1. EARLY FINDINGS OF AN ENERGY STORAGE PRACTICAL DEMONSTRATION Peter LANG - UK Power Networks Neal WADE and Philip TAYLOR – Durham University Peter JONES ABB UK and Tomas LARSSON ABB Sweden Authors Peter LANG and Neal WADE LANG – UK – S4 – 0413

2. Frankfurt (Germany), 6-9 June 2011  Many documents have been written about the theoretical benefits of energy storage  In 2005 AuraNMS set out to research network optimisation taking into account DG and Electrical energy storage  The energy storage device was to be designed, supplied and installed by ABB  UKPN had to find a site where the anticipated benefits could be demonstrated Background

3. Frankfurt (Germany), 6-9 June 2011 Network and Location Requirements  Connected to an 11kV distribution network  Wind generation nearby  Demand profiles that change  Away from the primary substation  Be able to assess the benefits e.g. voltage support, losses reduction, increase quality of supply and many more that are of value to other network users

4. Frankfurt (Germany), 6-9 June 2011 Candidate Network

5. Frankfurt (Germany), 6-9 June 2011 Preparation  Assess the distribution network  Obtain planning permission  Lease the land  Design review  Appoint CDM co-ordinator  Arrange contractors

6. Frankfurt (Germany), 6-9 June 2011 Delivery, Installation and Commissioning

7. Frankfurt (Germany), 6-9 June 2011 The Energy Storage Device

8. Frankfurt (Germany), 6-9 June 2011 Characteristics of DynaPeaQ  Li-ion Batteries from SAFT  200 kW for 1 hour  600 kvar inductive 725 kvar capacitive  Controlled by ABB’s MACH2 control system  Operating as intended  The next phase…

9. Frankfurt (Germany), 6-9 June 2011 Realising Benefits on the Network

10. Frankfurt (Germany), 6-9 June 2011 Network Instrumentation  Measurement of: real power reactive power voltage  Industrial PC: data processing communications

11. Frankfurt (Germany), 6-9 June 2011 Test Programme  Initial Gradual ramping of power exchanges Pre-determined ESS set-points Operation at ‘quiet’ times  Operational Power exchanges dictated by prevailing network conditions Voltage control Power flow management

12. Frankfurt (Germany), 6-9 June 2011 Control Algorithm  Steady-state  Rule based respond to triggers on network manage battery state-of-charge  Example:

13. Frankfurt (Germany), 6-9 June 2011 Network interventions  Voltage control: in response to local or remote measurements.  Power flow management: supply reactive power (wind-farm Q demand), supply real power (thermal constraint), peak shaving, absorb real power (wind-farm generation), absorb real power (reverse power flow), and loss minimisation.

14. Frankfurt (Germany), 6-9 June 2011 Assessing the Benefits  Reduction in primary reverse-power-flow