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Collaborative planning and optimization for electric-thermal-hydrogen-coupled energy systems with portfolio selection of the complete hydrogen energy chain

arXiv

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arXiv 2023年

作者： Yi, Xinning Lu, Tianguang Li, Yixiao Ai, Qian Hao, Ran School of Electrical Engineering Shandong University Jinan250061 China School of Engineering and Applied Sciences Harvard China Project Harvard University CambridgeMA02138 United States Jinan250013 China Key Laboratory of Control of Power Transmission and Conversion Shanghai Jiao Tong University Shanghai200240 China National Power Dispatching and Control Center State Grid Coporation of China Beijing100000 China

Under the global low-carbon target, the uneven spatiotemporal distribution of renewable energy resources exacerbates the uncertainty and seasonal power imbalance. Additionally, the issue of an incomplete hydrogen energy chain is widely overlooked in planning models, which hinders the complete analysis of the role of hydrogen in energy systems. Therefore, this paper proposes a high-resolution collaborative planning model for electricity-thermal-hydrogen-coupled energy systems considering both the spatiotemporal distribution characteristics of renewable energy resources and the multi-scale bottom-to-top investment strategy for the complete hydrogen energy chain. Considering the high-resolution system operation flexibility, this paper proposes a hydrogen chain-based fast clustering optimization method that can handle high-dimensional data and multi-time scale operation characteristics. The model optimizes the geographical distribution and capacity configuration of the Northeast China energy system in 2050, with hourly operational characteristics. The planning optimization covered single-energy devices, multi-energy-coupled conversion devices, and electric-hydrogen transmission networks. Last but not least, this paper thoroughly examines the optimal portfolio selection of different hydrogen technologies based on the differences in cost, flexibility, and efficiency. In the Pareto analysis, the proposed model reduces CO2 emissions by 60% with a competitive cost. This paper provides a zero-carbon pathway for multi-energy systems with a cost 4% less than the social cost of carbon $44.6/ton, and the integration of the complete hydrogen energy chain reduces the renewable energy curtailment by 97.0%. Besides, the portfolio selection results indicate that the system favors the SOEC with the highest energy efficiency and the PEMFC with the fastest dynamic response when achieving zero-carbon emissions. Copyright © 2023, The Authors. All rights reserved.

关键词： Renewable energy resources

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Research of auxiliary frequency modulation in smart microgrid 13

Research of auxiliary frequency modulation in smart microgri...

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2020 13th International Conference on Computer and Electrical Engineering, ICCEE 2020

作者： Yu, Qingguang Jiang, Zhicheng Ma, Yingxin Long, Gaoxiang Liu, Yuming State Key Laboratory of Power Systems Department of Electrical Engineering Tsinghua University Beijing100084 China Power Dispatching and Control Center State Grid Jibei Electric Power Company Beijing100054 China

In this paper, the component model of bidirectional converter and inverter is established, and the precise control of input and output power of the energy storage system is realized by using dual loop control strategy and PQ control strategy. the control strategy of the energy storage system is proposed to improve the performance of the primary frequency modulation process. The grid interconnection model of offshore oil platform is established. The frequency variation in primary and secondary frequency modulation is simulated to verify the effectiveness of the control strategy. © Published under licence by IOP Publishing Ltd.

关键词： Frequency modulation

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A Nash–Stackelberg Game Approach to Analyze Strategic Bidding for Multiple Der Aggregators in Electricity Markets

SSRN

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SSRN 2023年

作者： Lei, Zhenxing Liu, Mingbo Shen, Zhijun Lu, Junqi Lu, Zhilin School of Electric Power Engineering South China University of Technology Guangzhou510640 China Guangdong Key Laboratory of Clean Energy Technology South China University of Technology Guangzhou510640 China Electric Power Dispatching Control Center of Guangdong Grid Co. Ltd. Guangzhou510600 China School of Mechatronic Engineering Xi’an Technological University Xi’an710021 China Energy Development Research Institute China Southern Power Grid Guangzhou510663 China

This paper discusses how to maximize the profits of multiple distributed energy resource (DER) aggregators in the electricity markets when considering the safe operation of the distribution system. A Nash–Stackelberg game model is constructed to analyze the strategic bidding behavior of each DER aggregator. Within this model, DER aggregators, as leaders, decide the bidding quantity and price to maximize their profits by aggregating DERs in the distribution system, whereas the independent system operator, as one follower, clears electricity markets, and the distribution system operator, as another follower, checks the security of the distribution system. Additionally, we propose a customized algorithm to obtain the Nash equilibrium point of this model with integer variables in the follower-level problem. The first step is the transformation of this model into a generalized Nash equilibrium (GNE) game model, which was done by applying the Karush–Kuhn–Tucker reformulation approach and the simplified shared-constraint method combined with the data-driven algorithm. Then, the GNE game model is further converted into a potential game model to solve. Lastly, simulations on two integrated transmission and distribution systems, a small and an actual system, were realized to verify the extensibility and efficiency of the proposed model and algorithm. © 2023, The Authors. All rights reserved.

关键词： Profitability

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Optimal Computation Resource Allocation Scheme for LEO Satellite Networks

Optimal Computation Resource Allocation Scheme for LEO Satel...

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作者： Jiajia Fu Zanhong Wu Yuhang Chen Xuchuan Huang Electric Power Dispatching Control Center of Guangdong Power Grid Co.Ltd. State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

Past few years have witnessed the development of the satellite technology. With the rapid growth of global mobile services, people have higher and higher requirements for the quality of satellite communications. The communication delay can be effectively reduced by offloading the computing task to satellite. This paper introduces a LEO(Low Earth Orbit, LEO) satellite computing resource allocation scheme based on on-board resource pool. Through the ISL(Inter Satellite Link, ISL), the computing equipment of each satellite is combined into a resource pool to allocate computing resources to users in a centralized *** order to ensure the fairness between users in the process of allocation, we describe the task of computing resource allocation as a constrained optimization problem with the goal of minimizing the variance between the supply and ***, the augmented Lagrange multiplier method is adopted to obtain the optimal solution, which dynamically allocates computing resources for each *** simulation results are presented to verify the effectiveness and convergence of the proposed scheme.

关键词： LEO satellite Computation resource allocation Augmented Lagrange multiplier method

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Multi-machines and Multi-tasks Scheduling for UAV power Inspection in Smart grid

Multi-machines and Multi-tasks Scheduling for UAV Power Insp...

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作者： Jiangang Lu Jiajia Fu Jian Zhang Keqin Zhang Electric Power Dispatching Control Center of Guangdong Power Grid Co.Ltd. State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

Transmission line inspection and maintenance are the foundation to ensure the normal operation of the power grid. However, transmission line inspection and maintenance in remote regions are expensive, especially in unmanned regions. Unmanned Aerial Vehicle(UAV) power inspection is significant development towards the space-ground collaborative smart grid. The UAV is used to patrol the power system, and the security problems and fault types can be detected in time by remote video transmission. But in a multi-tasks scenario how to schedule UAVs to complete tasks with the least cost(which can be energy consumption,distance, time) is rarely studied. This paper studies the scheduling problem of multi-machines and multi-tasks in UAVs power inspection, formulates the schedule of UAVs as a multi-traveling salesman problem applied in this scenarios. Two scheduling strategies based on Genetic algorithm and Tabu Search algorithm are proposed to solve the multi-traveling salesman problem. In particular, the Genetic algorithm has a fast convergence speed and a better objective function ***, it is easier to meet the rapid emergency requirements in the multi-tasks scenarios of the UAVs.

关键词： UAV power inspection Multi-machines and multi-tasks Multi-traveling salesman model intelligent optimization algorithm

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5G Green Communications: Multigroup Multicasting Transmission with SWIPT in C-RAN

5G Green Communications: Multigroup Multicasting Transmissio...

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作者： Ying Zeng Jiangang Lu Zhan Shi Song Kang Electric Power Dispatching Control Center of Guangdong Power Grid Co.Ltd. State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

The work investigates the downlink multigroup multicast transmission in cloud radio access network(C-RAN), where remote radio heads(RRHs) collaboratively provide information and energy services for single-antenna information and energy receivers. We aim to minimize the total power consumption by designing beamforming vectors, subject to the constraints of data rate, fronthaul capacity and per-RRH transmit power. However, this optimization problem is nonsmooth and nonconvex. To overcome this challenge, a low-complexity algorithm is developed to find the nearly optimal solution, via successive convex approximation and smooth approximation techniques. Through numerical results, the impacts of the thresholds of fronthaul capacity and energy harvested on the optimum power consumption have been investigated.

关键词： Beamforming Cloud radio access networks Fronthaul links power minimization

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An end-edge-cloud technology architecture for integrated intelligent control of small hydropower - an example from Hunan Province, China

An end-edge-cloud technology architecture for integrated int...

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Electrical Engineering and Automation (IFEEA), International Forum on

作者： Zhuomin Zhou Jian Liang Aiqin Yu Zhengbin Qin Haotian Liu Yanchao Sheng Wei Guo Development Planning Department Hunan Key Laboratory of Energy Internet Supply Demand and Operation State Grid Hunan Electric Power Company Limited Changsha China Institute of Economic Research Hunan Key Laboratory of Energy Internet Supply Demand and Operation State Grid Hunan Electric Power Company Limited Changsha China Institute of Economic Research State Grid Xiangtan Electric Power Company Limited Changsha China R&D Department Three Gorges Intelligent Industrial Control Technology Co. Ltd. Wuhan China

The main technical issues for small hydropower currently are aging equipment and insufficient intelligence level, which cannot effectively support the development of new power systems. To solve this problem, this paper proposes an end-edge-cloud technology architecture for intelligent control of small hydropower. Specifically, an intelligent sensing architecture for small hydropower units is proposed, which can fully sense the operating conditions of small hydropower units. An edge computing PLC with IOT functions is proposed, which can effectively integrate the speed regulation, excitation, monitoring and protection algorithms of small hydropower units, and can greatly simplify the complexity of control systems. At the same time, the edge computing PLC transmits the on-site operation data to the cloud platform through high-density compression transmission, and uses big data analysis and processing technology to realize centralized monitoring and remote operation and maintenance of small hydropower stations within the province. Finally, the intelligent sensing, integrated edge control device and cloud platform proposed in this paper are technologically verified at a small hydropower station in Jingshan Reservoir, and the results fully demonstrate the effectiveness of this technical architecture.

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Multi-fault Diagnosis of Wind Turbine Based on Imprecise Probability

Multi-fault Diagnosis of Wind Turbine Based on Imprecise Pro...

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2020 IEEE/IAS Industrial and Commercial power System Asia, I and CPS Asia 2020

作者： Bo, Yifan Yang, Ming Zeng, Xiangjun Zhou, Yu Jing, Linguo Key Laboratory of Power Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China State Grid Binzhou Electric Power Company Binzhou China

ISBN: (纸本)9781728143033

In this paper, an imprecise probability multi-fault diagnosis approach was proposed based on imprecise probability, which could simultaneously diagnose multi-fault events of the wind turbine. The approach excavated the dependence relationships between fault events and variables using the greedy search algorithm and constructed a credal network structure to express the relationships in an abstract way. The expanded imprecise Dirichlet model is used to obtain the imprecise conditional probability table at each evidence node in the network, thus to realize the parameter estimation of the credal network It was shown that based on the constructed model, features of different targets can adaptively be extracted from the same signal, and then these features are used to perform multi-fault diagnosis. The test results showed that the proposed approach realizes the correct diagnosis of faults under multiple working conditions. © 2020 IEEE.

关键词： Wind turbines

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Carrier Network Fault Diagnosis Algorithm Based on Network and Business Relationship

Carrier Network Fault Diagnosis Algorithm Based on Network a...

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作者： Yutu Liang Zhan Shi Ying Zeng Song Kang Electric Power Dispatching Control Center of Guangdong Power Grid Co. Ltd. State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

In order to solve the problem of low performance of fault diagnosis algorithms caused by high noise in the carrier network environment, this paper proposes a carrier network fault diagnosis algorithm based on the relationship between network and business. First, the relationship between power business and underlying network resources is analyzed, and a fault propagation model is established. Second, calculate the reliability of each link failure based on the relationship between the symptoms and the expected symptoms. Based on the virtual service carrying capacity of each link, the reliability of link failure is optimized. Finally, from the two dimensions of the probability of the observed abnormal service explained by the failure set and the probability of all abnormal services explained by the failure set, the interpretation ability of the suspected failure set is evaluated. In terms of performance analysis, comparing the algorithm in this paper with the existing algorithms, it is verified that the algorithm in this paper improves the accuracy of the fault diagnosis results and reduces the false alarm rate of the fault diagnosis algorithm results.

关键词： Carrier network Fault diagnosis Fault propagation model Bayesian network

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Carrier Network Fault Diagnosis Algorithm Based on Dynamic Bayes Theory

Carrier Network Fault Diagnosis Algorithm Based on Dynamic B...

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作者： Zhan Shi Ying Zeng Yutu Liang Keqin Zhang Electric Power Dispatching Control Center of Guangdong Power Grid Co. Ltd. State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

The fault diagnosis model in the carrier network environment is inaccurate, resulting in low performance of the fault diagnosis algorithm. To solve this problem, this paper proposes a carrier network fault diagnosis algorithm based on dynamic Bayes theory. First, build a bipartite graph fault propagation model based on the relationship between faults and symptoms. Calculate the credibility of the failure according to the faulty node, calculate the credibility of the abnormal symptom node and filter the false symptom. Second, in order to improve the accuracy of the fault diagnosis model, a dynamic Bayesian fault propagation model is established based on the optimized fault and symptom data. Finally, based on the dynamic Bayesian fault propagation model, two steps are taken to calculate the maximum possible failure node state set in the previous stage and the maximum possible failure node state set in the current stage to locate the fault. In the performance analysis part, the algorithm of this paper is compared with the existing algorithms, and it is verified that the algorithm of this paper improves the accuracy of the fault diagnosis algorithm and reduces the false alarm rate of the fault diagnosis algorithm.

关键词： Carrier network Fault diagnosis Network virtualization Dynamic Bayes

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