Researcher

Dr Ke Meng

My Expertise

  • Electric power system modelling and analysis
  • Power system control and operation
  • Renewable energy systems and grid integration
  • Demand Response and distribution level energy market
  • RTDS-based control and power hardware-in-the-loop (HIL) test
  • Generator registration and connection, generator performance standards (GPS), model acceptance test (MAT), and benchmarking
  • Specialize in power system simulation software, PSS/E, PSCAD/EMTDC, RSCAD, etc.

Keywords

Biography

Dr Ke Meng joined the School of Electrical Engineering and Telecommunications as a senior lecturer in energy system in 2018. He received his Ph.D. degree from the University of Queensland, followed by post-doctoral appointments at the Department of Electrical Engineering, the Hong Kong Polytechnic University. In 2012, he transferred to the Centre for Intelligent Electricity Networks at the University of Newcastle as an associate lecturer and...view more

Dr Ke Meng joined the School of Electrical Engineering and Telecommunications as a senior lecturer in energy system in 2018. He received his Ph.D. degree from the University of Queensland, followed by post-doctoral appointments at the Department of Electrical Engineering, the Hong Kong Polytechnic University. In 2012, he transferred to the Centre for Intelligent Electricity Networks at the University of Newcastle as an associate lecturer and was promoted to the research academic in late 2012. In 2015, he joined the University of Sydney as a lecturer in the School of Electrical and Information Engineering. He has also held research positions in China and Hong Kong SAR.

Dr Ke Meng has been involved in renewable energy research since 2008. He has established an independent research profile in wind energy, more specifically on easing large-scale integration of wind energy into the power system. This includes direct experience in power system dispatch, power system computation, stability assessment, and controller design for wind farms.

Ten career-best research outputs

  • K. Meng, W. Zhang, J. Qiu, et al., “Offshore transmission network planning for wind integration considering AC and DC transmission options,” IEEE Transactions on Power Systems, vol. 34, no. 6, pp. 4258-4268, Nov. 2019.
  • K. Meng, Z.Y. Dong, Z. Xu, et al., “Coordinated dispatch of virtual energy storage systems in smart distribution networks for loading management,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 49, no. 4, pp. 776-786, Apr. 2019.
  • K. Meng and P. Li, “Software-defined web-of-nest: A fully distributed framework for managing power distribution networks,” IEEE Smart Cities Newsletter, Jul. 2018.
  • K. Meng, W. Zhang, Y. Li, et al., “Hierarchical security-constrained OPF considering wind energy integration through multi-terminal VSC-HVDC grids,” IEEE Transactions on Power Systems, vol. 32, no. 6, pp. 4211-4221, Nov. 2017.
  • K. Meng, H. Yang, Z.Y. Dong, et al., “Flexible operational planning framework considering multiple wind energy forecasting service providers,” IEEE Transactions on Sustainable Energy, vol. 7, no. 2, pp. 708-717, Apr. 2016.
  • K. Meng, Z.Y. Dong, Z. Xu, et al., “Cooperation-driven distributed model predictive control for energy storage systems,” IEEE Transactions on Smart Grid, vol. 6, no. 6, pp. 2583-2585, Nov. 2015
  • K. Meng, Z.Y. Dong, D.H. Wang, et al., “A self-adaptive RBF neural network classifier for transformer fault analysis,” IEEE Transactions on Power Systems, vol. 25, no. 3, pp. 1350-1360, Aug. 2010.
  • K. Meng, Z.Y. Dong, K.P. Wong, et al., “Speed-up the computing efficiency of power system simulator for engineering-based power system transient stability simulations,” IET Generation, Transmission & Distribution, vol. 4, no. 5, pp. 652-661, May 2010.
  • K. Meng, H.G. Wang, Z.Y. Dong, et al., “Quantum-inspired particle swarm optimization for valve-point economic load dispatch,” IEEE Transactions on Power Systems, vol. 25, no. 1, pp. 215-222, Feb. 2010.
  • K. Meng, Z.Y. Dong, and K.P. Wong, “Self-adaptive radial basis function neural network for short-term electricity price forecasting,” IET Generation, Transmission & Distribution, vol. 3, no. 4, pp. 325-335, Apr. 2009.

My Grants

  • CI, Stability Assessment of Australia’s Future Electrical Grids, ARC Future Fellow, 2020-2024

This project will provide a unique insight into the dynamics of asynchronous power generators in weak power grid condition, to facilitate their comprehension and mathematical description and to develop well-suited simulation techniques that can capture the potential instabilities. The breakthrough derived from this project will provide the least costly system strength remediation scheme, ensuring generators survive more severe, lower probability non-credible contingency events. It will also provide additional guidance for regulators on introducing new generator performance standards, promote energy independence and sustainability, and eventually lead to a low-carbon economy in Australia.

  • Co-CI, ARC Research Hub for Integrated Energy Storage Solutions; ARC Industrial Transformation Research Hubs, 2019-2022.

The ARC Research Hub for Integrated Energy Storage Solutions aims to develop advanced energy storage technologies, including printed batteries, structural supercapacitors, innovative fuel cells and power-to-gas systems. It plans to integrate these storage solutions with existing energy networks and applications using novel storage monitoring, control and optimisation technologies. The Hub is expected to generate new knowledge in storage technology manufacturing, control and management. Expected outcomes include cheaper and more effective storage devices and better storage integration solutions, supporting renewables, reducing carbon emissions, and improving efficiency in the energy sector. Resulting benefits include a more sustainable, secure, reliable and economically efficient energy supply. This Hub will contribute to improving the economic efficiency of Australia’s energy sector.

  • Co-CI, Wide-area Interconnected Clean Energy Highway; ARC Discovery Grant, 2017-2019.

This project aims to facilitate the deployment of the clean energy highway, an integrated electricity and gas network. Renewable energy sources, advanced transmission facilities and power-to-gas technologies are changing energy systems. All these changes, while potentially making energy systems more responsive, efficient and resilient, also make implementation difficult. This project aims to make implementation easier to ensure more sustainable solutions for energy generation, delivery and use in this new energy era. The expected outcome is a sound and robust suite of models and associated methodologies to study, analyse and design the clean energy highway.

  • 2012   Grid connection studies for 4xx MVA synchronous generator in VIC.
  • 2013   Generator and exciter parameters identification of a 4x MW gas turbine in NSW.
  • 2014   Exciter modelling of a 7xx MVA synchronous generator in NSW.
  • 2018   Grid connection studies for a 7.x MW solar farm in VIC.
  • 2018   Grid connection studies for an 8x MW solar farm in QLD.
  • 2018   Grid connection studies for a 4xx MW solar farm in QLD.
  • 2018   Due diligence for a 1xx MW solar farm in QLD.
  • 2019   Grid connection studies for a 1xx MW solar farm in VIC.
  • 2019   Grid connection studies for a 6x MW solar farm in NSW.
  • 2019   Grid connection studies for a 5xx MW wind farm in VIC.
  • 2019   Hardware-in-the-loop testing for a 5xx MW wind farm in VIC.
  • 2019   Economic feasibility analysis for a 1xx MWh battery storage system in NSW.
  • 2020   Registration for a 7.x MW solar farm in VIC.
  • 2020   Grid connection studies for a 2x MWh battery storage system in NSW.

My Awards

  • 2017   Best Reviewer, IEEE Transactions on Smart Grid
  • 2017   Outstanding Reviewer, IEEE Transactions on Sustainable Energy
  • 2017   Dedicated Board Members, International Transactions on Electrical Energy Systems
  • 2017   Most Cited Paper Award, Journal of Modern Power Systems and Clean Energy
  • 2016   Outstanding Reviewer, Journal of Modern Power Systems and Clean Energy
  • 2016   Award of Excellence in Research Cluster Projects Development and Management
  • 2010   Chinese Government Scholarship for Outstanding Oversea Students
  • 2008   Richard Jago Memorial Prize

My Research Activities

With increasing levels of weather-dependent energy resources added to the features of Australia’s grid, i.e. long distances over an island grid, the fossil fuel-dominated Australian power system faces a number of unique challenges. Large-scale wind generation is being connected in areas with good resources, which tends to be the weaker parts of the grid, primarily designed to supply local loads. Whilst geographical and technological diversity smooths the impact of intermittency, due to the current inter-regional transmission constraints and the low power system inertia conditions, the Australian power grid is becoming more susceptible to prevalent disturbances than ever before. Secure and reliable operation of the power grid becomes now one of the basic needs for national security. To achieve a smooth grid connection, wind farm developers need to assess and comply with a range of regulatory requirements specified in the “Grid Code”. Therefore, it is important to understand the ISO’s requirements on connecting new wind power plants, grid’s ability to accommodate new wind generation, as well as its potential impacts on system stability.

  • Solving technical issues originated from interpretation of national and international standards and grid codes.
  • Providing market-leading insight, advice and technical solutions for client project.
  • Providing ongoing key-expert support during pre-contract negotiations.
  • Managing customer requests for models in PSS/E, PSCAD, DigSilent etc.
  • Managing grid stability/impact studies and load flow calculation.
  • Supporting customer’s grid consultants during GPS connection studies.
  • Managing static, dynamic and harmonic assessments of proposed project connections.
  • Liaising with manufacturer model support team and coordinate model validation.
  • Preparing grid technology related documentation for clients.
  • Contributing in stakeholder meetings to provide grid engineering expertise.
  • Liaising with consultants and client to prepare a complete connection application.

Grid connection studies

The Renewable Energy Integration Team (REIT) in UNSW provides a wide range of services to assess system-wide impact of increased penetration level of wind energy, allowing TNSPs and DNSPs to integrate renewables without harming network reliability. The REIT has expertise on technical and financial feasibility analysis, including wind resource assessment, wind data generation, wind turbine selection, micrositing optimization, electrical layout optimization and wind farm energy estimates for the business case. The team has years’ experience in modelling of various wind generators (DFIG, PMSG, etc) necessary for the grid connection studies. Equipped with a range of state-of-the-art simulation software, full grid integration studies and system studies are performed, in compliance with the relevant national grid codes and standards. The service covers all aspects of grid reliability when integrating renewables from pre-test simulations, GPS compliance assessment, to R2 model validation. Specifically,

  • Complete set of PSSE / PSCAD software simulation models
  • Generator Performance Standards (GPS)
  • Connection studies report(s)
  • Releasable User Guide (RUG)
  • Power System Design and Setting Data Sheet
  • PSSE Model Acceptance Test (MAT) Report
  • PSSE / PSCAD Generating System model benchmarking report

The REIT works with and maintain relationships with consulting firms, and AEMO, NSPs, EPC contractor, and 3rd party advisors to successfully deliver project and get an Offer to Connect.

Filed testing facilities

Except for electrical feasibility studies, grid codes and compliance assessments, a smooth process and risk mitigation is ensured through on-site measurements and testing. In order to ensure the stable and reliable operation of the grid-connected wind farms, fault ride through capabilities are required in the national grid code. Low voltage ride through capability (LVRT) – ability of the wind turbines to withstand credible fault conditions, and support to network voltage recovery by injecting reactive current; high voltage ride through capability (HVRT) – wind turbines should have the ability to operate at high voltage condition and stay connected for a certain period.

UNSW has developed a LVRT/HVRT testing facility. The testing equipment consists of a series-connected impedance Z1 capable of limiting the short-circuit current, a parallel-connected impedance Z2 capable of reducing the voltage level of the turbine side, and a capacitor C for raising the voltage. The impedances Z1 and Z2 consist of several coils each. By changing the ratio Z1 to Z2 the depth of the voltage dip can be configured. Depending on the respective grid code, different depths of voltage dips and rises can be simulated, ranging from 0% to 140% with a step of 1% of the rated voltage. The duration of the dip depends on the depth and ranges from 1000 milliseconds to 3000 milliseconds. Different grid faults can be simulated, including line to line (L-L), double line to ground (LL-G), and line to line to line (L-L-L). It can test generating plants up to 8 MVA in grids and up to 40 kV system.


My Engagement


My Teaching

  • ENGG1000 - Introduction to Engineering Design and Innovation
  • ELEC1111 - Electrical and Telecommunication Engineering
  • ELEC3111 - Distributed Energy Generation
  • ELEC4100 - Electrical Systems
  • ELEC5203 - Topics in Power Engineering
  • ELEC5208 - Intelligent Electricity Networks
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Location

Room 306, Electrical Engineering Building (G17)

Map reference (Google map)

Contact

+61-2-9385-6649

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