INTEGRATED TESTING OF GRID-SCALE LITHIUM-ION BATTERY AND WIND TURBINE SYSTEMS Davion Hill, DNV GL Elizabeth Endler, Shell Ben Schenkman, Sandia National Labs Ben Gully, DNV GL Mark Harral, Group NIRE Dan Borneo, Sandia National Labs Colleen Ferrall, Group NIRE Overview and Project Objectives Controlled tests of grid-connected, utility scale renewable energy assets Lithium Ion energy storage system: 1 MW / 1 MWh, LMO chemistry Wind turbine: 2 MW, GE Alstom Over 12 weeks of testing and observation under representative operations Frequency Regulation Test Profiles and Response Evaluate system response to varying intensities of frequency regulation signals, using PJM signals as classified by Sandia National Labs / PNNL (Pacific Northwest) Constant Power Cycling Evaluation of effect of different power levels on efficiency, as well temperature rise Battery Used for Ramp Rate Control of Wind Turbine Power Output Utilization of the battery system to mitigate fluctuations in wind turbine output to the grid. Primarily reduce output ramp rates. Combined Frequency Regulation and Wind Ramp Rate Control Applications The system is programmed to respond to ramp rate control requirements as before, but is doing so in the process of frequency regulation. Tests conducted at Group NIRE facility at Reese Technology Center Located in Lubbock, Texas; Connected to South Plains Electric Cooperative (SPEC) Using test protocol defined by Sandia / PNNL Repeated 2-hour profile sampled from PJM Reg D (frequency response program specifically rewarding fast actors like storage) Average representing typical operation and aggressive depicting extreme conditions All frequency regulation tests were conducted with both test profiles: PJM Frequency Regulation – Average Profile Smaller cycles, more frequently, lower total throughput Max power ~750 kW 165 cycles per day at 1.6% 2.64 equivalent full cycles per day Average AC efficiency: 72.60 Average DC efficiency: 83.60 PJM Reg D Precision score: 99.74 PJM Frequency Regulation – Aggressive Profile Larger cycles, greater total throughput, higher power = higher efficiency Uses max battery power of 1,000 kW 131 cycles per day at 2.6% 3.40 equivalent cycles per day Average AC efficiency: 79.47 Average DC efficiency: 86.37 PJM Reg D Precision Score: 99.64 Constant Power Cycling for Efficiency Assessment Higher power produced higher efficiency Less auxiliary power draw from shorter operation time Higher electrochemical efficiency AC losses (including inverter and transformer) 6.32% to 7.28% higher Round Trip Efficiencies (RTE) as tested, expressed as percentage: Battery Used for Ramp Rate Control of Wind Turbine Power Output Objective is to minimize fluctuation in output power to grid during any given 1-minute interval Capability is limited to battery’s power of 1 MW Power outputs of each device shown in top graph Bottom graph shows change in power output in each 1-minute interval From wind turbine and from wind turbine including battery assistance Requirements for charge and discharge (occurrence, power level) were very balanced Battery successfully demonstrated ability to reduce power output fluctuation by its maximum power level Demonstrated as being dominantly a power application Single extreme case of max power 5-minute duration caused Delta State of Charge (DSOC) of 25% Majority of support operations are low power Combined Frequency Regulation and Wind Turbine Ramp Rate Control Applications Using same metric of power output fluctuation within each minute Controls prioritizing turbine ramp rate control, when needed, over frequency regulation Single instance of battery not providing full power for ramp control During aggressive frequency response Single instance of frequency response requiring same power as wind and both signals cancelling Highest DSOC experienced was 25% 1,170 kW for just under 5 minutes Maximum temperature of 27°C, temperature gradient of 8°C across pack. Given low rate of occurrence, wind turbine ramp support activities proved to have minimal effect on PJM Reg D Precision Score Conclusions Demonstrated 82.2-91.7% DC-DC RTE Higher powers providing higher efficiency AC RTE 6.3-8.4% lower Significant impact of HVAC and auxiliary loads which can be up to 50 kW Frequency regulation showed 72-86% RTE – again with higher power yielding greater RTE 2.64 (average) and 3.40 (aggressive) equivalent full cycle throughput per day Combined application testing proved to have minimal or zero effect on PJM Reg D precision score compared to frequency regulation testing alone Frequency regulation and wind ramp support proved to equally be ‘power’ applications Primary consideration in sizing should be peak power requirements (not energy) Energy should be considered under pretense of aggressive downsizing Contact Ben Gully, DNV GL: Benjamin.Gully@DNVGL.com Davion Hill, DNV GL: Davion.M.Hill@DNVGL.com Elizabeth Endler, Shell International Exploration & Production: Elizabeth.endler@shell.com 1 MW / 1 MWh Li-Ion (LMO) Battery, Younicos 2 MW GE-Alstom ECO-86 wind turbine   Precision Performance Score Stacked Application Test Number Average Frequency Regulation Aggressive Frequency Regulation 1 99.23 99.26 2 99.94 99.66 Baseline (no wind) 99.74 99.64 Thank you The DOE Office of Electricity and Dr. Imre Gyuk, Program Manager of the Electrical Energy Storage Program GroupNIRE Sandia National Laboratories   Cycle 1 Cycle 2 Cycle 3 Average AC-DC Power (kW) DC RTE AC RTE ΔRTE 250 81.16 73.67 82.08 75.42 83.25 75.55 82.16 74.88 7.28 500 91.03 83.57 88.64 79.38 -- 89.84 81.47 8.37 1000 91.65 85.33 6.32