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学者姓名：丁涛
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Abstract ：
Promoting the construction of the power market and the implementation of renewable energy policies to facilitate the use of renewable energy has become the industry consensus. In recent years, the renewable energy installed capacity in China has exploded, the varieties of market-oriented transactions for renewable energy have been continuously enriched, and the renewable energy policies also have been improved. However, the lack of quantitative analysis synthetically considering the impact of market, policy, and physical boundary on renewable energy utilization makes it difficult to measure and compare the effect of power market and policies. To solve this problem, this paper constructs a quantitative analysis model for renewable energy utilization and analyzes the influence mechanism of the market, policy, and physical boundary on renewable energy utilization to minimize system operating costs. The validity of the proposed model is verified by numerical results. © 2022 IEEE.
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| GB/T 7714 | Xu, Liang , Dong, Xiaoliang , Qiao, Ning et al. Quantitative Analysis of the Impact of Power Market and Policy on Renewable Energy Utilization [C] . 2022 : 976-981 . |
| MLA | Xu, Liang et al. "Quantitative Analysis of the Impact of Power Market and Policy on Renewable Energy Utilization" . (2022) : 976-981 . |
| APA | Xu, Liang , Dong, Xiaoliang , Qiao, Ning , Zhang, Chao , Sun, Yuge , Ding, Tao . Quantitative Analysis of the Impact of Power Market and Policy on Renewable Energy Utilization . (2022) : 976-981 . |
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Abstract ：
Frequency regulation (FR) plays an important role in maintaining the power balance and stability of power systems. How to fairly and reasonably compensate generators and actively stimulate generators in the frequency regulation ancillary service market is an urgent problem to be solved by power market reforms. In this paper, a blockchain community thinking with decentralization, multi-party consensus and token incentive was proposed. Based on the token incentive feature, an FR credit was designed to integrate the global FR effect and individual participation performance, and then a frequency response model of the distributed FR system with decentralized features was established. Furthermore, the settlement process of the FR credit was designed by using multiparty consensus thinking, which can motivate generators to participate in FR and ensure the authenticity and reliability of the results. Case study verifies the effectiveness of the distributed FR system, which can effectively complete the system FR tasks and credit settlements, and fully mobilize the FR generators to enhance the efficiency of distributed FR resources. © 2022 Chin. Soc. for Elec. Eng.
Keyword ：
Blockchain Commerce Frequency response
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| GB/T 7714 | Mu, Chenggang , Ding, Tao , Ju, Chang et al. Power System Frequency Regulation Model Based on Blockchain Community Thinking [J]. | Proceedings of the Chinese Society of Electrical Engineering , 2022 , 42 (4) : 1375-1387 . |
| MLA | Mu, Chenggang et al. "Power System Frequency Regulation Model Based on Blockchain Community Thinking" . | Proceedings of the Chinese Society of Electrical Engineering 42 . 4 (2022) : 1375-1387 . |
| APA | Mu, Chenggang , Ding, Tao , Ju, Chang , Li, Li , Chi, Fangde , He, Yuankang et al. Power System Frequency Regulation Model Based on Blockchain Community Thinking . | Proceedings of the Chinese Society of Electrical Engineering , 2022 , 42 (4) , 1375-1387 . |
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Abstract ：
The uncertainty of renewable generation makes the operating status of distribution systems more volatile, as fully controllable resource at the distribution level is rare. A dispatchable region refers to the set that consists of all admissible patterns of nodal renewable power injections under which the power flow is solvable without violating security bound constraints. This article studies the dispatchable region in distribution networks under alternating current power flow model. A rank minimization problem is proposed to test power flow solvability under a fixed nodal power injection pattern, providing basic operation to construct the exact dispatchable region. A sequential low-order semidefinite programming procedure is developed to solve the problem. Furthermore, based on a global outer approximation of the second-order conic relaxation of the distflow model, a linear programming-based polyhedral projection algorithm is developed to calculate an outer approximation of the dispatchable region. The projection algorithm is also applied to the traditional linearized distflow model. Combining the feasibility test procedure, it is shown that the intersection of the respective dispatchable regions obtained from two linearized power flow models produces a fairly accurate approximation for the true dispatchable region under the exact nonlinear distflow model. The proposed method is an extension of existing studies on security assessment for distribution systems under uncertainty.
Keyword ：
Dispatchable region distflow model Distribution networks distribution system Load modeling Mathematical models Renewable energy sources renewable generation security assessment Uncertainty Visualization Voltage
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| GB/T 7714 | Shen, Ziqi , Wei, Wei , Ding, Tao et al. Admissible Region of Renewable Generation Ensuring Power Flow Solvability in Distribution Networks [J]. | IEEE SYSTEMS JOURNAL , 2022 , 16 (3) : 3982-3992 . |
| MLA | Shen, Ziqi et al. "Admissible Region of Renewable Generation Ensuring Power Flow Solvability in Distribution Networks" . | IEEE SYSTEMS JOURNAL 16 . 3 (2022) : 3982-3992 . |
| APA | Shen, Ziqi , Wei, Wei , Ding, Tao , Li, Zhigang , Mei, Shengwei . Admissible Region of Renewable Generation Ensuring Power Flow Solvability in Distribution Networks . | IEEE SYSTEMS JOURNAL , 2022 , 16 (3) , 3982-3992 . |
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Abstract ：
Microgrids incorporate an increasing number of distributed energy resources (DERs), which induce a higher variability and faster dispatch capabilities in power systems. This paper proposes a two-layer real-time scheduling model for microgrids, based on approximate future cost function (AFCF), where the future cost represents the opportunity cost for the microgrid operation in subsequent periods. At the upper layer, the look-ahead rolling scheduling is adopted to optimize microgrid operations, in which the future cost function (FCF) in deterministic and stochastic scenarios is approximated by a piecewise linear function. At the lower layer, a real-time parameter updating strategy based on real-time data is proposed. In this case, the real-time scheduling readjusts the look-ahead schedule using the immediate cost in the current period and the future cost calculated by the updated AFCF. The proposed two-layer real-time scheduling model uses an offline optimization, in which most of the computation tasks are completed at the upper layer, and applies a real-time optimization, in which the time-consuming problem is avoided at the lower layer. The effectiveness of the proposed two-layer real-time scheduling model of microgrids is validated by using a grid-connected microgrid system. For comparison, other existing real-time scheduling methods are also implemented in the same microgrid system.
Keyword ：
Cost function Dynamic scheduling future cost function Load modeling Microgrid Microgrids Processor scheduling real-time scheduling Real-time systems State of charge two-layer scheduling
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| GB/T 7714 | Liu, Chunyang , Zhang, Hengxu , Shahidehpour, Mohammad et al. A Two-Layer Model for Microgrid Real-Time Scheduling Using Approximate Future Cost Function [J]. | IEEE TRANSACTIONS ON POWER SYSTEMS , 2022 , 37 (2) : 1264-1273 . |
| MLA | Liu, Chunyang et al. "A Two-Layer Model for Microgrid Real-Time Scheduling Using Approximate Future Cost Function" . | IEEE TRANSACTIONS ON POWER SYSTEMS 37 . 2 (2022) : 1264-1273 . |
| APA | Liu, Chunyang , Zhang, Hengxu , Shahidehpour, Mohammad , Zhou, Quan , Ding, Tao . A Two-Layer Model for Microgrid Real-Time Scheduling Using Approximate Future Cost Function . | IEEE TRANSACTIONS ON POWER SYSTEMS , 2022 , 37 (2) , 1264-1273 . |
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Abstract ：
The stochastic cloud cover on photovoltaic (PV) panels affects the solar power outputs, producing high instability in the integrated power systems. It is an effective approach to track the cloud motion during short-term PV power forecasting based on data sources of satellite images. However, since temporal variations of these images are noisy and non-stationary, pixel-sensitive prediction methods are critically needed in order to seek a balance between the forecast precision and the huge computation burden due to a large image size. Hence, a graphical learning framework is proposed in this study for intra-hour PV power prediction. By simulating the cloud motion using bi-directional extrapolation, a directed graph is generated representing the pixel values from multiple frames of historical images. The nodes and edges in the graph denote the shapes and motion directions of the regions of interest (ROIs) in satellite images. A spatial-temporal graph neural network (GNN) is then proposed to deal with the graph. Comparing with conventional deep-learning-based models, GNN is more flexible for varying sizes of input, in order to be able to handle dynamic ROIs. Referring to the comparative studies, the proposed method greatly reduces the redundancy of image inputs without sacrificing the visual scope, and slightly improves the prediction accuracy.
Keyword ：
Bidirectional control Brightness temperature Clouds deep learning Extrapolation Forecasting graphical learning Predictive models satellite images Satellites Solar PV power prediction
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| GB/T 7714 | Cheng, Lilin , Zang, Haixiang , Wei, Zhinong et al. Solar Power Prediction Based on Satellite Measurements - A Graphical Learning Method for Tracking Cloud Motion [J]. | IEEE TRANSACTIONS ON POWER SYSTEMS , 2022 , 37 (3) : 2335-2345 . |
| MLA | Cheng, Lilin et al. "Solar Power Prediction Based on Satellite Measurements - A Graphical Learning Method for Tracking Cloud Motion" . | IEEE TRANSACTIONS ON POWER SYSTEMS 37 . 3 (2022) : 2335-2345 . |
| APA | Cheng, Lilin , Zang, Haixiang , Wei, Zhinong , Ding, Tao , Sun, Guoqiang . Solar Power Prediction Based on Satellite Measurements - A Graphical Learning Method for Tracking Cloud Motion . | IEEE TRANSACTIONS ON POWER SYSTEMS , 2022 , 37 (3) , 2335-2345 . |
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Abstract ：
A virtual energy storage (VES) model is proposed in this paper to accommodate renewable energy under a special market regulation. Such VESs can provide or consume electricity to the main power grid under the premise that the daily net electricity energy is balanced. Furthermore, a multi-stage distributionally robust optimization (MSDRO) model is set up in this paper to address the temporal uncertainties in the day-ahead economic dispatch model. Compared with the traditional two-stage distributionally robust optimization, the proposed multi-stage approach provides more flexibilities so that the decision variables can be adjusted at each time period, leading to a complex nested formulation. To efficiently solve the MSDRO model, a stochastic dual dynamic programming method is employed to decompose the original large-scale optimization model into several sub-problems in the stages, as two steps: forward pass and backward pass. In the forward pass, the expected cost-to-go function is approximated by piecewise-linear functions and then several samples are used to generate a lower bound; the backward pass will generate Benders' cuts at each stage from the solution of the forward pass. The forward and backward passes are performed iteratively until the convergence is reached. Numerical results on an IEEE 118-bus system and a practical power system in China verify the proposed method.
Keyword ：
Computational modeling Distributionally robust optimization economic dispatch Load modeling multi-stage stochastic programming Optimization Power systems renewable energy Renewable energy sources stochastic dual dynamic programming Stochastic processes Uncertainty virtual energy storage
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| GB/T 7714 | Ding, Tao , Zhang, Xiaosheng , Lu, Runzhao et al. Multi-Stage Distributionally Robust Stochastic Dual Dynamic Programming to Multi-Period Economic Dispatch With Virtual Energy Storage [J]. | IEEE TRANSACTIONS ON SUSTAINABLE ENERGY , 2022 , 13 (1) : 146-158 . |
| MLA | Ding, Tao et al. "Multi-Stage Distributionally Robust Stochastic Dual Dynamic Programming to Multi-Period Economic Dispatch With Virtual Energy Storage" . | IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 13 . 1 (2022) : 146-158 . |
| APA | Ding, Tao , Zhang, Xiaosheng , Lu, Runzhao , Qu, Ming , Shahidehpour, Mohammad , He, Yuankang et al. Multi-Stage Distributionally Robust Stochastic Dual Dynamic Programming to Multi-Period Economic Dispatch With Virtual Energy Storage . | IEEE TRANSACTIONS ON SUSTAINABLE ENERGY , 2022 , 13 (1) , 146-158 . |
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The public safety power shutoff policy in California state of America is a new type of active blackout measures taken to prevent wildfire disasters, it is an urgent problem to be solved of how to ensure the safe operation of power system under public safety power shutoff policy and improve the operation resi-lience of system. The public safety power shutoff policy in California state is summarized and analyzed, and the basic process of safe operation of power grid under public safety power shutoff policy is reported, further the current existing problems and possible future research directions on security control under public safety power shutoff policy in California state are discussed. The proposed viewpoints can provide new insights of future resilient power system construction and wildfire prevention in China. © 2022, Electric Power Automation Equipment Press. All right reserved.
Keyword ：
Disaster prevention Disasters Electric load flow Electric power system control Electric power system security Electric power transmission networks Fires
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| GB/T 7714 | Wang, Zekai , Ding, Tao , Li, Li et al. Policies and measures of public safety power shutoff for enhancing grid resilience under catastrophic wildfire in California state of America [J]. | Electric Power Automation Equipment , 2022 , 42 (3) : 36-44 . |
| MLA | Wang, Zekai et al. "Policies and measures of public safety power shutoff for enhancing grid resilience under catastrophic wildfire in California state of America" . | Electric Power Automation Equipment 42 . 3 (2022) : 36-44 . |
| APA | Wang, Zekai , Ding, Tao , Li, Li , Wang, Kang , Chi, Fangde . Policies and measures of public safety power shutoff for enhancing grid resilience under catastrophic wildfire in California state of America . | Electric Power Automation Equipment , 2022 , 42 (3) , 36-44 . |
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This article investigates the resiliently distributed fixed-time control of frequency recovery and power allocation in a multi-terminal high voltage direct current (MTDC) system against denial-of-service (DoS) attacks. An MTDC system typically consists of several AC areas, on which the DoS attacks may cause communication faults by blocking communication channels, preventing certain AC areas from sending message and damaging related facilities. A novel distributed security control scheme is proposed in this paper, which introduces attack detection method and communication repair mechanism to restore the paralyzed topology caused by DoS attacks. By extension, a resiliently distributed fixed-time control is presented under this frame. The proposed control scheme can not only realize frequency restoration but also accomplish active power sharing under DoS attacks. Furthermore, different from existing control strategies, the advanced scheme can guarantee the convergence time without considering the initial value, which helps improve the robustness and stability of the MTDC system. The resilient stability of the proposed scheme is proved by Lyapunov-Krasovskii stability theory. Finally, case studies on an MTDC system are conducted to demonstrate the effectiveness and validity of the proposed controller. Note to Practitioners-MTDC system is a large-scale power system connecting various AC grids. It has the characteristics of distributed and high intelligence, which is prone to be attacked by an adversary. As an index to measure the safe and stable operation of MTDC system, frequency is the focus of this paper. We propose a novel topology recovery mechanism for MTDC systems under DoS attack and design a resilient fixed-time secondary frequency controller based on the idea of multi-agent. The experimental results show that under DOS attack, the proposed topology recovery mechanism and controller can recover the frequency to the rated value in a fixed time and realize the proportional distribution of active power. In practical application, engineers can learn from the controller to resist DoS attack and realize the stable operation of large-scale distributed power system.
Keyword ：
Denial-of-service attack distributed fixed-time control DoS attacks Frequency control Frequency modulation MTDC system Power system stability resilience Time-frequency analysis Topology Voltage control
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| GB/T 7714 | Zhang, Xiaoyue , Liu, Xinghua , Ding, Tao et al. On Resilience and Distributed Fixed-Time Control of MTDC Systems Under DoS Attacks [J]. | IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING , 2022 . |
| MLA | Zhang, Xiaoyue et al. "On Resilience and Distributed Fixed-Time Control of MTDC Systems Under DoS Attacks" . | IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING (2022) . |
| APA | Zhang, Xiaoyue , Liu, Xinghua , Ding, Tao , Wang, Peng . On Resilience and Distributed Fixed-Time Control of MTDC Systems Under DoS Attacks . | IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING , 2022 . |
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Abstract ：
Load aggregators (LAs) play a key role in fully tapping the demand response (DR) resources of small and medium-sized end-users to enable a more flexible power grid. In the ancillary service market, the LA can provide DR to the system by aggregating the resources of its users. In response to the issued DR program, end-users offer to provide DR resources. To help optimize the user bidding strategy, an evolutionary game model is presented here in view of the bounded rationality of bidders. A combined Q-learning and compound differential evolution (CDE) algorithm is proposed to deal with the problems of incomplete information and uncertainties in the opponents' decision-making, and prevent the evolutionary stable strategy (ESS) from falling into a local optimum. Moreover, a cloud-computing-based framework is designed and agent servers are introduced to protect data privacy. Numerical results show that by adopting the proposed algorithm, the user's bidding price keeps slightly lower than the opponents' price which guarantees its revenue remains on a high level. This indicates that the proposed algorithm has good adaptability for addressing incomplete information and uncertainties in opponents' decision-making.
Keyword ：
Cloud computing compound differential evolution demand response evolutionary game Q-learning
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| GB/T 7714 | Han, Ouzhu , Ding, Tao , Bai, Linquan et al. Evolutionary Game Based Demand Response Bidding Strategy for End-Users Using Q-Learning and Compound Differential Evolution [J]. | IEEE TRANSACTIONS ON CLOUD COMPUTING , 2022 , 10 (1) : 97-110 . |
| MLA | Han, Ouzhu et al. "Evolutionary Game Based Demand Response Bidding Strategy for End-Users Using Q-Learning and Compound Differential Evolution" . | IEEE TRANSACTIONS ON CLOUD COMPUTING 10 . 1 (2022) : 97-110 . |
| APA | Han, Ouzhu , Ding, Tao , Bai, Linquan , He, Yuankang , Li, Fangxing , Shahidehpour, Mohammad . Evolutionary Game Based Demand Response Bidding Strategy for End-Users Using Q-Learning and Compound Differential Evolution . | IEEE TRANSACTIONS ON CLOUD COMPUTING , 2022 , 10 (1) , 97-110 . |
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Abstract ：
This article proposes an innovative integrated power and hydrogen distribution system (IPHDS) restoration model in response to multiple outages caused by natural disasters. During the restoration, repair crews and mobile battery-carried vehicles are considered to repair faulted lines and support critical power loads. Also, the network reconfiguration is taken into consideration in the restoration model to pick up loads. Besides, to address the different response time of hydrogen and power systems, the aerodynamic law-based dynamic hydrogen flow model is applied in the hydrogen system. The proposed model is presented as a mixed-integer linear program, which is verified on a 33-bus-48-node IPHDS with multiple outages. The present results verify the effectiveness of the proposed method.
Keyword ：
Aerodynamics Dynamic hydrogen flow Hydrogen integrated system restoration Load modeling Maintenance engineering mobile battery-carried vehicles (MBCVs) Natural gas network reconfiguration Power system dynamics repair crews (RCs) resilience Resilience
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| GB/T 7714 | Wang, Zekai , Ding, Tao , Jia, Wenhao et al. Multi-Period Restoration Model for Integrated Power-Hydrogen Systems Considering Transportation States [J]. | IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS , 2022 , 58 (2) : 2694-2706 . |
| MLA | Wang, Zekai et al. "Multi-Period Restoration Model for Integrated Power-Hydrogen Systems Considering Transportation States" . | IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 58 . 2 (2022) : 2694-2706 . |
| APA | Wang, Zekai , Ding, Tao , Jia, Wenhao , Mu, Chenggang , Huang, Can , Catalao, Joao P. S. . Multi-Period Restoration Model for Integrated Power-Hydrogen Systems Considering Transportation States . | IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS , 2022 , 58 (2) , 2694-2706 . |
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