually-stable prosumer grouping. The second element of the ELEKTRA framework employs a distributed non-cooperative game-theoretic approach. This addresses how prosumers strategically consume energy to meet their needs while maximizing their payoff by procuring additional energy from the utility company. Also, utilizing the theory of n-person concave games allows for a thorough evaluation of accuracy, performance, and complexity in determining optimal energy consumption for prosumers. A comprehensive evaluation of the ELEKTRA framework is conducted using real data from the southwest region of USA. The results demonstrate the operational effectiveness of the ELEKTRA framework, showcasing its superiority in optimizing prosumer payoff compared to existing models. The performance assessment, grounded in real-world data, provides valuable insights into the efficacy of the ELEKTRA framework in contrast to current state-of-the-art.

Microwave Metamaterial Absorber with Radio Frequency/Direct Current Converter for Electromagnetic Harvesting System

This article presents the analysis of the electromagnetic (EM) properties of a novel metamaterial (MM) array in the microwave frequency range. The background for this work is the rapid development of portable devices with low individual energy consumption for the so-called “Internet of Things” (IoT) and the demand for energy harvesting from the environment on a micro scale through harvesters capable of powering billions of small receivers globally. The main goal of this work was to check the potential of the novel MM array structure for EM energy harvesting. The proposed MM array was analyzed in the CST Studio simulation environment. This resulted in the determination of the substitute average EM parameters (absorption, reflection, and transmission) of the MM array. Then, the MM array was manufactured, and the simulation results of the MM array parameters were experimentally validated in a microwave waveguide test system. Based on this conclusion, a prototype of the microwave MM absorber, together with an RF/DC converter, was designed and manufactured for harvesting EM energy from the environment. The system’s energy efficiency was evaluated, and its potential application in energy harvesting technology was appraised. Using a microwave horn antenna, the EM energy harvesting efficiency of the prototype was evaluated. It was about 50% at a microwave frequency of about 2.6 GHz. This may make the prototype attractive as an EM energy harvester or bolometric sensor.

IoT Connected Smart Energy Meter

Abstract: Dawn of household electricity has revolutionized the world making life much easier and improving standard of living but still 940 million (13% of the world) do not have access to electricity. It is therefore the responsibility of those with stable power supply to keep their use of electricity in check as the less power we waste the more there will be for the ones who need it. Our goal is to design and implement a system to accurately measure the power consumption of a household in kWh using PZEM-004T module and, using IoT principles, wirelessly transmit the data to the ThingSpeak cloud server where it could be visually displayed This could help individual real time energy consumption data so they can take action accordingly. We also aim to collect data from multiple households and use data analysis techniques to find out valuable information and make accurate predictions regarding the future power consumption and consequential actions to be taken.

Intelligent Reflecting Surface-Assisted Wireless Powered Heterogeneous Networks

In this paper, we introduce an intelligent reflecting surface (IRS)-assisted wireless powered heterogeneous network (WPHN) consisting of two heterogeneous groups of devices. Specifically, one group of devices, i.e., energy-harvesting devices (EHDs), are charged by external energy supplies, while the other group of devices, i.e., non-energy-harvesting devices (NEHDs), are powered by internal energy supplies. An IRS aims to participate in the wireless energy transfer (WET) in downlink and the wireless information transfer (WIT) in the uplink. A sum throughput maximization problem is formulated subject to the constraints of individual energy consumption, transmission time scheduling, and IRS phase shifts. To cope with the non-convexity of the problem, we first derive the optimal IRS phase shifts of the uplink WIT independently. Next, the semi-definite programming (SDP) relaxation is adopted to recast this non-convex problem into the convex one, which can be numerically solved. Then, a novel low-complexity scheme is developed to gain more insights and mitigate the computational complexity induced by the SDP relaxation. In particular, the dual problem and Karush-Kuhn-Tucker conditions are first utilized to obtain the optimal transmission time scheduling. Then, we propose a method based on Riemannian manifold optimization to compute the optimal IRS phase shifts of the downlink WET in closed-form. Finally, simulation results are presented to verify the optimality of our proposed scheme, and highlight the benefits induced by the IRS to coordinate these heterogeneous devices.

Energy consumption and operational profile of a wellboat—Analysis of a field study

Wellboats are specialised vessels designed for the transport and treatment of live fish in fish farms. These processes are highly energy demanding and hence a significant contributor to CO2 emissions. Norwegian fisheries and fish farming are targeting a 55% reduction by 2030 as compared to 1990 levels. This will require novel fuel concepts, based on zero-emission or low-carbon energy carriers, all of which have lower energy density and require more storage space than the traditional fossil energy carriers. To evaluate novel fuel concepts and measures to increase energy efficiency for these vessels, an operational profile including power and energy demand is needed. The purpose of this study was to identify the operational profile and to understand the individual energy consumption processes of a wellboat. A field study was conducted to collect operational data, and a manual log was made to describe the various operational phases and activities. The novelty of this study is the identification and definition of operational phases during a wellboat mission. The results show that the operational profile of a wellboat could be identified and divided into the following phases: Delousing, Transit, Loading, Unloading and Hotel load. The main findings show that Delousing and Transit are the phases that account for most of the energy consumption.

Proposition of an Energy Intake Estimating Scale through Item Response Theory.

Traditional methods for assessing individual energy consumption often involve lengthy and intricate procedures. This study aims to introduce an Energy Consumption Estimation Scale, utilizing Item Response Theory (IRT) for adolescents aged 18-19 years. This psychometric investigation applies IRT to 93 items extracted from a validated food frequency questionnaire. The study encompasses a representative sample of 2515 adolescents from the São Luís birth cohort in Brazil. The latent trait, energy intake, is derived using IRT and subsequently validated through hierarchical multiple linear regression modeling. Significance was established at p < 0.05. A Samejima's model was successfully fitted (CFI and TLI > 0.9 and RMSEA < 0.08), effectively capturing variations across all energy consumption levels. Factors associated with the latent trait demonstrate consistent behavioral patterns. Adolescents with higher energy intake exhibited increased consumption of dairy products, artificially sweetened beverages, and seasonal fruits and vegetables. The proposed Energy Consumption Estimation Scale demonstrates a reliable measurement of energy intake and serves as a practical and concise alternative for assessing energy consumption among adolescents. These findings suggest the potential for adapting similar models for different age groups and incorporating diverse food items based on the obtained results.

Development of Smart Meter to Monitor Real Time Energy Consumption for Sustainability

This study constructed a Smart Energy Meter where energy consumption can be viewed by the consumers based on rreal time using data from smart meters. Its goals are to increase productivity, make readings more precise, and take less time to determine an individual residence's energy consumption. The device is made up of the PZEM-016 AC Energy Meter, RS-485 UART Serial Converter, NodeMCU ESP8266, Blynk IoT Application, Arduino Uno R3, and LCD Arduino Keypad Module Shield Board. The PZEM-016 is used in this smart energy meter to measure voltage, current, power, frequency, power factor, and energy consumption. Because it lacks its own display, an RS-485 was utilized to communicate with the NodeMCU and Arduino Uno. The NodeMCU sends the parameters to Blynk IoT App as long as it is connected to a fixed mobile WiFi. The Blynk will then display a real-time measurement of the parameters. The Arduino Uno is programmed to display the parameters to the LCD Keypad Module. The device was tested in an actual household. The researchers conducted 48-hour observation on the household where the energy displayed in the Blynk IoT App and the LCD display matches at approximately 9 kWh which is the same as the actual energy meter of the house that is 9kWh. The device is also tested on different appliances which resulted in the same energy consumption in both the Blynk IoT App and LCD display with the ratingsof the appliances. The device was found functional.

Use of Automatic Dishwashers and Their Programs in Europe with a Special Focus on Energy Consumption

Due to the current high awareness and rising energy costs, the energy label of domestic appliances is an important indicator for consumers when buying a dishwasher. However, not all consumers use efficient Eco cycles on a regular basis. When investigating the use of domestic dishwashers and the chosen programs in a survey with 6090 participants from 11 countries in Europe, it turned out that only 25% used Eco cycles regularly while the vast majority of 48% prefer to use Normal/Auto cycles. We also assessed individual energy and water consumption as well as duration and temperature of the programs. Considering the fact that Eco programs are not well accepted due to their duration, our study shows that Short programs, which on average only last about 30 min and consume little energy and water, might be an economical and convenient alternative to the more time-consuming Eco programs. In fact, some Short programs considered in this study proved to consume less energy for a full dishwasher load (0.74 kWh on average) than the standard Eco programs (0.90 kWh on average), especially due to their shorter duration, but it is important to note that, according to the manufacturer, these programs are designed for rather lightly soiled dishes.

Leveraging realities of saving energy at home: Contributions of co-design to behavioural interventions

While reducing individual energy consumption contributes to climate change mitigation, many individuals who share this belief fail to act on it. While behavioural interventions try to address such intention-behaviour gaps, few approaches have worked with consumers to understand the realities of their opportunities and limitations to save energy at home. We argue that co-design is well-suited to address the unique challenges of climate-relevant behaviour change and propose an abductive co-design methodology to develop a behavioural intervention with household members based on the Model of Action Phases (MAP) framework. We implement the methodology to design an energy savings app and behaviour change intervention in Switzerland. The methodology shifts participants into an expert role and elucidates their motivations, real-life challenges, and knowledge gaps to save energy. Through group problem-solving and self-reflection, participants provided design inputs which address the socio-psychological gaps to progress behaviour through the preaction, action and postaction phases of the MAP. We assess the originality and feasibility of the co-design inputs, as well as reflect on the experience of the researchers and participants during the process. We conclude that co-design provided novel inputs relevant for progressing through the behaviour change stages identified by the MAP framework.

The thing that made me think

Abstract Given the threatening consequences of anthropogenic climate change, it is vital to modify energy-intensive daily routines to minimize individual energy consumption. However, changing daily routines is challenging due to their abstract, future-oriented nature and the comfort they provide. Interactive technologies can play a crucial role in facilitating this process. Instead of relying on rhetorical persuasion through information and appeals, we propose two design approaches within the research agenda of the MOVEN research group: (1) employing friction to disrupt routines, and (2) advocating for the interests of natural entities using counterpart technologies. Regarding the disruption of routines, we explore the use of humor as a design element to dampen the resulting resistance (i.e., psychological reactance). Moreover, we reflect on the opportunities of counterpart technologies as a new interaction paradigm in the context of sustainability. Finally, we discuss the potentials and limitations of individual behavior change for a holistic, sustainable transformation.

STUDY ON WALK-THROUGH ENERGY AUDIT OF A FACULTY BUILDING

Nigeria has been facing energy crisis for several years to meet the growing energy needs. Therefore, for sustainable environment and to contribute towards carbon neutrality, it is very much crucial to introduce energy audit in every sector in order to cut the growing demand. As such, this paper focuses on walk-through energy audit of Faculty of Engineering building in Federal University Dutsin-Ma. Data was collated manually and “Microsoft Excel” tool was used to analyze the building’s energy consumption. Electrical systems in the building were partitioned in to 68% for Surface panel light, 19% for Fan, 8% for AC, 3% for Fridge, 1% for Computer, 0.2% for projector, and 0.4% for printer and TV respectively. The result obtained shows total connected electric load as 131254-watt, with 10480-watt for lighting, 3380-watt for electrical equipment and 117394-watt for cooling and ventilation systems. Moreover, average individual energy consumption per day was found to be 463-kWh for AC, 151-kWh for Fan, 73-kWh for lighting, 23-kWh for fridge, 0.3-kWh for printer, 0.4-kWh for projector, 0.7-kWh for TV, and 10-kWh for Computer. The result also revealed that lighting systems have the highest percentage on number of appliances, whilst cooling and ventilation parameters have the highest power consumption amongst other parameters. Therefore, energy conservation measures discussed for AC being the highest energy consuming appliance may result to optimistic energy saving. Furthermore, reliable environmental-friendly alternative energy source that is up to 131-kW can be use to power lighting, cooling &amp; ventilation and electrical appliances of the Faculty building.

Retracted: A Method for Short-Term Prediction of the Metro Station's Individual Energy Consumption Item Based on G-ACO-BP Model.

[This retracts the article DOI: 10.1155/2021/3474077.].

Supporting Solar Energy Coordination among Communities

The transition to renewable energy is likely to require the creation of growing numbers of energy communities: collectives organized around shared, local renewable resources. Unlike individual households however, the requirements for such communities to share a resource and demand-shift their consumption are still unexplored. By deploying a custom sensor energy monitoring kit and data physicalization workshops with 17 households, we examine the factors that impact their coordination around the shared resource. We found that collective demand-shifting has an extended set of considerations including trade-offs related to privacy, flexibility and social cohesion which are core for navigating already delicate neighborly relations. We use these factors to propose design considerations for a digital system that can act as a mediator among households. Such a system should enable multiple levels of immediacy to account for people's routines, should have adjustable levels of privacy to balance policing and fairness and should be able to offload some of the mundane decision-making. This study moves beyond individual energy consumption behavior to help identify energy as a collective issue that demands collective action. Accordingly, our findings contribute to the development of a next generation of Ubicomp technologies that can support collective action for environmental sustainability.

Nonintrusive Load Monitoring Using Recurrent Neural Networks with Occupants Location Information in Residential Buildings

Nonintrusive load monitoring (NILM) is a process that disaggregates individual energy consumption based on the total energy consumption. In this study, an energy disaggregation model was developed and verified using an algorithm based on a recurrent neural network (RNN). It also aimed to evaluate the utility of the occupant location information, which is nonelectrical information. This study developed energy disaggregation models with RNN-based long short-term memory (LSTM) and gated recurrent unit (GRU). The performance of the suggested models was evaluated with a conventional method that uses the factorial hidden Markov model. As a result, when developing the GRU disaggregation model based on an RNN, the energy disaggregation performance improved in accuracy, F1-score, mean absolute error (MAE), and root mean square error (RMSE). In addition, when the location information of the occupants was used, the suggested model showed improved performance and good agreement with the real power and electricity consumption by each appliance.

A digital twin of a local energy system based on real smart meter data

The steadily increasing usage of smart meters generates a valuable amount of high-resolution data about the individual energy consumption and production of local energy systems. Private households install more and more photovoltaic systems, battery storage and big consumers like heat pumps. Thus, our vision is to augment these collected smart meter time series of a complete system (e.g., a city, town or complex institutions like airports) with simulatively added previously named components. We, therefore, propose a novel digital twin of such an energy system based solely on a complete set of smart meter data including additional building data. Based on the additional geospatial data, the twin is intended to represent the addition of the abovementioned components as realistically as possible. Outputs of the twin can be used as a decision support for either system operators where to strengthen the system or for individual households where and how to install photovoltaic systems and batteries. Meanwhile, the first local energy system operators had such smart meter data of almost all residential consumers for several years. We acquire those of an exemplary operator and discuss a case study presenting some features of our digital twin and highlighting the value of the combination of smart meter and geospatial data.

COMPREHENSIVE METHOD OF ENERGY-EFFICIENT WORKLOAD PROCESSING IN THE INFORMATION AND COMMUNICATION NETWORK

Background. Peculiarities of the workload in a modern information and communication network (ICN) determine specific requirements for energy efficiency, performance and availability of its processing system. Existing approaches to increase energy efficiency and performance of workload processing do not take into account the possibility of dynamic changes in ICN workload arrival rate and individual energy consumption characteristics of computing nodes of the system.&#x0D; Objective. The purpose of the paper is to increase the energy efficiency and performance of ICN workload processing while meeting the requirements for the availability of the processing system, taking into account dynamic changes in the input workload arrival rate and the individual characteristics of the computing nodes’ energy consumption.&#x0D; Methods. A mathematical model of the workload processing system was built using the queueing theory methods, and an ontological model of this system was built using intelligent data analysis methods, which made it possible to quantitatively and qualitatively describe the complex relationships between system parameters and workload processing efficiency indicators. On the basis of the built models, a comprehensive method of energy-efficient workload processing was proposed, which differs from the known ones by the use of individual energy consumption models of computing nodes, combining the advantages of horizontal scaling and energy-efficient scheduling taking into account dynamic changes in workload arrival rate.&#x0D; Results. The efficiency of ICN workload processing is increased by 15.722% according to the efficiency criterion, which includes energy efficiency and performance indicators, compared to the known energy-efficient Backfill approach while meeting the requirements for the availability of the processing system.&#x0D; Conclusions. The energy efficiency, performance and availability of the ICN workload processing system can be improved by combining horizontal scaling and energy-efficient scheduling approaches using individual energy consumption models of computing nodes and taking into account dynamic changes in the input workload arrival rate.

Who, How and How Far? Renewable Energy Transitions in Industrialized and Emerging Countries

The purpose of this paper is to analyze the current implementation status of renewable energy projects, analyzing not only the five country leaders during the last decade, in terms of their installed capacity, but also a set of emerging countries playing an important role at regional levels (the who of energy transitions), the sources of green energy that they have chosen (how the transitions are being done), and the trends in greenhouse gas reduction that they have achieved (how far the transitions have progressed). Calculations based on various statistical sources—mainly the International Renewable Energy Agency (IRENA)—show that, while renewable energy installed capacity and implementation of renewable energy (RE) projects have grown in China, they have decreased to differing extents during the last ten years in the four other countries among the top five leaders in renewables (the US, Brazil, Germany and Canada). On the other hand, some non-industrialized countries have emerged in the regional renewable energy scene, and although they still do not stand out globally, they do play a significant role. In fact, in terms of transition toward a renewable energy matrix, the data shows that industrialized/high-GDP countries have made less progress at the national level than emerging ones. Regarding CO2 emissions, there are contrasting trends among the latter set of countries; however, the data analysis also shows that although economic growth negatively affects the decrease of CO2 emissions, individual energy consumption patterns might have an even greater positive impact in reducing emissions; current data from the US, China, Iran and the United Arab Emirates are good examples.

Nudges and peak pricing: A common pool resource energy conservation experiment

Using a contextualised common pool resource framework, individual energy consumption choices are studied. Individuals are nudged towards the socially optimal level of consumption by the use of a happy (sad) face if they are underconsuming (overconsuming). A price is set to incentivise a second group to choose the level of consumption observed in the nudge treatment in order to quantify the nudge via an equivalent price. Across all 10 periods, consumption is significantly lower in treatment groups compared to control groups without nudges and prices. The price treatment leads to an average level of consumption above the Nash equilibrium. There are implications for policy makers as the nudge treatment performs as well, on average, as an equivalent price without the implied loss of welfare, and is understood and integrated into subjects’ decision making quicker than an equivalent price. However, there is a tendency for both the nudge and the price to reinforce existing consumption behaviour as those who overconsume continue to overconsume.