Research on Smart Energy Monitoring and Management System Based on Digital Twin Technology

Smart energy monitoring and management system lays a foundation for the application and development of smart energy. However, in recent years, the work efficiency of smart energy development enterprises has generally been low, and there is an urgent need to improve the application efficiency, resilience and sustainability of smart energy monitoring and management system. Digital twin technology provides a data-centric solution to improve smart energy monitoring and management system, bringing an opportunity to transform passive infrastructure assets into data-centric systems. This paper expounds on the concept and key technologies of digital twin, and designs a smart energy monitoring and management system based on digital twin technology, which has dual significance for promoting the development of smart energy field and promoting the application of digital twin.

An Ethereum-based solution for energy trading in smart grids

The need for a flexible,dynamic,and decentralized energy market has rapidly grown in recent years.As a matter of fact,Industry 4.0 and Smart Grids are pursuing a path of automation of operations to insure all the steps among consumers and producers are getting closer.This leads towards solutions that exploit the paradigm of public blockchain,which represents the best platform to design flat and liquid markets for which providing trust and accountability to mutual interactions becomes crucial.On the other hand,one of the risks arising in this situation is that personal information is exposed to the network,with intolerable threats to privacy.In this paper,we propose a solution for energy trading,based on the blockchain Ethereum and Smart Contracts.The solution aims to be a concrete proposal to satisfy the needs of energy trading in smart grids,including the important feature that no information about the identity of the peers of the network is disclosed in advance.

Peer-to-peer Electricity Transaction Decisions of the User-side Smart Energy System Based on the SARSA Reinforcement Learning

With the deep integration of advanced information technologies,such as artificial intelligence and traditional energy technologies,smart energy systems have been proposed as a method to provide the best solution for the coordination,balance,and control of the entire energy system.As a new way of energy balance and interaction in the user side energy market,a peer-to-peer(P2P)electricity transaction can effectively promote energy sharing within the user group and improve the economic benefits of users participating in the energy market.Reinforcement learning(RL)is an artificial intelligence method in which agents continuously acquire relevant experience and knowledge during the interaction with the environment,automatically update their decision-making behavior;and achieve maximum return.It is a suitable approach for P2P transaction decision analysis of small-scale users in the context of smart energy.First,this paper establishes a P2P transaction model that includes a participant model,equipment model and price model.Secondly,the transaction problem is equivalent to a Markov decision process(MDP)and each learning element model is established.Then,the MDP problem is solved and analyzed using the SARSA RL algorithm with average discrete processing.Finally,a case study of a community with multiple users is conducted to verify the effectiveness,economy,and security of the RL method in solving energy storage action selection and transaction decision problems of energy storage users.

Low Carbon Building Design Optimization Based on Intelligent Energy Management System

The construction of relevant standards for building carbon emission assessment in China has just started,and the quantitative analysis method and evaluation system are still imperfect,which hinders the development of low-carbon building design.Therefore,the use of intelligent energy management system is very necessary.The purpose of this paper is to explore the design optimization of low-carbon buildings based on intelligent energy management systems.Based on the proposed quantitative method of building carbon emission,this paper establishes the quota theoretical system of building carbon emission analysis,and develops the quota based carbon emission calculation software.Smart energy management system is a low-carbon energy-saving system based on the reference of large-scale building energy-saving system and combined with energy consumption.It provides a fast and effective calculation tool for the quantitative evaluation of carbon emission of construction projects,so as to realize the carbon emission control and optimization in the early stage of architectural design and construction.On this basis,the evaluation,analysis and calculation method of building structure based on carbon reduction target is proposed,combined with the carbon emission quota management standard proposed in this paper.Taking small high-rise residential buildings as an example,this paper compares and analyzes different building structural systems from the perspectives of structural performance,economy and carbon emission level.It provides a reference for the design and evaluation of low-carbon building structures.The smart energy management system collects user energy use parameters.It uses time period and time sequence to obtain a large amount of data for analysis and integration,which provides users with intuitive energy consumption data.Compared with the traditional architectural design method,the industrialized construction method can save 589.22 megajoules(MJ)per square meter.Based on 29270 megajoules(MJ)per ton of standard coal,the construction area of the case is about 8000 m2,and the energy saving of residential buildings is 161.04 tons of standard coal.This research is of great significance in reducing the carbon emission intensity of buildings.

2011 IEEE International Conference on Smart Grid and Clean Energy Technologies

2011 1EEE International Conference on Smart Grid and Clean Energy Technologies （IEEE ICSGCE2011） will be held in September 27-30, 2011 in Chengdu, China. IEEE ICSGCE2011 is sponsored by International Association of Computer Science and Information Technology （IACSIT）, Journal of Electronic Science and Technology （JEST - International）, the Institute of Electrical and Electronic Engineers （IEEE）, and University of Electronic Science and Technology of China （UESTC）. The Conference is also supported by University of Wollongong （Australian） and China Energy Association （CEA）.

Call for Papers 2011 IEEE International Conference on Smart Grid and Clean Energy Technologies

2011 IEEE International Conference on Smart Grid and Clean Energy Technologies （IEEE ICSGCE2011） will be held in September 27-30, 2011 in Chengdu, China. IEEE ICSGCE2011 is sponsored by the Institute of Electrical and Electronic Engineers （IEEE）, Journal of Electronic Science and Technology （JEST - International）, and University of Electronic Science and Technology of China （UESTC）. The Conference is also supported by University of Wollongong （Australian） and China Energy Association （CEA）.

Three dimensional photovoltaic fibers for wearable energy harvesting and conversion

As the development of smart electronics, self-powered sources have been attracting increasing attention.This review summarizes research progress of photovoltaic fibers and their integrated power sources with multi-stage energy conversion. Recent development of three dimensional photovoltaic fibers is glanced with special attention to structure design and materials of typical photovoltaic types（inorganic, organic,dye/quantum dot sensitized and perovskite solar cells）. The application of carbon materials in fiber energy is focused as it is a hot topic recently. The hybrid energy systems based on fiber solar cells and fiber supercapacitors, fiber batteries and fiber nanogenerators are summarized together with hybrid energy textiles. This review provides a macroscopic view of novel energy fibers and will attract research interest in flexible/wearable fiber electronics and energy textiles.

The Crowd Energy Concept

After the Fukushima disaster, European politicians began to reassess the energy strategy for their countries. The focus is now on renewable energy sources and as a result on decentralization. The decentralized generation, storage, and of course the consumption of energy is the central point. Now with the new develop-ments under the roof of energy turnaround the way back from the centralized architecture of our energy system to a more decentralized one is predetermined. Decentralization implies the change in the role of today＇s consumers. They become energy prosumers. This is the basis for the crowd energy concept. In this position paper the crowd energy concept is introduced and necessary research fields are identified.

Smart Local Energy Systems Towards Net Zero:Practice and Implications from the UK

In transition towards net-zero carbon emissions,a high penetration of renewable power generation and electrification of heat and transport at the grid edge will increase total and peak power consumption significantly with greater uncertainties,thus posing serious challenges to electric power systems.Smart local energy systems,which manage distributed energy resources locally with various smart technologies and commercial arrangements,are one of the promising solutions to this problem.This paper provides a comprehensive review and analysis of the practice of local energy systems in the UK in the context of net-zero transition.At the macro level,local conditions,local businesses,profitability,investment and whole electricity system impacts of local energy systems are reviewed.Then,a practical case in North Wales,UK,is analyzed for demonstrating technical,commercial and regulatory arrangements available and needed for setting up a local energy system practice.Implications are summarized for providing a useful reference for developing smart local energy systems within and beyond the UK.

Online Fuzzy Logic Base Algorithm for Electricity Price Prediction

This paper presents a web-based system to predict the electricity prices.The proposed system captures the geographical location,weather forecast,and oil price for one week ahead.The captured parameters are fed to a fuzzy-logic-based algorithm to calculate electric energy prices.Based on predicted electricity prices,consumers can turn ON/OFF or reschedule operations of their home appliances to reduce their electricity bill.The proposed algorithm was developed and hosted in a utility server(U-server).On the consumer side,a home gateway(H-gateway),and a monitoring and control system was designed,built,and tested by using a single chip microcontroller.

A survey of Digital Twin techniques in smart manufacturing and management of energy applications

With the continuous advancement and exploration of science and technology,the future trend of energy technology will be the deep integration of digitization,networking,intelligence with energy applications.The increasing maturity of digital technologies,such as the Internet of Things,big data,and cloud computing,has given rise to the creation and use of a potential technology–Digital Twin.Currently,research on Digital Twin has produced many concepts and outcomes that have been applied in many fields.In the energy sector,while some relevant ideas and case studies of Digital Twin have been generated,there are still many gaps to be explored.As a potential technology with advantages in many aspects,Digital Twin is bound to generate more promotion and applications in the energy fields.This paper systematically reviews the existing Digital Twin approaches and their possible applications in the energy fields.In addition,this paper attempts to analyze Digital Twin from different perspectives,such as definitions,classifications,main features,case studies and key technologies.Finally,the directions and challenges of possible future applications of Digital Twin in the energy fields have been presented.

Paving the Way to Smart Micro Energy Grid:Concepts,Design Principles,and Engineering Practices

The interconnection between initially independent energy infrastructures offers additional system flexibility and efficiency.The integration at distribution level simplifies the implementation of the integrated energy system functionalities.This paper proposes concepts and design principles of a smart micro energy grid(MEG)for accommodating micro-grids,distributed poly-generation systems,energy storage facilities,and associated energy distribution infrastructures.The energy management system is responsible for the smart operation of the MEG while supporting multiple criteria,such as safety,economy,and environmental protection.To realize the vision of the smart MEG,an engineering game theory based energy management system with self-approaching-optimum capability is investigated.Based on the proposed concepts,design principles,and energy management system,this paper presents a prototype of China’s first conceptual solar-based smart MEG,established in Qinghai University.

Call for Papers

The electric industry is being transformed from a centralized network to one that is less centralized and allows more consumer interaction in the form of a smart grid. A smart grid is a power transmission and distribution network that can incorporate millions of sensors all connected through an advanced, two-way communications and data acquisition system to provide real-time monitoring, diagnosis and control. Smart grid enables more efficient, reliable and secure energy service, facilitate grid-integration of renewable systems and energy storage, and better routing of power and demand management. The move to a smarter grid promises to change the industry＇s entire business model and its relationship with all stakeholders, involving and affecting power companies, regulators, energy service providers, technology and automation vendors, and all consumers of electric power.

Next-generation blockchain enabled smart grid: Conceptual framework, keytechnologies and industry practices review

Technological advancements in smart grid energy systems (SGESs) are introducing sustainable frameworksto meet the demand for the fourth industrial energy revolution. These frameworks are planned to be usedin the forthcoming future to maintain the energy network operation with optimization, energy trading, gridautomation, and so on. Blockchain (BCn), developing after passing a diverse period of the research journey,comes to the mind of researchers and its integration in SGES paves the way to reach the goal of energydemand. However, still of interest is ongoing in the improvement of BCn features which can be regarded asthe next-generation blockchain framework. This paper exhibits the technical framework of the next-generationBCn framework and explores its benefits and challenges in performing the emerging aspects of SGES. Thisframework enables some advanced features for the sustainable operation of SGES like smart metering, peer-topeer (P2P) energy trading, self-operation, and transparency. The technical explanation of this BCn technologyestablished on essential features and requisites is also presented in this paper from various points of viewwhich include smart mechanism, intelligent storage system, and interoperability. We also highlight the recentprogress and limitations of the current BCn framework in SGES. Finally, some challenges towards integratingthe next-generation BCn technology in SGES are reported. This work can provide extended support for thepractitioner and researcher in the context of BCn technology and SGES.

From Independence to Interconnection--A Review of AI Technology Applied in Energy Systems

The development of diversified energy structures,distributed energy scheduling models and active participation ability of users,leads to a rapid movement toward energy system in which different energy carriers and systems interact together in a synergistic way.This energy development will face many challenges with the requirements of big data processing capability,professional skill,distributed collaboration and realtime monitoring for the energy system that demands an intelligent and flexible tool to realize the smart energy.Artificial intelligence(AI)technology has become a focus because of its better performance.This paper proposed a classification method that incorporates the intelligence of an independent energy unit(IEU)and the intelligence among interconnected energy units(IEUS)to review the development of AI technology in energy systems.The dominant structures of IEU can be considered from three aspects including perception,decision and implementation to study the optimal strategy for AI methods utilized in IEU.And considering the interaction relationship of IEUS,the AI applied for it can be described by the coordinated relationship and adversarial relationship problems to achieve consensus.By discussing the AI technologies and the potentials of AI in the energy system,some suggestions are presented to improve intelligent technologies for sustainable energy systems in the future.

Advanced energy materials for flexible batteries in energy storage:A review

Smart energy storage has revolutionized portable electronics and electrical vehicles.The current smart energy storage devices have penetrated into flexible electronic markets at an unprecedented rate.Flexible batteries are key power sources to enable vast flexible devices,which put forward additional requirements,such as bendable,twistable,stretchable,and ultrathin,to adapt mechanical deformation under the working conditions.This review summarizes the recent advances in construction and configuration of flexible batteries and discusses the general metrics to benchmark various flexible batteries with different materials and chemistries.Moreover,we present advanced prototype flexible batteries developed by some companies to afford general envision of the technological status.Lastly,the critical points are summarized in the development of flexible batteries and remaining challenges are also presented for the future design of flexible batteries in practical perspectives.

Comprehensive Overview of Multi-agent Systems for Controlling Smart Grids

Agents are intelligent entities that act flexibly and autonomously and make wise decisions based on their intelligence and experience.A multi-agent system(MAS)contains multiple,intelligent,and interconnected collaborating agents for solving a problem beyond the ability of a single agent.A smart grid(SG)combines advanced intelligent systems,control techniques,and sensing methods with an existing utility power network.For controlling smart grids,various control systems with different architectures have already been developed.MAS-based control of power system operations has been shown to overcome the limitations of time required for analysis,relaying,and protection;transmission switching;communication protocols;and management of plant control.These systems provide an alternative for fast and accurate power network control.This paper provides a comprehensive overview of MASs used for the control of smart grids.The paper provides a wide-spectrum view of the status of smart grids,MAS-based control techniques and their implementation for the control of smart grids.Use of MASs in the control of various aspects of smart grids-including the management of energy,marketing energy,pricing,scheduling energy,reliability,network security,fault handling capability,communication between agents,SG-electrical vehicles,SG-building energy systems,and soft grids—have been critically reviewed.More than a hundred publications on the topic of MAS-based control of smart grids have been critically examined,classified,and arranged for fast reference.

Energy storage systems:a review

The world is rapidly adopting renewable energy alternatives at a remarkable rate to address the ever-increasing environmental crisis of CO_(2) emissions.Renewable energy system offers enormous potential to decarbonize the environment because they produce no greenhouse gases or other polluting emissions.However,the RES relies on natural resources for energy generation,such as sunlight,wind,water,geothermal,which are generally un-predictable and reliant on weather,season,and year.To account for these intermittencies,renewable energy can be stored using various techniques and then used in a consistent and controlled manner as needed.Several researchers from around the world have made substantial contributions over the last century to developing novel methods of energy storage that are efficient enough to meet increasing energy demand and technological break-throughs.This review attempts to provide a critical review of the advancements in the energy storage system from 1850-2022,including its evolution,classification,operating principles and comparison.

Review of stochastic optimization methods for smart grid

This paper presents various approaches used by researchers for handling the uncertainties involved in renewable energy sources, load demands, etc. It gives an idea about stochastic programming (SP) and discusses the formulations given by different researchers for objective functions such as cost, loss, generation expansion, and voltage/V control with various conventional and advanced methods. Besides, it gives a brief idea about SP and its applications and discusses different variants of SP such as recourse model, chance constrained programming, sample average approximation, and risk aversion. Moreover, it includes the application of these variants in various power systems. Furthermore, it also includes the general mathematical form of expression for these variants and discusses the mathematical description of the problem and modeling of the system. This review of different optimization techniques will be helpful for smart grid development including renewable energy resources (RERs).

Blockchain-based Peer-to-Peer Transactive Energy System for Community Microgrid with Demand Response Management

Interest in transactive energy frameworks(TEFs)is proliferating due to the modern smart grid paradigm.This paper proposes a TEF,which applies auction-theory,incorporates a system of agents,and facilitates a transactive energy market(TEM)through an auctioneer.Further,it also enables peer-to-peer(P2P)energy trading among the residential buildings in community microgrid for possible monetary benefits.In this framework,there are three agents,namely,auctioneer,participants,and utility.The auctioneer is a managing agent modeled using auction theory to determine day-ahead internal market-clearing price and quantity.The participants are autonomous and rational decision-makers;they aim to minimize their electricity bills through the demand response(DR)management.Two types of architectures,one with the third-party agent demonstrated using the MATLAB environment and the other with the virtual agent(without third-party)implemented using the blockchain environment are presented.The simulation results reflect significant monetary benefits to each market participant,improved community selfsufficiency,self-consumption,and reduced reliance on the utility grid.