Publications
136 results found
Garcia-Munoz F, Teng F, Junyent-Ferre A, et al., 2022, Stochastic energy community trading model for day-ahead and intraday coordination when offering DER?s reactive power as ancillary services, SUSTAINABLE ENERGY GRIDS & NETWORKS, Vol: 32, ISSN: 2352-4677
- Author Web Link
- Cite
- Citations: 3
Higgins M, Xu W, Teng F, et al., 2022, Cyber-physical risk assessment for false data injection attacks considering moving target defences Best practice application of respective cyber and physical reinforcement assets to defend against FDI attacks, International Journal of Information Security, Vol: 22, Pages: 579-589, ISSN: 1615-5262
In this paper, we examine the factors that influence the success of false data injection (FDI) attacks in the context of both cyber and physical styles of reinforcement. Existing research considers the FDI attack in the context of the ability to change a measurement in a static system only. However, successful attacks will require first intrusion into a system followed by construction of an attack vector that can bypass bad data detection to cause a consequence (such as overloading). Furthermore, the recent development of moving target defences (MTD) introduces dynamically changing system topology, which is beyond the capability of existing research to assess. In this way, we develop a full service framework for FDI risk assessment. The framework considers both the costs of system intrusion via a weighted graph assessment in combination with a physical, line overload-based vulnerability assessment under the existence of MTD. We present our simulations on a IEEE 14-bus system with an overlain RTU network to model the true risk of intrusion. The cyber model considers multiple methods of entry for the FDI attack including meter intrusion, RTU intrusion and combined style attacks. Post-intrusion, our physical reinforcement model analyses the required level of topology divergence to protect against a branch overload from an optimised attack vector. The combined cyber and physical index is used to represent the system vulnerability against FDIA.
Ge P, Caputo C, Teng F, et al., 2022, A Wireless-Assisted Hierarchical Framework to Accommodate Mobile Energy Resources, Singapore, IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
Heylen E, Browell J, Teng F, 2022, Probabilistic Day-Ahead Inertia Forecasting, IEEE TRANSACTIONS ON POWER SYSTEMS, Vol: 37, Pages: 3738-3746, ISSN: 0885-8950
- Author Web Link
- Cite
- Citations: 5
Graham J, Heylen E, bian Y, et al., 2022, Benchmarking explanatory models for inertia forecasting using public data of the nordic area, 2022 17th International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), Publisher: IEEE, Pages: 1-6
This paper investigates the performance of a day-ahead explanatory model for inertia forecasting based on field data in the Nordic system, which achieves a 43% reduction in mean absolute percentage error (MAPE) against a state-of-the-art time-series forecast model. The generalizability of the explanatory model is verified by its consistent performance on Nordic and Great Britain datasets. Also, it appears that a long duration of training data is not required to obtain accurate results with this model, but taking a more spatially granular approach reduces the MAPE by 3.6%. Finally, two further model enhancements are studied considering the specific features in Nordic system: (i) a monthly interaction variable applied to the day-ahead national demand forecast feature, reducing the MAPE by up to 18%; and (ii) a feature based on the inertia from hydropower, although this has a negligible impact. The field dataset used for benchmarking is also made publicly available.
Caputo C, Cardin M-A, Korre A, et al., 2022, Energy System Evolution Strategies for Mobile Micro-grids using Deep Reinforcement Learning Flexibility Analysis, Espoo, Finland, 32nd European Conference on Operational Research (EURO 2022)
Teng F, Chhachhi SAURAB, Ge PUDONG, et al., 2022, Balancing privacy and access to smart meter data: an Energy Futures Lab briefing paper
Digitalising the energy system is expected to be a vital component of achieving the UK’s climate change targets. Smart meter data, in particular, is seen a key enabler of the transition to more dynamic, cost-effective, cost-reflective, and decarbonised electricity. However, access to this data faces a challenge due to consumer privacy concerns. This Briefing Paper investigates four key elements of smart meter data privacy: existing data protection regulations; the personal information embedded within smart meter data; consumer privacy concerns; and privacy-preserving techniques that could be incorporated alongside existing mechanisms to minimise or eliminate potential privacy infringements.
Hou X, Sun K, Zhang N, et al., 2022, Priority-driven self-optimizing power control scheme for interlinking converters of hybrid AC/DC microgrid clusters in decentralized manner, IEEE Transactions on Power Electronics, Vol: 37, Pages: 5970-5983, ISSN: 0885-8993
Hybrid AC/DC microgrid clusters are key building blocks of smart grid to support sustainable and resilient urban power systems. In microgrid clusters, the subgrid load-priorities and power quality requirements for different areas vary significantly. To realize optimal power exchanges among microgrid clusters, this paper proposes a decentralized self-optimizing power control scheme for interlinking converters (ILC) of hybrid microgrid clusters. A priority-driven optimal power exchange model of ILCs is built considering the priorities and capacities in subgrids. The optimization objective is to minimize the total DC-voltage/AC-frequency state deviations of subgrids. To realize the decentralized power flow control, an optimal-oriented quasi-droop control strategy of ILCs is introduced to not only achieve a flexible self-optimizing power flow management, but also provide an ancillary function of voltage support. Consequently, as each of ILCs only monitors the local AC-side frequency and DC-side voltage signals, the whole optimal power control of the wide-area microgrid clusters is achieved in a decentralized manner without any communication link. Thus, the proposed control algorithm has the features of decreased cost, increased scalability, reduced geographic restrictions and high resilience in terms of communication faults. Finally, the proposed method is validated by case studies with four interconnected microgrids through hardware-in-loop tests.
Bellizio F, Xu W, Qiu D, et al., 2022, Transition to Digitalized Paradigms for Security Control and Decentralized Electricity Market, PROCEEDINGS OF THE IEEE, ISSN: 0018-9219
Hua W, Jiang J, Sun H, et al., 2022, Consumer-centric decarbonization framework using Stackelberg game and Blockchain, APPLIED ENERGY, Vol: 309, ISSN: 0306-2619
Ge P, Teng F, Konstantinou C, et al., 2022, A resilience-oriented centralised-to-decentralised framework for networked microgrids management, Applied Energy, Vol: 308, ISSN: 0306-2619
This paper proposes a cyber–physical cooperative mitigation framework to enhance power systems resilience against power outages caused by extreme events, e.g., earthquakes and hurricanes. Extreme events can simultaneously damage the physical-layer electric power infrastructure and the cyber-layer communication facilities. Microgrid (MG) has been widely recognised as an effective physical-layer response to such events, however, the mitigation strategy in the cyber lay is yet to be fully investigated. Therefore, this paper proposes a resilience-oriented centralised-to-decentralised framework to maintain the power supply of critical loads such as hospitals, data centres, etc., under extreme events. For the resilient control, controller-to-controller (C2C) wireless network is utilised to form the emergency regional communication when centralised base station being compromised. Owing to the limited reliable bandwidth that reserved as a backup, the inevitable delays are dynamically minimised and used to guide the design of a discrete-time distributed control algorithm to maintain post-event power supply. The effectiveness of the cooperative cyber–physical mitigation framework is demonstrated through extensive simulations in MATLAB/Simulink.
Xu W, Jaimoukha IM, Teng F, 2022, Physical Verification of Data-Driven Cyberattack Detector in Power System: An MTD Approach
Stealthy false data injection attacks (FDIAs) have been shown to compromise power system state estimation. The data-driven detector is a promising way to counter FDIAs. However, it suffers from low interpretability and thus introduces uncontrollable false alarms, which has been overlooked by the literature. This paper proposes to utilise moving target defence (MTD) as an additional physics layer to verify the decisions made by the data-driven detector. First, the data-driven anomaly detector is extended to identify part of the attack vector through iterative normality projection. Second, a novel MTD algorithm is formulated to maintain the high detection rate of the data-driven detector on the identified attack vector with minimum usage. The proposed algorithm is thoroughly tested under the IEEE bus-14 system.
Chen Y, Lakshminarayana S, Teng F, 2022, Localization of Coordinated Cyber-Physical Attacks in Power Grids Using Moving Target Defense and Deep Learning, Pages: 387-392
As one of the most sophisticated attacks against power grids, coordinated cyber-physical attacks (CCPAs) damage the power grid's physical infrastructure and use a simultaneous cyber attack to mask its effect. This work proposes a novel approach to detect such attacks and identify the location of the line outages (due to the physical attack). The proposed approach consists of three parts. Firstly, moving target defense (MTD) is applied to expose the physical attack by actively perturbing transmission line reactance via distributed flexible AC transmission system (D-FACTS) devices. MTD invalidates the attackers' knowledge required to mask their physical attack. Secondly, convolution neural networks (CNNs) are applied to localize line outage position from the compromised measurements. Finally, model agnostic meta-learning (MAML) is used to accelerate the training speed of CNN following the topology reconfigurations (due to MTD) and reduce the data/retraining time requirements. Simulations are carried out using IEEE test systems. The experimental results demonstrate that the proposed approach can effectively localize line outages in stealthy CCPAs.
Zografopoulos I, Karamichailidis P, Procopiou AT, et al., 2022, Mitigation of Cyberattacks through Battery Storage for Stable Microgrid Operation, Pages: 238-244
In this paper, we present a mitigation methodology that leverages battery energy storage system (BESS) resources in coordination with microgrid (MG) ancillary services to maintain power system operations during cyberattacks. The control of MG agents is achieved in a distributed fashion, and once a misbehaving agent is detected, the MG,′s mode supervisory controller (MSC) isolates the compromised agent and initiates self-healing procedures to support the power demand and restore the compromised agent. Our results demonstrate the practicality of the proposed attack mitigation strategy and how grid resilience can be improved using BESS synergies. Simulations are performed on a modified version of the Canadian urban benchmark distribution model.
Rath S, Konstantinou C, Papari B, et al., 2022, Microgrids in mission--critical applications, CYBER SECURITY FOR MICROGRIDS, Editors: Sahoo, Blaabjerg, Dragicevic, Publisher: INST ENGINEERING TECH-IET, Pages: 39-58, ISBN: 978-1-83953-331-0
Graham J, Heylen E, Bian Y, et al., 2022, Benchmarking Explanatory Models for Inertia Forecasting using Public Data of the Nordic Area, 17th International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), Publisher: IEEE, ISSN: 2642-6730
- Author Web Link
- Cite
- Citations: 2
O'Malley C, Badesa L, Teng F, et al., 2021, Probabilistic scheduling of UFLS to secure credible contingencies in low inertia systems, IEEE Transactions on Power Systems, ISSN: 0885-8950
The reduced inertia levels in low-carbon power grids necessitate explicit constraints to limit frequency's nadir and rate of change during scheduling. This can result in significant curtailment of renewable energy due to the minimum generation of thermal plants that are needed to provide frequency response (FR) and inertia. Additional consideration of fast FR, a dynamically reduced largest loss and under frequency load shedding (UFLS) allows frequency security to be achieved more cost effectively. This paper derives a novel constraint from the swing equation to contain the frequency nadir using all of these services. The expected cost of UFLS is found probabilistically to facilitate its comparison to the other frequency services. We demonstrate that this constraint can be accurately and conservatively approximated for moderate UFLS levels with a second order cone (SOC), resulting in highly tractable convex problems. Case studies performed on a Great Britain 2030 system demonstrate that UFLS as an option to contain single plant outages can reduce annual operational costs by up to 559m, 52% of frequency security costs. The sensitivity of this value to wind penetration, abundance of alternative frequency services, UFLS amount and cost is explored.
Badesa L, Teng F, Strbac G, 2021, Conditions for regional frequency stability in power system scheduling—Part II: application to unit commitment, IEEE Transactions on Power Systems, Vol: 36, Pages: 5567-5577, ISSN: 0885-8950
In Part I of this paper we have introduced the closed-form conditions for guaranteeing regional frequency stability in a power system. Here we propose a methodology to represent these conditions in the form of linear constraints and demonstrate their applicability by implementing them in a generation-scheduling model. This model simultaneously optimises energy production and ancillary services for maintaining frequency stability in the event of a generation outage, by solving a frequency-secured Stochastic Unit Commitment (SUC). We consider the Great Britain system, characterised by two regions that create a non-uniform distribution of inertia: England in the South, where most of the load is located, and Scotland in the North, containing significant wind resources. Through several case studies, it is shown that inertia and frequency response cannot be considered as system-wide magnitudes in power systems that exhibit inter-area oscillations in frequency, as their location in a particular region is key to guarantee stability. In addition, securing against a medium-sized loss in the low-inertia region proves to cause significant wind curtailment, which could be alleviated through reinforced transmission corridors. In this context, the proposed constraints allow to find the optimal volume of ancillary services to be procured in each region.
Chu Z, Zhang N, Teng F, 2021, Frequency-Constrained Resilient Scheduling of Microgrid: A Distributionally Robust Approach, IEEE TRANSACTIONS ON SMART GRID, Vol: 12, Pages: 4914-4925, ISSN: 1949-3053
Badesa L, Teng F, Strbac G, 2021, Conditions for regional frequency stability in power system scheduling—Part I: theory, IEEE Transactions on Power Systems, Vol: 36, Pages: 5558-5566, ISSN: 0885-8950
This paper considers the phenomenon of distinct regional frequencies recently observed in some power systems. First, a reduced-order mathematical model describing this behaviour is developed. Then, techniques to solve the model are discussed, demonstrating that the post-fault frequency evolution in any given region is equal to the frequency evolution of the Centre Of Inertia plus certain inter-area oscillations. This finding leads to the deduction of conditions for guaranteeing frequency stability in all regions of a power system, a deduction performed using a mixed analytical-numerical approach that combines mathematical analysis with regression methods on simulation samples. The proposed stability conditions are linear inequalities that can be implemented in any optimisation routine allowing the co-optimisation of all existing ancillary services for frequency support: inertia, multi-speed frequency response, load damping and an optimised largest power infeed. This is the first reported mathematical framework with explicit conditions to maintain frequency stability in a power system exhibiting inter-area oscillations in frequency.
Xiang Y, Wang Y, Xia S, et al., 2021, Charging load pattern extraction for residential electric vehicles: a training-free nonintrusive method, IEEE Transactions on Industrial Informatics, Vol: 17, Pages: 7028-7039, ISSN: 1551-3203
Extracting the charging load pattern of residential electric vehicle (REV) will help grid operators make informed decisions in terms of scheduling and demand-side response management. Due to the multistate and high-frequency characteristics of integrated residential appliances from the residential perspective, it is difficult to achieve accurate extraction of the charging load pattern. To deal with that, this article presents a novel charging load extraction method based on residential smart meter data to noninvasively extract REV charging load pattern. The proposed algorithm harnesses the low-frequency characteristics of the charging load pattern and applies a two-stage decomposition technique to extract the characteristics of the charging load. The two-stage decomposition technique mainly includes: the trend component of the charging load being decomposed by seasonal and trend decomposition using loess method, and the low-frequency approximate component being decomposed by discrete wavelet technology. Furthermore, based on the extracted characteristics, event monitoring, and dynamic time warping is applied to estimate the closest charging interval and amplitude. The key features of the proposed algorithm include 1) significant improvement in extraction accuracy; 2) strong noise immunity; 3) online implementation of extraction. Experiments based on ground truth data validate the superiority of the proposed method compared to the existing ones.
Zhao P, Gu C, Cao Z, et al., 2021, Data-Driven Multi-Energy Investment and Management Under Earthquakes, IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, Vol: 17, Pages: 6939-6950, ISSN: 1551-3203
Pan G, Gu W, Hu Q, et al., 2021, Cost and low-carbon competitiveness of electrolytic hydrogen in China, ENERGY & ENVIRONMENTAL SCIENCE, Vol: 14, Pages: 4868-4881, ISSN: 1754-5692
- Author Web Link
- Cite
- Citations: 22
Zhao J, Wu Q, Hatziargyriou ND, et al., 2021, Decentralized Data-Driven Load Restoration in Coupled Transmission and Distribution System With Wind Power, IEEE TRANSACTIONS ON POWER SYSTEMS, Vol: 36, Pages: 4435-4444, ISSN: 0885-8950
- Author Web Link
- Cite
- Citations: 20
Li H, Qiao Y, Lu Z, et al., 2021, Frequency-Constrained Stochastic Planning Towards a High Renewable Target Considering Frequency Response Support From Wind Power, IEEE TRANSACTIONS ON POWER SYSTEMS, Vol: 36, Pages: 4632-4644, ISSN: 0885-8950
- Author Web Link
- Cite
- Citations: 21
Heylen E, Teng F, Strbac G, 2021, Challenges and opportunities of inertia estimation and forecasting in low-inertia power systems, Renewable and Sustainable Energy Reviews, Vol: 147, Pages: 1-12, ISSN: 1364-0321
Accurate inertia estimates and forecasts are crucial to support the system operation in future low-inertia power systems. A large literature on inertia estimation methods is available. This paper aims to provide an overview and classification of inertia estimation methods. The classification considers the time horizon the methods are applicable to, i.e., offline post mortem, online real time and forecasting methods, and the scope of the inertia estimation, e.g., system-wide, regional, generation, demand, individual resource. The framework presented in this paper facilitates objective comparisons of the performance of newly developed or improved inertia estimation methods with the state-of-the-art methods in their respective time horizon and with their respective scope. Moreover, shortcomings of the existing inertia estimation methods have been identified and suggestions for future work have been made.
Yong P, Zhang N, Hou Q, et al., 2021, Evaluating the Dispatchable Capacity of Base Station Backup Batteries in Distribution Networks, IEEE TRANSACTIONS ON SMART GRID, Vol: 12, Pages: 3966-3979, ISSN: 1949-3053
- Author Web Link
- Cite
- Citations: 21
Chu Z, Teng F, 2021, Short circuit current constrained UC in the high IBG-penetrated power systems, IEEE Transactions on Power Systems, Vol: 36, Pages: 3776-3785, ISSN: 0885-8950
Inverter Based Generators (IBGs) have been increasing significantly in power systems. Due to the demanding thermal rating of Power Electronics (PE), their contribution to the system Short Circuit Current (SCC) is much less than that from the conventional Synchronous Generators (SGs) thus reducing the system strength and posing challenges to system protection and stability. This paper proposes a Unit Commitment (UC) model with SCC constraint in high IBG-penetrated systems to ensure minimum operation cost while maintaining the SCC level at each bus in the system. The SCC from synchronous generators as well as the IBGs are explicitly modeled in the formulation leading to an SCC constraint involving decision-dependent matrix inverse. This highly nonlinear constraint is further reformulated into linear form conservatively. The influence of the SCC constraint on the system operation and its interaction with the frequency regulation are demonstrated through simulations on IEEE 30- and 118-bus systems.
Zhao P, Gu C, Cao Z, et al., 2021, A Cyber-Secured Operation for Water-Energy Nexus, IEEE TRANSACTIONS ON POWER SYSTEMS, Vol: 36, Pages: 3105-3117, ISSN: 0885-8950
- Author Web Link
- Cite
- Citations: 5
Tosatto A, Misyris G, Junyent-Ferre A, et al., 2021, Towards optimal coordination between regional groups: HVDC supplementary power control, IEEE Transactions on Power Systems, Vol: 37, Pages: 1-1, ISSN: 0885-8950
With Europe dedicated to limiting climate change and greenhouse gas emissions, large shares of Renewable Energy Sources (RES) are being integrated in the national grids, phasing out conventional generation. The new challenges arising from the energy transition will require a better coordination between neighboring system operators to maintain system security. To this end, this paper studies the benefit of exchanging primary frequency reserves between asynchronous areas using the Supplementary Power Control (SPC) functionality of High-Voltage Direct-Current (HVDC) lines. First, we focus on the derivation of frequency metrics for asynchronous AC systems coupled by HVDC interconnectors. We compare two different control schemes for HVDC converters, which allow for unilateral or bilateral exchanges of reserves between neighboring systems. Second, we formulate frequency constraints and include them in a unit commitment problem to ensure the N-1 security criterion. A data-driven approach is proposed to better represent the frequency nadir constraint by means of cutting hyperplanes. Our results suggest that the exchange of primary reserves through HVDC can reduce up to 10% the cost of reserve procurement while maintaining the system N-1 secure.
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.