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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Huan Yang Dongsheng Cai Olusola Bamisile Jian Li Zhenyuan Zhang Qi Huang School of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control University of Electronic Science and Technology of China Chengdu China

In the context of carbon neutrality, the power industry is becoming the main battlefield of carbon emission reduction. However, the low-carbon transformation of energy structure is a complex long-term task, it needs to be analyzed in combination with the actual situation. This paper is based on the microgrid in the grid connection mode, considering microgrid power output and carbon emission constraints. An optimal model is proposed to reduce carbon emission cost, the optimal economic operation, and build a low-carbon scheduling model of a microgrid system. In this paper, the improved multi-objective particle swarm optimization algorithm is used to solve the problem. Finally, the simulation results verify the effectiveness of the model and the superiority of the improved algorithm.

关键词： Job shop scheduling Costs Wind energy Heuristic algorithms Optimal scheduling Microgrids system integration

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A Hierarchical Optimization-Based Model for Microgrids with Energy Storage Considering Operation Cost and Net Load Mean Square Error

A Hierarchical Optimization-Based Model for Microgrids with ...

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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Zexiang Guan Dongsheng Cai Olusola Bamisile Jian Li Zhenyuan Zhang Qi Huang School of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control University of Electronic Science and Technology of China Chengdu China

When a high proportion of renewable energy is connected to the grid, the net load fluctuation can be suppressed by configuring energy storage. However, the current cost of energy storage is high. This paper proposes a bi-level optimization model that takes into account the dynamic allocation of shared energy storage (SES) capacity in response to electric load demand. The upper-layer objective function adopts EO optimization algorithm, which is to maximize the income of the shared energy storage operator (SESO). The lower-layer multi-objective function is to minimize the sum of the operating cost and the net load mean square error of multiple microgrids, which can be classified as the mixed integer linear programming problem. Then, the solution flow of the algorithm is given. Finally, under the constraints of the hierarchical optimization-based model, solving the problem by the CPLEX solver on the MATlab platform. The results demonstrate that the proposed method can allocate optimal capacity and reduce operating costs for microgrids. Simultaneously, this method increases the revenue of SESO and promotes the consumption of renewable energy.

关键词： Renewable energy sources Costs Fluctuations Microgrids Mean square error methods Mathematical models Classification algorithms

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Design of magnetic shielding structures for non-contact measurement of current in triangularly arranged cables

Design of magnetic shielding structures for non-contact meas...

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Electrical Engineering (CIYCEE), IEEE China International Youth Conference on

作者： Xingyu Zhou Dongsheng Cai Zhengyuan Zhang Peng Wang Arsalan Habib Khawaja Qi Huang College of Nuclear Technology and Automation Engineering Chengdu University of Technology China Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China School of Information Engineering Southwest University of Science and Technology Mianyang China

The triangular arrangement of cables has the advantages of good magnetic field balance and compact structure, making it a commonly used arrangement in tunnel power cable lines. Accurate measurement of its current helps to make accurate judgment of the line operation status. However, the tunnel transmission method involves a complex line arrangement in a small space. Therefore, non-contact wide-range current measurement based on magnetic sensors is a better solution. In the face of uncertain magnetic interference in transmission tunnels, the use of magnetic shielding can suppress its effect on magnetic sensors. In this paper, an M-shaped magnetic shield structure is proposed for current measurement in a triangular arrangement with strong magnetic interference at random locations. Then, the thickness, position, axial length, gap width and location of the sensing areas of the structure were investigated. The effectiveness of the structure was verified by finite element analysis methods for measured currents of 200 to 2000 A. The structure was also validated by the finite element analysis method. The mean shielding uncertainty (MSU) of the shielding structure is verified to be 0.19% under the uncertainty of strong magnetic interference for a measured current of 2000 A. The M-shaped shielding structure is more resistant to interference than the C-shaped shielding structure and fits better into the triangular arrangement of the cable geometry.

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A Fair and Effective Approach to Managing Distributed Energy Resources Through Peer-to-Peer Energy Trading with Load Prioritization Among Smart Homes

SSRN

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SSRN 2023年

作者： Ahmed, Syed Adrees Huang, Qi Amin, Waqas Afzal, Muhammad Hussain, Fazal Haider, Muhammad Husnain 1Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Sichuan China Chengdu University of Technology China National University of Sciences and Technology Pakistan Superior University Pakistan School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Sichuan China

This paper proposes a novel approach to managing distributed energy resources (DERs) through peer-to-peer (P2P) energy trading among smart homes, incentivizing peers to trade surplus energy to maximize social welfare. The proposed day-ahead demand-side management (DSM) technique considers load prioritization based on users' needs. It utilizes an energy allocation method that incentivizes peers to buy energy at a reduced price and sell energy at a higher price. This method maximizes the time of energy traded to higher-priority loads, followed by lower-priority loads while considering user choice. The proposed method results in an average reduction in energy costs from 14.8% to 2.82% for all consumers and an average increase in revenues from 17.35% to 9.07% for all prosumers compared to the grid and previously proposed studies. The simulation results show significant economic benefits for all market participants, improved community self-sufficiency, and reduced dependence on the main grid. The proposed methodology provides an effective and fair solution for managing DERs through P2P energy trading by prioritizing the load in smart homes, which describes its potential to create a sustainable and efficient energy ecosystem. © 2023, The Authors. All rights reserved.

关键词： Automation

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Hierarchical control Scheme for VSC-MTDC system with multiple Renewable Energy Sites Based on Optimal power Flow and Droop Scheme

Hierarchical Control Scheme for VSC-MTDC System with multipl...

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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Asif Raza Qi Huang Jian Li Olusola Bamisile Cai Dongsheng Ghalib Raza Sichuan Provincial Key Lab of Power System Wide –Area Measurement and Control School of Mechanical and Electrical Engineering University of Electronic Science & Technology of China College of Nuclear and Automation Engineering Chengdu University of Technology Sichuan Provincial Key Lab of Power System Wide–Area Measurement and Control School of Mechanical and Electrical Engineering University of Electronic Science & Technology of China University of Electronic Science & Technology of China College of Nuclear and Automation Engineering Chengdu University of Technology Sichuan P.R. China Benazir Bhutto Shaheed University of Technology & Skill Development Khairpur Pakistan

This paper designs a hierarchical control system to improve control performance in a multi-terminal high voltage direct current based on the voltage source converter (VSC-MTDC) transmission system. In this control scheme, the primary control layer employs droop control, while the secondary control layer has developed optimal power flow control (OPF) for maintaining the variation of DC voltage and regulating the active power, and simultaneously minimizing power loss. In the event of a power disturbance or a change in power generation or consumption in the DC system, based on OPF results a new stable droop operating mode is established to stabilize DC voltage variation and regulate active power in the network. A ±400 kV four-terminal VSC-MTDC test network has been developed by using PSCAD and MATlab simulation tools to assess the proposed control scheme. The primary controller is designed in PSCAD, and the secondary optimum control technique is applied in MATlab. The results of steady-state and transient operating modes demonstrate that the planned control technique can achieve DC voltage regulation and keep active power, and minimize the power losses in the MTDC system.

关键词： Renewable energy sources system integration control systems Steady-state power conversion Voltage control PSCAD

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A rapid warning method for wildfire occurrences along the transmission corridor driven by power system monitoring data

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FRONTIERS IN ENERGY RESEARCH 2022年 10卷

作者： Duan, Xiangxi Huang, Qi Chen, Zhe Li, Jian Ren, Xibi Univ Elect Sci & Technol China Chengdu Peoples R China State Grid Sichuan Elect Power Res Inst Chengdu Peoples R China Power Syst Wide Area Measurement & Control Key Lab Chengdu Peoples R China

This paper focuses on the problems of frequent wildfire occurrences along the transmission corridor and the lack of accurate and timely monitoring means for early warnings. Furthermore, this paper evaluates the rapid warning method for wildfire occurrences along the transmission corridor driven by power system monitoring data. First, we established the relationship between the historical data of wildfires along the transmission corridor and the operating state information of a power grid based on the Apriori association rule algorithm;the characteristic signals of the transmission line when wildfires occur were mined. Second, based on the characteristics of the time distribution of wildfire occurrences along the transmission corridor, a nonlinear regression model was created to further improve the prediction accuracy. Finally, by combining the characteristic signals and time distribution characteristics, we developed an early warning method. This method not only addresses the challenges faced by meteorological satellite remote sensors caused by the weather, the long transit time interval, and the high cost of adding sensors, but it also realizes the remote and rapid early warning of wildfires along the transmission corridor. Finally, a case study of practical data of a certain area in southwest China is used to verify the proposed method. The results show the high accuracy and timeliness of the proposed method.

关键词： wildfire occurrence along transmission corridor nonlinear regression model apriori association rule algorithm monitor data weather satellite

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A Tokenized Blockchain-Based Energy Eco-system Over Integrated Automated Market Makers

SSRN

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SSRN 2024年

作者： Adjei-Arthur, Bonsu Bamisile, Olusola Xia, Qi da Silva Tavares, Eliezer Eliezer Gao, Jianbin Xia, Hu Chengdu611731 China Blockchain Research Institute of UESTC-Chengdu Jiaozi Financial Holding Group Co.Ltd Chengdu610095 China Sichuan Provincial Key Lab for Power Systems Wide-Area Measurements and Control University of Electronic Science and Technology of China Sichuan Chengdu China Sichuan Industrial Internet Intelligent Monitoring and Application Engineering Research Center Chengdu University of Technology Sichuan 610059 China

In a complex system of multiple entities coming together and transacting energy from various sources, incentivization and energy utilization are difficult to achieve due to inefficiencies in current mechanisms set up to generate, distribute, utilize, and manage energy within varying ecosystems. We provide a solution to this by proposing a tokenized blockchain-based renewable/non-renewable energy ecosystem built on Automated Market Makers with an underlying Constant Function *** this work, we proved the feasibility of achieving a more efficient means of trading, controlling, and managing energy from multiple RE/NRE energy sources using AMMs. In this approach, we remove the need for buyers and sellers’ influence in the energy market and provide an automated means of ensuring energy flow, pricing, and regulation without the need for third parties. We were able to maintain the decarbonization degree of the entire system through the deployment of the decarbonization mechanism at a cost of 584,213 Wei, proving a self-realizing decarbonization mechanism. We observed a cost of 1,255,219 Wei for both RE/NRE participants to engage the network, showing a faster means of transacting among energy parties. A cheaper cost of 2,497,561 Wei was achieved for setting up the network for trading, a cost of 2,500,666 Wei for rebalancing energy prices, and a cost of 1,836,918 Wei for the management of the entire network. Our results thus prove the ability of our proposed idea to ensure the effective generation, control, and distribution of energy across energy ecosystems. It also offers flexibility to address the complexity within energy ecosystems. Its incentivization mechanism ensures the continuous generation of rewards, ensuring the continuity of energy systems achieved by leveraging the transparency inherent in token mechanisms in blockchain technology. © 2024, The Authors. All rights reserved.

关键词： Smart contract

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Multi-objective Optimization of A CCHP system Model Integrated with P2G for Decarbonization

Multi-objective Optimization of A CCHP System Model Integrat...

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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Pengyu Wei Olusola Bamisile Dongsheng Cai Jian Li Humphrey Adun Qi Huang School of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China Sichuan Provincial Key Lab of Power System Wide-area Measurement and Control University of Electronic Science and Technology of China Chengdu China Energy Systems Engineering Department Cyprus International University KKTC Mersin Turkey

To realize the dual carbon policy, the goal of energy saving, and emission reduction, it is important to develop ways to better promote the low carbon economic operation of energy systems. Therefore, this research proposes an optimal operation strategy considering the electric-gas-cooling-heat demand response. Considering the demand response of each participant, an integrated energy system model with photovoltaic, wind energy, and traditional grid as energy supply. Also, electric energy, natural gas, cooling, and heating subsystems with co-production are established. With minimizing the overall system operation cost and optimizing environmental protection, the improved particle swarm optimization algorithm is used to solve the multi-constrained objective optimization problem. Finally, the optimized model is tested. The results from this study show that the energy system under cogeneration can find a balance between economy and environmental friendliness, and provide a reference for the subsequent energy supply configuration.

关键词： Photovoltaic systems Renewable energy sources Wind energy systems operation system integration Demand response Particle swarm optimization

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Blockchain for Energy Market: A Comprehensive Survey

arXiv

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arXiv 2024年

作者： Jiang, Tianqi Luo, Haoxiang Yang, Kun Sun, Gang Yu, Hongfang Huang, Qi Vasilakos, Athanasios V. Glasgow College University of Electronic Science and Technology of China Chengdu611731 China Key Laboratory of Optical Fiber Sensing and Communications Ministry of Education University of Electronic Science and Technology of China Chengdu611731 China Guangyuan Power Supply Company State Grid Sichuan Electric Power Company Guangyuan628033 China Peng Cheng Laboratory Shenzhen518066 China Sichuan Provincial Key Laboratory of Power System Wide-Area Measurement and Control University of Electronic Science and Technology of China Chengdu611731 China School of Information Engineering Southwest University of Science and Technology Mianyang621010 China Center for AI Research University of Agder Grimstad4879 Norway

The energy market encompasses the behavior of energy supply and trading within a platform system. By utilizing centralized or distributed trading, energy can be effectively managed and distributed across different regions, thereby achieving market equilibrium and satisfying both producers and consumers. Additionally, the energy market can address future production control and environmental concerns such as energy shortages and environmental deterioration. However, recent years have presented unprecedented challenges and difficulties for the development of the energy market. These challenges include regional energy imbalances, volatile energy pricing, high computing costs, and issues related to transaction information disclosure. These factors have hindered the smooth operation of the energy market. Researchers widely acknowledge that the security features of blockchain technology can enhance the efficiency of energy transactions and establish the fundamental stability and robustness of the energy market. This type of blockchain-enabled energy market is commonly referred to as an energy blockchain. Currently, there is a burgeoning amount of research in this field, encompassing algorithm design, framework construction, and practical application. It is crucial to organize and compare these research efforts to facilitate the further advancement of energy blockchain. This survey aims to comprehensively review the fundamental characteristics of blockchain and energy markets, highlighting the significant advantages of combining the two. Moreover, based on existing research outcomes, we will categorize and compare the current energy market research supported by blockchain in terms of algorithm design, market framework construction, and the policies and practical applications adopted by different countries. Finally, we will address current issues and propose potential future directions for improvement, to provide guidance for the practical implementation of blockchain in the

关键词： Deterioration

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AI-aided power electronic converters automatic online real-time efficiency optimization method

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Fundamental Research 2023年第3期5卷 1111-1116页

作者： Tang, Yuanhong Cao, Di Xiao, Jian Jiang, Chenying Huang, Qi Li, Yunwei Chen, Zhe Blaabjerg, Frede Hu, Weihao Power System Wide-area Measurement and Control Sichuan Provincial Key Laboratory School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu 611731 China MORNSUN Guangzhou Science & Technology Co. Ltd. Guangzhou 510663 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu 611731 China Yangtze Delta Region Institute (Quzhou) University of Electronic Science and Technology of China Quzhou 324000 China Department of Chengdu State Grid Corporation of China Chengdu 610599 China Southwest University of Science and Technology Mianyang 621010 China Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6G 2V4 Canada Department of Energy Technology Aalborg University Aalborg 9220 Denmark

Energy losses during the conversion and supply of electric power are considered a significant issue and cannot be estimated. Improvement in the efficiency of energy conversion systems is highly restricted because of their internal nonlinearity and complexity. Thus, inspired by the successful utilization of robotic chemists, we demonstrate a pioneering concept of artificial intelligence (AI)-aided automatic online real-time optimization of a power electronics converter using a dual active bridge (DAB) converter as an example. An optimal modulation strategy was obtained through repeated automatic exploration experiments on a practical DAB converter platform. Specifically, the DAB experimental platform operated autonomously around the clock for approximately 71 h. It performed 120,000 consecutive experiments (12,000 episodes) within a six-variable experimental space driven by a deep deterministic policy gradient (DDPG) algorithm. The proposed AI-aided automatic online real-time optimization method achieved significantly improved efficiency of power conversion and supply. Consequently, zero carbon emissions may be obtained in the future. © 2023

关键词： Artificial intelligence Automatic online real-time exploration DC-DC converter Dual active bridge converter Energy conversion system power electronics

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