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

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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Optimal Phase Switch Device Placement Scheme for Low Voltage Distribution Network Considering Load and Renewable Energy Uncertainty

Optimal Phase Switch Device Placement Scheme for Low Voltage...

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2022 Asia Power and Electrical Technology Conference, APET 2022

作者： Liang, Feng Ni, Jianfu Zhu, Hao Xiong, Qingsheng Yu, Zhuofei Nari Group Corporation State Key Laboratory of Smart Grid Protection and Control R&d Department in Nari Technology Nanjing China Xi'an Jiaotong University Smart Grid Key Laboratory of Shaanxi Province Xi'an China

ISBN: (纸本)9781665453349

With the increase of single-phase devices and loads in the power system, the three-phase unbalance problem of the low voltage distribution network is more serious. Besides, the intermittency and volatility of renewable energy increase system uncertainty. To address this issue, this paper proposes a phase switch device placement model for the low voltage distribution network with renewable energy sources. The proposed model combines network reconfiguration and phase switch device to mitigate the three-phase unbalance. Considering the uncertainty of loads and renewable energy output, the proposed model is formulated as a mixed integer linear programming model based on stochastic programming, which can be solved by general commercial solvers and find the global optimal solution. The effectiveness of the proposed model is validated on the IEEE 13 node test feeder. The results show that the proposed model can significantly mitigate the three-phase unbalance of low voltage distribution network. © 2022 IEEE.

关键词： Renewable energy resources

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A Coordinated MMC control Strategy of Integrated Photovoltaic/Battery System 7

A Coordinated MMC Control Strategy of Integrated Photovoltai...

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7th IEEE International Conference on Energy Internet, ICEI 2023

作者： Yang, Yuexi Zhou, Xiao Wang, Sichao Li, Chunpeng Huang, Junwei Xu, Wenzheng State Grid Smart Grid Research Institute Co. Ltd. State Key Laboratory of Advanced Power Transmission Technology Beijing China State Grid Fujian Electric Power Research Institute Fujian Key Laboratory of Protection and Operation Control for Smart Grid Fuzhou China National Research Center for Active Distribution Network Technology Beijing Jiaotong University Beijing China

ISBN: (纸本)9798350386684

The grid-connecting control and maximum power point tracking control of photovoltaic inverters have long been the research focus in the field of solar power generation. In this paper, a new coordinated modular multilevel converter (MMC) control strategy based on virtual synchronization and MPPT is proposed for grid-connected inverters in the PV/Battery system. The proposed strategy realizes frequency and voltage droop control with the synchro's inertia and damping characteristics, and improves the power angle stability as well as system voltage stability. Simulation results in MATLAB/Simulink verifies the feasibility and effectiveness of the proposed control strategy. © 2023 IEEE.

关键词： Solar energy

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A Cooperative Development Path in Distribution Networks with Distinct Ownership Based on System Dynamics

A Cooperative Development Path in Distribution Networks with...

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2022 Asia Power and Electrical Technology Conference, APET 2022

作者： Ni, Jianfu Liang, Feng Yu, Tianying Xiong, Qingsheng Zhu, Jinda Nari Group Corporation State Key Laboratory of Smart Grid Protection and Control R&d Department in Nari Technology Nanjing China Xi'an Jiaotong University Smart Grid Key Laboratory of Shaanxi Province Xi'an China

ISBN: (纸本)9781665453349

The system dynamics is an effective tool to study the internal evolution mechanism of a system. In this paper, a distinct ownership interaction causal loop diagram of the distribution network is established by sorting out the relationship chain between distributed PV, distributed gas units, distributed energy storage, distribution company and residents. The distinct ownership co-evolution model of distribution network is further established, and the boundary conditions of distributed power supply construction of distribution network are obtained by analyzing the distribution network test case. The effective path to achieve the dual carbon target is verified. © 2022 IEEE.

关键词： Electric power distribution

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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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Thermal simulation optimization of DC charger based on ANSYS Icepak 14

Thermal simulation optimization of DC charger based on ANSYS...

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14th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Hangzhou 2023

作者： Wang, Yu Zhou, Feiyu Wen, Tan Su, Yan Yuan, Li Wang, Ke State Key Laboratory of Smart Grid Protection and Control Nari Group Corporation Nanjing China Nanjing University of Aeronautics and Astronautics College of Civil Aviation Nanjing China State Grid Electric Power Research Institute Nanjing China

ISBN: (纸本)9798350301359

As one of the most important charging facilities for electric vehicles, DC chargers provide power supplements for electric vehicles. With the continuous development of DC chargers, the power density of their internal functional modules is also increasing. It is urgent to choose a reasonable heat dissipation method to reduce the overall temperature rise inside the DC charger and ensure its safe operation. In this paper, the 80kW DC charger is taken as the research object, and based on ANSYS Icepak thermal simulation software, the internal temperature field and fluid field of the DC charger are simulated and analyzed, and the design scheme of the DC charger is optimized by studying the heat dissipation system. Finally, the optimization scheme of the air duct structure of the system is obtained by adjusting the position of the heat dissipation fan. © 2023 IEEE.

关键词： ANSYS Icepak DC charger heat dissipation temperature thermal simulation

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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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Fully Distributed Economic Dispatch for Cyber-physical Power System with Time Delays and Channel Noises

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Journal of Modern Power Systems and Clean Energy 2022年第6期10卷 1472-1481页

作者： Yuhang Zhang Ming Ni Yonghui Sun College of Energy and Electrical Engineering Hohai UniversityNanjing 210098China NARI Group Corporation(State Grid Electric Power Research Institute) Nanjing 211106China NARI Technology Co. Ltd.Nanjing 211106China State Key Laboratory of Smart Grid Protection and Control Nanjing 211106China

Economic dispatch problem(EDP)is a fundamental optimization problem in power system operation,which aims at minimizing the total generation *** fact,the power grid is becoming a cyber-physical power system(CPPS).Therefore,the quality of communication is a key *** this paper,considering two important factors,i.e.,time delays and channel noises,a fully distributed consensus based algorithm is proposed for solving *** critical maximum allowable upper bounds of heterogeneous communication delays and self-delays are *** should be pointed out that the proposed algorithm can be robust against the time-varying delays and channel noises considering generator *** addition,even with time-varying delays and channel noises,the power balance of supply and demand is not broken during the *** simulation studies are presented to validate the correctness and superiority of the developed results.

关键词： Distributed economic dispatch consensus-based algorithm cyber-physical power system time delay channel noises

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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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