Collaborative operation of active distribution network considering PV-storage-charging-compensationWu, Ning; Lin, Xiaoming; Han, Shuai; Qian, Bin; Lin, Rui; Xiao, Jing; Sun, Leping
doi: 10.1088/1742-6596/2874/1/012014pmid: N/A
With the conjunction of clean energy generation and electric cars, the power distribution network is gradually shifting from a traditional one-way radiative network to an active network. Coordinated control of these controllable elements of “source-grid-load-storage” can improve the operating voltage level and economic benefits, and reduce the load peak and off-peak difference. A collaborative dispatch model for active power distribution networks including PV-storage-charging-compensation is constructed in this paper, with the goal of minimizing network losses and PV curtailment costs. The cone transformation is used to handle non-linear constraints of power flow. Compared with existing ordered charging control methods, the constructed model can maximize the control efficiency of the distribution grid, enhance the PV absorption capacity, and effectively slow down the upgrading and renovation of the distribution network.
Analysis of green energy-saving retrofit for air-conditioning system in UHVDC converter stationsWang, Hui; Li, Chenxi; MA, Shiwen; Yin, Xiwei; Yu, Mingduo; Lu, Mengxue
doi: 10.1088/1742-6596/2874/1/012002pmid: N/A
The air-conditioning system in ultra-high-voltage direct current (UHVDC) converter stations uses hydrofluorocarbons (HFCs) as refrigerants currently, which pose a certain environmental hazard. Moreover, the cooling system of the converter valves contains a great deal of low-grade thermal energy, with waste heat being directly discharged into the air, resulting in significant energy wastage and air pollution. In light of the functional characteristics and energy wastage situation of current converter station buildings, a green energy-saving retrofit scheme for the air-conditioning system in UHVDC converter stations is proposed. It adopts a transcritical CO2 cycle system for building cooling and introduces an ejector into the system to improve its performance. Simultaneously, the heat pump technology is used to elevate the grade of waste heat from the converter valves, which is then utilized for heating in the control building. Simulation results demonstrate that this scheme is effective in enhancing ecological and environmental benefits while promoting green development of the converter station.
Research on distributed optimal scheduling method based on consensusDuan, Liwei; Yang, Chao
doi: 10.1088/1742-6596/2874/1/012010pmid: N/A
With access to large-scale distributed power sources, the physical structure of the power grid system tends to be distributed. The application of traditional centralized optimal scheduling methods will lead to a surge in communication overhead and computational complexity, which will affect the performance and efficiency of the solution. In this paper, the minimum operating cost of the system is taken as the goal, and the distributed direct current optimal power flow (DC-OPF) optimization calculation of the photovoltaic-storage power generation system is considered to approximately solve the economic dispatch problem. The DC optimal power flow model with energy storage charging penalty is constructed. Then, the distributed optimization method based on the consensus alternating direction multiplier method (ADMM) is adopted. By decoupling the objective function and constraints of the whole system problem, the fully distributed DC-OPF calculation is realized by introducing the global consensus variable to deal with the boundary buses. Finally, the improved IEEE 30-bus example is used to test the method, and the simulation results verify the convergence and accuracy of the method.
Assembly and operation optimization of proton exchange membrane water electrolyzer for performance enhancementKe, Shengjin; Jiang, Xuhui; Zhang, Xi; Wang, Song
doi: 10.1088/1742-6596/2874/1/012011pmid: N/A
Proton exchange membrane water electrolysis (PEMWE) for hydrogen production possesses wide-ranging and rapid dynamic response capabilities, offering promising applications in the consumption of new energy sources and the dynamic balancing of power grids with a high proportion of renewable energy. The assembly and operating conditions of PEMWE significantly affect its performance. Therefore, thoroughly studying and understanding the influence of PEMWE’s assembly and operating conditions on water electrolysis performance are crucial for enhancing PEMWE’s performance and promoting its applications. In this research, the influence of installation preload torque, feedwater flow rate, and operating temperature on the performance of the electrolyzer, including the electrochemical active specific surface area (ECSA), high-frequency resistance (HFR) and various types of polarizations (including activation polarization, ohmic polarization, and mass transfer polarization) during the operation of the electrolyzer, were detailedly investigated. The results showed that the optimal preload torque and operating temperature for the electrolyzer were 3 Nm and 80°C. Under these conditions, an optimized PEMWE performance would be achieved by ensuring that the feedwater flow rate exceeded the water consumption during electrolysis.
IEC104 protocol-based substation data upload IoT cloud platform implementationYang, Chao; Chen, Deji; Hu, Hongyuan
doi: 10.1088/1742-6596/2874/1/012006pmid: N/A
The Industrial Internet of Things (IoT) has been developing rapidly under the background of Internet technology, and the most crucial part of its realization is the unified collection and access of heterogeneous data from multiple sources across networks and regions. For the access of substation system data, this paper designs a scheme to read data from IEC 60870-5-104 protocol and upload the data to IOT cloud platform by converting the data to data format supported by Kafka protocol, solving the problem of incompatibility between communication protocols, obtaining data from 104 secondary stations by connecting to them, parsing and processing the data in different formats, and converting the data to JSON format by processing and sending it to the IOT cloud platform. The data is converted into JSON format through processing and sent to the Kafka server, and the cloud platform obtains its data by subscribing to the corresponding topics. This approach makes substation data access more convenient, and efficiently and effectively saves the cost of hardware gateway, solves the incompatibility and interoperability between the underlying equipment access protocol and the cloud platform communication protocol, and builds a bridge for the remote transmission of the underlying equipment data of the Industrial Internet of Things.
Large-signal stability analysis of an islanded DC microgrid with constant power loads based on mixed potential functionZhang, Shaojie; Wen, Sufang; Wang, Shunli
doi: 10.1088/1742-6596/2874/1/012013pmid: N/A
In DC microgrids, power electronic converters are widely used to connect loads and renewable energy sources to generate different voltages. These loads operate as constant power loads (CPL) within a closed control loop. When voltage fluctuates, these loads display negative impedance characteristics, potentially leading to system instability. Therefore, the analysis of the impact of CPL on DC microgrids during large disturbances is crucial. This paper employs mixed potential theory to study the large disturbance stability of DC microgrids under CPL. Deriving the stability criterion for the system under significant perturbations reveals the impact of load types and control parameters on system stability and provides a detailed analysis of how specific system parameters affect stability. Consequently, the stability criterion can ensure the system’s stability under large disturbances without the need for repeated calculations and simulations. Simulation results verify the correctness of this stability criterion.
Prefacedoi: 10.1088/1742-6596/2874/1/011001pmid: N/A
In the ever-evolving landscape of technological advancements, the fusion of smart energy systems and the Internet of Things has emerged as a pivotal force driving global sustainability and innovation. With this vision in mind, the 2024 3rd International Conference on Smart Energy and Energy Internet of Things (SEEIoT 2024) was successfully convened from June 21st to 23rd, 2024, in Chengdu, China.SEEIoT 2024 is not only a focused display of the latest research results in smart energy systems and the Internet of Things, but also an important platform to promote the development and application of disciplines and domains related to smart energy systems and the Internet of Things globally. It attracted scholars, experts, researchers and engineers from all over the world, and a total of about 100 delegates participated in the event, including some international delegates, which reflects the internationalization and extensiveness of the fields of smart energy systems and the Internet of Things.The event was packed with a diverse and engaging agenda, comprising keynote speeches, oral presentations, poster sessions, and academic discussions. During the conference, participants had in-depth discussions and exchanges on the latest progress and trends about smart energy systems and the Internet of Things. In the keynote speech session, a number of leading authorities in the field shared their research results and insightful perspectives, which provided participants with valuable academic insights and set the tone for the conference. In the oral presentation and poster sessions, participants gained more opportunities to demonstrate their research results and interacted directly with each other, which promoted the collision of academic ideas and deepened the cooperation and exchange.The Proceedings, a collection of accepted papers from SEEIoT 2024, covers a wide range of aspects such as Smart Grid, Intelligent Transmission and Distribution, Power Grid Dispatching and Automation Control, Power System Condition Monitoring, Energy Management for Microgrids, Ubiquitous Electric Internet of Things, Intelligent Energy Management, etc., which fully demonstrates the latest research trends and practical achievements in the fields of smart energy systems and the Internet of Things. It not only captures the essence of the conference discussions and presentations, but also serves as a valuable resource for researchers, practitioners, and policymakers alike.The successful organization of SEEIoT 2024 not only promotes academic exchanges and technical progress in the fields of smart energy systems and the Internet of Things, but also strengthens international cooperation and ties. And the international influence of the conference has been significantly enhanced, which has injected new vitality and impetus for the future development of relevant domains and industries.Finally, we extend our heartfelt gratitude to all the authors, reviewers, sponsors, organizers, and participants who made SEEIoT 2024 a truly remarkable event. Meanwhile, we also expect that the SEEIoT series of conferences will continue to play an important role in promoting international academic exchanges and technical cooperation, and contribute to the prosperity and development of smart energy systems and the Internet of Things.The Committee of SEEIoT 2024List of Committee Member is available in this PDF.
Application and practice of industrial IoT cloud platform in oilfield intelligent transformationHuang, Zhanwei; Zhao, Hui; Nan, Zhengqi; Ma, Hongxing; Li, Xuan; Li, Honghong; Nie, Shuaishuai
doi: 10.1088/1742-6596/2874/1/012004pmid: N/A
Under the context of global energy transformation and low-carbon development, the traditional petroleum industry is facing a series of challenges such as technological innovation, market competition, environment protection, etc. Therefore, there is an urgent demand to realize green, safe, economical, and efficient development of oil and gas through oilfield intelligent transformation. This study develops a novel cloud platform covering the whole business based on the technical architecture of the industrial Internet of Things (IoT) for assisting the intelligent transformation of oilfields. Since the application of the IoT-based cloud platform in Qingcheng Oilfield, functions such as automatic collection of whole-domain data, remote monitoring, early warning, as well as intelligent analysis and decision-making have been realized. Furthermore, compared with the traditional platform, the new platform has improved eight indicators, such as data processing efficiency and sharing capacity, by more than 20%. Consequently, the developed IoT-based cloud platform can significantly improve the production and management level of the oilfield, and efficiently support oilfield intelligent transformation.
Virtual energy dispatching method for hybrid microgrid demand response based on Lyapunov optimizationGebrie Jember, Adugna; Bao, Ruiyu; Wu, Wenqing; Wang, Zhao; Zhou, Zhenyu
doi: 10.1088/1742-6596/2874/1/012001pmid: N/A
The hybrid microgrid (HMG) possesses power generation, storage, and distribution capabilities, serving as an integrated foundational structure for advanced localized distribution networks. However, due to significant discrepancies in load demands and energy consumption among different users, the photovoltaic (PV) generation output and end-user load requirements exhibit unpredictability, resulting in relatively low self-sufficiency ratio (SSR) and self-consumption ratio (SCR) of the HMG PV system. To address this issue, this study proposes a virtual energy dispatching method for hybrid microgrid demand response based on Lyapunov optimization. Initially, a bidirectional virtual energy dispatching system model based on energy provider/buyer classification is constructed, optimizing load demands and energy management of both the load side and the main utility grid (MUG) while considering demand response. Subsequently, a Lyapunov optimization-based bidirectional virtual energy dispatching algorithm (LOBVED) is introduced, optimizing queueing systems in stochastic networks based on drift-plus-penalty technique to resolve the dynamic interactions among stability, performance, and energy self-sufficiency in the HMG environment, aiming to maximize the PV SSR and SCR of the HMG while ensuring the reliability of battery energy storage (BES) energy queues. Finally, the effectiveness of the proposed method is validated through MATLAB simulations.