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power and Electrical Engineering (ACPEE), 5th Asia Conference on

作者： Cuiping Li Yanli Wang Yiming Chen Xuesong Qi Yunjing Liu Qian Fang Shengyuan Cui Yuming Wang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Jilin China Science and Technology Section State Grid Shanghai South Power Supply Company Shanghai China Power dispatching and control center Jilin Power Supply Company Jilin China Science and Technology Section Jilin Power Supply Company Jilin China Ministry of Science and Technology Jilin Power Supply Company Jilin China

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

High percentage of photovoltaic gain connect to the wire line, so that the electricity grid from power distribution of the receiving end of the network into a set of production, storage, distribution of multi-source complex new network, the distribution network security operation and new energy consumption pressure increases. In response to the above, this paper puts forward the distributed ES multi-objective optimization configuration strategy of distribution network adapted to the high penetration rate distributed PV. And through a county power grid practical example to certify that the ES configuration approach proposed can effectively mitigate the impact of a high proportion of PV accessed, and it can reduce the abandonment of light.

关键词： Photovoltaic systems Wires Distribution networks Production power grids Regulation Resource management

Coordinated optimal configuration scheme of wind-solar ratio and energy storage considering wind-solar complementary characteristics

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Coordinated optimal configuration scheme of wind-solar ratio...

energy, power and Grid (ICEPG), International Conference on

作者： Xiuyu Yang Zhiwen Li Jian Peng Gang Miu Shaowei Yuan Zhengyin Zhu Key Laboratory of Modern Power System Simulation Control and New Green Energy Technology of Ministry of Education Northeasst Electric Power University Jilin China State Grid Xinjiang Power Supply Company State Grid Urumqi Power Supply Company Urumqi City China

ISBN: (数字)9798350377798

ISBN: (纸本)9798350377804

This study proposes a collaborative optimization configuration scheme of wind-solar ratio and energy storage based on the complementary characteristics of wind and light. On the premise of maintaining the stability of the wind-solar hybrid power generation system, the optimal allocation model of wind-solar ratio and energy storage considering the complementary characteristics of wind-solar is established with the minimum total cost of planning. At the same time, three indicators of power fluctuation index, wind-solar permeability and new energy abandonment rate are proposed to evaluate the scheme.

关键词： Wind energy generation Costs Stability criteria Wind power generation power system stability Planning Permeability Resource management Optimization energy storage

Optimal scheduling of island integrated energy systems considering multi-uncertainties and hydrothermal simultaneous transmission: A deep reinforcement learning approach

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arXiv

arXiv 2022年

作者： Li, Yang Bu, Fanjin Li, Yuanzheng Long, Chao Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China School of Artifcial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Water Energy and Environment Cranfield University CranfieldMK43 0AL United Kingdom

Multi-uncertainties from power sources and loads have brought significant challenges to the stable demand supply of various resources at islands. To address these challenges, a comprehensive scheduling framework is proposed by introducing a model-free deep reinforcement learning (DRL) approach based on modeling an island integrated energy system (IES). In response to the shortage of freshwater on islands, in addition to the introduction of seawater desalination systems, a transmission structure of "hydrothermal simultaneous transmission" (HST) is proposed. The essence of the IES scheduling problem is the optimal combination of each unit’s output, which is a typical timing control problem and conforms to the Markov decision-making solution framework of deep reinforcement learning. Deep reinforcement learning adapts to various changes and timely adjusts strategies through the interaction of agents and the environment, avoiding complicated modeling and prediction of multi-uncertainties. The simulation results show that the proposed scheduling framework properly handles multi-uncertainties from power sources and loads, achieves a stable demand supply for various resources, and has better performance than other real-time scheduling methods, especially in terms of computational efficiency. In addition, the HST model constitutes an active exploration to improve the utilization efficiency of island freshwater. © 2022, CC BY-NC-ND.

关键词： Desalination

Deep Sequence to Sequence Attention Network Approach for Short-Term Electricity Price Forecasting

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SSRN 2022年

作者： Chen, Haipeng Wu, Huayue Chen, Jian Kan, Tianyang Miao, Sen Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Department of Electrical Engineering Northeast Electric Power University Jilin132012 China Chengde Power Supply Company State Grid Jibei Electric Power Co. Ltd. Chengde067000 China

With increasing renewable energy penetration and the extension of the power system scale, accurate electricity price prediction has long become a challenging task. The complexity of electricity market information, insufficient model training, and the lack of model generalization ability limit the prediction accuracy of the existing electricity price forecasting methods. This paper proposes a Sequence-to-Sequence Attention algorithm based on the Double Deep Q Network optimization method for short-term electricity price prediction. This algorithm first conducts the maximum information coefficient correlation analysis to select the input dataset for the prediction model of electricity price. Secondly, the Sequence-to-Sequence Attention model is proposed for point forecasting and probabilistic forecasting of short-term electricity prices. Finally, the hyperparameters of the model are optimized by the Double Deep Q Network method, which improves the prediction accuracy and the generalization ability of the prediction model of electricity price. simulations are carried out on Pennsylvania–New Jersey–Maryland market data and the New South Wales electricity market. The results show that the proposed method has superior performance than the existing prediction methods, which is appliable for the short-term electricity price prediction and provides a powerful decision-making basis for market participants and regulators. © 2022, The Authors. All rights reserved.

关键词： Forecasting

Based on the Scenario Set Generation technology, the Shared energy Storage Site Selection and Capacity Determination Problem Considering the Grid Constraints

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Based on the Scenario Set Generation Technology, the Shared ...

power Science and technology (ICPST), IEEE International Conference on

作者： Xiaobiao Fu Jinyu Guo Baoju Li Cuiping Li Yao Wang Junhui Li Guanqun Zhang Xingxu Zhu Dispatching and Control Center State Grid Jilin Electric Power Co. Ltd Chang Chun China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education(Northeast Electric Power University) Ji Lin China Power Science Research Institute State Grid Jilin Electric Power Co. Ltd Chang Chun China

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047

This paper addresses the shared energy storage siting and sizing problem, considering grid constraints based on scenario generation techniques. In the context of high penetration of renewable energy, the power system faces practical challenges such as increased uncertainty and scarcity of flexible resources. To tackle these issues, a two-layer optimization model is proposed in this study. It utilizes scenario generation techniques to obtain possible scenarios for renewable energy and load outputs, and incorporates grid constraints for economic dispatch. Through iterative optimization, an optimal shared energy storage siting and sizing solution that meets the requirements of the power grid is obtained. Additionally, the paper discusses the impact on the accommodation capacity of renewable energy and proposes countermeasures in system economic dispatch. However, there are still limitations in uncertainty estimation, energy storage planning, and investment cost calculations in this paper. Furthermore, further enhancement is needed in terms of quantification theories supporting the economic evaluation of shared energy storage siting and sizing. Overall, this research aims to provide an optimization approach for the shared energy storage siting and sizing problem, incorporating scenario generation techniques and grid constraints, to promote stable operation and economic development of power systems with high penetration of renewable energy.

关键词： renewable energy sources Uncertainty Costs Optimization models Robustness Planning Scenario generation

Research on the Grid-connected Photovoltaic power Scheduling Strategy Considering the Flexible Load

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Research on the Grid-connected Photovoltaic Power Scheduling...

energy Engineering and power systems (EEPS), International Conference on

作者： Tao Meng Chenggang Li Dexin Li Jiajun Zhang Electric Power Research Institute State Grid Jilin Electric Power Co. Ltd Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education School of Electrical Engineering Northeast Electric Power University Changchun China Electric Power Research Institute State Grid Jilin Electric Power Co. Ltd Changchun China

With the target of "peak carbon dioxide emission" and "carbon neutrality", the installed capacity of renewable energy power generation is increasing rapidly. To improve the absorption capacity of renewable energy, the frequency regulation ability of flexible load is considered. Diffusion strategy is an optimal strategy for the distributed multi-agent system. Considering the flexible load, the grid-connected photovoltaic power applies the diffusion strategy to optimize the scheduling strategy. The effectiveness of the proposed optimal algorithm is verified by a simulation example. The results show that the proposed algorithm can realize frequency regulation, and improve the installed capacity of photovoltaic power generation.

关键词：

Optimal Scheduling Strategy of a Regional Integrated energy system Considering renewable energy Uncertainty and Heat Network Transmission Characteristics

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SSRN 2022年

作者： Chen, Haipeng Gao, Lin Zhang, Yongling Zhao, Chang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China Department of Electrical Engineering Northeast Electric Power University Jilin132012 China Gongqing Institute of Science and Technology Gongqing City 332020 China National New Energy Group Jilin Jiangnan Thermal Power Limited Company Jilin132012 China

In order to overcome the curtailment of wind energy caused by "power determined by heat" of combined heat and power units, this study proposes an integrated demand response strategy and optimization method for heat-electric energy dispatching in a regional integrated energy system. Firstly, a scene analysis model based on Latin Hypercube Sampling (LHS) and Backward Reduction (BR) is constructed to analyze the probabilistic properties of wind power output in various scenes, and further provide a necessary reference for integrated energy scheduling. Secondly, the schedulable electrical power and thermal demand are evaluated with the consideration of the transmission characteristics of the heat supply network, then the integrated demand response of electric-thermal coordination is adopted to facilitate suppress the heat load fluctuation and wind power consumption. Finally, the optimal scheduling model of regional integrated energy system is established considering the source-load coordination, and the optimal output of each power unit is determined with the goal of minimizing overall cost during the scheduling period. The simulation results demonstrated that the proposed scheduling method reduces the operation cost of the integrated energy system and effectively promotes the wind energy consumption. Furthermore, it serves as a benchmark for the coordinated operation of wind turbines and power grids. © 2022, The Authors. All rights reserved.

关键词： Electric power utilization

Ultra-Short-Term Multi-Step Prediction of Wind power Based on modernTCN and Multi-Task Learning

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Ultra-Short-Term Multi-Step Prediction of Wind Power Based o...

IEEE International Conference on power and power and renewable energy (ICPRE)

作者： Mao Yang Xiangyu Li Zifen Han Yong Sun Xiqiang Chang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China State Grid Gansu Electric Power Company Gansu China State Grid Jilinsheng Economic And Technological Research Institute Jilin China State Grid Xinjiang Electric Power CO. LTD Xinjiang China

ISBN: (数字)9798350377460

ISBN: (纸本)9798350377477

The intermittent and fluctuating nature of wind energy makes it difficult to accurately predict wind power, leading to low penetration in the wind power grid. To address this problem, this paper designs ultra-short-term multi-step prediction of wind power based on modernTCN and multi-task learning to improve the prediction accuracy. Firstly, modernTCN's ability to have a large receptive field and capture cross-variate timing dependencies is exploited to obtain multivariate timing feature information and establish a multi-step mapping of input features to power. Then it is inputted into the MMoE multi-task learning method, and the prediction results are corrected to obtain the ultra-short-term prediction of wind power using multiple expert networks and gating units. The experimental results show that the method proposed in this paper can effectively improve the ultra-short-term prediction accuracy of wind power, and can provide a favourable reference for the scheduling centre to adjust the power generation plan in real-time response to the power demand.

关键词： renewable energy sources Accuracy Wind energy Wind power generation Predictive models Multitasking Feature extraction Real-time systems Timing Wind forecasting

Optimization Charging Method of Lithium-Ion Battery Based on Multi-Objective Bbo Algorithm

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SSRN 2024年

作者： Duan, Shuangming Xia, Kuifeng Li, Junhui Zhao, Zhiqiang Liu, Haojun Key Laboratory of Modern Power System Simulation Control and New Green Energy Technology Ministry of Education Northeast Electricity Power University Jilin Jilin132012 China State Grid Hami Power Supply Company Xinjiang Uygur Autonomous Region Hami839000 China

Currently, the charging strategy of lithium-ion battery is usually an open-loop method, which lacks feedback in the charging process. In order to obtain a suitable charging strategy for lithium-ion battery, a simple and easy PID closed-loop constant temperature control system is proposed, which takes the temperature of lithium-ion battery as the feedback quantity, and improves the charging speed under the condition that the maximum temperature rise of lithium-ion battery is consistent. Secondly, SOC-based Multistage Constant Current (SMCC) based on SOC segmentation is proposed and orthogonal experiments are constructed by Taguchi method to determine the constant current values of each SMCC segment. Then, taking charging time, charging efficiency and SOH (State of Health) decay as the charging objectives to be optimized, multi-objective biogeographic-based optimization (BBO) is used. The MBBO algorithm optimizes each charging current under different weight coefficient combinations. According to the optimization results, Pareto optimal frontier is used to select the most balanced charging strategy from the six proposed charging strategies. Finally, SMCC charging current optimized by MBBO algorithm is connected to PID closed-loop constant temperature control system, and compared with SMCC charging strategy without constant temperature control and traditional 1C-CCCV method, the results show that compared with 1C-CCV charging strategy, The algorithm optimized SMCC can significantly reduce the charging time and SOH loss of lithium-ion batteries, and the SMCC charging current can be connected to PID closed-loop constant temperature control to further improve the charging speed, and keep the charging efficiency basically equal to the SOH attenuation. © 2024, The Authors. All rights reserved.

关键词： Taguchi methods

Research on Active Participation of Distributed Photovoltsics in power Grid Primary Frequency control Strategy

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SSRN 2024年

作者： Zhang, Runtao Wang, Lei Zeng, Siming Cheng, Ziwei Su, Can Li, Zhiwei Zhang, Hao State Grid Hebei Electric Power Research Institute Shijiazhuang China Hebei Key Laboratory of Simulation Modeling and Control for Energy Internet Shijiazhuang China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Baoding071003 China

Distributed photovoltaic systems can actively contribute to the primary frequency regulation of the power grid by reserving capacity. Traditional power reduction methods often employ fixed load reduction ratios, potentially resulting in inadequate frequency regulation capacity and unnecessary reserve power. This paper centers on optimizing power reserve control, starting with the construction of a two-stage model for a photovoltaic grid-connected inverter power generation system. It includes the design of a maximum power estimation method and the implementation of photovoltaic power reduction operation. The article proposes a strategy to utilize photovoltaic backup capacity for achieving primary frequency modulation effects in a short time scale. Additionally, it adopts a variable power reserve ratio operation strategy over the long term, aiming to enhance photovoltaic power generation and optimize solar energy utilization without compromising the grid's frequency and quality. Finally, a MATLAB/Simulink model is developed to validate the effectiveness of the control strategy. simulation results indicate that the proposed strategy satisfies frequency regulation requirements, enhances power generation efficiency, and improves the economic viability of photovoltaic operations. © 2024, The Authors. All rights reserved.

关键词： Frequency modulation