Reinforcement Learning Model for Energy System Management to Ensure Energy Efficiency and Comfort in Buildings

This article focuses on the challenges ofmodeling energy supply systems for buildings,encompassing both methods and tools for simulating thermal regimes and engineering systems within buildings.Enhancing the comfort of living or working in buildings often necessitates increased consumption of energy and material,such as for thermal upgrades,which consequently incurs additional economic costs.It is crucial to acknowledge that such improvements do not always lead to a decrease in total pollutant emissions,considering emissions across all stages of production and usage of energy and materials aimed at boosting energy efficiency and comfort in buildings.In addition,it explores the methods and mechanisms for modeling the operating modes of electric boilers used to collectively improve energy efficiency and indoor climatic conditions.Using the developed mathematical models,the study examines the dynamic states of building energy supply systems and provides recommendations for improving their efficiency.These dynamic models are executed in software environments such as MATLAB/Simscape and Python,where the component detailing schemes for various types of controllers are demonstrated.Additionally,controllers based on reinforcement learning(RL)displayed more adaptive load level management.These RL-based controllers can lower instantaneous power usage by up to 35%,reduce absolute deviations from a comfortable temperature nearly by half,and cut down energy consumption by approximately 1%while maintaining comfort.When the energy source produces a constant energy amount,the RL-based heat controllermore effectively maintains the temperature within the set range,preventing overheating.In conclusion,the introduced energydynamic building model and its software implementation offer a versatile tool for researchers,enabling the simulation of various energy supply systems to achieve optimal energy efficiency and indoor climate control in buildings.

Optimal Size for Maximal Energy Efficiency in Information Processing of Biological Systems Due to Bistability

Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biological unit in response to pulsatile inputs, and its spontaneous excitation rate due to noise perturbation. Then we analytically calculate the mutual information, energy cost, and energy efficiency of an array of these bistable units. We find that the optimal number of units could maximize this array＇s energy efficiency in encoding pulse inputs, which depends on the fixed energy cost. We conclude that demand for energy efficiency in biological systems may strongly influence the size of these systems under the pressure of natural selection.

Energy Efficiency in Smart Grid: A Prospective Study on Energy Management Systems

The term Smart Grid has become a term to represent the benefits of a smart and sophisticated electrical grid, which can meet various social expectations related to sustainability and energy efficiency. The Smart Grid promises to enable a better power management for energy utilities and consumers, to provide the ability to integrate the power grid, to support the development of micro grids, and to involve citizens in energy management with higher levels of responsibility. However, this context comes with potential pitfalls, such as vulnerabilities to cyber-security and privacy risks. In this article, a prospective study about energy management, and exploring critical issues of modeling of energy management systems in a context Smart. Grid is presented along with background of energy management systems. An analysis of the demand response condition is also presented. Finally, the advantages and disadvantages of the implementation of energy management systems, and a comparison with the Brazilian electricity system are discussed.

An Advanced Energy Management System

A brief outline of Energy Management System (EMS) in China is given and OPEN-2000 EMS, combined with the novel technique of computer science, is introduced. The system has been developed by Power System Control Division of NARI and put into operation in the middle of 1998.

Managing System Losses to Improve Energy Efficiency within the Electricity Company of Ghana (ECG) Limited

The inability to achieve the target of universal access to electricity is influenced by several factors including funding limitations, the use of obsolete equipment, power theft, and system losses confronting the electricity distribution services of the Electricity Company of Ghana Limited (ECG). The study assessed the components of system losses within the ECG by determining and computing the percentage of system losses within ECG, examining the causes of both commercial and technical losses in ECG, and determining ways to improve energy efficiency by reducing system losses in the most cost-efficient manner. The study adopted deductive reasoning and a quantitative approach to guide data collection and analysis of the research output. A sample of 345 technical and non-technical staff of ECG in the Greater Accra Metropolis was selected from a population of 2500. Purposive, simple random, and cluster sampling techniques were used in identifying and accessing respondents for the study. Descriptive statistics were applied to measure central tendency and degrees of dispersion and the Relative Importance Index (RII) to predict criterion and predictor variables. The impact of low voltage network losses can adversely contribute to technical losses (20%) and reduce energy efficiency in power or electricity distribution companies. Non-technical losses are mainly caused by illegal connections, meter problems, and billing problems. Each of the non-technical losses contributes a maximum of 10% to system losses. Contributors to system losses at ECG are ranked first for power theft and least for lack of incentives. System losses at ECG include metering inaccuracies, bad workmanship, unmetered supply, and lengthy distribution lines, each recording a mean value of above 3.5. Measures to improve monitoring of the networks and systems at ECG and discourage power theft should include an extensive quantification, patrolling, and inspection of the entire network to assess the extent of the network and conditions relevant for the placement of systematically planned maintenance programmes.

Temperature Effects on Information Capacity and Energy Efficiency of Hodgkin-Huxley Neuron

Recent experimental and theoretical studies show that energy efficiency, which measures the amount of infor- mation processed by a neuron with per unit of energy consumption, plays an important role in the evolution of neural systems. Here we calculate the information rates and energy efficieneies of the Hodgkin-Huxley （HH） neuron model at different temperatures in a noisy environment. It is found that both the information rate and energy efficiency are maximized by certain temperatures. Though the information rate and energy efficiency cannot be maximized simultaneously, the neuron holds a high information processing capacity at the tempera- ture corresponding to the maximal energy efficiency. Our results support the idea that the energy efficiency is a selective pressure that influences the evolution of nervous systems.

Development of Smart Micro-grid Energy Efficiency Technologies on Workplace Level

The objective of this paper was to understand the increasing importance of building energy consumption, an overview of the comfort needs of the occupants is first deemed necessary in new control strategy for automatic control and to present facts that characterize the energy consumption, most particularly at the workplaces level with new technology strategies. The study’s methodology applies functional and hierarchical separation. The contributions of this paper are static and dynamic models of individual users in a proposed existing building to create an office environment. To fulfill the purpose of the study and the research the following research questions will be investigated and analyzed from an architect’s perspective: (1) Are there appropriate technologies for improving energy efficiency in new buildings from the point of view the micro-grid, control and evaluation process in strategy? (2) Which sensor technology can determine the zone that needs or needs not to be considered the comfort?

Enhancing 5G energy efficiency through digital twin networks:A comprehensive review

In the era of 5G,seamless mobility handovers are critical in densely populated regions like Malaysia to mitigate disruptions and inefficiencies.5G networks offer unprecedented data speeds and reliability,essential for advancing mobile communication and Internet of Things applications.However,ensuring continuous connectivity and service during mobility remains challenging,especially in urban settings.Digital twin technology pre-sents a promising solution to enhance 5G handover mechanisms.A digital twin network(DTN)mirroring Malaysia's 5G infrastructure is proposed,utilising real-time data and user behaviour insights to optimise energy consumption during handovers.The focus is on energy-efficient protocols and algorithms,reviewed through a systematic literature review.The DTN aims to enhance mobility handover efficiency through predictive handovers and adaptive resource allocation,bolstered by sustainable practices such as edge computing.The potential of DTNs to optimise 5G handover processes is explored,starting with the foundational concepts of 5G mobility and digital twins,highlighting the need for improved strategies in high-mobility scenarios.Methodologies leveraging digital twins to predict network conditions,simulate handover scenarios,and proactively manage decisions are examined,reducing latency and packet loss.Case studies demonstrate how digital twins adapt dynamically to network changes and user mobility,thereby improving quality of service and user experience.Malaysia's specific 5G mobility challenges are addressed with a tailored DTN emphasising energy efficiency,evaluated through practical applications.Evaluation criteria assess effectiveness with in-depth analysis of methods,performance metrics,limitations,and recommendations for future research.Challenges and future directions including scalability,security,and real-time data processing,are discussed,aiming to integrate digital twin technology with 5G networks for enhanced connectivity.This abstract provides a roadmap for leveraging digital twins to optimise 5G network performance sustainably,guiding future research and implementation strategies.

A novel virtual machine deployment algorithm with energy efficiency in cloud computing

In order to improve the energy efficiency of large-scale data centers, a virtual machine(VM) deployment algorithm called three-threshold energy saving algorithm(TESA), which is based on the linear relation between the energy consumption and(processor) resource utilization, is proposed. In TESA, according to load, hosts in data centers are divided into four classes, that is,host with light load, host with proper load, host with middle load and host with heavy load. By defining TESA, VMs on lightly loaded host or VMs on heavily loaded host are migrated to another host with proper load; VMs on properly loaded host or VMs on middling loaded host are kept constant. Then, based on the TESA, five kinds of VM selection policies(minimization of migrations policy based on TESA(MIMT), maximization of migrations policy based on TESA(MAMT), highest potential growth policy based on TESA(HPGT), lowest potential growth policy based on TESA(LPGT) and random choice policy based on TESA(RCT)) are presented, and MIMT is chosen as the representative policy through experimental comparison. Finally, five research directions are put forward on future energy management. The results of simulation indicate that, as compared with single threshold(ST) algorithm and minimization of migrations(MM) algorithm, MIMT significantly improves the energy efficiency in data centers.

Developing and Applying a Ship Operation Energy Efficiency Evaluation Index Using SEEMP: a Case Study of South Korea

The CO2 emission reduction policy of the International Maritime Organization(IMO)recommends that the operation of ships,managed by maritime transport companies,should be energy-efficient.An evaluation method that can determine how successfully a ship implements the energy efficiency plan is proposed in this study.To develop this method,the measures required for energy-efficient ship operations according to the Ship Energy Efficiency Management Plan(SEEMP)operational guidelines were selected.The weights of the selected measures,which indicate how they contribute to the energy-efficient operation of a ship,were derived using a survey based on the analytic hierarchy process(AHP)method.Consequently,using these measures and their weights,a new evaluation method was proposed.This evaluation method was applied to shipping companies in South Korea,and their ship operation energy efficiency indices were derived and compared.This evaluation method will be useful to the government and shipping companies in assessing the energy efficiency of ship operations.

Improving the Energy Efficiency of Cyclone Dust Collectors for Wood Product Factories

Dust collection systems represent a significant portion of a wood product manufacturer’s total electricity use. The system fan works against the static pressure of the entire system—the blast gates, the ductwork, and the upstream or downstream cyclone and/or baghouse. A poor system design (e.g., sharp elbows or undersized ductwork) increases the total amount of static pressure in the system, the fan’s performance curve shifts, increasing the total brake horsepower required by the fan (up to the maximum point on the curve). Additionally, system designers may oversize a dust collection system to ensure adequate dust capture and transport, either to accommodate system expansion or simply to be conservative. Since theoretical fan energy use increases with its velocity cubed, this can be an expensive safety net. This paper presents a comprehensive literature review about industrial cyclone dust collectors energy saving in relation to management, technologies, and policies. Energy-saving technologies like high-efficiency motors (HEMs), variable-speed drives (VSDs), leak detection, and pressure drop reduction have all been examined. Based on energy saving technologies results, it has been found that in the industrial sectors, a sizeable amount of electric energy, and utility bill can be saved using these technologies. Finally, various energy-saving policies were reviewed.

Government regulation practices and issues on building energy efficiency in China

This paper analyzes the government control of building energy efficiency in China from the aspects of policies and regulations, technical standards, pilot demonstration projects and economic means, and expounds the characteristics and problems of government regulation practice in China. It is found that the government regulation of building energy conservation in our country has some problems, such as imperfect system, weak incentive policy, imperfect management system, and the lack of public participation. Through the deep analysis of the existing problems, it is pointed out that the fundamental reason for the poor operation of China's building energy efficiency market lies in the lack of understanding of the building energy efficiency market, the lack of government administrative functions and the weak consciousness of the main body.

A PARAMETRIC STUDY OF THE ENERGY EFFICIENCY OF EXISTING AIR-CONDITIONED BUILDINGS IN KUWAIT

In Kuwait air-conditioning systems consume approximately 70%of the grid energy during the long summer months.In this paper,various practical approaches are investigated to enhance the energy efficiency and decrease the energy consumption of five existing air-conditioned(AC)buildings in Kuwait City.The process of energy management in air-conditioned buildings in Kuwait is overwhelming due to high energy consumption in the building sector.This study proposed an optimization technique for the proper energy management of installed AC systems to target energy-efficient buildings.In this study the aim is to explore the effect of different operating parameters,both theoretically and experimentally,and to contribute to the reduction of AC energy consumption.Consequently,the relationship between the thermal load in the air-conditioned buildings and the actual electrical energy consumption is determined,and remedial measures,along with different recom-mendations for energy saving,are presented.The actual thermal loads of each selected building were calculated and compared with the installed cooling capacity of the AC systems.From the results obtained it was concluded that,by implement-ing the suggested remedial measures,the predicted load in the selected buildings could be decreased significantly from the existing installed capacity of the cooling systems.Most of the remedial measures suggested for energy management lead to a reduction in power consumption and increased energy efficiency at different levels based on the specifications of the buildings considered and the AC systems installed,resulting in improved in economy,a reduced carbon footprint,and a cleaner environment.

A Review of Energy Efficiency in Data Processing Centers

This article explores, through a case study, measures of energy efficiency in data processing centers. An analysis of this case demonstrates how the design criteria could improve the rate of consumption in IT centers, which is currently the second most contaminating industry on the planet, and is the responsible for 2% of CO2 emissions, surpassed only by the aeronautical industry. The present and future situation of IT center energy consumption and associated environmental effects is analyzed, and also looks at how state-of-the-art technology, correctly implemented, could ensure significant rationalization of data processing center energy consumption. The article will examine optimization techniques, specific problems and case studies.

EA-RDSP: Energy Aware Rapidly Deployable Wireless Ad hoc System for Post Disaster Management

In post disaster scenarios such as war zones floods and earthquakes,the cellular communication infrastructure can be lost or severely damaged.In such emergency situations,remaining in contact with other rescue response teams in order to provide inputs for both headquarters and disaster survivors becomes very necessary.Therefore,in this research work,a design,implementation and evaluation of energy aware rapidly deployable system named EA-RDSP is proposed.The proposed research work assists the early rescue workers and victims to transmit their location information towards the remotely located servers.In EA-RDSP,two algorithms are proposed i.e.,Hop count Assignment(HCA)algorithm and Maximum Neighbor Selection(MNS)algorithm.The EA-RDSP contains three types of nodes;the client node sends information about casualty in the disaster area to the server,the relay nodes transmit this information from client node to server nodes via multi-hop transmission,the server node receives messages sent by client node to alert rescue teams.The EAM-RDSP contains three types of nodes;the client node sends information about casualty in the disaster area to the server,the relay nodes transmit this information from client node to server nodes via multi-hop transmission,the server node receives messages sent by client node to alert rescue teams.The proposed EA-RDSP scheme is simulated using NS2 simulator and its performance is compared with existing scheme in terms of end-to-end delay,message delivery ratio,network overhead and energy consumption.

Joint Energy-Efficient Power Allocation and Beamforming Design for mm Wave-NOMA System with Imperfect CSI

The joint power allocation(PA)and beamforming(BF)design problem is studied to maximize the energy efficiency of a two-user downlink millimeter-wave system with non-orthogonal multiple access under imperfect channel state information(CSI).By means of block coordinate descent,convex-concave procedure,and successive convex approximate,we propose a suboptimal joint PA and BF design scheme to address this non-convex problem.Simulation results verify that the proposed joint PA and BF design scheme is more effective when compared to some existing schemes.

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 realtime 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).

Adaptive Energy-Efficient Power Allocation for DAS with Imperfect Channel State Information and Antenna Selection

Considering that perfect channel state information(CSI) is difficult to obtain in practice,energy efficiency(EE) for distributed antenna systems(DAS) based on imperfect CSI and antennas selection is investigated in Rayleigh fading channel.A novel EE that is defined as the average transmission rate divided by the total consumed power is introduced.In accordance with this definition,an adaptive power allocation(PA) scheme for DAS is proposed to maximize the EE under the maximum transmit power constraint.The solution of PA in the constrained EE optimization does exist and is unique.A practical iterative algorithm with Newton method is presented to obtain the solution of PA.The proposed scheme includes the one under perfect CSI as a special case,and it only needs large scale and statistical information.As a result,the scheme has low overhead and good robustness.The theoretical EE is also derived for performance evaluation,and simulation result shows the validity of the theoretical analysis.Moreover,EE can be enhanced by decreasing the estimation error and/or path loss exponents.

Initiative Optimization Operation Strategy and Multi-objective Energy Management Method for Combined Cooling Heating and Power

This paper proposed an initiative optimization operation strategy and multi-objective energy management method for combined cooling heating and power U+0028 CCHP U+0029 with storage systems. Initially, the initiative optimization operation strategy of CCHP system in the cooling season, the heating season and the transition season was formulated. The energy management of CCHP system was optimized by the multi-objective optimization model with maximum daily energy efficiency, minimum daily carbon emissions and minimum daily operation cost based on the proposed initiative optimization operation strategy. Furthermore, the pareto optimal solution set was solved by using the niche particle swarm multi-objective optimization algorithm. Ultimately, the most satisfactory energy management scheme was obtained by using the technique for order preference by similarity to ideal solution U+0028 TOPSIS U+0029 method. A case study of CCHP system used in a hospital in the north of China validated the effectiveness of this method. The results showed that the satisfactory energy management scheme of CCHP system was obtained based on this initiative optimization operation strategy and multi-objective energy management method. The CCHP system has achieved better energy efficiency, environmental protection and economic benefits. © 2014 Chinese Association of Automation.

Digital twin intelligent system for industrial internet of things-based big data management and analysis in cloud environments

This work surveys and illustrates multiple open challenges in the field of industrial Internet of Things(IoT)-based big data management and analysis in cloud environments.Challenges arising from the fields of machine learning in cloud infrastructures,artificial intelligence techniques for big data analytics in cloud environments,and federated learning cloud systems are elucidated.Additionally,reinforcement learning,which is a novel technique that allows large cloud-based data centers,to allocate more energy-efficient resources is examined.Moreover,we propose an architecture that attempts to combine the features offered by several cloud providers to achieve an energy-efficient industrial IoT-based big data management framework(EEIBDM)established outside of every user in the cloud.IoT data can be integrated with techniques such as reinforcement and federated learning to achieve a digital twin scenario for the virtual representation of industrial IoT-based big data of machines and room tem-peratures.Furthermore,we propose an algorithm for determining the energy consumption of the infrastructure by evaluating the EEIBDM framework.Finally,future directions for the expansion of this research are discussed.