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This report constitutes part of the work package deliverable 3.1 of the EUDP IEA Task 41 project, funded by Energy Technology Development and Demonstration Program (EUDP) of the Danish Energy Agency. The report presents a brief snapshot of the current research on wind power plant support from weather dependent active distribution networks, research carried out at DTU Wind and Energy systems department. It draws upon the research work carried out by the PhD student Aeishwarya Baviskar, under the supervision of Anca D. Hansen and Kaushik Das.

The control of large-scale offshore wind power plants (OWPPs) has historically been handled byseparating the control into different hierarchical levels in a wind power plant (WPP). A WPP control is traditionally implemented in a centralized processing unit, which receives and sends information from all the turbines and system operators. This is commonly known as a centralized control scheme, implemented in conventional networks. But for large-scale OWPP clusters with hundreds of wind turbines (WTs), the centralized control scheme may be impractical owing to the huge computation burden in order to process the large volume of information. Even the conventional control schemes such as droop-based or PI with/without optimization might fail to achieve optimal performance for large-scale OWPPs. This talk describes the need to breakdown the control problem into manageable sub-problems, possibly weakly related, such that the overall plant is no longer controlled by a single controller, but by several independent controllers. Thus, instead of having a fast powerful computer centralizing the control of the entire WPP cluster, the control responsibility can be shared among the wind turbines. This gives rise to two additional control architectures besides centralized control scheme: distributed and decentralized control. Modern WPPs can be visualised as smart grids with several intelligent agents (WTs) exchanginginformation with their neighbours to achieve a desired power profile and agree on a global outcome. Sucha control scheme, commonly known as distributed control, consists of a number of local controllers, each ofwhich controls a subset of the system, with a capability of communication between them. However, itpresents challenges such as the appropriate design of a distributed algorithm, reliability of communicationnetwork and coordination among agents with limited information exchange. The local controllers mightalso be designed to operate in an independent manner as in a decentralized control architecture.However, the local decentralized control centres could share the information to solve the larger problem.Strong interactions between the inputs and outputs of different controllers can even prevent one fromachieving stability.

This report is the first deliverable in WP1 in the project “Ancillary services from renewable power plants” (RePlan). RePlan is funded as PSO project 2015 no. 12347 by the Danish PSO-programme ForskEL, which is administered by Energinet.DK. RePlan is carried out in collaboration between DTU Wind Energy, DTU Elektro, Aalborg University Energy Technology, Aalborg University Wireless Communication Networks and Vestas Wind System A/S. DTU Wind Energy is manager of the project.

Modern ReGen plants can provide the distribution and transmission network with useful ancillary services, such as voltage and frequency control. The RePlan project has defined ReGen plant level control algorithms, modelled and simulated their technical performance, and tested them in a Real-Time Hardware-in-the-Loop (HIL) environment based on multi-domain physical systems or in a real small scale power system, namely the SYSLAB facility existing at the DTU Risø Campus. RePlan has developed and evaluated controllers for the delivery of ancillary services, incorporating communication properties in the control loops of the ReGen plant model and using state-of-the-art methods for simulation of renewable generation patterns and wind power forecast methods. Guidelines and recommendations for practical implementation of the developed control algorithms for targeted ancillary services have been defined. The technical ability is clear. The scientific contribution and industrial relevance is satisfactory. The continuation is straightforward, if commercial prospects prove their incentive.