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Comprehensive Evaluation of Electric Power Prediction Models Based on D-S Evidence Theory Combined with Multiple Accuracy Indicators

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Journal of Modern Power Systems and Clean Energy 2022年第3期10卷 597-605页

作者： Qiong Cui jizhong zhu Jie Shu Lei Huang Zetao Ma School of Electric Power South China University of TechnologyGuangzhouChina Key Laboratory of Renewable Energy Guangzhou Institute of Energy ConversionChinese Academy of SciencesGuangzhouChina

A comprehensive evaluation method of electric power prediction models using multiple accuracy indicators is *** obtain the preferred models,this paper selects a number of accuracy indicators that can reflect the accuracy of single-point prediction and the correlation of predicted data,and carries out a comprehensive ***,according to Dempster-Shafer(D-S)evidence theory,a new accuracy indicator based on the relative error(RE)is proposed to solve the problem that RE is inconsistent with other indicators in the quantity of evaluation values and cannot be adopted at the same ***,a new dimensionless method is proposed,which combines the efficiency coefficient method with the extreme value method to unify the accuracy indicator into a dimensionless positive indicator,to avoid the conflict between pieces of evidence caused by the minimum value of *** this basis,the evidence fusion is used to obtain the comprehensive evaluation value of each ***,the principle and the process of consistency checking of the proposed method using the entropy method and the linear combination formula are ***,the effectiveness and the superiority of the proposed method are validated by an illustrative instance.

关键词： Dempster-Shafer(D-S)evidence theory multiple accuracy indicators electric power prediction model comprehensive evaluation

Detection of False Data Injection Attacks on Load Frequency Control System with Renewable Energy Based on Fuzzy Logic and Neural Networks

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Journal of Modern Power Systems and Clean Energy 2022年第6期10卷 1576-1587页

作者： Ziyu Chen jizhong zhu Shenglin Li Yun Liu Tengyan Luo School of Electric Power Engineering South China University of TechnologyGunagzhou 510640China

Load frequency control(LFC)system may be destroyed by false data injection attacks(FDIAs)and consequently the security of the power system will be ***-efficiency FDIA detection can reduce the damage and power loss to the power *** paper defines various typical and hybrid FDIAs,and the influence of several FDIAs with different characteristics on the multi-area LFC system is *** detect various attacks,we introduce an improved data-driven method,which consists of fuzzy logic and neural *** logic has the features of high applicability,robustness,and agility,which can make full use of ***,we construct the LFC system on MATLAB/Simulink platform,and systematically simulate the experiments that FDIAs affect the LFC system by tampering with measurement *** them,considering the large-scale penetration of renewable energy with intermittency and volatility,we generate three simulation scenarios with or without renewable energy ***,the performance for detecting FDIAs of the improved method is verified by simulation data samples.

关键词： Load frequency control(LFC) wind turbine and photovoltaic generation fuzzy logic neural network

A Non-Iterative Network Utilization Pricing Mechanism for P2P Energy Trading

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 1301-1306页

作者： Yun Liu Yunqiang Gao Yuanzheng Li jizhong zhu Hoay Beng Gooi School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China School of Artificial Intelligence and Automation Ministry of Education Key Laboratory of Image Processing and Intelligence ControlHuazhong University of Science and TechnologyWuhan 430074China School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore IEEE

To sustain operation and maintenance of an active distribution network(ADN),a network fee should be charged by the distribution network service provider(DNSP)for facilitating the P2P energy trading *** this end,this paper models the interaction among the DNSP and multiple prosumers as a Stackelberg game,and then develops a non-iterative and decentralized transactive mechanism to simultaneously achieve optimal network utilization pricing and peer-to-peer(P2P)*** results in an ADN with four prosumers connected to a common substation bus validate the effectiveness and efficiency of the proposed scheme.

关键词： Distribution network service provider network fee non-iterative peer-to-peer trading prosumer

Short-term Residential Load Forecasting Based on K-shape Clustering and Domain Adversarial Transfer Network

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Journal of Modern Power Systems and Clean Energy 2024年第4期12卷 1239-1249页

作者： jizhong zhu Yuwang Miao Hanjiang Dong Shenglin Li Ziyu Chen Di Zhang School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China Department of Electrical Engineering The Hong Kong Polytechnic UniversityHong KongChina

In recent years,the expansion of the power grid has led to a continuous increase in the number of consumers within the distribution ***,due to the scarcity of historical data for these new consumers,it has become a complex challenge to accurately forecast their electricity demands through traditional forecasting *** paper proposes an innovative short-term residential load forecasting method that harnesses advanced clustering,deep learning,and transfer learning technologies to address this *** begin,this paper leverages the domain adversarial transfer *** employs limited data as target domain data and more abundant data as source domain data,thus enabling the utilization of source do-main insights for the forecasting task of the target ***,a K-shape clustering method is proposed,which effectively identifies source domain data that align optimally with the target domain,and enhances the forecasting ***,a composite architecture is devised,amalgamating attention mechanism,long short-term memory network,and seq2seq *** composite structure is integrated into the domain adversarial transfer network,bolstering the performance of feature extractor and refining the forecasting *** illustrative analysis is conducted using the residential load dataset of the Independent System Operator to validate the proposed method *** the case study,the relative mean square error of the proposed method is within 30 MW,and the mean absolute percentage error is within 2%.A signifi-cant improvement in accuracy,compared with other comparative experimental results,underscores the reliability of the proposed *** findings unequivocally demonstrate that the proposed method advocated in this paper yields superior forecasting results compared with prevailing mainstream forecast-ing methods.

关键词： Load forecasting domain adversarial K-shape clustering long short-term memory network seq2seq network attention mechanism

A Two-stage Stochastic Mixed-integer Programming Model for Resilience Enhancement of Active Distribution Networks

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Journal of Modern Power Systems and Clean Energy 2023年第1期11卷 94-106页

作者： Hongzhou Chen Jian Wang jizhong zhu Xiaofu Xiong Wei Wang Hongrui Yang State Key Laboratory of Power Transmission Equipment&System Security and New Technology Chongqing UniversityChongqing 400044China South China University of Technology Guangzhou 510641China Electric Power Research Institute State Grid Chongqing Electric Power CompanyChongqing 401123China IEEE

Most existing distribution networks are difficult to withstand the impact of meteorological disasters. With the development of active distribution networks(ADNs), more and more upgrading and updating resources are applied to enhance the resilience of ADNs. A two-stage stochastic mixed-integer programming(SMIP) model is proposed in this paper to minimize the upgrading and operation cost of ADNs by considering random scenarios referring to different operation scenarios of ADNs caused by disastrous weather events. In the first stage, the planning decision is formulated according to the measures of hardening existing distribution lines, upgrading automatic switches, and deploying energy storage resources. The second stage is to evaluate the operation cost of ADNs by considering the cost of load shedding due to disastrous weather and optimal deployment of energy storage systems(ESSs) under normal weather condition. A novel modeling method is proposed to address the uncertainty of the operation state of distribution lines according to the canonical representation of logical constraints. The progressive hedging algorithm(PHA) is adopted to solve the SMIP model. The IEEE 33-node test system is employed to verify the feasibility and effectiveness of the proposed method. The results show that the proposed model can enhance the resilience of the ADN while ensuring economy.

关键词： Active distribution network(ADN) resilience disastrous weather event stochastic programming

Day-ahead Network-constrained Unit Commitment Considering Distributional Robustness and Intraday Discreteness:A Sparse Solution Approach

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Journal of Modern Power Systems and Clean Energy 2023年第2期11卷 489-501页

作者： Xiaodong Zheng Baorong Zhou Xiuli Wang Bo Zeng jizhong zhu Haoyong Chen Waisheng Zheng School of Electrical Engineering Xi’an Jiaotong UniversityXi’an 710049China Electric Power Research Institute of China Southern Power Grid Co. Ltd.Guangzhou 510663China Shaanxi Key Laboratory of Smart Grid School of Electrical EngineeringXi’an Jiaotong UniversityXi’an 710049China Department of Industrial Engineering and the Department of Electrical and Computer EngineeringUniversity of PittsburghPittsburghPA 15260USA School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China China Southern Power Grid Co. Ltd.Guangzhou 510663China

Quick-start generation units are critical devices and flexible resources to ensure a high penetration level of renewable energy in power *** considering the wind uncertainty and both binary and continuous decisions of quickstart generation units within the intraday dispatch,we develop a Wasserstein-metric-based distributionally robust optimization model for the day-ahead network-constrained unit commitment(NCUC)problem with mixed-integer *** propose two feasible frameworks for solving the optimization *** approximates the continuous support of random wind power with a finite number of events,and the other leverages the extremal distributions *** solution frameworks rely on the classic nested column-and-constraint generation(C&CG)*** is shown that due to the sparsity of L_(1)-norm Wasserstein metric,the continuous support of wind power generation could be represented by a discrete one with a small number of events,and the rendered extremal distributions are sparse as *** this reduction,the distributionally robust NCUC model with complicated mixed-integer recourse problems can be efficiently handled by both solution *** studies are carried out,demonstrating that the model considering quick-start generation units ensures unit commitment(UC)schedules to be more robust and cost-effective,and the distributionally robust optimization method captures the wind uncertainty well in terms of out-of-sample tests.

关键词： Unit commitment distributional robustness mixed-integer recourse nested column-and-constraint generation(C&CG) sparsity Wasserstein metric

Probabilistic Residential Load Forecasting with Sequence-to-sequence Adversarial Domain Adaptation Networks

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Journal of Modern Power Systems and Clean Energy 2024年第5期12卷 1559-1571页

作者： Hanjiang Dong jizhong zhu Shenglin Li Yuwang Miao Chi Yung Chung Ziyu Chen the School of Electric Power Engineering South China University of TechnologyGuangzhouChina the Department of Electrical Engineering The Hong Kong Polytechnic UniversityHong KongChina

Lately,the power demand of consumers is increasing in distribution networks,while renewable power generation keeps penetrating into the distribution *** data make it hard to accurately predict the new residential load or newly built apartments with volatile and changing time-series characteristics in terms of frequency and ***,this paper proposes a short-term probabilistic residential load forecasting scheme based on transfer learning and deep learning ***,we formulate the short-term probabilistic residential load forecasting ***,we propose a sequence-to-sequence(Seq2Seq)adversarial domain adaptation network and its joint training strategy to transfer generic features from the source domain(with massive consumption records of regular loads)to the target domain(with limited observations of new residential loads)and simultaneously minimize the domain difference and forecasting errors when solving the forecasting *** implementation,the dominant techniques or elements are used as the submodules of the Seq2Seq adversarial domain adaptation network,including the Seq2Seq recurrent neural networks(RNNs)composed of a long short-term memory(LSTM)encoder and an LSTM decoder,and quantile ***,this study conducts the case studies via multiple evaluation indices,comparative methods of classic machine learning and advanced deep learning,and various available data of the new residentical loads and other regular *** experimental results validate the effectiveness and stability of the proposed scheme.

关键词： Domain adaptation neural network residential load forecasting transfer learning probabilistic forecasting

Review of demand-side energy sharing and collective self-consumption schemes in future power systems

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iEnergy

iEnergy 2023年第2期2卷 119-132页

作者： jizhong zhu Shenglin Li Alberto Borghetti Jing Lan Hong Li Taiheng Guo School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China Department of Electrical Electronic and Information EngineeringUniversity of BolognaBologna 40136Italy

The widespread use of distributed energy sources provides exciting potential for demand-side energy sharing and collective self-consumption ***-side energy sharing and collective self-consumption systems are committed to coordinating the operation of distributed generation,energy storage,and load ***,with the development of Internet technology,sharing economy is rapidly penetrating various *** application of sharing economy in the energy sector enables more and more end-users to participate in energy ***,the deployment of energy sharing technologies poses many *** paper comprehensively reviews recent developments in demand-side energy sharing and collective self-consumption *** definition and classification of sharing economy are presented,with a focus on the applications in the energy sector:virtual power plants,peer-to-peer energy trading,shared energy storage,and microgrid energy sharing *** and future research directions are thoroughly discussed.

关键词： Energy sharing future power systems demand-side energy management distributed energy resources sharing economy

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Guest Editorial

Journal of Modern Power Systems and Clean Energy 2017年第3期5卷 295-298页

作者： Mohammad SHAHIDEHPOUR jizhong zhu Ming NI Illinois Institute of Technology USA China Southern Power Grid China State Grid Electric Power Research Institute China

We are very pleased to present to you the special section of the Journal of Modern Power Systems and Clean Energy on the coordinated planning,operation,and control of electricity and natural gas *** special section aims at addressing the existing challenges in integrated planning,operation and control of natural gas and electric power systems that will enhance the resilience,economics,efficiency,reliability sustainability,and security of both *** had invited original submissions from various countries focusing on the computational and technological aspects of the integrated natural gas and electric power systems.

关键词： USA Guest Editorial