Efficient Use Of Energy Resources Research Articles

Microgrids with day-ahead energy forecasting for efficient energy management in smart grids: hybrid CS-RERNN

ABSTRACT By integrating smart grid technology with home energy management systems, households can monitor and optimise their energy consumption. This allows for more efficient use of energy resources, reducing waste and lowering energy bills. In this manuscript, a hybrid approach is proposed for smart grid home energy management with microgrids and day-ahead energy forecasts. The proposed control approach combines the Circle Search (CS) algorithm and Recalling-Enhanced Recurrent Neural Network (RERNN). Commonly it is named as CS-RERNN technique. The novelty of this paper is to optimise energy consumption and production within microgrids, thereby contributing to the overall efficiency of the smart grid system. The proposed method is used to reduce the electricity cost, peak-to-average ratio (PAR), and maximising consumer comfort. Energy management is performed based on the CS algorithm. A smart home connected to the external power grid (PG) is managed by the proposed method. Here, load demand is predicted by using RERNN. By then, the performance of the proposed method is implemented in MATLAB platform. The proposed method shows a high efficiency of 96%, and 22 $ of low electricity bill cost compared with other existing methods such as Particle swarm optimisation (PSO), Cuckoo search algorithm (CSA, and Border collie Optimisation (BCO).

Решение обратной задачи теплопередачи в конденсаторе турбоустановки со встроенным теплофикационным пучком

For power plants reduction of heat losses is one of the main ways to save energy. Energy saving issue is one of the priority areas of the development of science, engineering, and technology in the Russian Federation. Efficiency upgrading of the equipment operation are associated with the condensers of turbine units, since more than 50 percent of the fuel energy is released into the environment with cooling water. The operating efficiency of a condenser with built-in heating beams significantly affects the vacuum in the condenser and, thus, the operating efficiency of the entire unit. Diagnostics of the condition and improvement of operating modes of the condenser of a turbine unit with a built-in heating unit is an urgent scientific and practical issue. To develop a model of a condenser with a built-in heating beam, the methodology of matrix formalization of the description of heat and mass transfer processes has been used. To solve the problem of diagnosing the condition of equipment, methods of least squares and mathematical programming have been used. Within the framework of the matrix formalization methodology, the authors have developed an approach to solve inverse problems of diagnosing and designing multi-flow heat exchange equipment considering the phase transition in coolants. The authors have obtained and analyzed solutions of the inverse problem from the point of view of diagnosing the state of heat exchange equipment using the example of a turbine unit condenser with a built-in heating beam. Analysis of the calculated results has shown an adequate description by the model of the standard data for the analyzed condenser. Analysis results have shown the possibility to use the model for runtime diagnosis of the condition of power equipment and the efficient use of energy resources due to preventing ineffective modes. The proposed approach allows us to formulate and solve inverse problems of diagnosing the state of equipment of condensing units for various purposes.

Long Short-Term Memory-Based Twin Support Vector Regression for Probabilistic Load Forecasting.

A probabilistic load forecast that is accurate and reliable is crucial to not only the efficient operation of power systems but also to the efficient use of energy resources. In order to estimate the uncertainties in forecasting models and nonstationary electric load data, this study proposes a probabilistic load forecasting model, namely BFEEMD-LSTM-TWSVRSOA. This model consists of a data filtering method named fast ensemble empirical model decomposition (FEEMD) method, a twin support vector regression (TWSVR) whose features are extracted by deep learning-based long short-term memory (LSTM) networks, and parameters optimized by seeker optimization algorithms (SOAs). We compared the probabilistic forecasting performance of the BFEEMD-LSTM-TWSVRSOA and its point forecasting version with different machine learning and deep learning algorithms on Global Energy Forecasting Competition 2014 (GEFCom2014). The most representative month data of each season, totally four monthly data, collected from the one-year data in GEFCom2014, forming four datasets. Several bootstrap methods are compared in order to determine the best prediction intervals (PIs) for the proposed model. Various forecasting step sizes are also taken into consideration in order to obtain the best satisfactory point forecasting results. Experimental results on these four datasets indicate that the wild bootstrap method and 24-h step size are the best bootstrap method and forecasting step size for the proposed model. The proposed model achieves averaged 46%, 11%, 36%, and 44% better than suboptimal model on these four datasets with respect to point forecasting, and achieves averaged 53%, 48%, 46%, and 51% better than suboptimal model on these four datasets with respect to probabilistic forecasting.

Administrative and legal measures to overcome threats to energy security of Ukraine in the oil and gas sector

Under martial law conditions in Ukraine since February 24, 2022, the oil and gas sector has faced unprecedented threats to energy security. This article aims to comprehensively analyze the state’s administrative and legal measures in overcoming threats in the oil and gas industry during martial law, focusing on the fuel and gas sectors.
 The study employs various methods, including formal legal analysis of regulatory legal acts, the formal and dogmatic method to deduce the content of legal regulation for energy security in the oil and gas sector, and the systematic method to examine specific administrative and legal measures within the broader framework of Ukraine’s energy security.
 The study delves into the administrative and legal measures implemented by Ukraine to address threats in the fuel and gas sectors. In the fuel sector, measures include simplifying bureaucratic procedures, prioritizing fuel imports from the EU, altering pricing mechanisms, and tax relief. The gas sector involves legislative changes, moratoriums on pricing and tariff increases, funding allocations, export bans, and the involvement of large energy companies.
 Since martial law’s introduction, Ukraine applied diverse administrative and legal measures to enhance energy security in the oil and gas sector. The effectiveness of these measures requires a comprehensive approach, considering potential negative consequences. Strengthening the role of energy entities and aligning antimonopoly legislation with consumer protection is crucial. Timely legislation addressing the energy sector functioning under extraordinary circumstances is recommended for proactive threat response. Finally, the paper highlights the need for sustainable development criteria, emphasizing efficient energy resource use and the integration of renewable energy sources.

АНАЛИЗ СИСТЕМЫ ВОДОСНАБЖЕНИЯ ПРОИЗВОДСТВ ВСПЕНИВАЮЩЕГОСЯ ПОЛИСТИРОЛА

The scheme of water supply of the industrial site for the production of foaming polystyrene by the method of suspension polymerization is analyzed. The amount of suspended solids in the re-cycled water of this production has been experimentally determined, and a possible method of its purification has been proposed. The relevance of this work lies in the efficient use of energy resources, as well as ensuring the highly efficient operation of heat exchange equipment

Understanding energy poverty drivers in Europe

This paper tackles the issue of energy poverty in an attempt to identify the key factors that would enhance the affordability of energy services. We implement a set of recent panel data techniques which enable us to capture the presence of regime shifts and time-varying relationships between energy poverty and its main drivers. Using annual data from 25 European countries over the period 2006–2019, we point out the prominent role of income level and energy price in determining access to adequate and affordable energy. This outcome depends on the degree of income inequality, the energy efficiency, and the energy transition underway. Better income distribution among households and efficient use of energy resources would alleviate energy poverty. Nevertheless, policymakers would have to pay more attention to the cost of energy transition to not worsen household access to energy services.

Managerial Challenges Related to the Efficient Use of Energy Resources in the Hotel Industry

Managerial Challenges Related to the Efficient Use of Energy Resources in the Hotel Industry

Cost analysis of insulation materials used to increase energy performance in buildings with Net Present Value method

Today, producing solutions for the effective and efficient use of energy resources is among the priority areas in almost every sector. In terms of energy consumption, each solution developed in the building sector significantly reduces total energy consumption. In this study, different types of insulation materials used in walls and roofs were investigated in terms of cost-effectiveness to improve the energy performance of a building located in the 1st-degree day zone in Türkiye. Four commonly preferred insulation materials for walls and roofs were tested at specific thicknesses. The Design-Builder simulation program simulated scenarios for the specified thicknesses, and energy consumption values were determined. The initial investment costs of each alternative were calculated, and energy savings were determined. The initial investment costs and energy savings were evaluated according to the Net Present Value method, and each alternative's priority ranking was revealed. According to the results obtained, when the materials used in the study are compared, it is determined that the material with the highest net present value for the roof is glass wool, and the material with the highest net present value for the wall is stone wool.

Analysis of methods for improving the efficiency of “Iceberg” gas air coolers

Russia has the largest volume of natural gas reserves in the world. Recoverable natural gas reserves amount to about 67 trillion cubic meters, according to the Ministry of Natural Resources and Environment of the Russian Federation for 2023. In recent years, the development of the Unified Gas Supply System has been growing rapidly. Since 2021 the Government of the Russian Federation has been actively introducing draft laws and regulations related to the scaling of the country’s gasification. In June 2021 came out the Federal Law No. 184-FZ, which instructed the Government of the Russian Federation to adopt regulations aimed at implementation of provisions of free gasification of the country [1]. In September 2021 there was issued Decree No. 1547, [2] approving the new Rules for connecting gas-using equipment and capital construction facilities to gas distribution networks, which introduces the concept of pre-gasification. It is worth noting that new gas mains, compressor stations (CS) are put into operation, active reconstruction of the existing shops with exhausted gas compressor units (GCU) is carried out. One of the most urgent issues of the gas industry today is the efficient use of energy resources. Besides using the energy of flue gases from gas turbine drive of GPA, energy at gas throttling at gas distribution stations and other methods of energy saving, the significant role is played by the effective operation of air coolers of gas (ACG), the operation of which affects the reliable transportation of gas in the main gas pipeline (MG). The paper analyzes the methods of technical condition of gas air cooling devices of “Iceberg” type operated at the production site of the booster compressor station of “Gazprom Dobycha Nadym” LLC. The thermal efficiency of air coolers with all fans turned on and off was determined for the coldest and hottest months of the year. The electric energy savings of the frequency controlled drive (VFD) were calculated.

Integrating Smart Energy Management System with Internet of Things and Cloud Computing for Efficient Demand Side Management in Smart Grids

The increasing price of and demand for energy have prompted several organizations to develop intelligent strategies for energy tracking, control, and conservation. Demand side management is a critical strategy for averting substantial supply disruptions and improving energy efficiency. A vital part of demand side management is a smart energy management system that can aid in cutting expenditures while still satisfying energy needs; produce customers’ energy consumption patterns; and react to energy-saving algorithms and directives. The Internet of Things is an emerging technology that can be employed to effectively manage energy usage in industrial, commercial, and residential sectors in the smart environment. This paper presents a smart energy management system for smart environments that integrates the Energy Controller and IoT middleware module for efficient demand side management. Each device is connected to an energy controller, which is the inculcation of numerous sensors and actuators with an IoT object, collects the data of energy consumption from each smart device through various time-slots that are designed to optimize the energy consumption of air conditioning systems based on ambient temperature conditions and operational dynamics of buildings and then communicate it to a centralized middleware module (cloud server) for management, processing, and further analysis. Since air conditioning systems contribute more than 50% of the electricity consumption in Pakistan, for validation of the proposed system, the air conditioning units have been taken as a proof of concept. The presented approach offers several advantages over traditional controllers by leveraging real-time monitoring, advanced algorithms, and user-friendly interfaces. The evaluation process involves comparing electricity consumption before and after the installation of the SEMS. The proposed system is tested and implemented in four buildings. The results demonstrate significant energy savings ranging from 15% to 49% and highlight the significant benefits of the system. The smart energy management system offers real-time monitoring, better control over the air conditioning systems, cost savings, environmental benefits, and longer equipment life. The ultimate goal is to provide a practical solution for reducing energy consumption in buildings, which can contribute to sustainable and efficient use of energy resources and goes beyond simpler controllers to address the specific needs of energy management in buildings.

ВПРОВАДЖЕННЯ КОРОТКОСТРОКОВИХ НАВЧАЛЬНИХ ПРОГРАМ З ЕНЕРГОЕФЕКТИВНОСТІ В РАМКАХ РЕАЛІЗАЦІЇ ПРОЄКТУ «FUTURE PROFI» НА БАЗІ ДНЗ «БОГУСЛАВСЬКИЙ ЦЕНТР ПРОФЕСІЙНО-ТЕХНІЧНОЇ ОСВІТИ»

The current state of the economy is characterized by significant changes in the labor market. New trends – the rapid development of innovations and technologies, the emergence of new specialties at the intersection of several industries, the need for saving and efficient use of energy resources, the spread of new forms and types of employment, increased competition, increased migration, the possibility of constantly changing the place of work and profession - put forward new requirements for ownership knowledge, skills and abilities. Soft universal interprofessional skills (soft skills), such as knowledge and information management, self-organization, negotiation, the ability to analyze and make effective decisions, solve complex problems, allow a person to quickly adapt to new conditions, together with specialized specialized knowledge – allow to gain competitiveness and demand in the labor market. Such specialized knowledge today are qualifications in the energy efficiency and energy saving sector.

Development of ways to saving energy when operating winding machines

Energy efficiency or energy saving is the practical implementation of scientific, technical, economic and industrial measures aimed at the efficient use of energy resources. Therefore, one of the challenges facing the textile industry is energy saving in technological processes in the production of products. To solve this problem, it is proposed to introduce into production advanced technological processes with low energy costs, the use of technological equipment equipped with electric motors with high rates of consumed electrical energy. This problem is also inherent in winders and similar machines equipped with a bobbin changer. Since most of the time of operation of these devices is wasted and, accordingly, electricity is also wasted. However, to date, these issues have not been given due attention, and studies on this subject have not been conducted. In this work, the operation of the apparatus for changing bobbins in winding and similar machines has been studied in order to reduce power consumption. As a result of the study, a mathematical model of the relationship between the operating mode and technological parameters of machines and apparatuses was obtained, which makes it possible to identify ways to eliminate shortcomings in their work. Discontinuous, on signal and sectional methods of operation of the apparatus for changing bobbins have been developed, which make it possible to reduce power consumption on winding machines by 2.8–4.2 times compared to the existing method of operation. And the autonomous method of operation of the device, proposed in the work, completely eliminates the consumption of electricity consumed by the device for changing bobbins. The results of the study can be used in spinning and weaving mills.

Transforming Bakery Production Lines in Finnish SMEs Through Modeling, Simulation, and Co-Robotization for Efficient Use of Energy Resources

Transforming Bakery Production Lines in Finnish SMEs Through Modeling, Simulation, and Co-Robotization for Efficient Use of Energy Resources

Real-Time Pricing-Enabled Demand Response Using Long Short-Time Memory Deep Learning

Sustainable energy development requires environment-friendly energy-generating methods. Pricing system constraints influence the efficient use of energy resources. Real-Time Pricing (RTP) is theoretically superior to previous pricing systems for allowing demand response (DR) activities. The DR approach has been useful for correcting supply–demand imbalances as technology has evolved. There are several systems for determining and controlling the DR. However, most of these solutions are unable to control rising demand or forecast prices for future time slots. This research provides a Real-Time Pricing DR model for energy management based on deep learning, where the learning framework is trained on demand response and real-time pricing. The study data in this article were taken from the Australian Energy Market Operator (AEMO), and the learning framework was trained over 17 years of data to forecast the real future energy price and demand. To investigate the suggested deep learning-based dynamic pricing strategy, two prediction instances are addressed: actual–predicted demand and actual–predicted price. We estimated pricing and demand outcomes using long short-term memory (LSTM), which were then greatly improved by architectural changes in the model. The findings showed that the suggested model is suitable for energy management in terms of demand and price prediction.

A meta-heuristic-based energy efficient route modeling for EVs integrating start/stop and recapturing energy effect

The research interest in electric vehicles (EVs) has recently sparked exponentially on account of curbing carbon emissions and paucity of fuel resources. No doubt, these vehicles are ecologically sustainable and move smoothly at a moderate speed that is economical on fuel, but their limited range due to the battery reserve demands an efficient use of energy resources. An immediate solution to overcome this problem lies in regulating the EV route, with optimum energy usage. Thus, this study presents a mathematical model that accounts for vehicle energy consumption with the vehicle’s start/stop energy expenditure. To achieve the objective of maximizing the energy-efficiency, it also introduces Amplified-ACO (A2CO), a routing algorithm based on Ant Colony Optimization (ACO) principles that make use of the probabilistic selection model (DS2 relies on Distance, Speed, and State-of-Charge). This study simulates the proposed model over the real-time map of Chandigarh (India) and provides a comparative study against some of the nature-inspired meta-heuristic approaches such as classical ACO and Particle Swarm Optimization (PSO). The proposed model justifies its significance under various parameters, viz. energy consumption, travel time, total travel distance, and remaining SoC.

Использование методов планирования в повышении энергетической эффективности экономики Российской Федерации

The importance of careful elaboration of state and regional policy measures to attract and protect investments in measures to improve the energy efficiency of the economy of the Russian Federation, primarily from the banking sector and private investment in the ongoing activities, is revealed. At the same time, public policy measures should ensure the protection of investments with guaranteed payback. Efficient use of energy resources is considered as the most important factor in ensuring sustainable growth of the real sector of the economy, the development of most sectors of the fuel and energy, industry, transport, housing and communal services. That is why the new Energy Saving and Energy Efficiency Improvement Plan should be closely linked to all current Economic Development Strategies. It is shown that only at the state level as a whole, with the participation of financial specialists and technical experts of all interested parties, it is possible to develop and achieve results and balance measures to improve the efficiency of energy resources use both at the federal and regional levels, as well as by sectors of the economy and end users of energy of all levels and forms of ownership.

Measures to ensure the efficient use of energy resources during crisis situations

Measures to ensure the efficient use of energy resources during crisis situations

Can we make color switchable photovoltaic windows?

The development of smart windows could enhance the functionality of the large glass facades found in modern buildings around the globe. While these facades offer occupants views and natural light, the poor insulating qualities of glass cut against the desire for more efficient use of energy resources. In this perspective article, we explore recent developments for next-generation smart window technologies that can offer improved energy management through dynamic color switching, reducing heating and cooling loads, while also generating electricity through the photovoltaic effect. Approaches with chromogenic organic dyes and halide perovskite semiconductors have been developed for switchable photovoltaic windows, but each of these comes with unique challenges. These approaches are briefly discussed and evaluated with an eye to their future prospects. We hope that this perspective will spur other researchers as they think about the various materials and chemical design challenges associated with color switchable photovoltaic windows. Perhaps these initial demonstrations and research ideas can then become marketable products that efficiently use space to improve occupant comfort and reduce the energy demand of the built environment.

İNŞAAT ATIKLARININ İKLİM DEĞİŞİKLİĞİ ÜZERİNE ETKİLERİ: DAHA ÇEVRECİ BİR İNŞAAT SEKTÖRÜ MÜMKÜN MÜ?

Due to the increasing population, the rapid consumption of natural resources has revealed the necessity of protecting nature from people. Increasing building stock due to population growth has triggered climate change. The energy and natural resources consumed during production in the construction sector have created important environmental problems such as global warming and climate change in the sector. Greenhouse gas emissions caused by construction materials can be considered as one of the main causes of climate change problems and emphasizes the necessity of considering environmental effects. Greenhouse gas is one of the most important factors affecting the ecological environment and climate change, as it is one of the gases with the highest carbon dioxide emission rate. Concrete and steel used in the construction industry are among the materials that have a negative impact on climate change. This study revealed the effects of waste materials used in the construction industry on the problem of climate change and the importance of promoting the efficient use of energy resources for the management of this problem. In addition, this study emphasized the importance of focusing on sustainable structures in order to leave a cleaner and healthier environment for future generations, and that priority should be given to developing environmentally friendly materials.

Methods of Enhancing Energy Efficiency at the Stage of Construction of High-Rise Residential Buildings

Introduction. People’s growing needs in energy resources in conditions of resource deposits depletion makes it relevant the development of methods of enhancing buildings energy efficiency. The article notes the importance of increasing the level of energy efficiency by selecting a set of measures for the efficient use of energy resources at all stages of the life cycle. The analysis of Rostov-on-Don housing stock and positive trend in housing commissioning capacity growth in Russia point at the need to enhance the energy efficiency of buildings being under construction.Materials and Methods. Energy efficient methods are as follows: the application of modern thermal insulation materials and "green" building technologies. The latter implies the approach to the design of buildings inferring minimized impact on the environment at all stages of the life cycle - from a building’s design to its elimination - including the application of "green" technologies: Smart Energy Glass windows, recuperators, solar panels.Results. The results of energy-efficient technologies application were considered on the example of “Ostrovsky” residential compound being under construction in Rostov-on-Don. As a result the planned energy efficiency class B (high) was upgraded to A + (very high), which corresponds to one of the green building criteria.Discussion and Conclusions. The use of energy efficient measures in construction of residential buildings allows to save considerable amounts of energy and resources at the stage of high-rise buildings operation, resulting in their energy efficiency class enhancement.