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Energy Procurement and Retail Pricing for Electricity Retailers via Deep Reinforcement Learning with Long Short-term Memory

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CSEE Journal of Power and Energy Systems 2022年第5期8卷 1338-1351页

作者： Hongsheng Xu Jinyu Wen Qinran Hu Jiao Shu Jixiang Lu Zhihong Yang State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical Electronic Engineering Huazhong University of Science and TechnologyWuhan 430074China NARI Group Corporation Nanjing 211106China School of Electrical Engineering Southeast UniversityNanjing 210096China State Key Laboratory of Smart Grid Protection and Control Nanjing 211106China

The joint optimization problem of energy procurement and retail pricing for an electricity retailer is converted into separately determining the optimal procurement strategy and optimal pricing strategy,under the“price-taker”*** aggregate energy consumption of end use customers(EUCs)is predicted to solve for the optimal procurement strategy vis a long short-term memory(LSTM)-based supervised learning *** optimal retail pricing problem is formulated as a Markov decision process(MDP),which can be solved by using deep reinforcement learning(DRL)***,the performance of existing DRL approaches may deteriorate due to their insufficient ability to extract discriminative features from the time-series vectors in the environmental *** propose a novel deep deterministic policy gradient(DDPG)network structure with a shared LSTM-based representation network that fully exploits the Actor’s and Critic’s *** designed shared representation network and the joint loss function can enhance the environment perception capability of the proposed approach and further improve the optimization performance,resulting in a more profitable pricing *** simulations demonstrate the effectiveness of the proposed approach.

关键词： Deep reinforcement learning electricity market energy procurement long short-term memory retail pricing

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Research on control Strategy of Transient Disturbance Based on the Three-level Hybrid Energy Storage Converter

Research on Control Strategy of Transient Disturbance Based ...

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2022 International Conference on New Energy, Energy Storage and Power Engineering, NESP 2022

作者： Chen, Jinyu Dai, Liyu Li, Zhicheng Deng, Chaoping State Grid Fujian Electric Power Research Institute Fuzhou China Fujian Key Laboratory of Protection and Operation Control for Smart Grid Fuzhou China

This paper proposes a control strategy of transient disturbance based on the three-level hybrid energy storage converter. The hybrid energy storage control strategy switches to the supercapacitor when the voltage sag occurs. Its characteristics of high power density can provide rapid and smooth voltage support for the distribution network so that the distribution network system will not be greatly affected by the impact. In the case of long-term voltage sag or power failure, it is important to switch to the energy storage battery and use its characteristics of high energy density to provide an emergency power supply to support the continuous operation of essential equipment. The control strategy proposed in this paper can realize the coordinated working between supercapacitor and energy storage battery and the fast and stable switching between two different working states of the energy storage system, which effectively solves voltage sag in the main power grid. Finally, a prototype is built, and the simulation and experimental results both verify the correctness and feasibility of the proposed control strategy. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Electric power supplies to apparatus

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Coupling Model and Cooperative Optimization Operation of Multi-energy Complementary Integrated Energy System 1

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8th Purple Mountain Forum on smart grid protection and control, PMF 2023

作者： Yizhi, Chen Chenghong, Tang Dongmei, Yang Wenjie, Ye Wenjun, Xu Yuxiang, Meng State Key Laboratory of Smart Grid Protection and Control Nanjing211106 China Nanjing211106 China NARI Technology Development Co. Ltd. Nanjing211106 China Nanjing Normal University Nanjing210023 China

ISBN: (数字)9789819992515

ISBN: (纸本)9789819992508

Driven by the goal of "carbon peak and carbon neutrality", a comprehensive energy system that integrates multiple energy structures has emerged. How to realize multi-energy complementarity and collaborative optimization among different sources, effectively improve energy utilization efficiency and promote the consumption of renewable energy has become a research hotspot. In this paper, the architecture of the user-side multi-energy complementary integrated energy system is studied, and the coupling equipment and energy supply network are analyzed. A multi-time scale coupling model, including a static coupling model and dynamic coupling model, is established for the multi-energy conversion equipment, Furthermore, the multi-energy coupling integration model is described. Then, a multi-energy coupling collaborative optimization method was proposed, and the objective function and constraint conditions of the system optimization operation were established. Finally, based on the coupling model and optimization method proposed in this paper, a multi-energy complementary comprehensive energy management and control system is developed. The system has been piloted and applied in several typical comprehensive energy scenarios across the country. Through data analysis and practical application verification, energy efficiency and the economy can be effectively improved. © 2024, state grid Electric Power.

关键词： Energy efficiency

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Non-intrusive load perception and flexibility evaluation for electric vehicle charging station: a deep learning based approach 5

Non-intrusive load perception and flexibility evaluation for...

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Wang, Jiarui Deng, Jiewen Liu, Yu Wang, Yi China Southeast University School of Electrical Engineering Nanjing China State Key Laboratory of Smart Grid Protection and Control Nanjing China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

Electric vehicles have the advantages of zero carbon emission, high energy efficiency and simple structure, and have been widely used today. Under the control of V2G, electric vehicles can be used as loads and distributed power sources, and become participants in the operation of auxiliary systems. Aiming at how to evaluate the load states and controllability of electric vehicle charging stations, this paper proposes a load sensing method for electric vehicle charging stations based on unsupervised learning and non-intrusive load monitoring. The proposed load sensing method firstly establishes the load sensing model according to the unsupervised learning strategy, and then uses the neural network model of the supervised learning strategy to evaluate the available regulation capability, so as to realize the load perception and regulation capability evaluation of the electric vehicle charging station. Through the verification of simulation data, it is proved that the proposed method has good performance in the evaluation of load perception and controllability of electric vehicle charging stations, which provides a feasible solution to the practical implementation of auxiliary responses by electric vehicles. © 2022 IEEE.

关键词： Electric vehicles

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A Day-ahead Scheduling Strategy for Electric vehicles Based on Converted Economical Objective 5

A Day-ahead Scheduling Strategy for Electric vehicles Based ...

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Bai, Chenhui Wang, Jiarui Deng, Jiewen Liu, Yu Wang, Yi State Key Laboratory of Smart Grid Protection and Control China School of Electrical Engineering Southeast University Nanjing China Nanjing China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

In recent years, with the rapid development of electric vehicles (EVs), the connection of a large number of EVs to the power grid has adversely affected the economic operation and system stability of the power grid. Therefore, research on the effective dispatch of EVs is of great significance. This paper proposes a day-ahead scheduling strategy for EVs based on converted economical objective, which makes full use of the flexibility of EV loads, takes into account the interests of the grid side and the user side, and reduces the negative impact of EVs connected to the grid. For the limitation of the objective function with the smallest variance, objective function converts the technical index of grid load peak-to-valley difference into an economic index with the smallest charging cost for users, and uses CPLEX to solve the day-ahead scheduling model of small-scale fast charging stations. The calculation example shows that this strategy can effectively reduce the peak-to-valley difference of grid load, which proves the rationality of the strategy. © 2022 IEEE.

关键词： Electric vehicles

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Power System Operation Mode Generalization and Stability control Strategy Modification Based on Data-Driven Method 5

Power System Operation Mode Generalization and Stability Con...

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Yuan, Huling Liu, Panpan Tai, Wei State Key Laboratory of Smart Grid Protection and Control System Protection Laboratory Nari Technology Co. Ltd. Nanjing China Nanjing Dongbo Smart Energy Research Institute Nanjing China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

The power grid operating mode will grow more complicated and diversified as power grid structure becomes more complex, as does the high share of renewable energy and the rising permeability of power electronic equipment. As a result, evaluation and analysis methodologies designed for ordinary operating modes will not be able to fulfill the needs of future power system operation planning, analysis, and strategy selection. Therefore, this paper provides a data-driven power system operating mode analysis as well as a technique for selecting a stability control strategy This method first builds the characteristics of the typical scenario is suitable for the operation of the electric properties and the method of data preprocessing, then identifies the typical operation mode through clustering and tightness index saturation point, respectively, and selects the corresponding stability control strategy in place to ensure that the grid can still keep the stable operation unaffected. Finally, an example is generated and examined using real power grid operating data from southwest China to demonstrate the efficacy and dependability of the proposed strategy. © 2022 IEEE.

关键词： Electric power transmission networks

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Identification Methods for Transformer Turn-to-Turn Faults and Inrush Current Based on Electrical Information

Identification Methods for Transformer Turn-to-Turn Faults a...

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2021 International Conference on Intelligent Power and Systems, ICIPS 2021

作者： Gong, Xinyi Zheng, Yuping Pan, Shuyan Wu, Chonghao Deng, Jinzhao NARI Research Institute NARI Group Corporation State Grid Electric Power Research Institute Nanjing China State Key Laboratory of Smart Grid Protection and Control China

Power transformer is the most imperative and crucial equipment in electrical power system. Accurately monitoring the occurrence of transformer faults and rapidly isolating the faults are of great significance to ensure the reliability of power supply and avoid serious damage to the transformer. There are many methods used in the transformer to monitor transformer running state. This paper provides a comprehensive overview of transformer turn-to-turn fault and inrush current identification methods based on electrical information, and expounds the systematic research content that needs to be carried out for transformer turn-to-turn fault identification methods based on magnetic flux leakage information. © Published under licence by IOP Publishing Ltd.

关键词： Power transformers

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Short-term operation planning of power grid flexibility regulation under uncertain risk scenario

Short-term operation planning of power grid flexibility regu...

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2021 IEEE Sustainable Power and Energy Conference, iSPEC 2021

作者： Xie, Dongliang Wang, Cai Xue, Yusheng Lai, Yening Zhang, Zheng Cai, Linjun Song, Xiaofang Zhang, Huilin Yu, Chen State Key Laboratory of Smart Grid Protection and Control Nanjing China

ISBN: (纸本)9781665414395

Traditional power grids for volatility, uncertainty, usually set a pro rata sufficient spare margin, but when the new energy grid capacity increases, if the volatility is so great, this 'one size fits all' decision is often expensive, too high thermal power start-up and even result in waste of resources. Therefore, based on the study of the multi-scale flexibility control measures of source network load storage, this paper puts forward the operation planning algorithm to reduce the total operation control risk effectively by coordinating and lowering the backup measures. Synergy with the value of various flexible resources in short-term operation planning to prevent and control the risk of wind, light and power outages in power systems, to achieve flexible operation planning. Finally, through the study, the algorithm proposed in this paper is verified that the algorithm can solve the problem of risk prevention and control in operation planning more economically and safely under the condition of large-scale grid-connected new energy. © 2021 IEEE.

关键词： Electric power transmission networks

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Instantaneous Frequency Measurement and Tracking under Out of Step Oscillation 7

Instantaneous Frequency Measurement and Tracking under Out o...

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7th International Conference on smart grid and smart Cities, ICSGSC 2023

作者： Cai, Ke Su Zhang, Gan Feng Ji, Rong Rong Zheng, Sui Sheng Xia, Cheng Lin Lan, Tian Yu State Grid Electric Power Research Institute State Key Laboratory of Smart Grid Protection and Control Nari Group Corporation NanJing China Ultra High Voltage Branch Company State Grid Zhejiang Powe Company HangZhou China Nari Group Corporation State Grid Eelectric Power Research Institute NanJing China

ISBN: (纸本)9798350305913

As an important operating parameter of the power system, the instantaneous frequency of the current can reflect the actual operating state of the current system, especially when the system is out of step. The characteristics of the current in the oscillation line are analyzed in this paper. An algorithm for measuring instantaneous frequency of current while power system swings is presented, based on the broad definition of angular frequency. According to the feature of the actual power system, a new method for measuring the instantaneous current frequency by real-time sampling is proposed. Finally, the algorithm is simulated on the model of the equivalent systems. When the system swings, the real-time frequency is gained by sampling the current in the line, combined with the frequency of the equivalent machine of both sides. It shows that the obtained current frequency is reasonable and effective, compared to the characteristics of the system. © 2023 IEEE.

关键词： angular frequency instantaneous frequency oscillation sampling

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DC operating circuit anomaly detection based on node voltage unsupervised time series 2

DC operating circuit anomaly detection based on node voltage...

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2nd International Conference on New Energy and Power Engineering, ICNEPE 2022

作者： Zhang, Shen Qi Yuan, Wei Yi, Ran Chen, Li State Grid NanTongPower Supply Company Jiangsu NanTong226000 China NARI Technology Nanjing Control Systems Co. Ltd Jiangsu Nanjing211106 China State Key Laboratory of Smart Grid Protection and Control Nari Group Corporation Jiangsu Nanjing211106 China

With the increase in power system load, the number of switch cabinets increases rapidly, and the accidents caused by DC operating circuits become more and more obvious. Abnormal detection has become an important part of the DC operating circuit. Abnormal data, mainly voltage measurement, often contain important information. Finding and analyzing these abnormal data can give early warning for circuit failure or failure. However, abnormal data is often difficult to obtain and lacks marks, that is, the problem of sample imbalance and unsupervised problems, resulting in abnormal detection methods that can not meet the increasing accuracy and efficiency requirements. Generative adversarial network (GAN) is an unsupervised deep learning model, which has been successfully applied to unsupervised time series anomaly detection. However, GAN has technical difficulties in the anomaly detection process, and there is still room for optimization in accuracy. In this paper, the unsupervised time series anomaly detection method based on GAN is studied, and an anomaly detection method of a DC operating circuit combined with LSTM and GAN is designed. © Published under licence by IOP Publishing Ltd.

关键词： Generative adversarial networks

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