Simplified flexibility parameters for evaluating renewable - PowerPoint PPT Presentation

Simplified flexibility parameters for evaluating renewable integration JRC Workshop on Addressing Flexibility in Energy Models Paul Denholm December 5, 2014 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Approaches to Capacity Expansion Planning • Traditional load-duration curve approaches o Screening curves identify least cost mixes based on levelized cost of energy o Doesn’t incorporate any chronological (time -series) analysis • Linear and Mixed-Integer optimization o Finds lowest cost mix based on a life-cycle cost o Can incorporate chronology in the objective function o But full year hourly (or sub-hourly) simulations are computationally complex 2

Approaches to Incorporating Time Series in Capacity Expansion Models • Reduced set of time-periods o Full time-series for a few weeks that (hopefully) represent the entire year o Variable generation makes picking “typical” periods challenging • Time-slice (non chronological) approach o Estimates typical dispatch characteristics in a set of representative time periods o Requires establishing parametric relationships for key parameters such as curtailment o NREL approach in the ReEDS models 3

NREL’s Grid Modeling Tools 4

ReEDS Model (Regional Energy Deployment System Model) A spatially and temporally resolved model of capacity expansion in the U.S. electric sector. Designed to explore potential electric-sector growth scenarios in the U.S. out to 2050 under different economic, technology, and policy assumptions. 5

ReEDS Model: History and Team ReEDS has been in use for >10 years, with a steady increase in sophistication and capabilities over that time. Current team is ~10 staff (not all full-time on ReEDS). Selected studies: • 2008 20% Wind Vision • 2012 Renewable Electricity Futures • 2012 SunShot • Various RPS, CES, PTC, … analyses 6

What does ReEDS do? • Each 2-year solve produces a set of new investments and described operation of new and existing fleet. • Between solves, ReEDS updates: o Existing generator fleet, including retirements o Existing transmission o Performance of existing fleet o Costs/performance of new technologies o Electricity demand, reserve margin requirements o Variable renewable capacity values, curtailment, operating reserve requirements • Skip forward two years, and solve again. 7

Reduced-form Dispatch Seventeen time-slices: four seasons x four diurnal + one superpeak. Continuous units: minimum turndown, but no startup or shutdown, flat heatrate. Constraints guarantee adequacy requirements and ancillary services. 8

Modeling Framework ABB inc. GridView (hourly production cost) rooftop PV penetration does it balance 2050 mix hourly? of generators Black & Veatch Technology cost & performance Technology Teams Resource availability Demand projection Flexible Resources Demand-side technologies End-Use Electricity Grid operations System Operations Transmission costs Transmission Implications GHG Emissions Water Use Capacity & Generation Land Use 2010-2050 Direct Costs 9

Integration with Operational Model • To supplement ReEDS’ reduced -form unit-commitment model, for the REF analysis we rebuilt ReEDS infrastructure in GridView, a commercial production cost model to test how the ReEDS-projected infrastructure might behave in an hourly dispatch. • We are now automating the capability, using PLEXOS this time instead of GridView. 10

UC on NREL’s HPC NREL PIX 24580 Peregrine Characteristics: • 11520 Intel Xeon E5-2670 "SandyBridge" cores • 14400 next-generation Intel Xeon "Ivy Bridge" core • 576 Intel Phi Intel Many Integrated Core (MIC) core co-processors with 60+ cores each • 32 GB DDR3 1600Mhz memory per node • Peregrine will deliver a peak performance of 1 petaFLOPS 11

Can we include more chronology in the objective function? • Fundamental tradeoff between chronology and simplicity. o But can we incorporate full chronological simulations but avoid many of the key complications? • Unit commitment • Full storage optimization • Can reduced form chronological simulations still provide valuable insights? • And is 1-hour simulation good enough? 12

Renewable Energy Flexibility (REFlex) Model • Dispatch only model • Block dispatch by generator type • Simplify key parameters traditionally captured in unit commitment o Minimum generation point for thermal generation o Minimum thermal generation for ramp • Simplified valley-filling algorithm for storage and DR dispatch 13

What can this approach do? • Analyze optimal mixes of VG in high penetration scenario • Examine curtailment • Analyze impact of storage and DR • Run very fast • What it can’t (probably) do: o Optimize new conventional generation mix in low VG scenarios o Basically assumes thermal fleet is relatively static or decaling 14

Example – Curtailment Analysis • At high penetration, economic limits will be due to curtailment o Limited coincidence of VG supply and normal demand o Minimum load constraints on thermal generators o Thermal generators kept online for operating reserves 15

Minimum Generation Levels Limited by Baseload Capacity 250 Wholesale Price ($/MWh) 200 Price/Load 150 Relationship in PJM 100 50 0 0 10000 20000 30000 40000 50000 60000 Load (MW) 35 30 Wholesale Price ($/MWh) Below Cost Bids 25 20 15 10 5 0 18000 20000 22000 24000 26000 Load (MW) 16 16

Min den depends on VG Mix 17 17 17

Example – Curtailment as a Function of Penetration 50% Solar / Wind Mix 45% 0/100 40% 20/80 30/70 Fraction of VG Curtailed 35% 40/60 30% 60/40 80/20 25% 20% 15% 10% 5% 0% 20% 30% 40% 50% 60% 70% 80% Fraction of System Electricity from Solar and Wind Reflex < 1 Minutes per run 18

Results from Full UC/ED Model PLEXOS Simulations (DAUC/SCED) ~5 Hours per run 19

Example – Storage Dispatch • Full storage optimization is computationally complex • Valley filling (search) algorithms can be much faster 20

REFlex CSP Dispatch 70 60 Curtailed Solar 50 Dispatched CSP Generation (GW) Usable PV 40 Wind Conventionals 30 Load Non-Dispatched CSP 20 Dispatched CSP 10 0 1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 Hour Dispatch of CSP May 10-13 21 National Renewable Energy Laboratory Innovation for Our Energy Future

PLEXOS CSP Dispatch 140,000 45,000 40,000 120,000 35,000 CSP Inflow/Generation (MW) 100,000 30,000 Net Load (MW) 80,000 25,000 20,000 60,000 15,000 40,000 10,000 20,000 5,000 0 0 0 24 48 72 96 120 144 168 Hour Net Load with Wind and PV CSP Inflow CSP Generation Dispatch of CSP in WWSIS-2 Study (July) 22 National Renewable Energy Laboratory Innovation for Our Energy Future

Example – Energy Storage 40% No Storage 4 hours 35% 8 hours 30% 12 hours Fraction of VG Curtailed 24 hours 25% 20% 15% 10% 5% 0% 20% 30% 40% 50% 60% 70% 80% Fraction of System Electricity from Wind&Solar 23

Example – Electric Vehicle Charging 1.6 Average Charging Demand Per Vehicle (kW) SUV-40 Vehicle 1.4 SUV-20 1.2 Sedan-40 Availability Sedan-20 1.0 0.8 0.6 0.4 0.2 0.0 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 Time (In 5-Minute Intervals) Net Load with PV Normal Load Solar PV Output 45000 40000 35000 30000 Load (MW) 25000 20000 High PV 15000 Impacts 10000 5000 0 0 24 48 72 96 Hour 24

Example – Electric Vehicle Charging Net Load with PHEVs & PV Normal Load Net Load with PV PHEV Charging Profile Overnight 45000 40000 optimized, 35000 uncontrolled 30000 Load (MW) 25000 daytime charging 20000 15000 10000 5000 0 0 24 48 72 Net Load with PHEVs & PV 96 Normal Load Hour Net Load with PV PHEV Charging Profile 45000 40000 35000 Optimized 30000 Load (MW) overnight, 25000 20000 imperfect 15000 10000 foresight 5000 daytime 0 0 24 48 72 96 Hour 25

What else can we ignore? • Subhourly Dispatch? • Incorporation of cycling costs into UC/ED process? 26

Example: Western Wind and Solar Integration Study Phase 2: Cycling Cost and Emissions Impacts From a system perspective, cycling costs are relatively small Emissions impacts of cycling are relatively small • Phase 3: Frequency Response and Grid Impact  What happens to the transmission grid’s frequency with high penetration of distributed PV at low load?  What happens to the grid when remote transmission lines are highly- loaded to move wind long distances? 27

5- minute dispatch This 5-minute ramp 130000 may exceed 1-Hour 129000 committed capability 5-Minute 128000 127000 126000 125000 124000 UC based on this 1- 123000 hour ramp rate 122000 121000 120000 0:00 0:20 0:40 1:00 1:20 1:40 2:00 28