Periodic Reporting for period 2 - WinGrid (Wind farm - grid interactions: exploration and development)
Okres sprawozdawczy: 2021-10-01 do 2024-03-31
WinGrid aims to train the next generation of researchers on future power system integration issues associated with large-scale deployment of wind generation, focusing on the modelling and control aspects of wind turbine design, and the system stability issues and supervisory structures required for robust implementation. The volume of wind installations is growing rapidly, giving rise to various concerns about future power system stability. More sophisticated modelling capability is required to fully assess the growing complexity as we advance towards a 100% RES resilient power system, while new wind generation technologies are emerging which may radically impact how the future system evolves, against a background of more stringent grid code requirements and emerging system service markets. Highly-skilled researchers, capable of solving such problems, are scarce and in high demand by industry. WinGrid comprises 10 academics from 8 beneficiary organisations. It also has 11 internationally renowned companies ranging from the whole supply chain. Combined together we provide wide-ranging expertise in power electronics converters, control theory, system stability analysis, power system operation and electricity markets. The ESRs enjoy a highly integrated, multi-disciplinary training environment, including access to specialist software and hardware-in-the-loop test environments, enriched through secondments with the network of industrial partners. WinGrid enable critical learning across all training aspects, in order to ensure that comprehensive, robust and implementable solutions are obtained and validated to face the grid integration challenges of the future.
Research objectives:
Objective A: To develop advanced model reduction and robust control strategies to evaluate the dynamic interactions between individual wind turbines, between wind farm strings, and between wind farms and the grid.
Objective B: To develop technical solutions which maximise the potential for wind turbines to provide frequency control support services, when such systems are implemented at scale with high wind shares, and to assess the opportunities for deploying local energy storage for optimisation of ancillary service revenue streams and a reduction in the maintenance cost cycle. Also balancing services from wind-hybrid solutions including solar PV and energy storage will be developed.
Objective C: To develop advanced modelling and control techniques for the emerging technologies of synchronverter based and hydrostatic transmission based wind turbines.
Social impact:
Contribution to structuring doctoral/early-stage research training at the European level and to strengthening European innovation capacity: The WinGrid consortium aims to provide an excellent training to our ESRs in an area at the interface of control engineering, power electronics, power systems and wind energy. WinGrid will structure the European research in the field, and enhance the innovation capability in Europe.
Strengthening EU research innovation capacity: The training provides highly technical academic skills to the ESRs, in addition to interpersonal skills, which will feed through to develop the next generation of intellectual and technical leaders in European academia and industry and will therefore enhance the EU’s leadership status in this area.
Industrial impact: The proposed research is dealing with a few challenging topics in wind farm – grid interactions, as evidenced by the enthusiastic participation in the WinGrid network by industries. These industries are vital to the EU’s economy and energy security. For example, the European Wind Energy Association predicts that by 2050, 50% of the EU’s electricity demand will be met by wind. Thus, the proposed research into the wind farm-grid interactions addresses a growth area of the EU economy and will therefore contribute to its economic, environmental and societal wellbeing
Research objectives:
Objective A: To develop advanced model reduction and robust control strategies to evaluate the dynamic interactions between individual wind turbines, between wind farm strings, and between wind farms and the grid.
Objective B: To develop technical solutions which maximise the potential for wind turbines to provide frequency control support services, when such systems are implemented at scale with high wind shares, and to assess the opportunities for deploying local energy storage for optimisation of ancillary service revenue streams and a reduction in the maintenance cost cycle. Also balancing services from wind-hybrid solutions including solar PV and energy storage will be developed.
Objective C: To develop advanced modelling and control techniques for the emerging technologies of synchronverter based and hydrostatic transmission based wind turbines.
Social impact:
Contribution to structuring doctoral/early-stage research training at the European level and to strengthening European innovation capacity: The WinGrid consortium aims to provide an excellent training to our ESRs in an area at the interface of control engineering, power electronics, power systems and wind energy. WinGrid will structure the European research in the field, and enhance the innovation capability in Europe.
Strengthening EU research innovation capacity: The training provides highly technical academic skills to the ESRs, in addition to interpersonal skills, which will feed through to develop the next generation of intellectual and technical leaders in European academia and industry and will therefore enhance the EU’s leadership status in this area.
Industrial impact: The proposed research is dealing with a few challenging topics in wind farm – grid interactions, as evidenced by the enthusiastic participation in the WinGrid network by industries. These industries are vital to the EU’s economy and energy security. For example, the European Wind Energy Association predicts that by 2050, 50% of the EU’s electricity demand will be met by wind. Thus, the proposed research into the wind farm-grid interactions addresses a growth area of the EU economy and will therefore contribute to its economic, environmental and societal wellbeing
WinGrid has five work packages:
WP1 mainly contributes to the Objective A
• The small-signal stability modelling of the grid-connected converter has been completed, which is based on state-space modelling.
• The detailed small-signal model of the grid-forming converter connected to the grid has been developed, based on state-space modelling with experiment and simulation validation.
• The application of passivity based control on grid following and grid forming converter topologies has been completed.
WP2 mainly contributes to objectives A and B.
• A comprehensive multi-voltage level distribution grid model titled, ‘DTU-7k Bus Active Distribution Grid model’ has been developed.
• An aggregated offshore wind farm connected to the IEEE- 39bus AC grid through a point-to-point VSC-HVDC system has been modelled and simulated.
• A simulation benchmark of the OWPP connected with MMC has been completed. The design of wind turbine VSC with grid-following control, and MMC with grid-forming control has been completed.
WP3 contributes to the objective B.
• A modelling framework has been proposed to analyze the possible changes in the frequency stability problem of the evolving distributed power grid which can be characterized by the presence of fewer synchronous generators, more distributed inverter-based power system elements.
• A detailed model of grid-connected wind farm has been developed to evaluate the impact of frequency control on the mechanical structure of WTs.
WP4 mainly contributes to objective C.
• A multi-agent reinforcement learning method has been proposed to optimize the control policy of wind farms.
• Simulation results show that the control policy not only achieves high performance in wind farm power generation but also is stable in fluctuating environments.
WP5 mainly contributes to objective C.
• Theoretical stability analysis of the electric grid based on simplified and high order models has been conducted.
• Analysing the factors that affect the generation of sub-synchronous oscillation due to interaction between converter and the weak grid has been conducted.
• Experimental validation of different damping mechanisms in a microgrid has been conducted.
WP1 mainly contributes to the Objective A
• The small-signal stability modelling of the grid-connected converter has been completed, which is based on state-space modelling.
• The detailed small-signal model of the grid-forming converter connected to the grid has been developed, based on state-space modelling with experiment and simulation validation.
• The application of passivity based control on grid following and grid forming converter topologies has been completed.
WP2 mainly contributes to objectives A and B.
• A comprehensive multi-voltage level distribution grid model titled, ‘DTU-7k Bus Active Distribution Grid model’ has been developed.
• An aggregated offshore wind farm connected to the IEEE- 39bus AC grid through a point-to-point VSC-HVDC system has been modelled and simulated.
• A simulation benchmark of the OWPP connected with MMC has been completed. The design of wind turbine VSC with grid-following control, and MMC with grid-forming control has been completed.
WP3 contributes to the objective B.
• A modelling framework has been proposed to analyze the possible changes in the frequency stability problem of the evolving distributed power grid which can be characterized by the presence of fewer synchronous generators, more distributed inverter-based power system elements.
• A detailed model of grid-connected wind farm has been developed to evaluate the impact of frequency control on the mechanical structure of WTs.
WP4 mainly contributes to objective C.
• A multi-agent reinforcement learning method has been proposed to optimize the control policy of wind farms.
• Simulation results show that the control policy not only achieves high performance in wind farm power generation but also is stable in fluctuating environments.
WP5 mainly contributes to objective C.
• Theoretical stability analysis of the electric grid based on simplified and high order models has been conducted.
• Analysing the factors that affect the generation of sub-synchronous oscillation due to interaction between converter and the weak grid has been conducted.
• Experimental validation of different damping mechanisms in a microgrid has been conducted.
1. 25 journal papers, 40 conference papers, 13 conference abstracts and one dataset have been published. In addition, there are 27 journal papers under revision(5)/review(9)/preparations(13) and 3 conference papers under review.
2. WinGrid held three special sessions in international conferences and one International Workshop on Wind Farm-Grid Interactions: Exploration and Development, see Sec. 1.2.7.1 of the final report.
3. 40 video lectures from WinGrid training and disseminations were produced and published on the project website and Twitter, linked via the WinGrid YouTube channel. So far, there are 219 subscribers of the WinGrid YouTube channel. The lectures have been viewed 9281 times, a high number of views considering the technical complexity of the topics and specific groups of audiences. So far, the website has received around 29924views. 61% of the website audiences are aged 18-34, in which they are the main targeted audiences of the WinGrid project to transfer the knowledge to the young and early career researchers.
4. See Sec. 1.2.8.4 and 1.2.8.5 of the final report for ESR disseminations and exploitations.
2. WinGrid held three special sessions in international conferences and one International Workshop on Wind Farm-Grid Interactions: Exploration and Development, see Sec. 1.2.7.1 of the final report.
3. 40 video lectures from WinGrid training and disseminations were produced and published on the project website and Twitter, linked via the WinGrid YouTube channel. So far, there are 219 subscribers of the WinGrid YouTube channel. The lectures have been viewed 9281 times, a high number of views considering the technical complexity of the topics and specific groups of audiences. So far, the website has received around 29924views. 61% of the website audiences are aged 18-34, in which they are the main targeted audiences of the WinGrid project to transfer the knowledge to the young and early career researchers.
4. See Sec. 1.2.8.4 and 1.2.8.5 of the final report for ESR disseminations and exploitations.