Network reconfiguration under a stochastic optimisation framework for Day-Ahead Operation Planning for Future Distribution Networks (2023)
Conference Proceeding
Higuera, G., & Kazemtabrizi, B. (2023). Network reconfiguration under a stochastic optimisation framework for Day-Ahead Operation Planning for Future Distribution Networks. . https://doi.org/10.1049/icp.2023.0963

This paper proposes a novel Active Network Management (ANM) framework for day-ahead operations planning of a medium-voltage active Distribution Network (DN) using a heuristic Network Reconfiguration (NR) algorithm with a Curtailment Minimisation Sche... Read More about Network reconfiguration under a stochastic optimisation framework for Day-Ahead Operation Planning for Future Distribution Networks.

Stochastic Optimization of an Active Network Management Scheme for a DER-Rich Distribution Network Comprising Various Aggregators (2023)
Conference Proceeding
Adeniji, O., & Kazemtabrizi, B. (2023). Stochastic Optimization of an Active Network Management Scheme for a DER-Rich Distribution Network Comprising Various Aggregators. In 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). https://doi.org/10.1109/EEEIC/ICPSEUROPE57605.2023.10194840

With large-scale acceptance of solar and wind energy generation into electric grids, large energy storage is expected to provide sufficient flexibility for the safe, stable and economic operation of power systems under uncertainty. Active Network Man... Read More about Stochastic Optimization of an Active Network Management Scheme for a DER-Rich Distribution Network Comprising Various Aggregators.

Optimum operational planning of wind-integrated power systems with embedded Multi-terminal High Voltage Direct Current Links using the Flexible Universal Branch Model (2023)
Conference Proceeding
Hamzah, S. K., & Kazemtabrizi, B. (2023). Optimum operational planning of wind-integrated power systems with embedded Multi-terminal High Voltage Direct Current Links using the Flexible Universal Branch Model. In 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). https://doi.org/10.1109/EEEIC/ICPSEurope57605.2023.10194786

This paper presents a comprehensive analysis of a meshed MT-HVDC topology with three wind farms connected to the Substation Ring Topology (SRT) and investigates the steady state performance of the MT-HVDC system based on the VSC control strategies (i... Read More about Optimum operational planning of wind-integrated power systems with embedded Multi-terminal High Voltage Direct Current Links using the Flexible Universal Branch Model.

Calculating the Maximum Penetration of Electric Vehicles in Distribution Networks with Renewable Energy and V2G (2023)
Conference Proceeding
Thomas, H., Sun, H., & Kazemtabrizi, B. (2023). Calculating the Maximum Penetration of Electric Vehicles in Distribution Networks with Renewable Energy and V2G. In 2023 IEEE PES Conference on Innovative Smart Grid Technologies - Middle East (ISGT Middle East). https://doi.org/10.1109/isgtmiddleeast56437.2023.10078520

The uptake of electric vehicles and distributed energy generation is adding significant new demand to distribution networks, however it is unknown whether this can be accommodated by existing infrastructure. This paper first presents an Optimisation... Read More about Calculating the Maximum Penetration of Electric Vehicles in Distribution Networks with Renewable Energy and V2G.

Performance comparison of Probabilistic and Artificial Neural Network Models for Long-sequence Generation of Wind Speed Forecasts (2022)
Conference Proceeding
Pina-Gongora, D. C., Kazemtabrizi, B., & Crabtree, C. (2022). Performance comparison of Probabilistic and Artificial Neural Network Models for Long-sequence Generation of Wind Speed Forecasts. . https://doi.org/10.1049/icp.2022.2777

This paper presents a new method for generating long-sequence wind speed time-series forecasts for purposes of offshore wind farm asset and operations planning. Our goal is to develop a planning decision support tool with which wind farm planners and... Read More about Performance comparison of Probabilistic and Artificial Neural Network Models for Long-sequence Generation of Wind Speed Forecasts.

Electric Vehicle Battery Pack Design for Mitigating Thermal Runaway Propagation (2022)
Conference Proceeding
Copsey, E., Sun, H., & Jiang, J. (2022). Electric Vehicle Battery Pack Design for Mitigating Thermal Runaway Propagation. . https://doi.org/10.1109/vtc2022-fall57202.2022.10012777

The production of electric vehicle battery packs with ever-increasing energy densities has accelerated the electrification of the world’s automotive industry. With increased attention on the electric vehicle markets, it is vital to increase the safet... Read More about Electric Vehicle Battery Pack Design for Mitigating Thermal Runaway Propagation.

Digital Twins for Smart Cities: Case Study and Visualisation via Mixed Reality (2022)
Conference Proceeding
Piper, W., Sun, H., & Jiang, J. (2022). Digital Twins for Smart Cities: Case Study and Visualisation via Mixed Reality. . https://doi.org/10.1109/vtc2022-fall57202.2022.10012753

Digital twins is an increasingly valuable technology for realising smart cities worldwide. Visualising this technology using mixed reality creates unprecedented opportunities to easily access relevant data and information. In this paper, a digital tw... Read More about Digital Twins for Smart Cities: Case Study and Visualisation via Mixed Reality.

A Microgrid Management System Based on Metaheuristics Particle Swarm Optimization (2022)
Conference Proceeding
Deng, H., Jiang, J., Qian, H., & Sun, H. (2022). A Microgrid Management System Based on Metaheuristics Particle Swarm Optimization. . https://doi.org/10.1109/icsgsc56353.2022.9963000

Microgrid is playing an increasingly important role in making the utility grid more intelligent and efficient, since it can make better use of the renewable energy resources to simultaneously relieve the grid supply pressure and reduce carbon emissio... Read More about A Microgrid Management System Based on Metaheuristics Particle Swarm Optimization.

Demand side management considering household appliances and EV (2022)
Conference Proceeding
Dong, Z., Jiang, J., Qian, H., & Sun, H. (2022). Demand side management considering household appliances and EV. . https://doi.org/10.1109/icsgsc56353.2022.9963032

Combination of the information technology and the power engineering is the feature of next-generation grid. Depending on bidirectional communications, demand side management (DSM) aims at optimizing the electricity usage pattern of customers to impro... Read More about Demand side management considering household appliances and EV.

Protecting privacy in microgrids using federated learning and deep reinforcement learning (2022)
Conference Proceeding
Chen, W., Sun, H., Jiang, J., You, M., & Piper, W. (2022). Protecting privacy in microgrids using federated learning and deep reinforcement learning. . https://doi.org/10.1049/icp.2023.0100

This paper aims to improve the energy management efficiency of home microgrids while preserving privacy. The proposed microgrid model includes energy storage systems, PV panels, loads, and the connection to the main grid. A federated multi-objective... Read More about Protecting privacy in microgrids using federated learning and deep reinforcement learning.

Appliance Scheduling Optimisation Method Using Historical Data in Households with RES Generation and Battery Storage Systems (2022)
Conference Proceeding
Correa-Delval, M., Sun, H., Matthews, P. C., & Chiu, W. (2022). Appliance Scheduling Optimisation Method Using Historical Data in Households with RES Generation and Battery Storage Systems. . https://doi.org/10.1109/repe55559.2022.9949497

In recent years, the importance of reducing carbon dioxide (CO2) emissions has increased. With the use of technologies such as artificial intelligence, we can improve the way households manage their energy use to decrease cost and carbon emissions. I... Read More about Appliance Scheduling Optimisation Method Using Historical Data in Households with RES Generation and Battery Storage Systems.

Air-Gapped Current Transformer simulation and accuracy assessment (2022)
Conference Proceeding
Ceron-Oliver, L., Wang, Q., & Zeze, D. (2022). Air-Gapped Current Transformer simulation and accuracy assessment. . https://doi.org/10.1109/melecon53508.2022.9843105

The implementation of smart grids makes it necessary to have reliable and efficient measuring devices. Current sensors used for metering purposes in the grid must be accurate enough to overcome new challenges that power networks face such as injectio... Read More about Air-Gapped Current Transformer simulation and accuracy assessment.

Statistical Power Grid Observability under Finite Blocklength (2022)
Conference Proceeding
Zhan, Q., Liu, N., Pan, Z., & Sun, H. (2022). Statistical Power Grid Observability under Finite Blocklength. . https://doi.org/10.1109/cniot55862.2022.00026

We study the stochastic observability of the power grid system under communication constraints in the finite blocklength regime. Compared to the study under the assumption of infinite blocklength, we introduce two new elements: probability of decodin... Read More about Statistical Power Grid Observability under Finite Blocklength.

Statistical Power Grid Observability under NOMA-based Communication Constraints (2022)
Conference Proceeding
Zhan, Q., Liu, N., Pan, Z., & Sun, H. (2022). Statistical Power Grid Observability under NOMA-based Communication Constraints. . https://doi.org/10.1109/cniot55862.2022.00017

This paper studies the observability of the power grid by jointly considering the power system with the wireless communication system under the strict latency requirements of Phasor Measurement Units (PMUs), which is characterized via the theory of e... Read More about Statistical Power Grid Observability under NOMA-based Communication Constraints.

Structure health monitoring of concrete structures using magnetic flux leakage (2022)
Conference Proceeding
Zhang, Y., Wang, Q., & Huang, S. (2022). Structure health monitoring of concrete structures using magnetic flux leakage. . https://doi.org/10.11159/iccste22.214

Reinforcing bar, usually made of steel, is widely used in civil structures to increase the tensile strength of concrete. Heatinduced delayed expansion and corrosion expansion resulting in rust occupies a greater volume than rebar. This expansion crea... Read More about Structure health monitoring of concrete structures using magnetic flux leakage.

A comparison of air pollution in developed and developing cities: A case study of London and Beijing (2022)
Conference Proceeding
Sun, S., & Wang, Q. (2022). A comparison of air pollution in developed and developing cities: A case study of London and Beijing.

With the rapid development of industrialization, countries in different stages of development in the world have gradually begun to pay attention to the impact of air pollution on health and the environment. Air control in developed countries is an ef... Read More about A comparison of air pollution in developed and developing cities: A case study of London and Beijing.

Enhanced Methods for Evolution in-Materio Processors (2022)
Conference Proceeding
Jones, B. A., Al Moubayed, N., Zeze, D. A., & Groves, C. (2022). Enhanced Methods for Evolution in-Materio Processors. . https://doi.org/10.1109/icrc53822.2021.00026

Evolution-in-Materio (EiM) is an unconventional computing paradigm, which uses an Evolutionary Algorithm (EA) to configure a material's parameters so that it can perform a computational task. While EiM processors show promise, slow manufacturing and... Read More about Enhanced Methods for Evolution in-Materio Processors.

Blockchain Smart Contracts for Grid Connection Management in Achieving Net Zero Energy Systems (2021)
Conference Proceeding
Hua, W., Jing, R., Zhou, Y., Zhang, X., Jiang, J., & Sun, H. (2022). Blockchain Smart Contracts for Grid Connection Management in Achieving Net Zero Energy Systems. . https://doi.org/10.46855/energy-proceedings-9190

Energy systems are transitioning towards a decentralized and decarbonized paradigm with the integration of distributed renewable energy sources. Blockchain smart contracts have the increasing potential to facilitate the transition of energy systems d... Read More about Blockchain Smart Contracts for Grid Connection Management in Achieving Net Zero Energy Systems.

Short-term load forecasting using artificial neural networks and social media data (2021)
Conference Proceeding
Boyd, A., Sun, H., Black, M., & Jesson, S. (2021). Short-term load forecasting using artificial neural networks and social media data. . https://doi.org/10.1049/icp.2021.1552

Evolving practices around energy generation, storage and trading within the UK have made it more necessary than ever to provide accurate means of forecasting electricity demand. This paper considers deep neural networks with convolutional and recurre... Read More about Short-term load forecasting using artificial neural networks and social media data.

Appliance Classification using BiLSTM Neural Networks and Feature Extraction (2021)
Conference Proceeding
Correa-Delval, M., Sun, H., Matthews, P., & Jiang, J. (2021). Appliance Classification using BiLSTM Neural Networks and Feature Extraction. . https://doi.org/10.1109/isgteurope52324.2021.9640061

One significant challenge in Non-Intrusive Load Monitoring (NILM) is to identify and classify active appliances used in a building. This research focuses on the classifying process, exploring different approaches for the feature extraction of the app... Read More about Appliance Classification using BiLSTM Neural Networks and Feature Extraction.