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.

Design and Implementation of Enterprise Office Automation System Based on Web Service Framework & Data Mining Techniques

The advancement of science and technology has introduced the concept of big data, which has significantly transformed the business management environment of enterprises. Currently, most administrative tasks in companies heavily rely on human resources, with skilled management staff using their expertise to oversee business operations. However, this approach is susceptible to human subjective biases. The method assists managers in formulating efficient strategies for implementing management measures and enhancing the effectiveness of production, sales, financial, and people organization structure management. This ultimately leads to a more evidence-based approach to corporate management. This technique expands the utilization of Web services from a strategy focused on integrating services to a comprehensive framework for Service-Oriented Computing (SOC). The primary focus is implementing WS-session to manage sessions in general Web services applications, defining a bidirectional entire duplex interface for communication in Web services, and developing the Web Services Initiation Protocol, presenting WIP, a thorough multimedia and voice communication framework constructed using Web services and Service-Oriented Architecture (SOA). The office automation management system, created utilizing ASP.net and SQL Server technology, encompasses the evaluation of viability, analysis of needs, and system design. Office automation refers to using equipment with computing capabilities to carry out various office tasks and utilize associated tools and applications. Office automation uses computer-based systems to collect, organize, and modify visual and auditory information to enhance business energy efficiency and time management. Office automation refers to auto-mating essential tasks employees perform, including identification, automatic appointment reminders, and automatic power management for personal computers. The employee image is obtained through the utilization of the Java media framework. Attendance data for all employees are collected and methodically examined. The database enables the retrieval of these records monthly or weekly. An office automation system offers organizations enhanced features for managing office information, significantly improving office efficiency and quality. Moreover, it improves office administration and decision-making procedures by automating and strengthening the scientific elements of office functions. The ongoing progress of organizational information technology has led to a strong focus on sharing information resources in scientific research initiatives. Conventional firms exhibit intricate company processes, inadequate managerial efficacy, and unnecessarily elevated operational expenses, resulting in diminished competitiveness. Thus, using an ERP management system is the optimal decision for organizations to restore their crucial competitive advantage. This technology enhances their operational methods, streamlines their operations, and enhances transparency in their operational approaches. The system comprises six modules: buy plan, purchase order, purchase contract, purchase document inquiry, purchase to order, and purchase return. These modules effectively meet the operational needs of enterprises.

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 Energy-Efficient Mobile-Controlled Vertical Handover Management for Real Time Services

Multiple wireless access technology has been embedded into a single mobile device as a fundamental feature, aiming to give end users ubiquitous access at any time. To allow the users to enjoy the ubiquitous connectivity, the mobile device has to consume higher energy for the simultaneous activation of multiple wireless interface and the continuous connectivity. In addition, a seamless vertical handover between the access technologies is a mandatory requirement to insure the quality, reliability and continuity of real time services. In this paper, the continuity of real time services as well as energy saving for mobile devices has been taken into account. The conceptual idea is that whenever traffic rate is lower than a threshold it will be smoothly handed over to a low energy consumption technology, i.e., Bluetooth. When the traffic exceeds the limitation of Bluetooth bandwidth, it will be handed over to a wider bandwidth technology, i.e., Wi-Fi. In the considered scenarios, the technologies are not interconnected;hence, the vertical handover management must be fully controlled by the mobile devices. The performance of the system including energy saving and maintaining the continuity of real time services has been evaluated by direct measurements in a real testbed.

Respecting Each Other and Being Loyal to ZTE Career Providing Refined Service and Focusing on Customers' Requirements Working Hard to Create Famous ZTE Brand Improving ZTE Efficiency with Scientific Management

ZTE Corporation is China’s largest listedtelecommunications equipment provider spe-cialized in offering a full range of tailor-madesolutions for customers in high-,middle-andlow-end markets.

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.

A unified model for diagnosing energy usage abnormalities in regional integrated energy service systems

An integrated energy service company in an industrial park or commercial building is responsible for managing all energy sources in their local region, including electricity, water, gas, heating, and cooling. To reduce energy wastage and increase energy utilization, it is necessary to perform efficiency analyses and diagnoses on integrated energy systems(IESs). However, the integrated energy data necessary for energy efficiency analyses and diagnoses come from a wide variety of instruments, each of which uses different transmission protocols and data formats. This makes it challenging to handle energy-flow data in a unified manner. Thus, we have constructed a unified model for diagnosing energy usage abnormalities in IESs. Using this model, the data are divided into working days and non-working days, and benchmark values are calculated after the data have been weighted to enable unified analysis of several types of energy data. The energy-flow data may then be observed, managed, and compared in all aspects to monitor sudden changes in energy usage and energy wastage. The abnormal data identified and selected by the unified model are then subjected to big-data analysis using technical management tools, enabling the detection of user problems such as abnormalities pertaining to acquisition device, metering, and energy usage. This model facilitates accurate metering of energy data and improves energy efficiency. The study has significant implications in terms of fulfilling the energy saving.

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.

Distributed generator-based distribution system service restoration strategy and model-free control methods

The rapid growth of distributed generator(DG)capacities has introduced additional controllable assets to improve the performance of distribution systems in terms of service restoration.Renewable DGs are of particular interest to utility companies,but the stochastic nature of intermittent renewable DGs could have a negative impact on the electric grid if they are not properly handled.In this study,we investigate distribution system service restoration using DGs as the primary power source,and we develop an effective approach to handle the uncertainty of renewable DGs under extreme conditions.The distribution system service restoration problem can be described as a mixed-integer second-order cone programming model by modifying the radial topology constraints and power flow equations.The uncertainty of renewable DGs will be modeled using a chance-constrained approach.Furthermore,the forecast errors and noises in real-time operation are solved using a novel model-free control algorithm that can automatically track the trajectory of real-time DG output.The proposed service restoration strategy and model-free control algorithm are validated using an IEEE 123-bus test system.

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.

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.

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.

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.

A Motor Management Strategy for Optimising Energy Use and Reducing Life Cycle Costs

With increasing energy costs and renewed focus on using energy in ways that support the environment, a structured approach is required to ensure that energy is used efficiently. A comprehensive motor management strategy to reduce motor life cycle costs while increasing reliability is presented. The application of energy management principles is combined with benefits that can be obtained from using energy-efficiency motors. An economic model for determining the optimal time a motor should be replaced with a higher efficiency motor is proposed. The strategy presented incorporates benefits that can be obtained from using in-situ motor efficiency estimation and condition monitoring techniques as part of a motor management system.

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.

Energy Aware Processor Architecture for Effective Scheduling and Power Management in Cloud Using Inclusive Power-Cognizant Processor Controller

The fast acceptance of cloud technology to industry explains increasing energy conservation needs and adoption of energy aware scheduling methods to cloud. Power consumption is one of the top of mind issues in cloud, because the usage of cloud storage by the individuals or organization grows rapidly. Developing an efficient power management processor architecture has gained considerable attention. However, the conventional power management mechanism fails to consider task scheduling policies. Therefore, this work presents a novel energy aware framework for power management. The proposed system leads to the development of Inclusive Power-Cognizant Processor Controller (IPCPC) for efficient power utilization. To evaluate the performance of the proposed method, simulation experiments inputting random tasks as well as tasks collected from Google Trace Logs were conducted to validate the supremacy of IPCPC. The research based on Real world Google Trace Logs gives results that proposed framework leads to less than 9% of total power consumption per task of server which proves reduction in the overall power needed.

Energy Planning in Small Municipalities Based on Monitoring Results and Demand Side Management

Recent estimates state that the European Union is on course to achieve only half of the 20% energy consumption reduction target by 2020. As the first governmental stakeholders involved in the implementation of energy saving initiatives, municipalities play a strategic role in the energy planning process. This paper focuses on establishment of an energy planning methodology for small municipalities with numbers of inhabitants in range of 1,000-10,000 which often face common problems associated with low efficient district heat supply systems and decreasing energy consumption in buildings. Particular attention is paid to DSM （demand side management） activities. DSM scheme includes legislative and financial flows with small investments from municipality side. Based on increased information and motivation it promotes reduction of energy consumption in all kinds of buildings. Practical experience has shown that application of DSM measures allows achieving 20% energy savings in municipal buildings during the first year.

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.

Technologies for Efficient Use of Irrigation Water and Energy in China

While the shortage of water and energy is a well-recognized worldwide natural resources issue, little attention has been given to irrigation energy efficiency. In this paper, we examine the potential energy savings that can be achieved by implementing improved irrigation technologies in China. The use of improved irrigation management measures such as a flow meter, irrigation scheduling, and/or regular maintenance and upgrades, typically reduces the amount of water pumped over the course of a growing season. The total energy saved by applying these improved measures could reach 20%, as compared with traditional irrigation methods. Two methods of irrigation water conveyance by traditional earth canal and low pressure pipeline irrigation （LPPI） were also evaluated. Our study indicated that LPPI could save 6.48x 109 kWh yr1 when applied to 11 Chinese provinces. Also, the COz emission was reduced by 6.72 metric tons per year. Among these 11 surveyed provinces, the energy saving potential for two provinces, Hebei and Shandong, could reach 1.45 x 109 kWh yr^-1. Using LPPI, potential energy saved and CO2 emissions reduced in the other 20 Chinese provinces were estimated at about 2.97×109 kWh yr-1 and 2.69 metric tons per year, respectively. The energy saving potential for Heilongjiang, a major agriculture province, could reach 1.77× 109 kWh yr-1, which is the largest in all provinces. If LPPI is applied to the entire country, average annual energy saving of more than 9 billion kWh and average annual CO2 emission reduction of more than 9.0 metric tons could be realized. Rice is one of the largest users of the world＇s fresh water resources. Compared with continuous flooding irrigation, intermittent irrigation （ITI） can improve yield and water-use efficiency in paddy fields. The total increments of net output energy and yield by ITI in paddy fields across China could reach 2.5× 1016 calories and l07 tons, respectively. So far only a small part of agricultural land in China has adopted water and energy saving technologies. Therefore, potential water and energy savings in China by adapting improved irrigation technology could be significant and should be carefully studied and applied.