Distributed Optimal Co-multi-microgrids Energy Management for Energy Internet

Unlike conventional power systems,the upcoming energy internet(EI) emphasizes comprehensive utilization of energy in the whole power system by coordinating multi-microgrids,which also brings new challenge for the energy management.To address this issue,this paper proposes a novel consensus-based distributed approach based on multi-agent framework to solve the energy management problem of the energy internet,which only requires local information exchange among neighboring agents.Correspondingly,two consensus algorithms are presented,one of which drives the incremental cost of each distributed generator(DG) converge to the state of the leader agent-energy router,and the other one is used to estimate the global power mismatch,which is a first-order average consensus algorithm modified by a correction term.In addition,in order to meet the supply-demand balance,an effective control strategy for the energy router is proposed to accurately calculate the power exchange between the microgrid and the main grid.Finally,simulation results within a 7-bus test system are provided to illustrate the effectiveness of the proposed approach.

Trading platform for cooperation and sharing based on blockchain within multi-agent energy internet

With the release of the electricity sales side,large-scale small-capacity distributed power generation units are connected to the distribution side,forming multi-type market entities such as microgrids,integrated energy systems,and virtual power plants.With the large-scale integration of distributed energy,the energy market under the energy internet is different from a traditional transmission grid.It is currently developing in the direction of diversified entities and commodities,a flat structure,and a flexible and competitive multi-agent market mechanism.In this context,this study analyzes the value of combining blockchain and the electricity market presents the design of a blockchain trading framework for multi-agent cooperation and sharing of the energy internet.The nodes in market transactions are modeled through power system modeling in the physical layer and the transaction consensus strategy in the cyber layer;moreover,the nodes are verified in a modified IEEE 13 testing feeder of a distribution network.A transaction example is demonstrated using the multi-agent cooperation and sharing transaction platform based on the Ethereum private blockchain.

Development of the interconnected power grid in Europe and suggestions for the energy internet in China

The European power grid is one of the largest regional interconnected power grids in the world.It realizes a multinational grid operation,which is rare.The total installed capacity of the European power grid is the largest throughout the world.In addition,the integration and utilization of renewable energy in this grid is a great benchmark for other countries and can help promote energy transformation and achieve a high proportion of renewable energy consumption.Based on the analysis of the existing status of the European interconnected power grid and the development history of this power grid,this paper summarizes four key development stages of the European power grid.In addition,the characteristics of each stage and the development prospect of the European power grid are analyzed.On this basis,this paper gives suggestions for the development and construction of China’s energy internet;this can provide valuable reference for further studies on China’s energy internet.

Research on task scheduling and concurrent processing technology for energy internet operation platform

The energy Internet operation platform provides market entities such as energy users,energy enterprises,suppliers,and governments with the ability to interact,transact,and manage various operations.Owing to the large number of platform users,complex businesses,and large amounts of data-mining tasks,it is necessary to solve the problems afflicting platform task scheduling and the provision of simultaneous access to a large number of users.This study examines the two core technologies of platform task scheduling and multiuser concurrent processing,proposing a distributed task-scheduling method and a technical implementation scheme based on the particle swarm optimization algorithm,and presents a systematic solution in concurrent processing for massive user numbers.Based on the results of this study,the energy internet operation platform can effectively deal with the concurrent access of tens of millions of users and complex task-scheduling problems.

Technical System Construction in the Market Trading System for Demand Response Based on the Energy Internet

With the explosive growth of variable renewable energy,the balance between the supply and demand of the power grid is faced with new challenges.Based on the development experience from typical countries and the state quo in China,this paper further analyzes the system architecture and development trend of demand response under the background of Energy Internet.Five dimensions are considered:Energy Internet platform,demand response application scenarios,system architecture,information technology system construction,and demand response development trend.The results show that the application of the Energy Internet platform can effectively solve the problems of data acquisition and processing,“terminal-edge-network-cloud”cooperation of demand response,etc.The system architecture of the demand response platform that supports user resource management,user information access,control instruction receiving,control strategy issuing,and response process monitoring is proposed in this paper.It is also helpful to provide a feasible technical choice for expanding the application services of Energy Internet towards government and society.

Modeling of comprehensive power load of fishery energy internet considering fishery meteorology

Accurate calculation for comprehensive power load of fishery energy internet plays a significant role in reasonable using of energy and reducing environmental pollution.However,as fishery power load is of greatly unique meteorology sensitivity,it continues to be a difficult problem.Therefore,the research of fishery meteorology is an important part of the rational development of fishery resources,the protection of production safety,and the pursuit of high and stable yield.This paper makes a deep study on the power load of the fishery energy internet under the influence of fishery meteorology and takes onshore fish pond as the research object.First of all,the power load is divided into three parts:oxygen enrichment power load,feeding power load,and water replenishment and drainage power load.The impact mechanism of fishery meteorology(including temperature,surface wind speed,precipitation,relative humidity,etc.)on it is described,and then the overall power load is obtained through modeling and integration.Finally,taking the Yuguang Complementary Project in Zhouquan Town,Tongxiang,Zhejiang Province,China as an example,using the meteorological data of its typical spring day and using the MATLAB tool to solve,the hourly comparison of the three types of power loads,the comprehensive power load demand,the full-day electricity charge forecast and the total annual power consumption are calculated.The annual power consumption per hectare and per kilogram of output calculated by simulation are basically consistent with the order of magnitude of the survey data,which proves the validity of the model proposed.The model established in this paper is an original work,and the exploration of fishery energy internet can draw lessons from it.

Key technologies and applications of agricultural energy Internet for agricultural planting and fisheries industry

Energy consumption in the agricultural sector is significant,reaching 20%of the total energy consumption in China.Agricultural Energy Internet,an important extension of Energy Internet in the agricultural field,significantly contributes to agricultural modernization.Key technologies of Agricultural Energy Internet are vital factors supporting its development.This article systematically reviews the key technologies of Agricultural Energy Internet for two areas:agriculture and fishery.The working mechanisms and power consumption characteristics of some state-of-the-art new-energy agricultural intelligent equipment are described.In addition,the principles and profit methods underlying the agro-industrial complementary operation model are introduced.Moreover,against the Agricultural Energy Internet background,the development trends of some state-of-theart new energy agricultural intelligent equipment,agro-industrial complementary,and carbon–neutral technology are proposed in this paper,providing novel perspectives on the promotion of the development of Agricultural Energy Internet and related technological innovation research.An unmanned farm is the main form of the future agricultural system,which is powered by the Agricultural Energy Internet based on smart agriculture and a smart grid.It will become the inevitable trend of modern agriculture to replace oil agriculture with electric farms.The electricity in farming is mainly generated by renewable energy.Renewable energy power generation has low carbon emissions and is the future direction for the development of agricultural energy systems.In addition,the Internet of Things will be further strengthened to realize automation and intelligence of agricultural energy systems。

Research on Intelligent Organization and Application of Multi-source Heterogeneous Knowledge Resources for Energy Internet

To improve the informationization and intelligence of the energy Internet industry and enhance the capability of knowledge services,it is necessary to organize the energy Internet body of knowledge from existing knowledge resources of the State Grid,which have the characteristics of large scale,multiple sources,and heterogeneity.At the same time,the business fields of State Grid cover a wide range.There are many sub-fields under each business field,and the relationship between fields is diverse and complex.The key to establishing the energy Internet body of knowledge is how to fuse the heterogeneous knowledge resources from multiple sources,extract the knowledge contents from them,and organize the different relationships.This paper considers transforming the original knowledge resources of State Grid into a unified and wellorganized knowledge system described in OWL language to meet the requirements of heterogeneous resource integration,multi-source resource organization,and knowledge service provision.For the State Grid knowledge resources mainly in XML format,this paper proposes a Knowledge Automatic Fusion and Organization idea and method based on XSD Directed Graph.According to the method,the XML corresponding XSD documents are transformed into a directed graph in the first stage during which the graph neural network detects hidden knowledge inside the structure to add semantic information to the graph.In the second stage,for other structured knowledge resources(e.g.,databases,spreadsheets),the knowledge contents and the relationships are analyzed manually to establish the mappings from structured resources to graph structures,using which the original knowledge resources are transformed into graph structures,and merged with the directed graphs obtained in the first stage to achieve the fusion of heterogeneous knowledge resources.And expert knowledge is introduced for heterogeneous knowledge fusion to further extend the directed graph.And in the third stage,the expanded directed graph is converted to the body of knowledge in the form of OWL.This paper takes the knowledge resources in the field of human resources of the State Grid as an example,to establish the ontology of the human resources training field in a unified manner,initially demonstrating the effectiveness of the proposed method.

Energy internet or comprehensive energy network?

What needs to be developed from the concept of"Smart Grid"is that:when renewable energy sources are absolutely prevailing in power generation,distributed power generation and distributed energy storage systems are widespread across the grid,and electric vehicle charging loads are prevailing in power load demands,how can the power grid support electric power as a core secondary energy source,undertake the role of a bridge between primary energy and end-use energy,and achieve the coordination and the optimization in macro energy perspective;how to guarantee the security of both macro energy and environment as well as the reliability of electricity.If a new term is needed,it should be Comprehensive Energy Network,not Energy Internet.

Optimal dispatch of zero-carbon-emission micro Energy Internet integrated with non-supplementary fired compressed air energy storage system

To utilize heat and electricity in a clean and integrated manner,a zero-carbon-emission micro Energy Internet(ZCE-MEI) architecture is proposed by incorporating non-supplementary fired compressed air energy storage(NSF-CAES) hub.A typical ZCE-MEI combining power distribution network(PDN) and district heating network(DHN) with NSF-CAES is considered in this paper.NSF-CAES hub is formulated to take the thermal dynamic and pressure behavior into account to enhance dispatch flexibility.A modified Dist Flow model is utilized to allow several discrete and continuous reactive power compensators to maintain voltage quality of PDN.Optimal operation of the ZCE-MEI is firstly modeled as a mixed integer nonlinear programming(MINLP).Several transformations and simplifications are taken to convert the problem as a mixed integer linear programming(MILP)which can be effectively solved by CPLEX.A typical test system composed of a NSF-CAES hub,a 33-bus PDN,and an 8-node DHN is adopted to verify the effectiveness of the proposed ZCE-MEI in terms of reducing operation cost and wind curtailment.

Constructing a V2G-enabled Regional Energy Internet for Cost-efficient Carbon Trading

The increasing penetration of plug-in electric ve- hicles (PEVs) has highlighted the importance of coordinating ubiquitous distributed energy resources (DERs) via the internet of things (IoT).With the help of vehicle-to-grid (V2G) technology, PEVs can be aggregated to behave as a storage system, yielding both economic and environmental benefits. In this paper, we propose an optimal bidding framework for a V2G-enabled re- gional energy internet (REI) to participate in day-ahead markets considering carbon trading. The REI operator aims to maximize the net profits from day-ahead markets while anticipating real- time adjustments. A detailed battery model is developed to depict the charging and discharging capability of V2G-enabled PEVs. A two-stage stochastic optimization model is formulated to schedule the operation of PEV fleets against various sources of uncertainties, e.g., the arrival and departure time of PEVs, solar power and real-time prices. Case studies undertaken based on realistic datasets demonstrate that the coordination of the V2G- enabled PEVs and other DERs can facilitate the accommodation of renewable energy, thus improving the REI’s revenues in energy and carbon markets.

Multi-objective optimal allocation strategy for the energy internet in Huangpu District, Guangzhou, China

To improve the overall efficiency of the energy system,the basic structure for the energy internet of coordination and optimization of“generation-grid-load-storage”of Huangpu District,Guangzhou,China is designed,while the arrangement for the output of centralized and distributed energy module and energy storage are proposed.Taking economic benefit maximization,environmental benefit maximization and energy efficiency maximization as sub-objectives,the mathematical model of multi-objective optimal allocation and operation strategy of the energy internet is established considering supply-demand balance constraints,equipment characteristic constraints,operation mode constraints,and energy conditions constraints.The calculation results show that without considering the outsourced electricity,the balanced strategy,the economic development strategy,the environmental protection strategy,and the energy efficiency strategy are obtained by calculation,which are all superior to the traditional energy supply strategy.Moreover,considering the outsourced electricity,the proportion of outsourced electricity to total electricity is 19.8%,which is the system optimization of the energy internet under certain power demand.Compared with other strategies without outsourced electricity,the outsourced electricity strategy can have a certain emission reduction effect,but at the same time reduce the economic benefit.Furthermore,the huge difference in demand for thermal and cooling load between industrial and commercial areas results in the installed capacity of gas distributed energy stations in industrial areas being nearly twice as large as that in commercial areas.The distributed photovoltaic power generation is allocated according to the proportion of the installed roof areas of photovoltaic power generation system in residential,industrial,and commercial areas.

Distributed Energy Sharing in Energy Internet Through Distributed Averaging

This paper proposes a distributed averaging iteration algorithm for energy sharing in microgrids of Energy Internet based on common gossip algorithms. This algorithm is completely distributed and only requires communications between neighbors. Through this algorithm, the Energy Internet not only allocates the energy effectively based on the load condition of grids, but also reasonably schedules the energy transmitted between neighboring grids. This study applies theoretical analysis to discuss the condition in which this algorithm can finally reach supply-and-demand balance. Subsequently, the related simulation validates the performance of the algorithm under various conditions.

Optimal Operation of Energy Internet Based on User Electricity Anxiety and Chaotic Spatial Variation Particle Swarm Optimization

Ignoring load characteristics and not considering user feeling with regard to the optimal operation of Energy Internet（EI） results in a large error in optimization. Thus, results are not consistent with the actual operating conditions. To solve these problems, this paper proposes an optimization method based on user Electricity Anxiety（EA） and Chaotic Space Variation Particle Swarm Optimization（CSVPSO）. First, the load is divided into critical load, translation load, shiftable load, and temperature load. Then, on the basis of the different load characteristics,the concept of the user EA degree is presented, and the optimization model of the EI is provided. This paper also presents a CSVPSO algorithm to solve the optimization problem because the traditional particle swarm optimization algorithm takes a long time and particles easily fall into the local optimum. In CSVPSO, the particles with lower fitness value are operated by using cross operation, and velocity variation is performed for particles with a speed lower than the setting threshold. The effectiveness of the proposed method is verified by simulation analysis.Simulation results show that the proposed method can be used to optimize the operation of EI on the basis of the full consideration of the load characteristics. Moreover, the optimization algorithm has high accuracy and computational efficiency.

Learning-based Green Workload Placement for Energy Internet in Smart Cities

The Energy Internet is a fundamental infrastructure for deploying green city applications, where energy saving and job acceleration are two critical issues to address. In contrast to existing approaches that focus on static metrics with the assumption of complete prior knowledge of resource information, both application-level properties and energy-level requirements are realized in this paper by jointly considering energy saving and job acceleration during job runtime. Considering the online environment of smart city applications, the main objective is transferred as an optimization problem with a model partition and function assignment. To minimize the energy cost and job completion time together, a green workload placement approach is proposed by using the multi-action deep reinforcement learning method. Evaluations with real-world applications demonstrate the superiority of this method over state-of-the-art methods.

Security Protection Method of Energy Internet with Android

As a product of the combination of information and energy technology,the energy internet is enormous and complex,and the absence of security safeguards at any aspect of it can cause incalculable damage.Aiming at the problems that Energy Internet terminals are difficult to be trusted and the integrity of massive terminals cannot be guaranteed,this paper designs and implements a set of comprehensive credibility measures and security protection schemes,isolates various malicious operations,and ensures that the system is always in a credible state.Specifically,we develop a secure TF card control program in the Android terminal application layer to realize the overall security scheme.Experimental results prove that this security protection scheme can effectively detect illegal application packages in energy Internet terminal devices,resist malicious programs,and protect key data from theft at the same time,achieving security protection in the“thing-to-thing”interconnection scenario of the Energy Internet.

Fine-Grained Access Control Mechanism of Energy Internet

The Energy Internet has generated huge amounts of information on the production devices,transmission devices,and energy consumption devices.The leakage of data in the collection,transmission,and storage process will cause serious security problems.The existing Energy Internet security methods rely on traditional access control mechanisms and specific network boundary defense mechanisms,which has the limitations of static strategies and coarse design.We combine the advantages of role-based access control(RBAC)and attribute-based access control(ABAC),and propose a trusted Energy Internet fine-grained access control model based on devices'attribute and users'roles.We have not only achieved fine-grained Energy Internet resource allocation,but also ensured that the access control process is related to the security status of the environment in real time.Experimental results show that the access control model can safely and accurately execute access decisions in the Energy Internet scenario,and the processing performance is more stable.

Call for Papers Special Issue on Energy Internet

The publication of Tsinghua Science and Technology was started in 1996.It is an international academic journal sponsored by Tsinghua University and published bimonthly.This journal aims at presenting the state-of-art scientific achievements in computer science and other IT fields.From 2012,the journal enters into IEEE Xplore Digital Library with the

Enabling Industrial Internet of Things(IIoT) towards an emerging smart energy system

The increasing penetration of renewable energy on the transmission and distribution power network is driving the adoption of two-way power flow control, data and communications needed to meet the dependency of balancing generation and load. Thus, creating an environment where power and information flow seamlessly in real time to enable reliable and economically viable energy delivery, the advent of Internet of Energy(IoE) as well as the rising of Internet of Things(IoT) based smart systems.The evolution of IT to Io T has shown that an information network can be connected in an autonomous way via routers from operating system(OS) based computers and devices to build a highly intelligent eco-system. Conceptually, we are applying the same methodology to the Io E concept so that Energy Operating System(EOS) based assets and devices can be developed into a distributed energy network via energy gateway and self-organized into a smart energy eco-system.This paper introduces a laboratory based IIo T driven software and controls platform developed on the NICE Nano-grid as part of a NICE smart system Initiative for Shenhua group. The goal of this effort is to develop an open architecture based Industrial Smart Energy Consortium(ISEC) to attract industrial partners, academic universities, module supplies, equipment vendors and related stakeholder to explore and contribute into a test-bed centric open laboratory template and platform for next generation energy-oriented smart industry applications.In the meanwhile, ISEC will play an important role to drive interoperability standards for the mining industry so that the era of un-manned underground mining operation can become the reality as well as increasing safety regulation enforcement.

Supply and Demand Oriented Energy Management in the Internet of Things

The Internet of Things (IoT) is emerging as an attractive paradigm involving physical perceptions, cyber interactions, social correlations and even cognitive thinking through a cyber-physical-social-thinking hyperspace. In this context, energy management with the purposes of energy saving and high efficiency is a challenging issue. In this work, a taxonomy model is established in reference to the IoT layers (i.e., sensor-actuator layer, network layer, and application layer), and IoT energy management is addressed from the perspectives of supply and demand to achieve green perception, communication, and computing. A smart home scenario is presented as a case study involving the main enabling technologies with supply-side, demand-side, and supply-demand balance considerations, and open issues in the field of IoT energy management are also discussed.