Energy-efficient Problem Research Articles

Efficient multiobjective optimization for an AGV energy-efficient scheduling problem with release time

In recent years, green manufacturing has attracted wide attention from researchers. However, the energy efficiency problem in matrix manufacturing workshops is still a blank area. This paper considers a novel automatic guided vehicle (AGV) energy-efficient scheduling problem with release time (AGVEESR) to optimize the three objectives of energy consumption, number of AGVs used and customer satisfaction simultaneously. Considering the development of the AGVEESR, we extract problem-specific knowledge, establish a multiobjective mathematical model, and design a hybrid constructive heuristic. Due to the complexity of the problem, we propose an efficient multiobjective greedy algorithm (MOGA) with effective strategies such as new population initialization, greedy operation, and self-adaptive multiple neighbourhood local search. Meanwhile, an ideal-point-based construction operator in the greedy operation phase is presented to lower the computational complexity. Simulation results show that the proposed MOGA has a tremendously superior performance to the five state-of-the-art algorithms in solving the problem considered.

Forming a Two-Tier Heterogeneous Air-Network via Combination of High and Low Altitude Platforms

In this paper, an aerial heterogeneous wireless network consists of a high altitude platform (HAP) and low altitude platforms (LAPs) as aerial base stations (ABSs) in a downlink orthogonal division multiple access (OFDMA) transmission is investigated. Two types of spectrum sharing, including spectrum underlay access (SUA) and spectrum overlay access (SOA) are employed to evaluate the inter-tier interference. Distributed problem formulation and solving method are used to reduce the computational complexity, communication overhead and system latency. Subcarrier assignment and power allocation in spectral efficiency (SE), energy efficiency (EE) and transmission power optimization problems are accomplished by the proposed two-layer algorithm. In the proposed algorithm, first, subcarrier assignment based on constraints of the optimization problems is carried out to cover both SUA and SOA with low computational complexity. Second, the proposed algorithm performs power allocation. The simulation results show the relation between spectrum reuse and inter-tier interference, such that system SE, EE and the number of served users are maximized when both spectrum reuse and inter-tier interference management are performed together.

Waste Management in the Agri-Food Industry: The Conversion of Eggshells, Spent Coffee Grounds, and Brown Onion Skins into Carriers for Lipase Immobilization.

One of the major challenges in sustainable waste management in the agri-food industry following the “zero waste” model is the application of the circular economy strategy, including the development of innovative waste utilization techniques. The conversion of agri-food waste into carriers for the immobilization of enzymes is one such technique. Replacing chemical catalysts with immobilized enzymes (i.e., immobilized/heterogeneous biocatalysts) could help reduce the energy efficiency and environmental sustainability problems of existing chemically catalysed processes. On the other hand, the economics of the process strongly depend on the price of the immobilized enzyme. The conversion of agricultural and food wastes into low-cost enzyme carriers could lead to the development of immobilized enzymes with desirable operating characteristics and subsequently lower the price of immobilized enzymes for use in biocatalytic production. In this context, this review provides insight into the possibilities of reusing food industry wastes, namely, eggshells, coffee grounds, and brown onion skins, as carriers for lipase immobilization.

Review of energy modelling, energy efficiency models improvement and carbon dioxide emissions mitigation options for the cement industry in South Africa

The cement sector in South Africa contributes approximately 1 % to the South African national greenhouse gas inventory. In line with the country’s GDP increasing which will cause population to increase, the demand for housing, public and private structural infrastructures continues to increase. It is assumed that the demand for cement will also increase proportionally as well as its associated CO2 emission. The purpose of this study is to firstly; review previous energy modelling strategies in South Africa and specifically in the cement industry if any in order to examine the alignment of the cement industry’s strategies with that of the South African government since becoming part of the Paris agreement signatories. Previous studies of energy efficiency, modelling, and GHG emissions were analyzed and reviewed for the understanding of the readiness of South Africa’s cement industry to tackle her energy and global warming issues. South Africa is in a position to tackle the energy efficiency and GHG emissions problem through redesigning and consolidated critical data collection will, driven by the government and responsible stakeholders. Secondly; if any previous strategies are in place but in isolation, to examine the potential for long-term energy efficiency strategies and CO2 mitigation options for the cement sector in South Africa; as these two elements have a distinguishable link. Cement production is an energy-intensive process that consists of combustion-and process-related emissions. This study will employ-two modelling frameworks to examine strategies for reducing cement sector energy demand and associated CO2 emission for the period 2015 to 2050 (35 years) with 5-year intervals parallel to the Paris agreement. After reviewing energy models, the study will employ the low emissions analysis platform (LEAP) to model possible energy saving methods in the combustion process and other forms of energy supply in the context of South African cement sector. The existing reviewed methods and results will be compared and the LEAP will provide a second set of comparable results in order to influence policy and inform decision-making. For process-related emissions in the sector, the study will develop an excel-based model to examine possible strategies for reducing CO2 emission in the sector. The results will be examined in terms of cumulative energy savings, GHG emissions, and marginal abatement cost of carbon.

THEORETICAL AND ANALYTICAL STUDY OF THE INFLUENCE OF THE CRISIS ON THE ACTIVITIES OF THE ENTERPRISE

Objective. The objective of the present article is a theoretical-analytical study of the impact of the crisis on the company's activities in order to determine the key problems and areas of industrial enterprise crises. Methods. To achieve the objective, the synthesis method, the theoretical and analytical method, the analysis method, the horizontal analysis, the vertical analysis, the statistical verification method, the generalization method, the induction and deduction methods, the trend analysis, the methodical assessment of the probability of bankruptcy, and the taxonomic method were used. Results. A theoretical and analytical study of the features of modern crises made it possible to find out that the crises of recent years at the micro level are caused by external factors, in addition, the sphere of their occurrence is the sphere of health (the COVID-19 pandemic and lockdown) and war (military aggression of Russia against Ukraine). An algorithm for conducting an analytical study of the impact of crises on the activities of PJSC «ArcelorMittal Kryvyi Rih» was formed, as a result of which the probability of bankruptcy was estimated, profiles of integral indicators were built in the pre-crisis period (2018) and during the crisis (2020). To identify the signs of the crisis, we will compare the indicators of the economic environment at three levels: macro level, meso level, and micro level. The results of the analytical study made it possible to determine the key problems and areas of crises of the studied industrial enterprise: global lockdown due to the COVID-19 pandemic; the Russian invasion of Ukraine at the end of February 2022; with the beginning of the war, logistics became the main problem of the enterprise; high tariffs for freight transportation of JSC «Ukrzaliznytsia»; problems with the export of metallurgical products (both ore and finished products); reducing the supply of scrap metal to Ukrainian metallurgical enterprises; decrease in world prices for steel and iron ore, primarily due to the weakening of business activity in most regions of the world. Therefore, the key components of the anti-crisis plan for ArcelorMittal Kryvyi Rih PJSC should be solving the problems of energy efficiency, resource provision and logistics.

Methods for the Efficient Energy Management in a Smart Mini Greenhouse

To solve the problem of energy efficiency of modern enterprise it is necessary to reduce energy consumption. One of the possible ways is proposed in this research. A multi-level hierarchical system for energy efficiency management of the enterprise is designed, it is based on the modular principle providing rapid modernization. The novelty of the work is the development of new and improvement of the existing methods and models, in particular: 1) models for dynamic analysis of IT tools for data acquisition and processing (DAAP) in multilevel energy management systems, which are based on Petri nets; 2) method of synthesis of DAAP tools in energy efficiency management information systems (EEMIS) of the enterprise which provides a reduction in hardware and time costs from 10% to 40%; 3) method of conflict-free data exchange determining the minimum memory speed for the synthesis of real-time exchanges, it reduces the cost and energy consumption; 4) method of calculating the signal of postsynaptic excitation of neural elements decreases the processing time of technological data two or more times. The proposed methods, models and tools have been tested while implementing the EEMIS of the intelligent mini-greenhouse, as a result, energy efficiency has increased by 12%–25% (depending on season and peculiarities of growing plants).

Research Status and Future Development of Cooling Technologies for Green and Energy-Efficient Data Centers

Data centers are important infrastructure in China, with constantly increasing industry size, market revenues, and electricity consumption. The major cooling systems of data centers currently in operation in China are air-cooled, with a low energy utilization rate and great potentials for energy saving. Therefore, it is imperative to develop novel cooling technologies for green and energy-efficient data centers. The cooling technology needs to solve two problems. First, as equipment heat production increases, the cooling capacity of the cooling system needs to be improved to match heat production and transfer rates. Second, to address the low energy efficiency problem, green and energy-efficient cooling technologies with industrial application prospects need to be developed. This study reviews the development status of data center cooling methods and categorizes cooling technologies into air conditioner cooling, fresh air cooling, indirect cooling, direct single-phase liquid cooling, and direct two-phase liquid cooling. We analyze the development trends of cooling technologies and suggest that green and high-efficient data centers should focus on the improvement in the efficiency of cooling systems, optimizations of hot and cold fluid channels, applications of new liquid cooling materials, and promotion of heat recovery systems. Furthermore, we propose suggestions for the stable and orderly development of the data center industry from the aspects of optimizing top-level design, developing key technologies, formulating scientific standards, improving industrial layout, and focusing on energy structure.

Color sensor application in high-temperature spectral ratio pyrometer

Contactless thermal control tools play an important role in solving the high-temperature technological processes improving energy efficiency problems. In order to create such controls, the authors analyzed the developing possibility of spectral ratio high-temperature pyrometer using a multispectral radiation receiver (color sensor) TCS34725. In the paper this receiver application coefficients are determined, signals ratio graphs in different spectral intervals on temperature are given for two applications: without additional filtration of the control object radiation infrared component and using an opaque in the infrared spectrum part external filter.

AI-Driven Energy-Efficient Content Task Offloading in Cloud-Edge-End Cooperation Networks

To tackle a challenging energy efficiency problem caused by the growing mobile Internet traffic, this paper proposes a deep reinforcement learning (DRL)-based green content task offloading scheme in cloud-edge-end cooperation networks. Specifically, we formulate the problem as a power minimization model, where requests arriving at a node for the same content can be aggregated in its queue and in-network caching is widely deployed in heterogeneous environments. A novel DRL algorithm is designed to minimize the power consumption by making collaborative caching and task offloading decisions in each slot on the basis of content request information in previous slots and current network state. Numerical results show that our proposed content task offloading model achieves better power efficiency than the existing popular counterparts in cloud-edge-end collaboration networks, and fast converges to the stable state.

Energy efficient management for distributed state estimation under DoS attacks

AbstractIn this article, we consider the issue of energy efficient management for distributed state estimation over unknown packet‐dropping communication channels which are exposed to Denial‐of‐Service (DoS) attacks. After a packet is transmitted, the sensor determines whether to retransmit and the retransmission power levels based on the feedback information from the receiving sensor. We formulate the energy efficient management problem as a modified Markov decision problem (MMDP), and proposed an algorithm to seek a retransmission power schedule that achieves optimal tradeoff between energy consumption and communication rate for given channel noise power. In the case of unknown channel state, we design a statistical learning method to estimate channel noise power. Besides, inspired by the hypothesis testing, we design an anomaly detector to guarantee the instantaneity of channel noise power estimation and efficiency of energy management. Furthermore, we derive the optimal gain for each estimator, and provide a sufficient condition for the stability of estimator under the energy management. Finally, we verify the main results by numerical examples.

Review of the basic mechanisms of energy efficiency management and emissions control from ships

Increasing relevance of the problem of energy conservation and use of alternativesources of energy in connection with global and local resource crises led to the formation of adeveloped system of international standards in the field of energy management, which is aimed atregulating and disclosing the content of the principles of energy efficient processes and development.Rational policy in enterprises of various industries and the implementation of energy-savingmeasures, particularly in the maritime transport. The dynamics of implementation of projects aimedat increasing the efficiency of energy use is growing steadily at different levels and in different sectorsof industry. It is widespread in the fields of design, modernization and reconstruction of energyefficient buildings and structures, construction of industrial infrastructure elements, technologicalproduction processes. Implementation of such projects is a priority line of activity for enterprises andcompanies of various types of economic activity. Accordingly, the leading sectors of industry develop strategies to improve environmental safety and energy efficiency - ship navigation is no exception.Indeed, the process of increasing energy efficiency is achieved by reducing fuel consumption, whichwithout exception leads to a reduction in the amount of waste products discharged into theatmosphere. Therefore, the problems of energy efficiency in order to increase requirements forenvironmental safety of transport and increasing responsibility of shipowners become the centralobject of research of current theory and practice of operation of maritime transport means. Anotherurgent issue is the improvement of universal principles of energy efficiency within the framework ofindividual ship-owning companies and the development of tools for economic analysis of energyefficiency of the own fleet, search for new ways to form professional competencies of shipcrewmembers in the field of energy conservation.

Implementation of "Intellectual networks" – direction of ensuring the energy efficiency of the national economy of Ukraine

At the present stage of development of the world economy and almost all countries’ national economies, the problem of energy saving and energy efficiency rises. In developed countries, the solution to this problem depends not only on reducing energy consumption but also on the introduction of new innovative processes in power supply systems and energy systems. In particular, there is a growing interest in the modernization of energy systems in the world in recent years based on a new concept called Smart Grid ("intelligent power system"). The problem of energy efficiency is especially relevant for Ukraine, which has the highest value of energy intensity of gross domestic product, and the country's energy system is characterized by extremely high losses of electricity in the grid. The largest consumers of electricity in Ukraine are large industrial enterprises, where the high energy intensity of production is caused by the depreciation of fixed assets; lack of incentives to implement energy efficiency measures and of a systematic approach to energy consumption; lack of financial resources for the implementation of energy efficiency measures. Issues of identifying the problems of energy efficiency of the economy and ways to solve them are set out in the scientific works of such researchers as S. M. Baliuta, O. S. Bykonia, A. Yu. Danilkova, Ya. V. Krutohorskyi, O. O. Liakhova, Yu. T. Matvieieva, H. H. Pivniak, S. V. Sapozhnikov, O. V. Fedirets, V. O. Shvedun. Without diminishing the results of the previous research, it should be noted that a number of problematic issues on this topic are still studied insufficiently, which determines the relevance of the research topic. The aim of this research is to assess energy efficiency as a factor of the competitiveness of Ukraine's industrial products, justify the main reasons for the high energy intensity of GDP in Ukraine, and the necessity of innovative direction for the future development of energy through the implementation of "smart grids". Analysis of the energy sector’s current state and development has shown that the problems in the power industry today can not be solved only by extensive capacity-building of grids and increasing the number of electrical equipment. A new direction in the future development of energy is the implementation of smart grids ("Smart Grid"). The domestic national economy has problems with energy efficiency and energy saving. The solution to these problems lies in the field of implementing energy management and audit, studying and using foreign experience in the development of intelligent energy.

PECULIARITIES OF DETERMINATION OF ECONOMIC INDICATORS OF EXECUTIBILITY OF IMPLEMENTATION OF MEASURES TO INCREASE ENERGY EFFICIENCY

The work is devoted to the analysis of the peculiarities of determining the economic indicators of the feasibility of implementing measures to improve energy efficiency. In contrast to energy saving, which aims to reduce the consumption of energy resources, energy efficiency is a matter of appropriate energy consumption. That is, the use of less energy for the same level of supply of buildings or industries. The topic is relevant, because now energy prices are rising every year. At the same time, the International Energy Agency estimates an increase in total resource needs by 25% by 2040.
 To achieve this goal, standard measures aimed at improving the energy efficiency of buildings, the effects of the implementation of these measures, a number of economic indicators, including PP, ARR, NPV, PI, BCR, SIR, MARR, IRR and DPP, were analyzed, evaluated and grouped. The focus was on the dynamic group of indicators due to the fact that their calculation involves the use of a discounting procedure. The general scheme of all dynamic indicators is the same and is based on forecasting costs and revenues for the planning period. The indicators of this group take into account changes in the value of money over time, which is neglected by the indicators of the static group. The most popular indicators are the calculation of net present value (NPV) and the definition of profitability index (PI). This work can be used to solve the problem of low energy efficiency and insufficient funding for the modernization of the building

Protruder Optimization-Based Routing Protocol for Energy-Efficient Routing in Wireless Sensor Networks

WSNs find valuable application in monitoring purposes, but they suffer from energy-efficiency issues that affect the network lifetime. The energy-efficiency problem is addressed using the cluster head (CH) formation, data aggregation, and routing techniques. Therefore, an energy-aware routing algorithm named protruder optimization algorithm is proposed, which boosts the network lifetime through finding the optimal routing path. The proposed protruder optimization is developed with the hybridization of the wave propagator characteristics and weed characteristics in such a way that the global optimal convergence is boosted while selecting the optimal routing path. Moreover, the communication in the network through the optimal path is progressed through the optimal CHs selection based on fractional artificial bee colony optimization (FABC), and in turn, the energy minimization problem is aided with data aggregation process using sliding window approach that avoids retransmission of the data. The results of the proposed method are compared with the existing methods on the basis of its performance measures, such as energy, alive nodes, and throughput.

Analysis of the energy intensity of the galvanic complex of machine-building production

Considered are the problems of energy efficiency of products of a large machine-building enterprise associated with the impossibility of regulating steam consumption and the seasonality of changes in energy consumption. The analysis of the consumption of energy resources by a typical large machine-building enterprise of small-scale and unit-type production is carried out. The reasons for the additional costs of the enterprise with centralized steam supply associated with condensate losses have been identified. It has been established that the most power-consuming is the galvanic complex. The reasons for the increased energy consumption of the galvanic complex are considered. The energy balance of the technological section - the galvanic complex, was compiled, reflecting the calculated thermal loads when heating the electrolyte and maintaining the thermal regime, depending on the operating time of the baths and the mass of the processed parts, taking into account the peculiarities of the operation of technological equipment. The most effective methods of energy supply have been determined depending on the load factor and the fuel and energy resource used for two typical baths of the galvanic complex. Three options of technological power supply are considered, depending on the load factor of the equipment and the technical possibility of its parallel-sequential connection. It was found that with all three schemes for connecting to alternative sources of heat supply, there is an increase in the energy efficiency of the use of fuel and energy resources, as well as a decrease in the cost of energy supply of technological processes in comparison with centralized steam supply. It was revealed that when organizing the operation of technological equipment in a parallel-sequential scheme, uniform efficient loading of steam generators and high energy efficiency of galvanic production are ensured. For the power supply of the galvanic complex, a combined scheme of heat supply by local heat sources from the power grid and gas steam generators is proposed, taking into account their fullest load.

Energy-efficient opportunistic multi-carrier NOMA-based resource allocation for beyond 5G (B5G) networks

The interplay between the non-orthogonal multiple access (NOMA) and the opportunistic cognitive radio (CR)-based orthogonal frequency multiple access (OFDMA) has been recently realized as a promising paradigm to support the unprecedented massive connectivity demands of future beyond fifth-generation (B5G) wireless communication systems. In such systems, which are called multi-carrier NOMA CR-based systems, each licensed band reserved for primary users can be opportunistically utilized based on power-domain NOMA to serve a group of secondary users simultaneously. An important challenge in this domain is how to provide energy-efficient resource allocation techniques that attempt to strike a balance between the total throughput (i.e., the achieved sum-rate) and the power required to achieve that rate while satisfying network QoS demands and being aware of the unique characteristics of the CR operating environment. In this paper, we propose an energy-efficient resource allocation technique for multi-carrier NOMA CR-based systems, which aims at maximizing the overall energy efficiency (EE) of the system under a set of CR and NOMA constraints. The EE maximization problem is shown to be a fractional non-convex optimization, which is, in general, hard to optimize. To deal with the fractional and the non-convexity nature of the formulated EE maximization problem, we exploit the Dinkelbach’s algorithm to transfer the EE problem to a parameterized optimization problem. Then we use an iterative optimization approach to obtain the solution for the EE maximization problem. Simulation results reveal that this EE maximization-based resource allocation technique outperforms the existing resource allocation techniques in terms of the overall EE of the system while striking a good balance between the sum-rate and the transmit power consumption.

A refined consumer behavior model for energy systems: Application to the pricing and energy-efficiency problems

Sum-utility maximization is an important problem in the optimization of energy systems. A conventional assumption in addressing this problem is that the utility to be maximized is concave. But for some key applications, such an assumption is not reasonable and does not reflect well the actual behavior of the consumer. To address this issue, the authors pose and address a more general optimization problem, namely by assuming the consumer’s utility to be sigmoidal and in a given class of functions. The considered class of functions is attractive for at least two reasons. First, the classical NP-hardness issue associated with sum-utility maximization is circumvented. Second, the considered class of functions encompasses well-known performance metrics used to analyze problems of pricing and energy-efficiency. This allows one to design a new and optimal inclining block rate (IBR) pricing policy which also has the virtue of flattening the power consumption and reducing the peak power. We also show how to maximize the energy-efficiency using a low-complexity algorithm. When compared to existing policies, simulations fully support the benefit of using the proposed approach.

Optimum energy harvesting model for bidirectional cognitive radio networks

Wireless devices’ energy efficiency and spectrum shortage problem has become a key concern worldwide as the number of wireless devices increases at an unparalleled speed. Wireless energy harvesting technique from traditional radio frequency signals is suitable for extending mobile devices’ battery life. This paper investigates a cognitive radio network model where primary users have their specific licensed band, and secondary users equipped with necessary hardware required for energy harvesting can use the licensed band of the primary user by smart sensing capability. Analytical expressions for considered network metrics, namely data rate, outage probability, and energy efficiency, are derived for uplink and downlink scenarios. In addition, optimal transmission power and energy harvesting power are derived for maximum energy efficiency in downlink and uplink scenarios. Numerical results show that outage probability improves high transmission power in the downlink scenario and high harvested power in the uplink scenario. Finally, the result shows that energy efficiency improves using optimum transmission power and energy harvesting power for downlink and uplink scenarios.

Hybrid Energy Resource Allocation for Simultaneous Wireless Information and Power Transfer for Green Communications

In this paper, we consider a simultaneous wireless information and hybrid power transfer system for cellular green networks. The small cells (SCs) use hybrid power of on-grid power and green energy harvested from environments, whilst the user equipments (UEs) are enabled by a power-splitting receiver. A quality-of-service (QoS) constrained problem is designed to maximize energy efficiency (EE) considering joint strategies of hybrid power allocation, resource block assignment, and power splitting ratio adjustment. We propose a joint wireless charging and hybrid power based resource allocation (J-WHA) algorithm by transforming the non-concave EE problem into a solvable one based on proved concavity property and Karush-Kuhn-Tucker (KKT) conditions. Moreover, a separated wireless charging and hybrid power based resource allocation (S-WHA) algorithm is proposed to obtain sub-optimal solutions with lower computational complexity. Simulation results demonstrate the convergence of both proposed algorithms in relation to transmission power utilization, wireless charging amount, and system EE. It is shown that the proposed J-WHA and S-WHA algorithms outperform existing schemes in terms of EE performance.

Методологія системного аналізу щодо дослідження проблем енергоефективності в Україні

The results of the research on the application of a systematic approach to solving energy efficiency problems in Ukraine are presented. The reasons for restraining the level of energy efficiency are highlighted, among which are the hollowing: ineffective policy of incentives to reduce energy consumption; lack of investments and conditions for their attraction; inefficient tariff and price policy in the energy sector of the economy, non-compliance with regulations, programs of various levels and measures. The need to increase the level of energy efficiency in Ukraine is substantiated and a system analysis is proposed to solve this problem. The methodology of systems analysis is implemented using a systems approach, in particular, to the interpretation of the process of energy efficiency development as an open, nonlinear, complex system. As an element of systems analysis, the study uses a multilevel approach, which provides an opportunity to consider the object of study at different hierarchical levels: the international community, state, industry, region and individual. It is noted that in order to successfully develop the progress of energy efficiency in Ukraine, it is necessary to take into account global trends and recent large-scale changes in this area. Examples of progress realization at the state level are given, in particular, implementation of a large number of legal acts, a number of stimulating measures for energy saving, etc. The importance of the sectoral level to increase energy efficiency in Ukraine is indicated. The importance of energy efficiency potential at the regional level is emphasized, which can give a significant boost to its entire economy and significantly improve the lives of the population. The importance of optimizing the process of energy efficiency at the level of various institutions is presented; as one of the options for solving this problem, it is proposed to popularize its benefits both among the population and the individual. The multilevel approach to energy efficiency in Ukraine proposed in the study presupposes an integrated combination of efforts at different levels and a synergistic effect of solving the problem. Key words: energy efficiency, system, multilevel approach