A Joint Estimation Method of SOC and SOH for Lithium-ion Battery Considering Cyber-Attacks Based on GA-BP

To improve the estimation accuracy of state of charge(SOC)and state of health(SOH)for lithium-ion batteries,in this paper,a joint estimation method of SOC and SOH at charging cut-off voltage based on genetic algorithm(GA)combined with back propagation(BP)neural network is proposed,the research addresses the issue of data manipulation resulting fromcyber-attacks.Firstly,anomalous data stemming fromcyber-attacks are identified and eliminated using the isolated forest algorithm,followed by data restoration.Secondly,the incremental capacity(IC)curve is derived fromthe restored data using theKalman filtering algorithm,with the peak of the ICcurve(ICP)and its corresponding voltage serving as the health factor(HF).Thirdly,the GA-BP neural network is applied to map the relationship between HF,constant current charging time,and SOH,facilitating the estimation of SOH based on HF.Finally,SOC estimation at the charging cut-off voltage is calculated by inputting the SOH estimation value into the trained model to determine the constant current charging time,and by updating the maximum available capacity.Experiments show that the root mean squared error of the joint estimation results does not exceed 1%,which proves that the proposed method can estimate the SOC and SOH accurately and stably even in the presence of false data injection attacks.

Dynamic Equivalent Modeling for Black-box Microgrids Under Multi-operating-point by Using LSTM

Since the high penetration of distributed energy sources complicates the dynamics of electrical power systems,accurate dynamic models are indispensable for study on the transient behavior of the microgrid(MG).In some practices,the lack of full detailed information results in failure of dif-ferential equation based dynamic modeling,which leads to a demand for a black-box MG modeling method.It is a critical challenge to maintain the effectiveness of the black-box model under a wide operating range and various fault conditions.In this paper,inspired by the mathematical equivalence between the recurrent neural network(RNN)and differential-algebraic equations(DAEs),a dynamic equivalent modeling method,using long short-term memory(LSTM),is presented to tackle this challenge.At first,the modeling equivalence and advantages of our basic idea are explained.Then,modeling procedures,including data preparation and design guidelines,are presented.Finally,the proposed method is applied to a multi-microgrid testing system for performance evaluation.The results,under various scenarios,reveal that the proposed modeling method has an adequate capability for representing the dynamic behaviors of a black-box MG under grid fault and operating point changing conditions.Index Terms-Deep learning,dynamic behavior,dynamic equivalent model,microgrid,neural network.

Review of Networked Microgrid Protection:Architectures,Challenges,Solutions,and Future Trends

Design and selection of advanced protection schemes have become essential for reliable and secure operation of networked microgrids.Various protection schemes that allow correct operation of microgrids have been proposed for individual systems in different topologies and connections.Nevertheless,protection schemes for networked microgrids are still in devel-opment,and further research is required to design and operate advanced protection in interconnected systems.Interconnection of these microgrids in different nodes with various intercon-nection technologies increases fault occurrence and complicates protection operation.This paper aims to point out challenges in developing protection for networked microgrids,potential solutions,and research areas that need to be addressed for their development.First,this article presents a systematic analysis of different microgrid clusters proposed since 2016,including several architectures of networked microgrids,operation modes,components,and utilization of renewable sources,which have not been widely explored in previous review papers.Second,the paper presents a discussion on protection systems currently available for microgrid clusters,current challenges,and solutions that have been proposed for these systems.Finally,it discusses the trend of protection schemes in networked microgrids and presents some conclusions related to implementation.IndexTerms—Adaptive eprotection,microgrid cluster,microgrid,multiple microgrid,networked microgrid,real-time simulation,smart grid.