Good Energy Management Research Articles

An Overview of Performance Validation, Testing Protocols, and Standards for Smart Meters

This document provides a thorough overview of the testing protocols and standards for smart meters, which are essential parts of the contemporary smart grid. It emphasizes the switch from analog to digital smart meters, which provide two-way communication and real-time data on electricity consumption. In order to guarantee accuracy, dependability, conformity with international standards such as those from the IEC, NIST, and BIS, and the protection of customer data, the document highlights the significance of conducting thorough testing. In order to evaluate several performance factors including insulation, accuracy, and electromagnetic compatibility, it covers a variety of tests, such as metrology, load switch capability, data exchange protocols, and communicability. Smart meters must be thoroughly tested and validated in order for them to operate effectively, reliably, and safely. This will help utilities minimize revenue losses and encourage good energy management.

Differences in Quality of Female Nursing Work Life Based on Gender and Nursing Perspectives

The quality of a nurse’s work life is the degree of satisfaction regarding personal and organizational needs based on experience in a work organization. A nurse with a dual role is the nurse who acts as a mother and a professional nursing staff at the same time. The purpose was to determine differences in the quality of female nurses’ work life in gender and nursing perspective at Balung General Hospital and Kalisat General Hospital in Jember Regency. The research method uses a comparative study with a quantitative research type. The sampling technique in this research is random sampling with a total of 115 samples. Data collection was conducted by using questionnaires about the quality of nurses’ work life from the nursing perspective and questionnaires conflict with women’s dual role from the gender perspective. Data processing using the Mann-Whitney analysis test with a 95% significance level (α=0.05). The results using Mann-Whitney analysis showed that there is a difference between the gender perspective and the nursing perspective (p=0.000). The mean results showed that the nursing perspective () is higher than the gender perspective (). The conclusion shows that the quality of female nursing work life from the gender perspective needs to be improved. The hospital needed to review further regarding work schedules and shift time; the family needed to provide full support and good cooperation; and female nurses themselves must also have good coping control, time, and energy management. Apart from that, it is necessary to have a policy from the room head and team leader regarding the distribution of schedules for female nursing staff without reducing the feeling of unfairness for male health workers.

Real-time indoor thermal comfort prediction in campus buildings driven by deep learning algorithms

Thermal comfort prediction is vital in achieving a good indoor environment and efficient energy management. However, thermal comfort is strongly nonlinear and dynamically changing over time, making it difficult to predict thermal comfort accurately. Two real-time thermal comfort prediction models on multi-time scales are proposed based on deep learning algorithms. The indirect prediction model for thermal comfort integrates the bidirectional long and short-term memory network to predict real-time environmental parameters. It subsequently combines the thermal comfort calculation method with the predicted environmental parameters to obtain the predicted thermal comfort value. The indirect prediction model for thermal comfort combines the bidirectional long and short-term memory network to realize real-time prediction of environmental parameters and then calculates thermal comfort by the thermal comfort calculation method to realize indirect thermal comfort prediction. The other is the direct prediction model of thermal comfort, which is realized using the bidirectional long short-term memory network for real-time thermal comfort prediction. The two real-time prediction models are compared and analyzed for 10-min, 30-min, and 60-min scales. Experimental results show that the prediction accuracy of the indirect prediction model is better than the direct prediction model, but the robustness of the indirect prediction model is lower than the direct prediction model. In addition, the accuracy of the thermal comfort prediction model on the small time scale is higher than that on the large time scale, in which the RMSE and MAE reached 0.0551 and 0.0543 (10-min scale), respectively. Therefore, the proposed thermal comfort prediction models can be integrated into the control model of heating, ventilation and air conditioning systems, providing a reference for optimizing indoor thermal comfort.

Machine learning-based energy harvesting for wearable exoskeleton robots

Wearable exoskeleton robot can provide additional movement assistance for the wearer in many fields and enhance their movement ability. Reduce the degree of long-term exercise fatigue and avoid injury during exercise. However, due to the limitation of battery technology and battery capacity, it is difficult for exoskeleton robots to work continuously for a long time. Therefore, the energy management and optimization of wearable exoskeleton robot become an important way to break through the bottleneck of its future development. In order to optimize the energy management system of exoskeleton robot, an energy management control strategy based on machine learning and a SOC11SOC: State of Charge. value prediction model were proposed. Based on the structure of composite power supply, this paper selects Q-learning in machine learning to build the battery energy management strategy system, and introduces the time difference reinforcement learning algorithm. The experimental results show that the energy management optimization system can effectively shorten the response time of the robot system, reduce the prediction error value of SOC value, and provide more accurate electricity information for the management and control system. At the same time, the system in this paper shows good energy management control under different working conditions, and can realize dynamic energy management and improve energy utilization according to the actual power demand and power supply operation of the exoskeleton robot.

Renewable Energy and Energy Storage Systems

The use of fossil fuels has contributed to climate change and global warming, which has led to a growing need for renewable and ecologically friendly alternatives to these. It is accepted that renewable energy sources are the ideal option to substitute fossil fuels in the near future. Significant progress has been made to produce renewable energy sources with acceptable prices at a commercial scale, such as solar, wind, and biomass energies. This success has been due to technological advances that can use renewable energy sources effectively at lower prices. More work is needed to maximize the capacity of renewable energy sources with a focus on their dispatchability, where the function of storage is considered crucial. Furthermore, hybrid renewable energy systems are needed with good energy management to balance the various renewable energy sources’ production/consumption/storage. This work covers the progress done in the main renewable energy sources at a commercial scale, including solar, wind, biomass, and hybrid renewable energy sources. Moreover, energy management between the various renewable energy sources and storage systems is discussed. Finally, this work discusses the recent progress in green hydrogen production and fuel cells that could pave the way for commercial usage of renewable energy in a wide range of applications.

Comparative Analysis of Energy Efficiency Programs in Large ASEAN Industries with Sustainable Energy Indicators

Reducing energy demand through energy efficiency (EE) policies is a key strategy in dealing with climate change and the energy needs of Southeast Asian countries (ASEAN). The industrial sector is the largest energy user sector and has significant energy-saving potential through good and sustainable energy management. This research is intended to analyze the progress of energy-saving programs in several ASEAN countries through policies that have been made with a focus on large industries. Five steps will be carried out, namely: searching for data on total population, GDP and total final energy consumption; conducting analysis with indicators of energy intensity, per capita energy consumption and GDP productivity; comparing the EE programs of ASEAN countries; designing savings strategies; and determine sustainable energy indicators. As a result, the energy consumption of ASEAN countries during the 2016 to 2020 time period has mostly increased. The policies that have been taken have similarities such as the implementation of energy audit and management, the application of minimum equipment performance standards, and the funding of the EE program. ASEAN countries need cooperation and coordination to ensure readiness in welcoming the energy transition.

Analysis of DC-coupled system efficiency losses and their financial effects for a PV-based EV charging station

Photovoltaic (PV)-powered electric vehicle charging stations (EVCS) are expected to play a critical role in achieving carbon neutrality in the transport sector, as PV power has a great ability to reduce CO 2-emission. By integrating PV into an EVCS, solar energy can supply a considerable portion of the electric vehicle (EV) energy demand. Besides a good energy management strategy (EMS) for the system, the efficiency of the system is an important aspect that needs to be discussed. Be it EV charging/discharging, energy exchange with the grid or battery use - power losses occur in the system. Previous studies have mostly only discussed the effects of EMS on energy losses in the system. In this paper we conduct a systematic analysis of the converter efficiency and its effect on the energy losses for an EVCS integrated with PV, stationary battery (BAT), and grid connection. A DC- and an AC-coupled EVCS are compared on the basis of example systems. Converter efficiency for PV, grid, BAT, and EVs and BAT efficiency are considered for the analysis. A comprehensive comparison of system efficiency and energy losses over different seasons and a full year is presented and discussed. Finally, we discuss the financial losses influenced by the efficiency losses in the system over the year. It is shown, that the overall system efficiency is almost the same for both EVCS with about 92%. The DC-coupled EVCS's higher number of converters leads to a higher sum of energy loss compared to the AC-coupled EVCS, even including the onboard-charger of the EVs. For the AC-coupled EVCS, more than 50% of the energy loss occurs due to the EV's onboard-charger. These losses are paid for by the EV user. However, even if the EVCS operator also owns the EV fleet, regarding the example system looked at, the AC-coupled EVCS is about 10% more profitable.

A Study of MPPT Charge Controller Roles in Photovoltaic Energy Management

Nowadays, the world's demand the energy is increasing. So, we need a good energy management system to use the available energy. An energy management system consists of maximum power point tracking (MPPT) charge controller, battery management, and the power conversion stage to control and reduce energy consumption. Solar energy is used solar radiation and is converted into electrical energy. In photovoltaic (PV) system consists of a PV module, charge controller, battery storage, and load. Arduino NANO is used in this project because it's low cost and has an efficient microcontroller in the MPPT charge controller to prevent the battery from overcharging and display the maximum power point (MPP). Perturb and Observe (P&O) and Incremental Conductance (InC) algorithm is used in the MPPT charge controller to transfer maximum power from the PV module which is executed using a microcontroller. The voltage, current, and power from the MPPT charge controller, are shown on a liquid crystal display (LCD). The benefit of this project is to achieve high efficiency and low cost of photovoltaic modules for the design of photovoltaic systems with a simple MPPT.

Energy baseline prediction for buildings: A review

Building energy consumption prediction has gotten a lot of attention in the literature since it is a complicated process influenced by a lot of different factors. Hence, precisely calculating the energy consumption of buildings and enhancing its efficiency is a difficult task. As a result, good energy management and prediction are becoming increasingly vital in the support of energy saving. For this purpose, an energy baseline model is a useful tool for modeling energy consumption for any building over a period of time. It can define as a comparison tool that allows to evaluate energy performance before and after some modification in the system (building). The primary goal of the energy baseline model is to estimate energy demand if energy efficiency measures are applied to a building for the sake of energy savings estimations. The purpose of this study is to examine current approaches for estimating building energy baselines, including physics-based, data-driven, and hybrid approaches, as well as model development process and essential elements. The choice of input independent variables is critical when developing energy baseline models since it affects the estimation of energy savings. Therefore, this review summarizes the input variables that influence energy consumption. Performance metrics are also provided to evaluate the energy baseline models and the effects of independent variables.

HUBUNGAN MANAJEMEN ENERGI DENGAN KELELAHAN PADA PASIEN DIABETES MELITUS TIPE 2

Metabolic disorders in blood sugar levels are caused by damage to insulin secretion so that it affects energy production. Fatigue is one of the complaints and symptoms of Diabetes Mellitus (DM) patients. This study aims to analyze the relationship between energy management and fatigue in patients with diabetes mellitus. This study used a correlational design with a cross sectional approach. Calculation of the sample in this study using the Slovin formula, which obtained 34 respondents with diabetes mellitus at the Kejayan Health Center, Pasuruan Regency using purposive sampling technique. Data collection in this study used an energy management questionnaire and Multidimensional Fatigue Invantory (MFI20). The results show that in energy management, energy management in patients with diabetes mellitus is obtained with a good category of 55,9%. On fatigue, the median result is 60.50 with a min-max value of 34-73. The correlation test showed that there was a relationship between energy management and fatigue (p = 0,033, r = -0,366, = 0,05). There is a negative correlation which shows that the higher the energy management, the lower the fatigue felt. Fatigue felt by diabetic patients does not go away easily so that energy management must be carried out properly. It is expected that diabetes mellitus patients maintain good energy management. It is a concern for nurses in improving energy management of diabetes mellitus patients to reduce the fatigue they feel.

Novel design of compound coupled hydro-mechanical transmission on heavy-duty vehicle for energy recycling

How to efficiently transmit power and reuse/recover energy has been the subjects of heated discussion in the high-power transmission field. Regarding heavy-duty vehicles, they used to be equipped with a gearbox as a typical type of high-power transmission to deliver power to the wheel. However, a gearbox transmission has quite complex mechanical structure for realizing a large speed-regulating range, and it has an inevitable drawback of weighing too much. In addition, it cannot reuse/recover energy. In this study, a novel design of a compound coupled hydro-mechanical transmission (CCHMT) is proposed to realize energy reuse/recovery on heavy-duty vehicles. The CCHMT has an optimal structure coupled with hydraulic and mechanical components, which makes its speed change continuously and keep the engine running with a high fuel economy. Moreover, compared with both hybrid and battery electric vehicles, vehicle with CCHMT has higher power density. To validate the transmission's feasibility and operational efficiency, simulation modeling and experiments are conducted. The CCHMT can transform unstable energy under a wide speed-regulation range, reuse/recover a vehicle's excess energy at an efficiency of 82.30%/62.94%, and provide a stable driving torque with a high efficiency of 76%, which shows a good energy management performance on heavy-duty vehicle's hydraulic system.

Modeling and Simulation of an Energy Management System for Plug-in Hybrid Electric Recreational Boat (PHERB) using Penambang Boat Driving Cycle

In order to ensure that the vehicle achieve an improvement in energy efficiency, reduction in emissions and fuel use, the good energy management system needed. This paper presents an innovation of water transportation namely Plug-in Hybrid Electric Recreational Boat (PHERB) on modeling and simulation results of an energy management strategy (EMS) for PHERB. In this work, firstly, through a power flow analysis, the vehicle components are sized to meet the expected power and energy requirements. Then, the model is tested numerically in the MATLAB/SIMULINK environment using the Penambang Boat drive cycle with the proposed EMS. The simulation results show that the PHERB model can be used as a reference to build a hybrid electric boat in Malaysia environment.

Strategies in the energy’s field in Kosovo

This paper treats some problems connected to the strategies used in the energy’s field in the Republic of Kosovo. It shows how attempts have been made to conduct research, analytical and theoretical analysis in the field of management of various operations in the field of energy, based on innovations to provide a clear picture of the application of new technologies and innovations such as contemporary trends in the country, the region and beyond as a necessity of the future. After a detailed assessment of the current energy situation in Kosovo, taking into account energy and its resources with energy consumption in general, the application of innovations to increase energy management efficiency, is read respectively their impact on improving the quality of energy services. In this paper an assessment of the current energy situation has been made, taking into account energy and its sources as well as energy consumption in general. 20 The application of innovations, good energy management and the changes that follow after the application of the above measures, respectively, their impact on improving the quality of energy services, combined with the use of renewable resources significantly leads to reduced electricity costs and dust emissions.

Control System for Smart Home Energy Management

The Increasing energy demand for residential load is often associated with a lot of energy waste due to lack of a good energy management system. In this work, we propose an intelligent energy management system (EMS) which is designed to control the electrical energy source from solar energy and the power plant from PLN resources both automatically and manually based on the Internet of Things. This control system can be controlled remotely during the process of connecting and disconnecting backup power sources that can be accessed through smartphone devices. Based on the test results of the control system of displacement of energy sources, the DC voltage sensor accuracy value is 99.44% and the PLN voltage measurement has an accuracy of 98.31%. In the control system transfer to a backup power source with manual control has an average duration of time of 0.74 seconds while the automatic control has an average duration of time of 0.98 seconds to 1.33 seconds and for automatic control with priority reading the battery capacity of 12.75 Volts can do transfer from the PLN power source to the backup power source and transfer to the PLN source if the voltage is less than 10.5 Volts with a 100% success rate.

Techno-economic evaluation of the Portuguese PV and energy storage residential applications

In the residential sector, energy micro-generation and its intelligent management have been creating novel energy market models, considering new concepts of energy usage and distribution, in which the prosumer has an active role in the energy generation and its self-consumption. The configuration of a solar photovoltaic system integrating energy storage in Portugal is yet unclear in the technical, energetic and economic point of view. The energy management jointly with the battery operation have great influence in the system configuration’s profitability value. The present work evaluates different photovoltaic system configurations with and without batteries for the normal low voltage Portuguese consumer profile with 3.45 kVA contracted power. This study presents the systems’ cost-effectiveness, within the Portuguese legislation, which promotes and enables policies for self-generation and self-consumption. The analysis is done in three different representative locations of the country, considering distinct electric tariffs. This work shows that despite the solar photovoltaic system without electricity storage is already economically viable, its integration with storage is not in most of the assessed configurations. However, it is shown that it is already possible to find profitable PV + battery configurations, even potentially improving these positive scenarios if a good energy management strategy is considered.

A Smart Metering Simulation in LABVIEW

The smart grid delivers electricity from producers to consumers using two-way digital technology and considers the involvement of the user. The implementation of smart grids should start at the consumer side using smart meters, control devices and a communication link. Smart metering is the bridge between smart buildings and smart grids. It is viewed as a crucial factor for an efficient functioning of the internal electricity market and a successful implementation of the renewable energy and security of supply. The replacement of the currently used electromechanical meters with smart digital meters along with domestic load controllers is identified for better energy conservation at the consumer side .These devices can be remotely read and are able to measure consumption multiple times per day which is beneficial for a good demand response, customer feedback and energy management. The purpose of the present paper is to illustrate how smart meters operate and how their implementation can improve the current grid

Feasibility Study on Energy Audit and Data Driven Analysis Procedure for Building Energy Efficiency: Bench-Marking in Korean Hospital Buildings

Growths in population, increasing demand for health care services and comfort levels, together with patients on the rise in time spent inside hospitals, assure the upward trend that energy demand will continue in the future. Since the hospital buildings operate 24 hours, 365 days a year for the treatment and restoration of patients, they are approximately 2–3 times more energy-intensive than normal buildings. For this reason, energy efficiency in hospitals is one of the prime objectives for energy policy at regional, national and international levels. This study aims to find how meaningful energy performance, reflecting good energy management and energy conservation measures (ECMs), can be operated for hospital buildings, a category encompassing complex buildings with different systems and large gaps between them. Energy audit allows us to obtain knowledge from the healthcare facility, in order to define and tune data driven analysis rules. The use of benchmarking in the energy audit of healthcare facilities enables immediate comparison between hospitals. Data driven energy analysis also allows ascertaining their expected energy consumption and estimating the possible savings margin by using the building energy flow chart. In the 2015–2017 periods, bench-marking of four public hospitals in Seoul were audited for the energy consumption related to weather conditions, total area, bed numbers, employee numbers, and analyzed for building energy flow by zones, energy sources, systems and equipment. This is a practice-based learning in a hospital project. The results reveal that the average annual energy consumption of a hospital under normal conditions, and energy efficiency factors are divided into energy baselines, energy consumption goals for energy saving and energy usage trends for setting ECMs, respectively. The indicator dependent on the area of inpatients (number of beds) proved to be the most suitable as a reference to quantify the energy consumption of a hospital.

Supercapacitors and Battery Energy Management based on New European Driving Cycle

This paper presents a new strategy of embedded energy management between battery and supercapacitors (SC) for hybrid electric vehicles (HEV) applications. This proposal is due to the present trend in the field, knowing that the major drawback of the HEV is the autonomy problem. Thus, using supercapacitors and battery with a good energy management improves the HEV performances. The main contribution of this paper is focused on DC-bus voltage and currents control strategies based on polynomial controller. These strategies are implemented in PIC18F4431 microcontroller for DC/DC converters control. Due to reasons of cost and available components (no optimized), such as the battery and power semiconductors (IGBT), the experimental tests are carried out in reduced scale (2.7 kW). Through some simulations and experimental results obtained in reduced scale, the authors present an improved energy management strategy for HEV.

Energy Management in Zero-Energy Building Using Neural Network Predictive Control

In the past decade, there has been an increase in the interest of domestic electric energy from renewable energy sources without relying on the electrical grid. Zero-energy building concept has been developed to support energy, due to the high cost of electricity and the availability of the renewable energy. This paper proposes a novel technique for managing the energy in a zero-energy building using neural network predictive control (NNPC). NNPC is a combination of two techniques: 1) neural network and 2) model predictive control. The main features of NNPC are the ability to work in real time, the ability to connect to the Internet, simple controls, and disturbance reduction. In addition, the system can learn from the human behavior. To ensure better management of energy in a zero-energy building, this paper also introduces an artificial neural network-based technique for forecasting renewable energy sources, wind, and photovoltaic. This makes NNPC able to achieve maximum exploitation of forecasted renewable energy without using the grid. The system under study in this paper is a house supplied from a 1.75 kW hybrid system plus two sets of 100 Ah storage units. Wind/solar data are measured and collected from a site in Mansoura city, Delta, Egypt, for seven months. The study is conducted on the most energy-consuming day June 8, 2017.

Coalition based game theoretic energy management system of a building as-service-over fog

For the better management of energy, a coordination based energy management system as-a-service on fog is presented. An efficient system model is introduced to handle a social networking problem in order to maintain the balance between the produced and the required energy. This social network problem is formulated as a game theory based coalition method. With the increase in number of electricity consumers, the computational complexity of energy management system is becoming a threat for system efficiency in real-time environment. To deal with this dilemma, the service providers shift their computational and storage units on cloud and fog. The fog is an intermittent layer between the cloud and the end user which helps to make the system faster as compared to the cloud. In this scenario, a building with multiple apartments is considered. Where, each apartment is taken as a player and the surplus power as pay-off. The surplus energy will be distributed among the energy deficient apartments using Shapley value that unevenly distributes the power according to the demand. The experimental results show that 13 kW extra power is saved and distributed among energy deficient apartments during different times of a day.