Analysis of Necessity of Transforming Electrical Grid Access Training and Examination Regulatory Agency Mode

There are numerous electricians,but only a few of them have obtained certificate. Training and examination agencies provide services relating to training,examination,and certificate application and so on.Thus,training resources are not rationally utilized,and the increased training demand cannot be fully satisfied.Under such circumstances,it is recommended to transform the regulatory agency mode by establishing a scientific management process,and put forward a new mode of electrical grid access training and examination to better meet related demands. Under the coordination of examination center regulatory agency, uniform training program,training materials,charging standard,examination and certificate can be guaranteed. This project is carried out as an effort to improve the quality of electronic- engineering training and examination,so that electricity accident rate can be reduced,and the security of electrical grid operation can be guaranteed to boost the rapidly developing economy.

Intelligent Power Grid Load Transferring Based on Safe Action-Correction Reinforcement Learning

When a line failure occurs in a power grid, a load transfer is implemented to reconfigure the network by changingthe states of tie-switches and load demands. Computation speed is one of the major performance indicators inpower grid load transfer, as a fast load transfer model can greatly reduce the economic loss of post-fault powergrids. In this study, a reinforcement learning method is developed based on a deep deterministic policy gradient.The tedious training process of the reinforcement learning model can be conducted offline, so the model showssatisfactory performance in real-time operation, indicating that it is suitable for fast load transfer. Consideringthat the reinforcement learning model performs poorly in satisfying safety constraints, a safe action-correctionframework is proposed to modify the learning model. In the framework, the action of load shedding is correctedaccording to sensitivity analysis results under a small discrete increment so as to match the constraints of line flowlimits. The results of case studies indicate that the proposed method is practical for fast and safe power grid loadtransfer.

Stress testing electrical grids:Generative Adversarial Networks for load scenarion

As the energy transition is upon us,the replacement of combustion engines by electrical ones will imply a greater stress on the electrical grid of different countries.Therefore,it is of paramount importance to simulate a great number of hypothetical multi-variant scenarios to correctly plan the roll-out of new grids.In this paper,we deploy Generative Adversarial Networks(GANs)to swiftly reproduce the non-Gaussian and multimodal distribution of real energy-related samples,making GANs a valuable tool for data generation in the field.In particular,we propose an original dataset deriving from the aggregation of two European providers including hourly electric inland generation from several European countries.This dataset also comes along with the corresponding season,day of the week,hour of the day and macro-economic variables aiming at unequivocally describing the country’s energetic profile.Finally,we evaluate the performance of our model via dedicated metrics capable of grasping the non-Gaussian nature of the data and compare it with the state-of-the-art model for tabular data generation.

Evaluation of Grid-Connected Photovoltaic Plants Based on Clustering Methods

Photovoltaic(PV)systems are electric power systems designed to sup-ply usable solar power by means of photovoltaics,which is the conversion of light into electricity using semiconducting materials.PV systems have gained much attention and are a very attractive energy resource nowadays.The substantial advantage of PV systems is the usage of the most abundant and free energy from the sun.PV systems play an important role in reducing feeder losses,improving voltage profiles and providing ancillary services to local loads.However,large PV grid-connected systems may have a destructive impact on the stability of the elec-tric grid.This is due to thefluctuations of the output AC power generated from the PV systems according to the variations in the solar energy levels.Thus,the elec-trical distribution system with high penetration of PV systems is subject to perfor-mance degradation and instabilities.For that,this project attempts to enhance the integration process of PV systems into electrical grids by analyzing the impact of installing grid-connected PV plants.To accomplish this,an indicative representa-tion of solar irradiation datasets is used for planning and powerflow studies of the electric network prior to PV systems installation.Those datasets contain lengthy historical observations of solar energy data,that requires extensive analysis and simulations.To overcome that the lengthy historical datasets are reduced and clus-tered while preserving the original data characteristics.The resultant clusters can be utilized in the planning stage and simulation studies.Accordingly,studies related to PV systems integration into the electric grid are conducted in an efficient manner,avoiding computing resources and processing times with easier and practical implementation.

Tilt Angle Optimality Criteria for Stand Alone PV Systems

The conventional approach to optimizing tilt angles for fixed solar panels aims to maximize energy generation over the entire year. However, in the context of a supply controlled electric grid, where solar energy availability varies, this criterion may not be optimal. This study explores two alternative optimization criteria focused on maximizing baseload supply potential and minimizing required storage capacity to address seasonality in energy generation. The optimal tilt angles determined for these criteria differed significantly from the standard approach. This research highlights additional factors crucial for designing solar power systems beyond gross energy generation, essential for the global transition towards a fully renewable energy-based electric grid in the future.

Smart Boilers: Grid Support Services from Non-Critical Loads

The aim of this paper is to present the concept of a simple and cheap upgrade for electric water boilers, allowing them to provide power quality services to the distribution grid. The upgrade requires only minimum additional hardware and it is easily installable. “Smart Boilers”, as the upgraded boilers are named, perform precise active and reactive power control, but most significantly mitigate line current harmonics. Αctive and reactive power control is implemented by appropriate regulation of the modulation sinewave amplitude and phase, respectively. This type of control is easily customizable in order to accommodate a variety of power quality targets, depending on the required level of services and available grid monitoring equipment. The method used for line current harmonic compensation is based on the injection of mirror harmonics created at the modulation stage of the converter. It is indifferent of harmonic source: it is equally successful at mitigating harmonics caused by the power electronic converter of the Smart Boiler, other sources of current harmonics or loads. The achieved grid services are clearly beyond the “on/off” operation of electric boilers, currently implemented by Demand Side Management (DSM) in order to shift load away from peak hours. It has been demonstrated through simulations, that Smart Boilers can assist voltage regulation at terminal buses, compensate reactive power and suppress harmonic currents at lines.

Wireless Sensor Networks Based Control Strategies for the Enhancement of Reliability in Smart Grids

The rapid increase in the demand for electricity necessitates the power quality improvement for achieving better reliability in smart grids. Wireless Sensor Networks (WSN) is the proven technology for reliable monitoring. This paper proposes a system model for the development and implementation of WSN based communication system for the monitoring of distributed generation, loads and transmission lines in the electrical grid and a controller system for automated control on the electrical grid. This work also aims to reduce the carbon footprints by reducing the dependency of electrical grid through the enhancement of distributed generation and grid sharing for avoiding voltage rise problem. To achieve this, a smarter electrical grid has been developed for the validation of smart grid considering a generation substation, a transmission substation and a distributed generation with loads. The occurrence of power quality issue and voltage rise has been controlled by active power control strategy. The communication network and controller has been modeled and tested for the performance of monitoring system and data communication capability on smart grid.

A Grid as Smart as the Internet

A new era of electricity is dawning that combines the decarbonization of the grid with the extensive electrification of all sectors of society.A grid as smart as the internet is needed to harness the full potential of renewables,accommodate technology disruptions,embrace the rise of prosumers,and seamlessly integrate nano-,mini-,and micro-grids.The internet is built upon a layered architecture that facilitates technology innovations,and its intelligence is distributed throughout a hierarchy of networks.Fundamental differences between data flows and power flows are examined.The current operating paradigm of the grid is based on the conviction that a centralized grid operator is necessary to maintain instantaneous power balance on the grid.A new distributed paradigm can be realized by distributing this responsibility to sub-grids and requiring each sub-grid to maintain its net power balance.A grid as smart as the internet based on this new paradigm,as well as a hierarchical network structure and a layered architecture of operating principles,is presented.

The evolution of interstate power grid formation

This study analyzes the process of electric power system integration in various regions worldwide.This process is implemented by creating both interstate electric ties and power grids.The analysis is comprehensive and examines the system,spatial,technical,organizational,and market aspects of the integration.Various countries,including developed countries such as Europe and North America,as well as economically developing countries such as Central America and Africa,are involved in this process.However,the rates and scales of electric power integration differ across various regions worldwide.The analysis shows that the process of electric power integration,which has decades of history,is still ongoing,despite the growth of other trends,such as the development of distributed generation.Further electricity integration is expected to lead to the formation of a global power interconnection in the long term.

An Approach for Cost-Efficient Grid Integration of Distributed Renewable Energy Sources

We describe a specific approach to capacity man a ge ment for distribution grids. Based on simulations, it has been found that by curtailing a maximum of 5% of the yearly energy production on a per-generator basis, distribution grid connection capacity can be doubled. We also present the setting and fi rst results of a fi eld test for validating the approach in a rural distribution grid in northern Germany.

National Electricity Generation,Electricity Consumption and Peak Load by Grid (April 2006)

Statistics on electricity generation and time of frequency over-limit;Statistics on electricity consumption and peak load.

National Electricity Generation,Electricity Consumption and Peak Load by Grid (March 2006)

Statistics on electricity generation and time of frequency over-limit;Statistics on electricity consumption and peak load.

Artificial Intelligence Driven Nuclear Power Reactors(A Technical Memorandum)

The 21st Century era and new modern technologies surrounding us day-in and day-out have opened a new door to“Pandora Box”,that we do know it as AI(artificial intelligence)and its two essential integrated components namely ML(machine learning)and DL(deep learning).However,the strive and progress in AI,ML,and DL pretty much has taken over any industry that we can think of,when it comes to dealing with cloud of structured data in form of BD(big data).A NPP(nuclear power plant)has multiple complicated dynamic system-of-components that have nonlinear behaviors.For controlling the plant operation under both normal and abnormal conditions,the different systems in NPPs(e.g.,the reactor core components,primary and secondary coolant systems)are usually monitored continuously,which leads to very huge amounts of data.Of course Nuclear Power Industry in form of GEN-IV(Generation IV)has not been left behind in this 21st century era by moving out of GEN-III(Generation III)to more modulars form of GEN-IV,known as SMRs(small modular reactors),with a lot of electronic gadgets and electronics that read data and information from it to support safety of these reactor,while in operation with a built in PRA(probabilistic risk assessment),which requires augmentation of AI in them to enhance performance of human operators that are engaged with day-to-day smooth operation of these reactors to make them safe and safer as well as resilience against any natural or man-made disasters by obtaining information through ML from DL that is collecting massive stream of data coming via omni-direction.Integration of AI with HI(human intelligence)is not separable,when it comes to operation of these smart SMRs with state of the art and smart control rooms with human in them as actors.This TM(technical memorandum)is describing the necessity of AI playing with nuclear reactor power plant of GEN-IV being in operation within near term sooner than later,when specially we are facing today’s cyber-attacks with their smart malware agents at work.

Protection Strategies against Cascading Failure for Power Systems of Ring Network

Power grid vulnerability is a key issue with large blackouts, causing power disruption for millions of people. The complexity of power grid, together with excessive number of components, makes it difficult to be modeled. Currently, researchers use complex networks to model and study the performance of power grids. In fact, power grids can be modeled into a complex network by making use of ring network topology, with substations and transmission lines denoted as nodes and edges, respectively. In this paper, three protection schemes are proposed and their effectiveness in protecting the power network under high and low-load attacks is studied. The proposed schemes, namely, Cascaded Load Cut-off (CLC), Cascaded Load Overflow (CLO) and Adaptive-Cascaded Load Overflow (A-CLO), improve the robustness of the power grids, i.e., decrease the value of critical tolerance. Simulation results show that CLC and CLO protection schemes are more effective in improving the robustness of networks than the A-CLO protection scheme. However, the CLC protection scheme is effective only at the expense that certain percentage of the network will have no power supply. Thus, results show that the CLO protection scheme dominates the other protection schemes, CLC and A-CLO, in terms of the robustness of the network, improved with the precise amount of load cut-off determined.

Towards electric digital twin grid: Technology and framework review

The major hindrances in the energy system are ecological consciousness, lack of clean and sustainableenergy management, insufficient energy distribution–transmission–optimization, expensive power transfercosts, and increased customer knowledge of energy charges. Thus why, universal access to the grid with highcybersecurity, and reliability is needed to solve all these challenges. The digital twin concept turns a newdimension of technology into the world. Electric Digital Twin grid can perform online analysis of the grid inreal-time and integrates all the past and present data and express the current grid status to the producers andconsumers and also predicts the future grid status. Thus, the power grid transmission loss and location of theoverheated line and power connection missing can be detected in addition decision-making and self-healingcan possible. The future prediction saves the power grid from small to long accidents such as power outagesand even blackout problems. The whole consumers and nation feel relief from these types of accidents andsaves from large economic and business loss. The blockchain-enabled digital twin grid provides high securityfor the grid from cyberattacks. The paper conveys the framework of the electric digital twin grid and theconcept of the DT grid processing and the way of serving the producer, prosumers, consumers even the wholenation in infrastructure, education, research, economic, business, and political development.

Caspian Energy Ring: Prospective vision

This paper presents the results of a technical and economic optimization study of the prospects of the Caspian Energy Ring(CER),connecting power systems of Russia,countries of the Caucasus,Central Asia,and South Asia.The CER,belonging partly to the emerging Asian Supergrid and partly to the existing European Supergrid,will become a bridge connecting these supergrids,laying the foundation for forming a global energy interconnection in the long term.The expansion of carbon-free renewable and nuclear facilities,low-carbon gas-fired power plants,and traditional thermal and hydro energy sources within the CER were considered in this study.The positive economic benefits of the creation of the CER are presented.Preliminary characteristics of the potential CER were also estimated.

Impacts of a Japan–South Korea power system interconnection on the competitiveness of electric power companies according to power exchange prices

In many regions,international power system interconnections provide economic,energy-security,environmental,and technical benefits.In contrast,such interconnections remain scarce in Northeast Asia.In 2016,after approving a joint memorandum of understanding between major electric power companies from China,Japan,South Korea,and Russia,related initiatives regained momentum in the region.Nevertheless,the corresponding developments in Japan remain limited,mainly owing to the lack of involvement of Japanese electric power companies.This study represents a pioneering attempt to provide an economic assessment based on power exchange prices of a power system interconnection between Japan and South Korea regarding the competitiveness of electric power companies in terms of competitive business segments and strategic consequences.We found that although the position of Japanese generators may slightly deteriorate,that of the supply segment would substantially improve,thus suggesting that more opportunities than threats are derived from the interconnection.This promising outcome may foster the adoption of an interconnection with South Korea considering the positive economic and business perspectives in Japan.Furthermore,realizing the interconnection may improve the energy security and air quality in the region.

Feasibility Ananlysis of Building Pithead Power Plants in North Shaanxi and Ningxia Coal Bases

North Shaanxi and Ningxia are extremely abundant in coal resources, with excellent geographical positions and transport facilities, suitable to build large size pithead power plants. This paper details the coal resources in North Shaanxi Province and Ningxia Autonomous Region, fuel coal and transportation conditions for building large size pithead power plants, and carries out the analyses of economic benefits and electricity prices of bidding for access to grid for the six recommended power plants. The analyses show that these power plants, after built up, will have strong competitive powers and make contributions for the sustainable development of power industry in North China and Shandong Province.

Managing power grids through topology actions: A comparative study between advanced rule-based and reinforcement learning agents

The operation of electricity grids has become increasingly complex due to the current upheaval and the increase in renewable energy production.As a consequence,active grid management is reaching its limits with conventional approaches.In the context of the Learning to Run a Power Network(L2RPN)challenge,it has been shown that Reinforcement Learning(RL)is an efficient and reliable approach with considerable potential for automatic grid operation.In this article,we analyse the submitted agent from Binbinchen and provide novel strategies to improve the agent,both for the RL and the rule-based approach.The main improvement is a N-1 strategy,where we consider topology actions that keep the grid stable,even if one line is disconnected.More,we also propose a topology reversion to the original grid,which proved to be beneficial.The improvements are tested against reference approaches on the challenge test sets and are able to increase the performance of the rule-based agent by 27%.In direct comparison between rule-based and RL agent we find similar performance.However,the RL agent has a clear computational advantage.We also analyse the behaviour in an exemplary case in more detail to provide additional insights.Here,we observe that through the N-1 strategy,the actions of both the rule-based and the RL agent become more diversified.

Evaluation of greenhouse gas emission reduction potential of a demand–response solution:a carbon handprint case study of a virtual power plant

The transition towards zero-carbon energy production is necessary to limit global warming.Smart energy systems have facilitated the control of demand-side resources to maintain the stability of the power grid and to provide balancing power for increasing renewable energy production.Virtual power plants are examples of demand–response solutions,which may also enable greenhouse gas(GHG)emission reductions due to the lower need for fossil-based balancing energy in the grid and the increased share of renewables.The aim of this study is to show how potential GHG emission reductions can be assessed through the carbon handprint approach for a virtual power plant(VPP)in a grid balancing market in Finland.According to our results,VPP can reduce the hourly based GHG emissions in the studied Finnish grid systems compared with the balancing power without the VPP.Typical energy sources used for the balance power are hydropower and fossil fuels.The reduction potential of GHG emissions varies from 68%to 98%depending on the share of the used energy source for the power balancing,thus VPPs have the potential to significantly reduce GHG emissions of electricity production and hence help mitigate climate change.