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EARLY FINDINGS OF AN ENERGY STORAGE PRACTICAL DEMONSTRATION

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. Background.

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EARLY FINDINGS OF AN ENERGY STORAGE PRACTICAL DEMONSTRATION

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  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. Background • 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

  3. 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. Candidate Network

  5. Preparation • Assess the distribution network • Obtain planning permission • Lease the land • Design review • Appoint CDM co-ordinator • Arrange contractors

  6. Delivery, Installation and Commissioning

  7. The Energy Storage Device

  8. 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. Realising Benefits on the Network

  10. Network Instrumentation • Measurement of: • real power • reactive power • voltage • Industrial PC: • data processing • communications

  11. 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. Control Algorithm • Steady-state • Rule based • respond to triggers on network • manage battery state-of-charge • Example:

  13. 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. Assessing the Benefits • Reduction in primary reverse-power-flow

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