A Wind Power Prediction Framework for Distributed Power Grids

To reduce carbon emissions,clean energy is being integrated into the power system.Wind power is connected to the grid in a distributed form,but its high variability poses a challenge to grid stability.This article combines wind turbine monitoring data with numerical weather prediction(NWP)data to create a suitable wind power prediction framework for distributed grids.First,high-precision NWP of the turbine range is achieved using weather research and forecasting models(WRF),and Kriging interpolation locates predicted meteorological data at the turbine site.Then,a preliminary predicted power series is obtained based on the fan’s wind speed-power conversion curve,and historical power is reconstructed using variational mode decomposition(VMD)filtering to form input variables in chronological order.Finally,input variables of a single turbine enter the temporal convolutional network(TCN)to complete initial feature extraction,and then integrate the outputs of all TCN layers using Long Short Term Memory Networks(LSTM)to obtain power prediction sequences for all turbine positions.The proposed method was tested on a wind farm connected to a distributed power grid,and the results showed it to be superior to existing typical methods.

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.

Impact of interconnections and renewable energy integration on the Philippine-Sabah Power Grid systems

This study presents a comprehensive impact analysis of the rotor angle stability of a proposed international connection between the Philippines and Sabah,Malaysia,as part of the Association of Southeast Asian Nations(ASEAN)Power Grid.This study focuses on modeling and evaluating the dynamic performance of the interconnected system,considering the high penetration of renewable sources.Power flow,small signal stability,and transient stability analyses were conducted to assess the ability of the proposed linked power system models to withstand small and large disturbances,utilizing the Power Systems Analysis Toolbox(PSAT)software in MATLAB.All components used in the model are documented in the PSAT library.Currently,there is a lack of publicly available studies regarding the implementation of this specific system.Additionally,the study investigates the behavior of a system with a high penetration of renewable energy sources.Based on the findings,this study concludes that a system is generally stable when interconnection is realized,given its appropriate location and dynamic component parameters.Furthermore,the critical eigenvalues of the system also exhibited improvement as the renewable energy sources were augmented.

A Federated Named Entity Recognition Model with Explicit Relation for Power Grid

The power grid operation process is complex,and many operation process data involve national security,business secrets,and user privacy.Meanwhile,labeled datasets may exist in many different operation platforms,but they cannot be directly shared since power grid data is highly privacysensitive.How to use these multi-source heterogeneous data as much as possible to build a power grid knowledge map under the premise of protecting privacy security has become an urgent problem in developing smart grid.Therefore,this paper proposes federated learning named entity recognition method for the power grid field,aiming to solve the problem of building a named entity recognition model covering the entire power grid process training by data with different security requirements.We decompose the named entity recognition(NER)model FLAT(Chinese NER Using Flat-Lattice Transformer)in each platform into a global part and a local part.The local part is used to capture the characteristics of the local data in each platform and is updated using locally labeled data.The global part is learned across different operation platforms to capture the shared NER knowledge.Its local gradients fromdifferent platforms are aggregated to update the global model,which is further delivered to each platform to update their global part.Experiments on two publicly available Chinese datasets and one power grid dataset validate the effectiveness of our method.

Multi-Criteria Decision-Making for Power Grid Construction Project Investment Ranking Based on the Prospect Theory Improved by Rewarding Good and Punishing Bad Linear Transformation

Using the improved prospect theory with the linear transformations of rewarding good and punishing bad(RGPBIT),a new investment ranking model for power grid construction projects(PGCPs)is proposed.Given the uncertainty of each index value under the market environment,fuzzy numbers are used to describe qualitative indicators and interval numbers are used to describe quantitative ones.Taking into account decision-maker’s subjective risk attitudes,a multi-criteria decision-making(MCDM)method based on improved prospect theory is proposed.First,the[−1,1]RGPBIT operator is proposed to normalize the original data,to obtain the best andworst schemes of PGCPs.Furthermore,the correlation coefficients between interval/fuzzy numbers and the best/worst schemes are defined and introduced to the prospect theory to improve its value function and loss function,and the positive and negative prospect value matrices of the project are obtained.Then,the optimization model with the maximum comprehensive prospect value is constructed,the optimal attribute weight is determined,and the PGCPs are ranked accordingly.Taking four PGCPs of the IEEERTS-79 node system as examples,an illustration of the feasibility and effectiveness of the proposed method is provided.

Study on Comprehensive Efficiency Evaluation of Rural Power Grid under Rural Revitalization Strategy Considering Regional Differences

As an essential infrastructure,the rural power grid is vital in promoting agricultural and rural carbon sequestration and improving rural energy electrification.It is necessary to carry out in-depth research on its comprehensive efficiency.Based on the requirements of“double carbon”and rural revitalization strategy for the rural Power Grid,this paper focuses on the modernization and low-carbon transformation of the rural Power Grid.It constructs an input-output index system for the investment efficiency of the rural Power Grid in China under the new situation.It uses the primary data of the rural Power Grid of 30 prefecture-level cities in China from 2019 to 2021 to evaluate the investment efficiency of the rural Power Grid in China through a three-stage DEA model.The empirical results show that:considering the regional differences,the comprehensive efficiency of the rural Power Grid in backward areas is significantly improved;that is,the three-stage DEA method can more objectively evaluate the comprehensive efficiency of the rural Power Grid.In the context of the continued promotion of the rural revitalization strategy,to improve the comprehensive efficiency of the rural Power Grid,it is necessary to improve the technical level of the rural Power Grid further and appropriately expand the scale of investment in the rural Power Grid.

Assessment on Fault Diagnosis and State Evaluation of New Power Grid:AReview

1 Introduction The proposal of the concept of“New Power System”aims to illustrate the transform direction of the traditional power system,acting as the development core of the future new power grid.To achieve this,the proposed strategic targets of“carbon neutralization and carbon peaking”must be implemented and insisted[1].The core feature of the new power system is that renewable energy plays a leading role and becomes the main source of energy supply,meanwhile,the goal of green energy utilization has also been put forward on the agenda.Green energy utilization includes two aspects,one is the exploitation and promotion of various green energy technologies,and the other is the digitalization of energy management.Under this trend,stochastic and fluctuating energy sources such as wind power and photovoltaic power replace deterministic controllable power sources such as thermal power,bringing challenges to power grid regulation and dispatching,as well as flexible operation.The large-scale integration of renewable energy and increasingly high proportion of power electronic equipment tend to bring about fundamental changes in the operation characteristics,safety control,and production mode of the power system.

Theory Study and Application of the BP-ANN Method for Power Grid Short-Term Load Forecasting

Aiming at the low accuracy problem of power system short-term load forecasting by traditional methods, a back-propagation artificial neural network （BP-ANN） based method for short-term load forecasting is presented in this paper. The forecast points are related to prophase adjacent data as well as the periodical long-term historical load data. Then the short-term load forecasting model of Shanxi Power Grid （China） based on BP-ANN method and correlation analysis is established. The simulation model matches well with practical power system load, indicating the BP-ANN method is simple and with higher precision and practicality.

Practice and Thinking on Current Planning Environmental Impact Assessment of Transmission and Transformation Power Grid in Jiangsu Province

The planning environmental impact assessment （EIA） of transmission and transformation power grid at levels of 500 and 220 kV had been finished completely in the 13 municipalities of Jiangsu Province by the end of 2012, which played important roles in guiding and planning the following transmission and transformation projects in environmental protection. In this paper, through the detail analysis on the objective and significance of the planning EIA of transmission and transformation power grid, legal basis and planning EIA practices, some suggestions and thinking about the planning EIA of transmission and transformation power grid were put forward.

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.

Sustainable Investment Forecasting of Power Grids Based on theDeep Restricted Boltzmann Machine Optimized by the Lion Algorithm

This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine(DRBM)optimized by the Lion algorithm(LA).Firstly,two factors including transmission and distribution price reform(TDPR)and 5G station construction were comprehensively incorporated into the consideration of influencing factors,and the fuzzy threshold method was used to screen out critical influencing factors.Then,the LA was used to optimize the parameters of the DRBM model to improve the model’s prediction accuracy,and the model was trained with the selected influencing factors and investment.Finally,the LA-DRBM model was used to predict the investment of a power grid enterprise,and the final prediction result was obtained by modifying the initial result with the modifying factors.The LA-DRBMmodel compensates for the deficiency of the singlemodel,and greatly improves the investment prediction accuracy of the power grid.In this study,a power grid enterprise was taken as an example to carry out an empirical analysis to prove the validity of the model,and a comparison with the RBM,support vector machine(SVM),back propagation neural network(BPNN),and regression model was conducted to verify the superiority of the model.The conclusion indicates that the proposed model has a strong generalization ability and good robustness,is able to abstract the combination of low-level features into high-level features,and can improve the efficiency of the model’s calculations for investment prediction of power grid enterprises.

Index system and methods for comprehensive assessment of cross-border power grid interconnection projects

With the global economy integration and progress in energy transformation,it has become a general trend to surpass national boundaries to achieve wider and optimal energy resource allocations.Consequently,there is a critical n eed to adopt scie ntific approaches in assessi ng cross-border power grid interconnection projects.First,con sidering the promotion of large-scale renewable energy resources and improvements in system adequacy,a comprehensive assessment index system,including costs,socio-economic benefits,environmental benefits,and technical benefits,is established in this study.Second,a synthetic assessment framework is proposed for cross-border power grid interconnection projects based on the index system comprising cost-benefit analysis,with market and network simulations,iterative methods for indicator weight evaluation,and technique for order preferenee by similarity to an ideal solution(TOPSIS)method for the project rankings.Fin ally,by assessi ng and comparing three cross-border projects betwee n Europe and Asia,the proposed index system and assessment framework have been proved to be effective and feasible;the results of this system can thus support investment decision-making related to such projects in the future.

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.

Modeling Distortion Signals of Power Grid Based on Wiener-G Functionals

The uniform mathematical model of distortion signals in power grid has been setup with the theory of Wiener-G Functional. Firstly,the Matlab simulation models were established. Secondly,the Wiener kernel of power load was found based on the Gaussian white noise as input. And then the uniform mathematical model of the power grid signal was established according to the homogeneous of the same order of Wiener functional series. Finally,taking three typical distortion sources which are semiconductor rectifier,electric locomotive and electric arc furnace in power grid as examples,we have validated the model through the Matlab simulation and analyzed the simulation errors. The results show that the uniform mathematical model of distortion signals in power grid can approximation the actual model by growing the items of the series under the condition of the enough storage space and computing speed.

Training, simulation, restoration expert system for power grid

The paper introduces some technology for training, simulation, restoration expert system of power grid, the structure of the system including function composition, hardware and software composition are discussed, knowledge representation and the method to establish device graphical library for expert system are given, the fault setting and diagnosis for training and simulation as well as restoration technology with deep first searching arithmetic and heuristic inference are presented. The research provides a good base for developing the training, simulation, restoration system of power companies.

Improved VSVPWM Modulation Method for Three-level NPC Inverter in Rural Power Grid

With the acceleration of agricultural electrification,a lot of nonlinear and shock loads appear in the rural power grid,and the resulting harmonic and reactive currents pollute the rural power grid more and more seriously.To solve the above problem,three-level neutral point clamped(NPC)inverters have been widely used,but their development is greatly restricted by the defect of neutral point voltage imbalance.In this paper,an improved virtual space vector pulse width modulation(VSVPWM)was proposed.Firstly,the mathematical models of various space vectors were established,and the influence of various space vectors on neutral point voltage was analyzed.The sum of the vector current at the neutral point was zero and the voltage control at the neutral point was completed by.introducing the time offset into different switching times of the redundant small vector.This method was simple in design and avoided the redundant calculation of the traditional VSVPWM method and tedious switch sequence design.This balancing control strategy could greatly reduce the influence of virtual vectors on neutral point voltage and effectively control the low-frequency oscillation of neutral point voltage.The validity of the method was verified by establishing a matlab simulation model.

Agents for Smart Power Grids

The future of electricity systems will compose of small-scale generation and distribution where end-users will be active participants with localized energy management systems that are able to interact on a free energy market. Software agents will most likely control power assets and interact together to decide the best and safest configuration of the power grid system. This paper presents a design of agents that can be deployed in real-time with capabilities that include optimization of resources, intensive computation, and appropriate decision-making. Jordan 51-bus system has been used for simulation with a total generation capacity of 4050 MW of which 230 MW represents renewable energy. The economic analyses demonstrated the use of smart grid technologies with 2016 generation—load profiles for nominal liquified gas (NLG) prices and ±20% sensitivity analysis. The results have shown variations in the range of 1% in the price of MWh with smart grid technologies. These variations are mainly driven by the fact that agents shift power generation to renewable power plants to produce maximum power at peak hours. As a result, there is a positive economic impact in both NLG ± 20% sensitivity analysis, due to the fact that agents coordinate to better displace expensive thermal generation with renewable generation. It is evident that renewable resources compensate for power at peak times and provide economic benefits and savings.

Coordinated voltage control of renewable energy power plants in weak sending-end power grid

The utilization of renewable energy in sending-end power grids is increasing rapidly,which brings difficulties to voltage control.This paper proposes a coordinated voltage control strategy based on model predictive control(MPC)for the renewable energy power plants of wind and solar power connected to a weak sending-end power grid(WSPG).Wind turbine generators(WTGs),photovoltaic arrays(PVAs),and a static synchronous compensator are coordinated to maintain voltage within a feasible range during operation.This results in the full use of the reactive power capability of WTGs and PVAs.In addition,the impact of the active power outputs of WTGs and PVAs on voltage control are considered because of the high R/X ratio of a collector system.An analytical method is used for calculating sensitivity coefficients to improve computation efficiency.A renewable energy power plant with 80 WTGs and 20 PVAs connected to a WSPG is used to verify the proposed voltage control strategy.Case studies show that the coordinated voltage control strategy can achieve good voltage control performance,which improves the voltage quality of the entire power plant.

Taking the Way of “Going Out”——SGCC Got the Franchise for Operating Philippine Power Grid

For Chinese power enterprises,investing overseas and actively seeking international cooperation in energy resources for mutual benefit accords with not only the desires of themselves to become bigger and stronger,but also China's energy strategy. Having won the first overseas state-level power-grid operation right,the State Grid Corporation of China (SGCC) took the lead in carrying out the strategy of "going out."

Northwest China covered by 750-kV power grid

Being abundant in hydropower, coal, wind energy and solar energy etc., Northwest China is an important energy base with great potential. In recent years, along with the vigorous development of the energy base,