Optimize Energy Use Research Articles

An Evolutionary Model for the Ancient Origins of Polycystic Ovary Syndrome.

Polycystic ovary syndrome (PCOS) is a common endocrinopathy of reproductive-aged women, characterized by hyperandrogenism, oligo-anovulation and insulin resistance and closely linked with preferential abdominal fat accumulation. As an ancestral primate trait, PCOS was likely further selected in humans when scarcity of food in hunter-gatherers of the late Pleistocene additionally programmed for enhanced fat storage to meet the metabolic demands of reproduction in later life. As an evolutionary model for PCOS, healthy normal-weight women with hyperandrogenic PCOS have subcutaneous (SC) abdominal adipose stem cells that favor fat storage through exaggerated lipid accumulation during development to adipocytes in vitro. In turn, fat storage is counterbalanced by reduced insulin sensitivity and preferential accumulation of highly lipolytic intra-abdominal fat in vivo. This metabolic adaptation in PCOS balances energy storage with glucose availability and fatty acid oxidation for optimal energy use during reproduction; its accompanying oligo-anovulation allowed PCOS women from antiquity sufficient time and strength for childrearing of fewer offspring with a greater likelihood of childhood survival. Heritable PCOS characteristics are affected by today's contemporary environment through epigenetic events that predispose women to lipotoxicity, with excess weight gain and pregnancy complications, calling for an emphasis on preventive healthcare to optimize the long-term, endocrine-metabolic health of PCOS women in today's obesogenic environment.

Advances in the Optimization of Energy Use in Buildings

Buildings are responsible for about 40% of final energy consumptions and 30% of total energy-related CO2 emissions [...]

The Impact of COVID-19 on the Energy Sector and the Role of AI: An Analytical Review on Pre- to Post-Pandemic Perspectives

The COVID-19 pandemic has disrupted global energy markets and caused significant socio-economic impacts worldwide, including the energy sector due to lockdowns and restricted economic activity. This paper presents a comprehensive and analytical review of the impact of COVID-19 on the energy sector and explores the potential role of artificial intelligence (AI) in mitigating its effects. This review examines the changes in energy demand patterns during the pre-, mid-, and post-pandemic periods, analyzing their implications for the energy industries, including policymaking, communication, digital technology, energy conversion, the environment, energy markets, and power systems. Additionally, we explore how AI can enhance energy efficiency, optimize energy use, and reduce energy wastage. The potential of AI in developing sustainable energy systems is discussed, along with the challenges it poses in the energy sector’s response to the pandemic. The recommendations for AI applications in the energy sector for the transition to a more sustainable energy future, with examples drawn from previous successful studies, are outlined. Information corroborated in this review is expected to provide important guidelines for crafting future research areas and directions in preparing the energy sector for any unforeseen circumstances or pandemic-like situations.

Energy (and Reactive Oxygen Species Generation) Saving Distribution of Mitochondria for the Activation of ATP Production in Skeletal Muscle.

Exercise produces oxidants from a variety of intracellular sources, including NADPH oxidases (NOX) and mitochondria. Exercise-derived reactive oxygen species (ROS) are beneficial, and the amount and location of these ROS is important to avoid muscle damage associated with oxidative stress. We discuss here some of the evidence that involves ROS production associated with skeletal muscle contraction and the potential oxidative stress associated with muscle contraction. We also discuss the potential role of H2O2 produced after NOX activation in the regulation of glucose transport in skeletal muscle. Finally, we propose a model based on evidence for the role of different populations of mitochondria in skeletal muscle in the regulation of ATP production upon exercise. The subsarcolemmal population of mitochondria has the enzymatic and metabolic components to establish a high mitochondrial membrane potential when fissioned at rest but lacks the capacity to produce ATP. Calcium entry into the mitochondria will further increase the metabolic input. Upon exercise, subsarcolemmal mitochondria will fuse to intermyofibrillar mitochondria and will transfer the mitochondria membrane potential to them. These mitochondria are rich in ATP synthase and will subsequentially produce the ATP needed for muscle contraction in long-term exercise. These events will optimize energy use and minimize mitochondria ROS production.

MANAGEMENT METHOD OF ELECTRICITY GENERATION SYSTEM USING WIRELESS TECHNOLOGIES

The subject of the study is the method of control and monitoring of the electricity generation system. The goal of the work is to investigate and develop a method for controlling the electricity generation system using wireless technologies. Relevance. The issues of energy efficiency and the use of alternative energy sources are relevant and important in modern conditions. In particular, solar energy is one of the most perspective areas in solving these problems. It is necessary to have the ability to monitor and control the generation process for optimal use of solar energy. The developed method should control the power generation system using wireless technologies and have flexible modes of operation. The development of the method of effective search for the point of maximum power and the power generation system in general is one of the most important tasks of the work. The object of the study is the process of control and monitoring of the electricity generation system. Research methods. Solar panel operation methods at maximum power: PWM (Pulse Width Modulation) and MPPT (Maximum Power Point Tracking). Results. The management method for the electricity generation system using wireless technologies is proposed in this work. A solar panel and a generator were chosen for electricity generation. The control of generation and system operation is based on the work of a microcontroller, which, in turn, transmits current data and the ability to control the system to a mobile application via a Wi-Fi module. This method can be used in a "Smart Home" system and other systems aimed at sustainable energy supply for consumers. Conclusion. The developed management method of the electricity generation system is planned to be used in systems of sustainable power supply for consumers. The method can be improved by integrating with other wireless technologies and adding other objects of electricity generation in the future.

Edge-based solution for battery energy management system: Investigating the integration capability into the building automation system

Recently, photovoltaic (PV) with energy storage systems (ESS) have been widely adopted in buildings to overcome growing power demands and earn financial benefits. The overall energy cost can be optimized by combining a well-sized hybrid PV/ESS system with an efficient energy management system (EMS). Generally, EMS is implemented within the overall functions of the Building Automation System (BAS). However, due to its limited computing resources, BAS cannot handle complex algorithms that aim to optimize energy use in real-time under different operating conditions. Furthermore, islanding the building's local network to maximize the PV energy share represents a challenging task due to the potential technical risks. In this context, this article addresses an improved approach based on upgrading the BAS data analytics capability by means of an edge computing technology. The edge communicates with the BAS low-level controller using a serial communication protocol. Taking advantage of the high computing ability of the edge device, an optimization-based EMS of the PV/ESS hybrid system is implemented. Different testing scenarios have been carried out on a real prototype with different weather conditions, and the results show the implementation feasibility and technical performance of such advanced EMS for the management of building energy resources. It has also been proven to be feasible and advantageous to operate the local energy network in island mode while ensuring system safety. Additionally, an estimated energy saving improvement of 6.23 % has been achieved using optimization-based EMS compared to the classical rule-based EMS, with better ESS constraints fulfillment.

Post-occupancy evaluation for enhancing building performance and automation deployment

Building automation systems are building control and management systems that control/operate different systems in a building such as HVAC, lighting, safety systems, security and access control, surveillance, indoor air quality, and waste management. These systems manage, control, and integrate other building systems to enhance living experience and optimise energy use through a set of sensors and actuators that are deployed in the building to collect data and execute commands that are sent through a gateway. These management systems generate real-time commands and act or reacts to stochastic occupant behaviours. Buildings in Oman used to be built with burned clay mixed with date palm leaves, and wadi stones and date palm trunks are used for building structure. This architecture keeps the indoor environment warm in winter and cold in summer. However, with advancing technology there has been a shift in building towards using concrete and steel that have high thermal conductivity and pose some challenges for energy use. This paper will show that the main concern of occupants in Oman is indoor temperature control, especially during summer months. This has raised concerns for building performance in Oman and shows a need to review building materials, recommend sustainable alternatives, and more widely, implement sustainable building techniques. This paper seeks to develop recommendations to overcome these issues by exploring post-occupancy satisfaction measures and potential use of BAS and sustainable building materials to enhance building performance in Oman. Following on from this, this paper explores the motivations behind people's decision in Oman to deploy home automation and explore techniques to enhance building performance.

Sensor-based indoor air temperature prediction using deep ensemble machine learning: An Australian urban environment case study

Accurate prediction of indoor temperature is critical for climate change adaptation and occupant health. The aim of this study is to investigate an improved deep ensemble machine learning framework (DEML), by adjusting the model architecture with several machine learning (ML) and deep learning (DL) approaches to forecast the sensor-based indoor temperature in the Australian urban environment. We collected ambient station-based temperatures, satellite-based outdoor climate characteristics, and low-cost sensor-based indoor environmental metrics from 96 devices from August 2019 to November 2022, and established DEML with a rolling windows approach to assess the prediction stability over time. The DEML model was compared with several benchmark models, including Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGboost), Long-short term memory (LSTM), and Super Learner model (SL). A total of 13,715 days [median: 341 days; IQR (the interquartile range): 221–977 days] of low-cost sensor-based indoor temperature were included in 25 commercial and residential buildings across eight cities. The prediction performance of DEML was superior to the other five benchmark models in most of the sensors [coefficients of determination (R2) of 0.861–0.990 and root mean square error (RMSE) of 0.125–0.886 °C], followed by RF and SL algorithms. DEML consistently achieved high accuracy across different climate zones, seasons, and building types, which could be used as a crucial tool for optimizing energy use, maintaining occupant comfort and health, and adapting to the impacts of climate change.

Accomplishments and challenges of metrics for sustainable energy, population, and economics as illustrated through three countries

The global Sustainable Development Goals require meeting multiple objectives on energy, population, economics, and ecosystems. Development and economic growth as defined by current metrics requires energy inputs, yet energy growth can also increase negative impacts on natural systems. To achieve sustainable development goals, policymakers and technologists will need energy system solutions that consider not only cost and efficiency but also population, quality of life, natural ecosystems, and culture that accommodates different starting points and transition timelines of various countries. To explore possible approaches, this perspectives paper summarizes energy in the context of economic growth and population, illustrating concepts through the diverse status and direction of three countries—Japan, the United States, and Bangladesh—as potential views into a post-growth sustainable future. Four fundamental questions on long-term energy development are identified, related to optimal energy use per capita, sustainable global energy demand, managing an energy transition with stable population, and the need for generalizable approaches across countries.

The householder is king: Engendering householder participation in bridging the performance gap in homes

Smart technologies are useful for performance monitoring i.e. to gather real-life evidence to address the design-performance gap, reduce emissions, optimise energy use, address energy inequalities, empower and engage citizens. Smart home performance monitoring therefore has wider connotations of societal utility. However, current technology adoption models do not address this question of societal value. This study investigates the correlations between acceptance, adoption, affordance, and active citizenship as the basis for householder participation in smart performance monitoring ‘for the common good’. The aim is to propose an integrated framework for engendering householders' participation in bridging the performance gap. The research design combined theoretical and methodological triangulation. First, it reviewed and consolidated existing technology adoption models to establish a conceptual household participation framework. Then, a survey was deployed until 972 nationally representative sample was achieved. Lastly, Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to test goodness-of-fit hypotheses, to validate the framework. The result confirms that smart home performance monitoring implementation promote acceptance first by addressing citizenship/active participation factors. Therefore, policy initiatives should prioritise issues of trust, capacity for sustainable, social and technology innovativeness, and cost-benefit. Then resolve affordance factors such as perceived cost, performance expectancy, data security and perceived savings to promote adoption. Significantly, hedonic value, and social influence were not proven as effective for promoting participation. Therefore, the proposed participation framework contributes new theoretical and strategic insights into how smart home performance monitoring can be deployed to address the performance gap and aid the transition to net zero homes.

Heterogeneous effects of energy productivity improvement on consumption-based carbon footprints in developed and developing countries: The relevance of improving institutional quality

Economic expansion often causes multifaceted damages to environmental well-being. Thus, the persistent degradation in the global environment has become a concerning issue for both developed and developing regions across the world. Against this backdrop, this study checks how the per capita carbon footprint figures of the developed Group of Seven (G7) and the developing Emerging Seven (E7) countries are influenced by energy productivity improvement, institutional quality, and other key macroeconomic factors. Considering annual data from 2000 to 2020, advanced panel data estimation techniques that are robust against data-related problems such as endogeneity, heterogeneous slope coefficients, and dependency among the cross-sectional units are utilized. Overall, the results certify that making productive use of energy reduces consumption-based carbon footprints in E7 countries but not in G7 countries. Besides, improving institutional quality is seen to not only reduce carbon footprints in both samples directly but also indirectly mediate and moderate the energy productivity-carbon footprint nexus in G7 and E7 countries, respectively. Moreover, financial globalization is observed to minimize carbon footprints in G7 countries while boosting them in E7 countries. Contrastingly, financial development is observed to homogeneously boost the carbon footprint levels of both G7 and E7 countries. Lastly, international trade is found not to influence the carbon footprint levels in both samples of countries. Therefore, taking these major findings into consideration, a set of policies apart from making optimal use of energy are recommended for inhibiting the consumption-based carbon footprint figures of the concerned countries.

Recent Advances in Molybdenum Disulfide and Its Nanocomposites for Energy Applications: Challenges and Development.

Energy storage and conversion are critical components of modern energy systems, enabling the integration of renewable energy sources and the optimization of energy use. These technologies play a key role in reducing greenhouse gas emissions and promoting sustainable development. Supercapacitors play a vital role in the development of energy storage systems due to their high power density, long life cycles, high stability, low manufacturing cost, fast charging-discharging capability and eco-friendly. Molybdenum disulfide (MoS2) has emerged as a promising material for supercapacitor electrodes due to its high surface area, excellent electrical conductivity, and good stability. Its unique layered structure also allows for efficient ion transport and storage, making it a potential candidate for high-performance energy storage devices. Additionally, research efforts have focused on improving synthesis methods and developing novel device architectures to enhance the performance of MoS2-based devices. This review article on MoS2 and MoS2-based nanocomposites provides a comprehensive overview of the recent advancements in the synthesis, properties, and applications of MoS2 and its nanocomposites in the field of supercapacitors. This article also highlights the challenges and future directions in this rapidly growing field.

Physical, Chemical, and Biological Pollution in Water, Air and Soil Industrial Products From PT. Torabika Eka Universe in Cikupa Tangerang

Technological developments certainly provide big changes in human life, starting from infrastructure management to the food industry, and the drug industry, everything is very easy to do by utilizing current technological sophistication. Many bad impacts arise from these technological advances, the most prominent of which is pollution due to waste generated from the industry. The impact that occurs from failure in waste treatment is the occurrence of air, soil, and water pollution. This research method is a qualitative descriptive research, where the researcher directly becomes the instrument and the company is the respondent. Based on research results Pollution of water, air, and soil due to the industrial products of PT. Torabika Eka Semesta found that Torabika is a well-known coffee drink brand in Indonesia. To maintain a healthy environment, the Torabika company can do several things, including 1) Companies reduce their use of single-use plastic packaging; 2) Use environmentally friendly raw materials; 3) Optimizing energy use; 4) Improve recycling programs; 5) Build environmental awareness among employees and customers; 6) Improve recycling programs; 7) Build environmental awareness among employees and customers; 8) Improve recycling programs; and 9) Build environmental awareness among employees and customers.

The corporate path to green innovation: does the digital economy matter?

As China's digital transformation accelerates, there is growing interest in whether the digital economy can effectively boost green innovation in industrial enterprises and enable China's development to break through the constraints of resources and environment. Therefore, this study analyzes the data of A-share industrial listed enterprises (2011-2020). Results indicate that the digital economy promotes green innovation. The impact of the digital economy on green innovation varies significantly among different types of enterprises, with stronger effects on state-owned enterprises. Digital economy enhances green innovation via boosting public attention and optimizing energy structure. Therefore, playing the role of monitoring public attention, and optimizing energy use are key strategies to promote corporate green innovation.

Energy Efficiency Evaluation Method for Township Power Users Based on OLAP Technology

With the development of the smart grid and energy Internet, the traditional demand side response is further expanded to the integrated energy management of users, which puts forward higher requirements for the energy management level of users. The energy consumption structure of users has changed greatly. How to measure the rationality of energy consumption, reduce the cost of energy consumption, save energy, and improve efficiency is very important for users. Aiming at the energy efficiency evaluation of township power users, this paper constructs an index system including users’ energy utilization. It also establishes an evaluation method based on the NSGA-III algorithm combined with OLAP technology to measure the closeness between each energy use scheme and the optimal energy use scheme. Finally, through the example analysis and verification, the results indicate that the proposed energy efficiency evaluation method based on OLAP technology is reasonable. Energy efficiency evaluation can meet the needs of information interaction between users and the smart grid, and improve the energy efficiency and energy-saving effect of township power users through energy efficiency evaluation and management.

Energy recovery in a commercial building using pico-hydropower turbines: An Australian case study

Optimising energy use in systems and buildings is crucial to reduce climate change. This paper aims to address the gap in knowledge for pico-hydropower (<5 kW) that has been identified as an area of untapped potential in the water industries. A literature review and multivariate analysis are used to find a suitable pico-hydro turbine to install into a coral reef aquarium system in a government owned facility. Key findings from the literature review are untapped potential, gaps in knowledge and global quantification of small hydropower for energy recovery, and lack of enabling data contributing to slow uptake of small hydropower. The study showed a propeller pico-hydropower turbine could be used to recover approximately 10% of the energy used for pumping water through a filtration system. At 2.3 m available head, and 90 L/s water flow, power output up to 1.124 kW was achieved. The project was economically viable with financial and non-financial benefits for the life cycle of the product. There remain sparse case studies for energy recovery using small hydropower in the scientific literature. A growing number of authors see the potential of this renewable energy technology to reduce global greenhouse gas emissions and contribute to the UN Sustainable Development Goals to provide affordable clean energy and address climate change. This study helps to shine a light on opportunities to find value from waste using a novel application of hydropower in a water industry.

The properties of machine-tractor unit (MTU) regarding soil preparation with bed ridging

BACKGROUND:One of the main criteria for assessment of work performance is productivity. It depends on a number of indicators: towing resistance, optimal use of energy, used technical equipment, the adaptability of the equipment to the operation conditions, etc. Experimental studies are required in order to establish the patterns of influence of these indicators on work efficiency.&#x0D; AIMS:Carrying out theoretical calculations and practical observations on the process of bed ridging for potatoes, assessment of the unit assembly for the technological process performing and the using of the unit.&#x0D; METHODS:Field tests of a machine-tractor unit with subsequent result processing using the Microsoft Office applications.&#x0D; RESULTS:Recommendations are given for practical use in the unit formation depending on velocity and operation width of the unit for various values of specific resistance.&#x0D; CONCLUSIONS:The practical value of the study lies in the opportunity of using the proposed patterns for optimization the machine-tractor unit assembly according to operation conditions, selection of power unit, development of combined machines and units.

The Energy Management System According to the Norm ISO 50001

Abstract The final paper presents an approach to solving the problem of optimal use of electrical energy in the production process. An analysis of all important parameters, limitations, and goals was performed, after which a mathematical model was created and used in writing Matlab code to solve the problems. It is the basis for further upgrading following the needs of each organization and because of that, it can be very significant.

Dynamic prognostic interaction between social development and energy consumption optimization: Evidence from european union member countries

Analyzing optimization of energy use becomes only possible when their interactions with the indicators of social development are properly estimated. The study employed the panel VAR and impulse response functions to investigate this causal interaction by analyzing panel data from 27 EU countries. The results reveal that a 1% increase in renewable energy consumption contributes to raising life expectancy, fertility and education by 2.20%, 1.27% and 2.11% respectively. However, a 1% surge in fossil fuel utilization contributes to lower life expectancy and fertility by 0.66% and 2.76% and gives rise to education by 0.33%. Reciprocally, fertility, education and research and development contribute to renewable energy utilization by 1.75%, 2.82% and 3.34% respectively whereas research and development contribute to decreasing fossil fuel combustion by 3.57%. Lastly, urbanization and internet subscriptions were found to have no statistically significant interaction with energy use, inferring that these social factors do not contribute to energy use. Therefore, this study urges policymakers to invest in the education sector and research and development to achieve sustainable socio-economic development by simultaneously optimizing energy consumption and increasing the overall share of renewable energy by diversifying its production from green energy sources (solar, wind and hydro) in the EU countries.

Vehicle refrigeration modification using an ejector: Optimization and exergoeconomic analysis

BackgroundAdvances in technology in recent years have increased energy consumption which has led to global warming. In line with the Paris agreement, the optimal use of energy is a way to overcome the issue. Air conditioning and refrigeration systems are among the sectors that account for a large share of energy consumption. This has elicited the implementation of optimization of refrigeration systems. MethodIn this research, the aim is to utilize the radiator waste heat of an engine with a volume of 2000 cc in an ejector refrigeration cycle as an alternative to conventional refrigeration cycles in vehicles. For this purpose, the ejector refrigeration cycle is modeled with energy, exergy, and eco-exergy equations and the ejector is modeled with dynamic gas equation. After modeling, effective parameters, namely, condenser outlet temperature, inlet temperature and pressure to the secondary nozzle, and inlet temperature to the primary nozzle are optimized using TOPSIS multi-objective optimization method. The selected objectives were reducing system capital investment cost, and increasing, COP, and the ejector performance (ω) criterion. ResultsIt was found that the ejector refrigeration cycle reduces the electric power and capital investment cost by 0.743 kW and 0.0028 $/h, respectively, and also increases the COP by 0.917 compared to the conventional refrigeration systems in the vehicle.