Level Of Energy Efficiency Research Articles

Slime Mould Algorithm (SMA) and Adaptive Neuro-Fuzzy Inference (ANFIS)-Based Energy Management of FCHEV Under Uncertainty

This manuscript proposes a hybrid technique for optimal energy management (EM) of fuel cell (FC) and ultra-capacitor (UC) hybrid electric vehicles (FCHEVs) under uncertainty. The proposed method is a joint execution of the Slime Mould Algorithm (SMA) and the Adaptive Neuro-fuzzy Inference System (ANFIS), otherwise called the SMA-ANFIS system. The main aim of the proposed system is to achieve and regulate the steady state of DC bus voltage with minimal steady-state error (SSE) under different load conditions by using the proposed SMA-ANFIS technique. FC supplies power during vehicular operation and it is used to regulate DC bus voltage to the chosen value and recharge, and UC supplies current optimally through the proposed technique. The optimal EMS performs and controls the power flows through the associated power converters to accomplish some power allocation and energy efficiency levels. Finally, the proposed method is done in the MATLAB platform, and the performance is compared with other methods.

Relationship Between Carbon Emissions and Economic Development of Industrial Parks Based on Decoupling Index

Industrial parks are the main carriers of industrial activities and are also key areas for carbon emissions. To deeply explore the decoupling state of carbon emissions and economic development of industrial parks and the driving forces, Zhengzhou Economic Development Zone were taken as example, based on the energy consumption data of industrial enterprises above a designated size from 2011 to 2020, the IPCC carbon emission accounting method, Tapio decoupling model, and logarithmic mean Divisia index decomposition method were used to analyze the characteristics of carbon emissions from energy consumption in the park, the relationship between carbon emissions and economic development, and the driving factors of decoupling. The results showed that:① in terms of carbon emission characteristics, the carbon emissions of energy consumption in Zhengzhou Economic Development Zone were mainly indirect carbon emissions, and the total carbon emissions showed a trend of rapid growth in the early stage, slowing down in the medium term, and negative growth in the later stage. The carbon emission intensity was decreasing annually. ② From the perspective of decoupling, the decoupling index between total carbon emissions and economic development in Zhengzhou Economic Development Zone from 2011 to 2016 was 1.021, which was in a state of growth linkage, and the decoupling index decreased to 0.089 from 2016 to 2020, turning into a weak decoupling state. ③ From the analysis of driving factors, from 2011 to 2016, four factors, namely carbon emission coefficient, energy efficiency, industrial structure, and economic level, all had a restraining effect on the decoupling of carbon emissions in Zhengzhou Economic Development Zone, and from 2016 to 2020, they all turned into promotion except for the economic level. This study showed that among the factors for the decoupling of carbon emissions in the Zhengzhou Economic Development Zone, the economic level played a major inhibitory role, and energy efficiency played a major role in promoting it. The results of this study can provide a reference for the industry-city integrated industrial park represented by Zhengzhou Economic Development Zone to formulate corresponding carbon emission reduction policies and achieve the carbon peaking and carbon neutrality goals.

INTELLIGENT BUILDING MONITORING AND MANAGEMENT SYSTEM «ARIANT»

The speed of development of technologies of automated systems determines regular updating, creation of new technical solutions in this field, the niche of home automation is no exception. The implementation of "smart" building monitoring and management systems is designed to ensure an increase in the level of energy efficiency of processes related to energy consumption, as well as the comfort and safety of these processes. Many variants of such systems are offered on the market [1,2,3]. Today, there are state documents that regulate the design, installation and operation of the relevant systems[4]. But the problems of the criteria for choosing the layout and functions of the system, understanding and correct use of its capabilities are extremely acute and open. In addition, the question of the influence of the operation of the automated system of a separate building on the characteristics of the external energy supply remains open. After all, the deterioration of external conditions will lead to an increase in losses during the delivery of an energy resource, accordingly, an increase in the tariff for the delivery of the corresponding resource.

IMPACT OF PARAVERTEBRAL BLOCKADE ON THE COURSE OF EARLY POSTOPERATIVE PERIOD FOLLOWING SURGICAL INTERVENTION FOR LUNG MALIGNANCIES UNDER INHALED SEVOFLURANE ANESTHESIA

The aim of the study is to investigate the impact of paravertebral blockade on the quality of anti-stress protection of general inhalation anaesthesia based on sevoflurane during operations in patients with lung malignancy. Material and methods. We examined 60 individuals of an average age 55±5.6 years, whose physical status was assessed as class II – III according to the ASA classification. The patients underwent open surgical procedures, including frontal or pneumonectomy, or partial lung resection. The patients were divided into 2 groups depending on the method of anaesthesia: SF group (sevoflurane) (n = 29) received inhaled anaesthesia with sevoflurane; SF+PVB group (n = 31) received the combination of inhaled anaesthesia with PVB. The following indicators were assessed: time of the first administration of the analgesic after surgery, pain intensity by the visual analogue scale (VAS), perfusion systemic pressure (PST), cardiac index (CI), oxygen content in arterial and venous blood, blood lactate levels, indicators of circulatory energy efficiency, cortisol, insulin and HOMA index levels. Indicators were recorded before the surgical operation, at the wake-up stage, on the 1st and 5th days following the operation. Results. In the SF+PVB group, the intensity of pain in the postoperative period was significantly lower than in the SF group. In the SF+PVB group, there was no necessity for administering narcotic analgesics on the first day, while in the SF group, the dose of morphine was 0.27±0.04 mg/kg∙day, the first administration was performed 65.5±10.3 minutes after surgery. CI during surgery and in a day was significantly higher in the SF+PVB group, and the arteriovenous difference in oxygen content was significantly lower. The energy efficiency of blood circulation at the same stages was significantly higher in the SF+PVB group. In the same group, there was a significantly lower concentration of markers of stress responses (cortisol levels and HOMA index). Conclusions. The use of paravertebral blockade under the general anaesthesia based on sevoflurane during operations in patients with lung malignancies contributes to a significant reduction in the pain intensity in the postoperative period; eliminates the need to use narcotic analgesics; provides significantly more stable hemodynamics and significantly more adequate oxygen supply during the operation and in the postoperative period; significantly reduces the intensity of stress reactions as well as significantly improves the energy efficiency of blood circulation.

SSFSCE: Design of a Sleep Scheduling based Fan Shaped Clustering Model to enhance working Energy Efficiency of WSN

To enhance energy level in WSN is a research requirement, which assists in improving their lifetime over a series of communications. To achieve this target, a various variety of clustering & sleep scheduling models are discussed by researchers. Most of these models deploy static clustering & sleep scheduling operations, which limits their applicability & scalability levels. Moreover, dynamic clustering & scheduling models are highly complex, which reduces temporal QoS performance under real-time use cases. In order to reduce the probability of these issues, this text discusses design of the proposed Sleep Scheduling based Fan Shaped Clustering Model to enhance working Energy Efficiency of WSN. The proposed model initially deploys a Grey Wolf Optimization (GWO) Method for dynamic sleep scheduling via temporal performance analysis. The GWO Method models a fitness function that combines temporal usage levels, temporal Quality of Service (QoS), and temporal energy levels. Based on this modelling process, nodes were categorized into wake & sleep nodes, which were further clustered via destination-aware Fan Shaped Clustering (FSC), that assisted in improving QoS performance under multiple scenarios. The FSC Model was combined with a QoS-aware routing model, that assisted in selection of routing paths that can achieve low delay, high throughput, and high packet delivery with higher energy efficiency levels. Efficiency of the model was tested on node & network conditions, and its QoS performance was checked in terms of communication delay, consumption of energy, level of throughput, and Packet Delivery Ratio (PDR) levels. On the basis of these comparative evaluations, it is observed that the new proposed model is able to enhance end-to-end delay by 8.5%, reduce level of energy by 15.5%, while increasing throughput by 8.3%, and PDR by 1.5%, thus making it useful for a different real-time conditions.

Taking a step back from glass towers facades to make them compatible with the 2050 targets

Skyscrapers or glass towers are an extremely common model throughout the world. In the current context of climate change and resource depletion, we need to develop new postures towards these objects, especially for existing buildings that are becoming obsolete. This article begins by showing how the nature of the facades of these buildings influences the urban climate. It continues with the analysis of an emblematic building from the 1970s, the Tour Areva in Paris-La Défense (France). Through this typical example, we show how it is possible to improve the quality of use and the energy performance by exploring various scenarios. The main theme is the transformation of the façade and how it is possible, through different actions, to simultaneously improve daylighting performance, visual and thermal comfort and overall energy performance. New approaches to geometry and photometry are explored and show, through daylighting and thermal simulations, that it is possible to give these objects a new start. This work concludes with a life cycle analysis that quantifies the valorization of the intrinsic energy stock associated with the building and which elements can be conserved or reused. In this project, we demonstrate that with good design, it is possible to convert these office buildings into pleasant and generous flats and to achieve a high level of energy efficiency and comfort, without forgetting the environmental objectives for the 2050 horizon.

Complementary Methodology for Energy Efficiency Ratio-Based Assessments with Change-Point Model Parameters

The energy consumption of existing buildings is not only affected by their physical features but also by their business activities (e.g., operating hours, number of workers, and climate). Energy Star’s energy efficiency ratio (EER) is a key energy performance indicator that has been used for more than 20 years. This method normalizes operation characteristics by calculating the estimated energy consumption of business activities using regression models and comparing it with the actual energy consumption. However, EER-based assessment is limited by the lack of information regarding the reasons for the evaluation results. This study proposes a balanced method for explaining the reasons underlying energy efficiency levels while maintaining the existing EER assessment system. The method constitutes data collection, EPI derivation, and energy performance assessment, utilizing the parameters of the change-point linear model (CPM) as an additional EPI to provide descriptive information. The results are summarized to provide a checklist guide for retrofitting, and additional energy saving potential for buildings with low and high scores can be identified by comparing the EER scores and CPM parameters. The proposed method shows that it is possible to interpret the energy efficiency assessment results by comparing CPM parameters, while maintaining the EER score.

Organizational and economic mechanism for increase in the energy efficiency of the national economy

The article discloses the methodological foundations of energy efficiency management based on the author's definition of the essence and content of the organizational and economic mechanism of increasing the energy efficiency of the national economy as a complex system of interacting organizational-technological, management-administrative and economic-ecological levers and regulators aimed at the rational use of available energy resources to optimize energy consumption, reduce energy costs and increasing the overall productivity of the state economy while rationalizing the development of the country's natural resource potential. The set of principles for implementing the national energy efficiency policy has been improved, the consideration of which is due to the catastrophic state of the energy sector and the urgency of its reconstruction, dividing them into five groups. The scale and nature of the destruction of the energy sector and environmental pollution because of large-scale military aggression of the Russian Federation are shown. The organizational and economic mechanism incorporates tools of a different nature, together with legal regulations, financial and credit support, technical and technological innovations, management decisions, and other measures that will contribute to the achievement of goals in the context of increasing energy efficiency and ensuring energy saving in industries and productions of the national economy. A complex set of priority levers and regulators has been formed to synchronously implement three constitutively crucial tasks: restoration of the domestic energy sector after destruction, rationalization of the development of natural resource potential, and improvement of the economy's energy efficiency. It was noted that the country's post-war recovery in the context of increasing the level of energy efficiency due to the introduction of renewable and alternative energy sources requires comprehensive information and educational and communication support. It is shown that the development of the organizational and economic mechanism for increasing energy efficiency requires the formation of its structure according to seven target sub-mechanisms, considering the destruction of the energy infrastructure and facilities. An algorithm of managerial actions regarding the formation and implementation of the organizational and economic mechanism for increasing the energy efficiency of the national economy in nine stages has been developed. Keywords: energy efficiency, energy saving, organizational and economic mechanism of increasing energy efficiency, principles of action implementation, target sub-mechanisms, the algorithm of management actions.

Green total-factor energy efficiency and its convergence of industrial sub-sectors in China.

Existing literature ignores to consider multiple types of pollutants when analyzing energy efficiency and its convergence. Under this background, using SuperSBM-GML model, the improved entropy method, and convergence model, this paper calculates the green total-factor energy efficiency and its evolution trend of 35 China's industrial sub-sectors considering multiple pollutants, and analyzes its convergence. The results indicate that the average score of industrial green total-factor energy efficiency is low, and there are significant differences among sub-sectors: "Utilization of waste resources" is the highest, while "Manufacture of paper and paper products" is the lowest. The green total-factor energy efficiency shows an overall upward trend from 2006 to 2021, the main driving force comes from technological progress, but numerous sub-sectors have not sufficiently caught up with existing cutting-edge technologies. Specifically, the growth rate of green total-factor energy efficiency in high-energy-consumption sub-sectors is higher than low-to-medium-energy-consumption sub-sectors. There are both σ-convergence and β-convergence in low-to-medium-energy-consumption group, indicating that development of sub-sectors is stable and outstanding. Nevertheless, the high-energy-consumption group only exhibits conditional β-convergence, revealing an imbalance in energy efficiency development. Consequently, formulating the benchmark level of energy efficiency and developing energy efficiency "leader" system are suggested for low-to-medium and high-energy-consumption sub-sectors, respectively.

Promoting Energy Efficiency and Emissions Reduction in Urban Areas with Key Performance Indicators and Data Analytics

With the increasing demand for sustainable urban development, smart cities have emerged as a promising solution for optimizing energy usage, reducing emissions, and enhancing the quality of life for citizens. In this context, the combined use of key performance indicators (KPIs) and data analytics has gained significant attention as a powerful tool for promoting energy efficiency and emissions reduction in urban areas. This paper presents a comprehensive conceptual framework in which a series of KPIs are proposed to serve as essential metrics for guiding, monitoring, and assessing energy efficiency and emissions reduction levels in smart cities. Some of the included KPIs in the analysis are 'annual energy consumption per person', 'reduction in greenhouse gas emissions', 'public transport use', and 'adoption of renewable energy'. By incorporating these KPIs, city planners and policymakers can gain valuable insights into the effectiveness of sustainability initiatives. Furthermore, the paper explores how the integration of KPIs with data analytics can be used for monitoring and assessing the overall performance of the city in terms of energy efficiency, emissions reduction, and the enhancement of urban living conditions. Visualization tools, such as radar plots, and time series analysis forecasting methods allow data to be processed and patterns to be identified, enabling informed decision-making and efficient resource allocation. Real-life case studies of ongoing smart city projects are presented in the paper, which also provides a KPI comparison among different European cities, as well as models to forecast the evolution of KPIs related to energy usage and emissions reduction in different European cities.

Enhancing school buildings energy efficiency under climate change: A comprehensive analysis of energy, cost, and comfort factors

Incorporating future weather predictions into building assessments is essential for enhancing resilience, energy efficiency, cost savings, comfort, and sustainable infrastructure development in response to climate change. This study investigates the interplay between climate change and building performance, primarily focusing on energy usage, cost implications, and occupant comfort. It examines how future weather conditions impact school buildings in different climates, analyzing energy, cost, and comfort aspects. The research underscores the significance of tailored climate adaptation strategies for various regions and emphasizes considering future performance, even for highly energy-efficient buildings. Employing a comprehensive simulation-based approach, the study implements and validates future weather data in a Turkish school building, incorporating envelope improvements and photovoltaic applications to boost energy efficiency. A distinctive feature is the rigorous validation of future weather predictions against current measured data, facilitating a regional-level assessment of climate change effects on building energy consumption. The study's novelty lies in its detailed evaluation of climate change's multifaceted impacts on buildings, innovative future climate data validation, and contribution to a more localized and climate-specific approach to addressing building energy-cost-comfort performance. Findings reveal that in hot climates, there is a potential for nearly doubling primary energy consumption, global costs, and CO2 emissions in the future for both cost-optimal and nearly zero-energy scenarios. Consequently, the savings would decrease from 53-63 % to 13–30 %. In contrast, in cold climates, the impact on these parameters differs slightly, with reduced primary energy consumption and CO2 emissions but higher global costs. Notably, a building retrofitted to a high energy efficiency level may experience a substantial increase in future energy consumption and global costs, approaching the levels of currently inefficient buildings.

An EEDI based method to better the selection of form and propulsion parameters and improve energy efficiency during preliminary designs of single screw seagoing general/bulk cargo ship

The third phase of the Energy Efficiency Design Index (EEDI) regulations, which came into force in 2022, states that new ships should reduce their emissions by at least 30% compared to the minimum energy efficiency level (EEDI baseline) set by the IMO's MEPC in 2013. Apart from its vital role in decarbonizing the global fleet and improving the transportation efficiency, the EEDI that is considered herein is a measure of vessel's mechanical performance. A simplified EEDI (SEEDI) is used to judge a series of designs in order to identify all possible efficient designs and to select the best option. A code was employed to iterate over all practical ranges of hull and propeller parameters to extract complete designs from methodical design and propeller series. All possible methods of manipulating form and propulsion parameters that might lead to reducing the SEEDI were investigated. The modifications were made while taking into consideration the practical and economical ranges of the non-dimensional ratios and form coefficients. Compared to the use of energy saving devices and slow steaming, significant reductions (up to 25%) in the SEEDI have been achieved after applying the proposed method.

Analytical Review of the Software for Creating a City Information Model

Introduction. The article describes a forward-looking technology in the field of construction industry and urban management – CIM (City Information Modeling) – an information model of a city. Emergence of the information modelling have led to the possibility to create the 3D models not only of individual objects, but also of a city as a whole with its buildings, infrastructure, geological and environmental factors. But creation and maintenance of the city models require the software tools. The aim of the present research is to make a review of the available software, describe its properties and field of application. CIM application capacities are also defined. The tasks, which can be solved by means of such a model, are described. The result of using GIS technologies in creating a city information model with respect to the data on housing stock energy efficiency level is shown.Materials and Methods. Within the research, an analytical review of the existing software for creating an information model of a city was carried out, the works of the scientists, who contributed to the issue of urban modeling, were studied. The information sources useful for further research were identified. Geo-information systems ARC GIS 10.1 ESRI were used to create a city information model.Results. A city information model can be described as a replication of the historical and cultural, socio-economic and religious events and phenomena; the three-dimensional models, geo-information virtual systems created by means of the space-based processing and information technologies, including BIM (Building Information Modeling) and GIS (Geographic Information Systems). The software complexes, which function based on the analysis of the valid data and creation of design entities, are used to create the information models of the urban territories. The major companies importing the urban modeling software, Autodesk and Bentley, offer both BIM and CIM tools.Discussion and Conclusions. The term "Smart City" has become especially popular due to development of BIM technologies. This is an innovative approach based on the digital technologies application, which directly affects the activities and efficiency of provided services and rising the city living standard. For solving the thematic problems, there exist the focused technologies and tools of the modern urban environment development. The main task of the "Smart City" is enhancement of the comfort standard of the residents’ living. This task is solved by creating a city information model integrating the information about the terrain, buildings and structures, roads, green spaces, etc.

Energy efficiency evaluation and optimization of active distribution networks with building integrated photovoltaic systems

With the rapid development of building integrated photovoltaic (BIPV) technology, rooftop PV grid-connected systems face challenges in operation. When the consumption rate of BIPV systems is low, power reverse increases distribution network losses and decreases power supply quality. Traditional energy efficiency evaluations for distribution networks do not consider the impact of low BIPV consumption rates on network losses. This paper establishes an energy efficiency evaluation model for distribution networks with BIPV systems based on adversarial interpretive structural modeling and proposes an energy efficiency indicator system applicable to distribution networks with BIPV systems. The method was applied to eight distribution networks with BIPV systems, achieving accurate energy efficiency level rankings. Through single-factor sensitivity analysis of the indicator system, the primary factors affecting distribution networks with BIPV systems energy efficiency were identified. A reactive power optimization model based on multi-objective particle swarm optimization algorithm was established. After optimization, network losses decreased by 153 kW, PV consumption rate increased by 73 %, and node voltage drift was significantly enhanced. Corresponding loss reduction strategies were proposed for other indicators. This paper provides valuable references for planning and renovating distribution networks with BIPV systems.

Inland waterway transport development: A Q-Method study on Tocantins River, Brazilian Amazon

In Brazil, increasing Inland Waterway Transport (IWT) figures among efforts for the Nationally Determined Contribution due to better energy efficiency and lower CO2 emission levels, when compared to highways and railways. Identifying barriers and drivers is useful to develop IWT as an alternative to terrestrial transportation modes, which are scarce in the Brazilian Amazon. As more than 50% of Brazilian electricity is generated in hydropower plants, the harmonic coexistence between multiple water uses is crucial. This paper aims to explore stakeholders' perceptions and priorities related to the development of inland waterway transport in the Tocantins River, Amazon, Brazil, where there are several hydropower plants. With an emphasis on sustainability issues, we used the Q-Method, a technique for assessing the relative importance of elements in various contexts. We identify and describe four perspectives (factors) using Q-method: (1) “critical shoals”; (2) “waterway, death project”; (3) “dams on waterways” and (4) “freedom for waterways”. Within these perspectives, economic incentives, with insights to cut down costs and increase freight are main concerns. We found disconnection between the reality of local communities and the lack of awareness on negative impacts by government officials and economic agents interested in waterway development. Mechanisms to guarantee social participation in IWT planning and implementing could foster socially acceptable solutions for technical, economic and governance issues.

How does the transition policy of mineral resource-exhausted cities affect the process of industrial upgrading? New empirical evidence from China

Recognizing the accelerated depletion of mineral resources such as coal, metallurgy, and petroleum in resource-depleted cities is merely a matter of time. Consequently, the industrial restructuring and upgrading of these cities have become a high-priority concern in ensuring sustainable natural resource utilization and environmental sustainability. In this way, this paper is about the mineral resource-exhausted city transition program. It uses China's county and enterprise data from 2004 to 2013 and a staggered difference-in-difference model to figure out how the supportive policy affected industrial upgrading. Our findings indicate that transition policies pose a significant promoting effect on stimulating the industrial upgrading process in Chinese mineral resource-exhausted cities. Specifically, this positive effect is more pronounced in counties characterized by high levels of energy efficiency and environmental performance. Carrying out robustness tests, the preliminary regression results are verified. Heterogeneous influences have been partially established among cities with distinct geographical regions and resource endowment attributes. Further mechanism analysis reveals that heightened cost pressures, incentives for innovation, economic performance attractiveness, and improvements in energy efficiency constitute the primary micro-channels driving industrial upgrading throughout the sample period. This study holds significant global relevance for the sustainable management of natural resources and the sustainable development of mineral resource-exhausted cities in similar emerging economies.

Графическое исследование показателей энергетической эффективности потребления топливно-энергетических ресурсов странами мира

The article is devoted to the comparative study of the energy characteristics of countries around the world, which is based on the construction of graphic maps of energy characteristics. The article presents the author’s maps of the energy intensity and electrical capacity of GDP by PPP of the countries of the world, the energy intensity and electrical capacity of per capita GDP by PPP of the countries of the world, a map of per capita energy consumption and electricity consumption in various countries of the world, and a map of the characteristics of CO2 emissions in various countries of the world, with the distribution of characteristics along the axes of GDP per capita and per capita electricity consumption. The materials analyze the results of the constructed maps and draw appropriate conclusions. Based on the maps of the energy intensity and electrical intensity of GDP by PPP of the countries of the world, conclusions are drawn about the high differences in the level of energy efficiency of the economies of different countries of the world, both in terms of total consumption of fuel and energy resources and electric energy, in particular. The constructed map of the energy intensity and electrical intensity of per capita GDP by PPP in various countries of the world makes it possible to group countries by indicators of energy efficiency of electricity consumption, taking into account the scale of economic development per capita. The identified country groups make it possible to carry out a subsequent analysis of the energy and economic characteristics of individual countries, to identify common features, and to develop principles, mechanisms, and methods of managing the economy and energy facilities of countries, taking into account the identified features. The map of per capita energy consumption and electricity consumption in various countries of the world presented in the materials made it possible to clearly identify that the indicators of per capita energy consumption and electricity consumption of the countries of the world are proportional. The article presents a map of the characteristics of CO2 emissions from different countries of the world, reflecting the distribution of countries relative to each other in terms of relative CO2 emissions, which allows us to clearly identify a significant difference in carbon dioxide emissions, which indicates a difference in the characteristics of the efficiency of consumption of fuel and energy resources. The results obtained make it possible to perform a subsequent grouping of countries with the identification of common features as well as the development of differentiated directions of energy policy aimed at effective economic development.

A Sigma-Delta Modulator with Single-Pole Double-Throw Analog Switch

In this paper, a high precision and high energy efficiency discrete-time switching capacitive 3-order Sigma-Delta modulator (SDM) is proposed. The SDM is applied to portable electroencephalograms (EEG) because of its little energy and good performance. The energy efficiency levels of the current mainstream modulator systems are analyzed and compared, and the CIFF modulator architecture which is most conducive to realizing high energy efficiency is selected. The single-loop CIFF structure is selected to give consideration to the accuracy and stability of the circuit. The circuit is implemented in a hierarchical structure, and a single-pole double-throw (SPDT) analog switch is adopted to overcome the difficulty of opening conventional CMOS analog switches at low supply voltages and the increase in threshold voltage Vth of NMOS devices due to the base bias effect. The proposed discrete-time Sigma delta ADC modulator is designed with SMIC 0.18um CMOS technology and achieves an SNDR of 101.6dB under a 1.8V power supply voltage and a signal bandwidth of 2kHz. The power consumption is 520uW and the significant bit (ENOB) is 16.58 bits.

The impact of the heat supply industry on the level of energy efficiency of industrial territories and regions of Russia

One of the most important areas for improving Russian economy under the influence of sanctions pressure is to increase the level of energy efficiency in the consumption of fuel and energy resources. The aim of the study is to study the place and role of the Russian economy in the process of forming the world fuel and energy balance. An analysis of the data on the production and consumption of fuel and energy resources by Russia emphasized that the country occupies a leading position in terms of reserves, production volumes, consumption and exports of global fuel and energy resources, while the efficiency of energy consumption in the country is significantly behind the world average, which negatively affects the internal economic processes taking place in the country and requires the search for solutions to increase the level of energy efficiency. Research analyzes analyzes the volume of thermal energy consumption in Russia in comparison with the global scale, as a result it was revealed that the annual volume of thermal energy consumption in Russia is 11 times more than, for example, in Germany, 12.5 times more than in the USA, 12.7 times more than in Kazakhstan, which underlines the significant contribution of the heat supply industry to the lag in the level of energy efficiency of the Russian economy from the indicators of most countries. Analysis of the statistical data of average temperatures in various countries of the world, as well as the federal districts of the country, revealed the influence of the climatic factor on the volume of thermal energy consumption in Russia, which determines the impossibility of excluding the consumption of thermal energy to maintain the functioning of the Russian economy. The main result of the study is the revealed high role of the Russian economy in shaping the global fuel and energy balance, as well as the need to increase the level of energy efficiency of fuel and energy consumption. The materials suggest the improvement of alternative replacement models for consumed primary and secondary fuel and energy resources. As an energy replacement resource, it is proposed to use electric energy in the system of combined district heating of industrial areas. The use of electric boilers makes it possible to increase the energy efficiency of integrated energy supply, enhance the environmental friendliness of heat supply, and reduce the cost of the economy for centralized heat supply of individual territories.

Machine learning-based energy use prediction for the smart building energy management system

Smart building is a building development approach utilizing digital and communication technology to improve occupants' comfort inside the building and help increase energy usage efficiency in building operations. Despite its benefits, the smart building concept is still slowly adopted, particularly in developing countries. The advancement of computational techniques such as machine learning (ML) has helped building owners simulate and optimize various building performances in the building design process more accurately. Therefore, this study aims to assist energy efficiency design strategies in a building by identifying the features of the smart building characteristics that can potentially foster building energy efficiency. Furthermore, an ML model based on the features identified is then developed to predict the level of energy use. K-Nearest Neighbor (k-NN) algorithm is employed to develop the model with the openly accessible smart building energy usage datasets from Chulalongkorn University Building Energy Management System (CU-BEMS) as the training and testing datasets. The validation result shows that the predictive model has an average relative error value of 17.76%. The energy efficiency levels obtained from applying identified features range from 34.5% to 45.3%, depending on the reviewed floor. This paper also proposed the dashboard interface design for ML-based smart building energy management.