1. GREDOR - GREDOR - Gestion des Réseaux Electriques de Distribution Ouverts aux Renouvelables Real-time control: the last safety net Journée de présentation GREDOR Thierry Van Cutsem, ULg Moulin de Beez, 29/04/2015

2. Test system with: 75 MV buses 22 DG units (doubly fed induction & small synchronous generators)  Distribution networks are expected to host larger amounts of dispersed renewable generation  voltage and congestion (thermal overload) problems are expected to occur more often  but, hopefully, over limited periods of time Context (1/3) 2

3.  Reinforcing the network (“fit-and-forget”) to deal with such temporary problems would be too expensive  there is a good opportunity to use Distributed Generation (DG) units as “control means” to remove the security limit violations  this is a service for which DG unit operators/owners could be financially compensated  see Task 1 of GREDOR  Loads with new consumption profiles  e.g. electric vehicles, heat pumps, etc.  Flexible loads are expected to also provide control means  through remote control, complementing smart meters  this presentation, however, focuses on DG units only. Context (2/3) 3

4.  Automatic control schemes are needed to assist the Distribution System Operator in:  correcting voltage and/or congestion emergencies  keeping the MV grids within desired operating limits  coordinating their actions with transmission system operator Context (3/3) 4

5.  Centralized control with system-wide monitoring and model preferred  requires a communication infrastructure…  …but offers more advanced control capabilities  …and communication cost will be much lower than network reinforcement  exploit less expensive controls first  e.g. reactive power modulation preferred to active power curtailment  act in a non discriminatory and transparent manner  optimize a system-wide objective with efforts shared by all relevant DG units  drive the system from the current (unacceptable) to the desired (secure) operating point  do not rely on models which may not be available / accurate  especially for loads (sensitivity to voltage not well known !)  rely on a simplified model (e.g. infrequently updated)  be robust with respect to inaccuracies of this simplified model Desired features of automatic corrective control 5

6. controller Centralized controller: inputs and outputs set-points (updated every ~ 10 s) P, Q (volt. set-point of load tap changer) measurements (refreshed every ~ 10 s) P, Q, V V 6

7. Model Predictive Control computed set-point (sent to DG unit) discrete time predicted output measurement discrete time 7

8. Mode 1 DSO Controller State estimation Network data Real-time measurements MPPT set points static data Non Dispatchable DG units Local controller measurements MPPT : MaximumPower Point Tracking DSO : Distribution System Operator 8

9. DSO Controller State estimation Network data Decision by non-DSO actor Corrective reports Dispatchable DG units Mode 2 Real-time measurements set points static data measurements DSO : Distribution System Operator 9

10.  22 DG units controlled  controls adjusted every 10 s  N c = 3  N p = 3 (larger if LTC actions anticipated) Test system 10

11. Mode 1. Wind increase (t = 20 → 70 s, all 22 wind generators) Congestion corrected by controller 11 Example 1

12. Mode 3.a Decision by non-DSO actor DG units DSO Controller State estimation Network data Corrective reports Real-time measurements set points static data measurements near-future schedule information 12

13. Mode 3.b DG units Controller State estimation Network data Operational planning Corrective reports DSO near-future schedule Real-time measurements set points static data measurements information 13

14. Mode 1 : 9 generators - wind increase (t= 20 → 70 s) Mode 3 : 13 generators - power schedule (t= 150 → 180 s) Overvoltages corrected by controller Example 2 generation schedule 14

15. 15 DG unitsControl strategy Capability of anticipating limit violation ? Mode 1 non- dispatchable Normal operating conditions: take no corrective action Emergency conditions: deviate as few as possible from the last normal operating conditions No. Correction is applied after violation is observed Mode 2 dispatched by non-DSO actor Modes 3a & 3b both dispatchable and non- dispatchable Normal operating conditions: control system to follow the schedule Emergency conditions: deviate as few as possible from the schedule Yes. Controls are applied to avoid exceeding the limits Overview of various modes

16.  Centralized controller collecting measurements and adjusting set-points of DG units to satisfy operating constraints:  currents below limits  voltages inside bounds  power factor at connection point with transmission system  relies on concept of Model Predictive Control  moving the operating point progressively from current to desired state  compensating for modelling inaccuracies (as a closed-loop control)  anticipating the effect of known changes (Modes 3.a & 3.b)  uses a simple, infrequently updated sensitivity model  takes into account the load tap changer operation  as a separate controller  or by controlling its voltage set-point  constrained optimization problem compatible with real-time operation Summary 16

17.  Extensions of formulation  treat discrete controls as such in optimization  reset DG units at maximum / scheduled power after emergency situation has been corrected and operating conditions improve  treat flexible loads and storage devices as additional control variables  mitigate high voltage problems in LV grid due to photo-voltaic installations  etc.  Implementation aspects and further tests  Assess practical telecommunication needs  Provide more meaningful results with the networks of GREDOR DSO partners  Further integration with Task 3 (operational planning) and Task 1 (interactions)  etc. Ongoing work in GREDOR 17