Title: Polar Clean Energy Laboratory Supports Renewable Energy Utilisation in Antarctica Qinling Station
Authors: Hongbin Sun, Yixun Xue, Yinke Dou, Bin Wang, Jiahe Xu
DOI: 10.1049/ein2.70006
Abstract: The world's first large-scale clean energy system in Antarctica has been launched at China's Qinling Station, marking a milestone in sustainable polar research. This system integrates wind, solar, hydrogen and battery technologies to establish a renewable energy framework suitable for polar environments. To tackle Antarctica's extreme conditions during research and development phases, Taiyuan University of Technology (TYUT) built a Polar Clean Energy Laboratory that simulates harsh environments such as strong winds, low temperatures and polar day/night cycles. The lab enables rigorous testing and optimisation of equipment before deployment. It also provides a closed-loop research cycle, from lab design to polar application and iterative upgrades, ensuring reliability and efficiency in extreme conditions. This progress not only supports eco-friendly polar operations but also offers insights for global clean energy development in extreme environments.
Title: Functional Safety Analysis and Mitigation in Power Systems: A Cyber-Physical Perspective
Authors: Shuyu Jia, Qinglai Guo
DOI: 10.1049/ein2.70007
Abstract: The economical, stable and efficient operation of power systems is intrinsically linked to secondary systems and their diverse functional applications. With the advancement of communication technologies, control algorithms, and emerging regulatory entities, modern power systems have evolved to become more intelligent yet complex compared to traditional grids. As the conceptual framework of power system security expands from primary system safety to a holistic cyber-physical paradigm, the functional safety of secondary systems has emerged as a critical and paramount requirement for ensuring overall grid stability and reliability. This paper systematically reviews research on functional safety analysis and mitigation strategies for secondary systems from a cyber-physical perspective. Firstly, the basic concept and propagation mechanism of power system functional security are introduced; secondly, the research difficulties of functional security are analysed from the three dimensions of system, data and software security; then, the current research status of functional security in different dimensions is summarised; finally, we offer a forward-looking perspective on future research directions for analysing and mitigating functional safety risks, emphasising the prevention of physical grid failures caused by secondary system anomalies from a cyber-physical viewpoint.
Title: A Learning-Based Joint Bidding Strategy for Photovoltaic-Energy Storage System Power Plant in Singapore Electricity Market
Authors: Qidi Zhou, Yang Xia, Yan Xu
DOI: 10.1049/ein2.70009
Abstract: With the rapid development of clean energy, photovoltaic (PV) power plants have gained increasing attention. However, the inherent intermittency of PV generation requires the integration of energy storage system (ESS) to smooth power output and enhance grid stability. Coordinating multiple PV–ESS plants is essential to maintain system reliability, balance stochastic renewable outputs with real-time load demands, and leverage time-varying electricity prices for economic benefits. In this paper, a learning-based joint bidding framework is proposed to maximise the aggregated profit of PV–ESS plants. First, a multi-PV–ESS model is built to emulate the coordinated operation of PV and ESS units in the power grid, aiming to maximise PV power revenues while considering penalty payments for power shortages, real-time load demands and dynamic power prices. Then, the joint bidding operations of PV–ESS plants are formulated as a Markov decision process, and a deep reinforcement learning algorithm is developed to learn optimal bidding strategies that adapt to load dynamics and price fluctuations. Extensive case studies on distribution systems of different scales, including the IEEE 33-bus and 69-bus systems, are conducted to demonstrate the effectiveness of the proposed method.
Title: Sensor Attacks and Robust Defence on HVAC Systems for Energy Market Signal Tracking
Authors: Guanyu Tian, Qunzhou Sun, Yiyuan Qiao
DOI: 10.1049/ein2.70008
Abstract: The power flexibility from smart buildings makes them suitable candidates for providing grid services. The building automation system (BAS) that employs model predictive control (MPC) for grid services relies heavily on sensor data gathered from IoT-based HVAC systems through communication networks. However, cyberattacks that tamper sensor values can compromise the accuracy and flexibility of HVAC system power adjustment. Existing studies on grid-interactive buildings mainly focus on the efficiency and flexibility of buildings’ participation in grid operations, whereas the security aspect is lacking. In this paper, we investigate the effects of cyberattacks on HVAC systems in grid-interactive buildings, specifically their power-tracking performance. We design a stochastic optimisation-based stealthy sensor attack and a corresponding defence strategy using a robust control framework. The attack and its defence are tested in a physical model of a test building with a single-chiller HVAC system. Simulation results demonstrate that minor falsifications caused by a stealthy sensor attack can significantly alter the power profile, leading to large power tracking errors. However, the robust control framework can reduce the power tracking error by over 70% under such attacks without filtering out compromised data.
Title: Planning Method for Electric Vehicle Charging Stations Considering Dynamic Traffic Load Demand Prediction
Authors: Jiawang Ji, Hongzhou Chen, Jiahui Zhang, Jia Su, Huajian Li, Tao Niu, Sidun Fang, Guanhong Chen, Ruijin Liao
DOI: 10.1049/ein2.70005
Abstract: With the increasing integration of electric vehicles (EVs) into urban energy systems, the strong coupling among the stochastic nature of EV charging behaviours, the dynamic operation of power grids, and the variability of transportation networks poses significant challenges to urban infrastructure planning. To address this issue, this paper proposes a charging station planning method incorporating dynamic traffic load forecasting. First, a charging demand prediction model is developed by integrating the urban traffic network structure with EV travel behaviour characteristics. Then, an optimisation model for charging station siting and capacity planning is formulated with the objective of minimising the total integrated cost, while considering the coupling constraints between the transportation network and the distribution system. The model is solved using an improved particle swarm optimisation (IPSO) algorithm. Finally, case studies based on the IEEE 33-bus distribution system and a 25-node transportation network are conducted. Simulation results demonstrate that the proposed method can effectively accommodate the dynamic charging demands of EVs, achieve rapid convergence, and reduce the overall cost of coordinated operation between charging stations and the distribution system by more than 10% compared with traditional methods, thereby enhancing overall operational efficiency.
Title: Coupling Modelling and Fault Propagation Simulation Method for Power Grid-Centric Urban Lifeline Systems Under Extreme Disasters
Authors: Chengeng Zhang, Yin Xu, Yiran Chen, Yufeng Gan
DOI: 10.1049/ein2.70010
Abstract: The interconnection of urban critical infrastructure poses new challenges to the secure operation of power grid-centric urban lifeline systems. The interdependencies among infrastructure systems increase the risk of cascading fault propagation, thereby threatening urban public safety. Coupling modelling and fault propagation simulation of urban lifeline systems provide a foundation for analysing disaster evolution mechanisms and support research on resilience assessment and enhancement technologies. In this paper, a coupling modelling and simulation method for urban lifeline systems under extreme disaster scenarios is proposed. First, based on fault propagation analysis requirements, the basic principles for coupling modelling are established, and simulation models suitable for lifeline systems under different time scales are analysed. Second, a co-simulation method combining time-driven and event-driven mechanisms is designed. Customised interfaces for information exchange between systems are developed based on mature simulation software, enabling the simulation of the disaster impact propagation process. Finally, the effectiveness of the proposed method is verified using a constructed urban lifeline coupling test system.
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审核：李兰欣
https://mc.manuscriptcentral.com/csee-theiet-ein
https://ietresearch.onlinelibrary.wiley.com/journal/29952166
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