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Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 74-87页

作者： Bogang Qu Zidong Wang Bo Shen Hongli dong Hongjian liu the College of Automation Engineering Shanghai University of Electric PowerShanghai 200090China IEEE the Department of Computer Science Brunel University LondonUxbridgeMiddiesex UB83PHUK the College of Information Science and Technology Donghua UniversityShanghai 200051 the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China the Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast PetroleumDaqing 163318 the Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of EducationAnhui Polytechnic UniversityWuhu 2410000 the School of Mathematics and Physics Anhui Polytechnic UniversityWuhu 241000China

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

关键词： Decentralized state estimation(SE) measurements with anomalies minimum error entropy unscented Kalman filter wide-area power systems

A benchmark-based method for evaluating hyperparameter optimization techniques of neural networks for surface water quality prediction

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Frontiers of Environmental Science & Engineering 2024年第5期18卷 13-27页

作者： Xuan Wang Yan dong Jing Yang Zhipeng liu Jinsuo Lu School of Environmental and Municipal Engineering Xi’an University of Architecture and TechnologyXi’an710055China Shaanxi Key Laboratory of Environmental Engineering Xi’an University of Architecture and TechnologyXi’an710055China State Key Laboratory of Green Building in West China Xi’an University of Architecture and TechnologyXi’an710055China

Neural networks(NNs)have been used extensively in surface water prediction tasks due to computing algorithm improvements and data *** essential step in developing an NN is the hyperparameter *** practice,it is common to manually determine hyperparameters in the studies of NNs in water resources *** may result in considerable randomness and require significant computation time;therefore,hyperparameter optimization(HPO)is *** study adopted five representatives of the HPO techniques in the surface water quality prediction tasks,including the grid sampling(GS),random search(RS),genetic algorithm(GA),Bayesian optimization(BO)based on the Gaussian process(GP),and the tree Parzen estimator(TPE).For the evaluation of these techniques,this study proposed a method:first,the optimal hyperparameter value sets achieved by GS were regarded as the benchmark;then,the other HPO techniques were evaluated and compared with the benchmark in convergence,optimization orientation,and consistency of the optimized *** results indicated that the TPE-based BO algorithm was recommended because it yielded stable convergence,reasonable optimization orientation,and the highest consistency rates with the benchmark *** optimization consistency rates via TPE for the hyperparameters hidden layers,hidden dimension,learning rate,and batch size were 86.7%,73.3%,73.3%,and 80.0%,*** the evaluation of HPO techniques directly based on the prediction performance of the optimized NN in a single HPO test,the proposed benchmark-based HPO evaluation approach is feasible and robust.

关键词： Neural networks Hyperparameter optimization Surface water quality prediction Bayes optimization Genetic algorithm

Discovering Latent Variables for the Tasks With Confounders in Multi-Agent Reinforcement Learning

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1591-1604页

作者： Kun Jiang Wenzhang liu Yuanda Wang Lu dong Changyin Sun the School of Automation Southeast UniversityNanjing 210096China the School of Artificial Intelligence Anhui UniversityHefei 230601China IEEE the School of Cyber Science and Engineering Southeast UniversityNanjing 211189China the Engineering Research Center of Autonomous Unmanned System Technology Ministry of EducationHefei 230601China

Efficient exploration in complex coordination tasks has been considered a challenging problem in multi-agent reinforcement learning(MARL). It is significantly more difficult for those tasks with latent variables that agents cannot directly observe. However, most of the existing latent variable discovery methods lack a clear representation of latent variables and an effective evaluation of the influence of latent variables on the agent. In this paper, we propose a new MARL algorithm based on the soft actor-critic method for complex continuous control tasks with confounders. It is called the multi-agent soft actor-critic with latent variable(MASAC-LV) algorithm, which uses variational inference theory to infer the compact latent variables representation space from a large amount of offline ***, we derive the counterfactual policy whose input has no latent variables and quantify the difference between the actual policy and the counterfactual policy via a distance function. This quantified difference is considered an intrinsic motivation that gives additional rewards based on how much the latent variable affects each agent. The proposed algorithm is evaluated on two collaboration tasks with confounders, and the experimental results demonstrate the effectiveness of MASAC-LV compared to other baseline algorithms.

关键词： Latent variable model maximum entropy multi-agent reinforcement learning(MARL) multi-agent system

Directional amine-based solvent extraction for simultaneous enhanced water recovery,salt separation and effective descaling from hypersaline brines

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Frontiers of Environmental Science & Engineering 2024年第3期18卷 83-92页

作者： Yuyao Zhang Litao Jia Jin Zhao Xuming liu Shuyu dong Chuanyang liu Yuanyuan Cui Shougang Research Institute of Technology Beijing 100043China Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision School of EnvironmentTsinghua UniversityBeijing 100084China

The feasibility of simultaneous water recovery,salt separation and effective descaling of hypersaline brine was investigated by diisopropylamine(DIPA)-based directional solvent extraction(DSE),using diluted/concentrated seawater with initial saline concentration range of 12–237 g/L at extraction temperatures of 5 and 15℃,*** water recovery shows an obvious boundary at saline concentration of 115 g/L under dual effect of specific water extraction efficiency and extraction *** Cl^(–) ion concentration in product water is in sharp contrast to the nearly complete removal of SO_(4)^(2–)and hardness ions,indicating that DIPA-based DSE process indeed achieved efficient separation and purification of Cl^(–) ion from hypersaline ***,the radical precipitation of Mg^(2+)and Ca^(2+)ions in form of Mg(OH)_(2)and CaCO_(3)demonstrates effective descaling potential,although it leads to more DIPA residues in dewatered raffinate than product ***,an exponential correlation between the Cl^(–) removal efficiency and specific water extraction efficiency further reveals the intrinsic relationship of water extraction process and transfer of Cl^(–) ion to the product ***,the study provides a novel approach for integrating the water recovery and separation of Cl^(–) ion from ultra-high-salinity brines with radical precipitation of Mg^(2+)and Ca^(2+) ions in one step.

关键词： Hypersaline brines Directional solvent extraction Salt separation Ca^(2+)and Mg^(2+)descaling

Data and Model Driven Task Offloading Strategy in the Dynamic Mobile Edge Computing System

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Journal of Systems Science & Complexity 2024年第1期37卷 351-368页

作者： dong Hairong WU Wei SONG Haifeng liu Zhen ZHANG Zixuan School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China School of Electronic and Information Engineering BeiHang UniversityBeijing 100191China CRSC Research&Design Institute Group Co. Ltd.Beijing 100070China

Mobile Edge Computing(MEC)provides communication and computational capabilities for the industrial Internet,meeting the demands of latency-sensitive ***,traditional model-driven task offloading strategies face challenges in adapting to situations with unknown network communication status and computational *** limitation becomes notably significant in complex industrial networks of high-speed *** by these considerations,a data and model-driven task offloading problem is proposed in this paper.A redundant communication network is designed to adapt to anomalous channel states when tasks are offloaded to edge *** link switching mechanism is executed by the train according to the attributes of the completed *** task offloading optimization problem is formulated by introducing data-driven prediction of communication states into the traditional ***,the optimal strategy is achieved by employing the informer-based prediction algorithm and the quantum particle swarm optimization method,which effectively tackle real-time optimization problems due to their low time *** simulations illustrate that the data and model-driven task offloading strategy can predict the communication state in advance,thus reducing the cost of the system and improving its robustness.

关键词： Data driven model informer mobile edge computing quantum particle swarm optimization task offloading.

Comparison of Direct Pore-Scale and Volume-Averaging Methods for the Performance Evaluation of Porous Volumetric Solar Receiver

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Journal of Thermal Science 2024年第5期33卷 1607-1617页

作者： DU Shen HE Yaling LI dong liu Zhanbin LI Mengjie National Innovation Platform(Center)for Industry-Education Integration of Energy Storage Technology Key Laboratory of Thermo-Fluid Science and Engineering of Ministry of EducationXi’an Jiaotong UniversityXi’an710049China

Direct pore-scale and volume-averaging numerical simulations are two methods for investigating the performance of porous volumetric solar *** clarify the difference in the prediction of heat transfer processes,a direct comparison between these two methods was conducted at both steady state and transient *** numerical models were established based on X-ray computed tomography scans and a local thermal non-equilibrium model,*** empirical parameters,which are indispensable to the volume-averaging simulation,were determined by Monte Carlo ray tracing and direct pore-scale numerical *** predicted outlet air temperature of the receiver by the volume-averaging simulation method corresponded satisfactorily to that in the direct pore-scale *** largest discrepancies were observed when the receiver's working temperature was elevated,with differences of 5.5%and 3.68%for the steady state and transient state simulations,***,the volume-averaging method is incapable of capturing the local temperature information of the air and porous *** underestimates the inlet temperature of the receiver,leading to an overestimation of the receiver's thermal efficiency,with the largest difference being 6.51%.The comparison results show that the volume-averaging model is a good approximation to the pore-scale model when the empirical parameters are carefully selected.

关键词： porous media volumetric solar receiver pore-scale method volume-averaging method thermal performance

Lightweight innovation ADIs help development of renewable energy and new technology industries in China

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China Foundry 2024年第5期21卷 507-515页

作者： Qi-dong Yan Xu-dong Gong Wen-bang Gong Jin-cheng liu ADI Committee of China Foundry Association Beijing 100000China Yuzhou Henglilai New Materials Co. Ltd.Xuchang 452570HenanChina Kunshan Changjian Foundry Industry Co.Ltd. Kunshan 215311JiangsuChina School of Mechanical Engineering and Automation Wuhan Textile UniversityWuhan 430200China WFO Ferrous Metals Commission Shenyang 110022China

The world is undergoing profound changes in energy and *** are vigorously developing new sustainable energy sources and *** energy sources encompass various technologies such as wind turbines,solar energy,nuclear energy,and ***,emerging technology fields include new energy vehicles,robots,and artificial intelligence devices,among *** renewable energy industries and implementation of new technologies necessitate the development and adoption of new equipment and *** ductile iron(ADI)is renowned for its unique microstructure and superior *** utilizing ADI,lightweight and innovative castings can be designed to not only reduce weight but also save energy and decrease *** importantly,these castings enhance the efficiency and reliability of new energy equipment and emerging technology *** paper describes the development,applications,and future prospects of lightweight and innovative ADI castings within sectors such as solar photovoltaic(PV),wind power generation,industry robots,and trucks in China.

关键词： lightweight ADI renewable energy emission reduction

Prediction on Failure Pressure of Pipeline Containing Corrosion Defects Based on ISSA-BPNNModel

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Energy Engineering 2024年第3期121卷 821-834页

作者： Qi Zhuang dong liu Zhuo Chen PetroChina Changqing Oilfield Company The Second Gas Production PlantXi’an710000China PetroChina Changqing Oilfield Company Safety and Environmental Supervision Department Co.Ltd.Xi’an710000China Sinopec Northwest Oilfield Company The Second Oil Production Plant Co.Ltd.Urumqi830016China

Oil and gas pipelines are affected by many factors,such as pipe wall thinning and pipeline *** prediction of failure pressure of oil and gas pipelines can provide technical support for pipeline safety *** at the shortcomings of the BP Neural Network(BPNN)model,such as low learning efficiency,sensitivity to initial weights,and easy falling into a local optimal state,an Improved Sparrow Search Algorithm(ISSA)is adopted to optimize the initial weights and thresholds of BPNN,and an ISSA-BPNN failure pressure prediction model for corroded pipelines is *** 61 sets of pipelines blasting test data as an example,the prediction model was built and predicted by MATLAB software,and compared with the BPNN model,GA-BPNN model,and SSA-BPNN *** results show that the MAPE of the ISSA-BPNN model is 3.4177%,and the R2 is 0.9880,both of which are superior to its comparison *** the ISSA-BPNN model has high prediction accuracy and stability,and can provide support for pipeline inspection and maintenance.

关键词： Oil and gas pipeline corrosion defect failure pressure prediction sparrow search algorithm BP neural network logistic chaotic map

Electromechanical Transient Modeling Analysis of Large-Scale New Energy Grid Connection

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Energy Engineering 2024年第4期121卷 1109-1125页

作者： Shichao Cao Yonggang dong Xiaoying liu Department of Electrical Engineering Hebei Vocational University of Technology and EngineeringXingtai054000China

The synchronous virtual machine uses inverter power to imitate the performance of the conventional synchronous *** also has the same inertia,damping,frequency,voltage regulation,and other external performance as the *** is the key technology to realize new energy grid connections’stable and reliable *** project studies a dynamic simulation model of an extensive new energy power system based on the virtual synchronous motor.A new energy storage method is *** mathematical energy storage model is established by combining the fixed rotor model of a synchronous virtual machine with the charge-discharge power,state of charge,operation efficiency,dead zone,and inverter *** rapid conversion of energy storage devices absorbs the excess instantaneous kinetic energy caused by *** branch transient of the critical cut set in the system can be confined to a limited ***,the virtual synchronizer’s kinetic and potential energy can be efficiently converted into an instantaneous *** simulation of power system analysis software package(PSASP)verifies the correctness of the theory and algorithm in this *** paper provides a theoretical basis for improving the transient stability of new energy-connected power grids.

关键词： New energy grid connection transient electromechanical modeling synchronous virtual machine PSASP software energy storage