Parametric Analysis Of Particle CSP System Performance And .

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Parametric Analysis of Particle CSPSystem Performance and Cost toIntrinsic Particle Properties andOperating ConditionsASME Energy and Sustainability July 16, 2019S e s s i o n 3 - 1 1 : I n t e g r a t e d C S P S y s t e m s Tw o ( E S 2 0 1 9 - 3 8 9 3 )Ke v i n J. A l b recht , M a tth e w L . B a u e r, Cl i fford K. H oSAND2019 - 8280CSandia National Laboratories is a multimissionlaboratory managed and operated by NationalTechnology & Engineering Solutions of Sandia,LLC, a wholly owned subsidiary of HoneywellInternational Inc., for the U.S. Department ofEnergy’s National Nuclear SecurityAdministration under contract DE-NA0003525.

2Particle heat transfer media is being considered for nextgeneration CSP plantsAdvantages: Stability over wide temperature range (sub-zero to 1000 C)Direct absorption of concentrated solar (no flux limitation)Inert, noncorrosive, low cost materialDirect storage of heat transfer mediaChallenges: Low heat transfer coefficient when indirectly heated or cooled (heat exchanger cost) Particle loss, attrition, erosion is a potential concern Low temperature rise, thermal efficiency for a single pass falling particle receiver

3Particle CSP needs a dedicated tool for cost and performanceanalysisParticle system technoeconomic analysis has previously used SAM’s generic model Component cost and performance can only be modeled at a high level (inputs) Influence of operating conditions on component sizing and cost is not easily captured Propagating particle properties into component performance and cost is not possibleNew Approach:Detailed component submodels are solved with fidelity that can propagatecomponent design information directly into the plant performance and economicsQuestions to be answered: What is the optimal solar multiple and storage size for a baseload plant?What is the optimal hot storage temperature and heat exchanger approach temperature?When does particle loss become an economic concern?What is the allowable tradeoff between particle absorptivity and cost?What is the optimal sCO2 cycle configuration?

4System Configuration and Modeling ApproachBaseline Particle System Configuration 100 MWe baseload plantLocated in Dagget, CAReceiver is free falling particle receiverHot and cold storage bins at located at ground levelHeat exchanger is moving packed bed in counterflowsCO2 cycle configuration is RCBCParticle lifting with skip hoistComponents are modeled using 1-D or 0-D and sized during the simulation based onoperating conditions and performance 1-D: Receiver, Primary Heat Exchanger, sCO2 Recuperators 0-D: Storage Bins, Lifts, Turbomachinery

5Gen3 Particle System Technoeconomic ToolModel developed in Engineering Equation Solver (EES) to easily couple to sCO2properties for power cycle analysisDispatched against hourly TMY data using a procedure to model annual production

6sCO 2 Power Cycle Operating ConditionsPower cycle operating conditions determine primary heat exchanger temperature rise(energy storage) and thermal to electric conversion efficiencyOptimizing thermal efficiency (50.2%) results in primary heat exchanger temperaturerise of 149.7 CIncreasing pressure ratio can increase primary power cycle temperature rise atreduced thermal efficiency

7Sensitivity of Efficiency and Temperature Rise to sCO 2 CyclePressure and TemperatureReducing compressor inlet temperature results in large improvements in thermalefficiency and primary heat exchanger temperature riseThermal efficiency and temperature rise shows significantly less sensitivity toturbine inlet temperature

8Sensitivity to Solar Multiple and StorageMetricReceiver Cost ( kWt-1)Storage Cost ( kWt-1hr-1)Heat Exchanger Cost ( kWt-1)Power Cycle Cost ( kWe-1)Receiver EfficiencyPower Cycle EfficiencyCapacity FactorLCOE ( kWe-1 hr-1)Target 0600.0085.7%50.2%71%0.0592LCOE minimizes at solar multiple of 2.5 and 14 hours of storagePredicted cost distribution varies from DOE targets, but meets 0.06/kWe-hr goal Low cost of falling particle receiver allows for heat exchanger and storage to exceed targets Receiver thermal efficiencies below 90% can still achieve cost targets

9Selection of Hot and Cold Storage TemperaturesIncreasing hot storage temperature reduces receiver thermal efficiency and heatexchanger size, but increases heat exchanger cost per surface areaReducing heat exchanger approach temperature reduces storage inventory, butincreases heat exchanger sizeApproach temperature optimizes between 10-15 C and LCOE reduces withincreased hot storage temperature

10Influence of Power Cycle Operating Conditions on LCOELCOE minimizes at RCBC operating conditions other than optimal efficiencyIncreasing pressure ratio increases the primary heat exchanger temperature rise andthe fraction of the heat exchanger constructed from high-nickel alloys

11Particle Cost and AbsorptivityLCOE cost targets can not be achieved with particle cost exceeding 1.00/kgLow cost particles can still achieve cost targets at reduced solar absorptivity Particle selection has many additional consideration (flowability, cohesion, durability, safety)

12Particle Loss and AttritionParticle loss of 10-5 kg/kg for 1/kg is tolerable without significantly affecting the LCOELarger values of particle loss (10-4 kg/kg) are tolerable at reduced cost of particle ( 1/kg)

13ConclusionsDeveloped a dedicated particle CSP technoeconomic tool capable of capturinginterdependence of operating conditions, component geometry, and heat transfermedia propertiesPath to achieving LCOE cost targets identified for particle CSP systemsLCOE was found to minimize at conditions that do not maximize power cyclethermal efficiencyLCOE targets are unlikely to be achieved for particle cost above 1/kgLow absorptivity particles ( 0.2) can achieve cost targets with no-cost particlesParticle loss/attrition needs to be below 10-5 for system to achieve cost targetsFuture Work: Working with ANU to integrate the detailed particle component models intoSolarTherm/Modelica

14AcknowledgementsThis work was funded in part or whole by the U.S. Department of Energy SolarEnergy Technologies Office under Award Number 34211. Technology Managers: Matthew Bauer, Vijay Rajgopal, Shane PowersSandia National Laboratories is a multimission laboratory managed and operated by NationalTechnology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary ofHoneywell International Inc., for the U.S. Department of Energy’s National Nuclear SecurityAdministration under contract DE-NA0003525.

Thank youSandia National Laboratories is a multimission laboratory managed and operated by NationalTechnology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of HoneywellInternational Inc., for the U.S. Department of Energy’s National Nuclear Security Administrationunder contract DE-NA0003525.

Parametric Analysis of Particle CSP System Performance and Cost to Intrinsic Particle Properties and Operating Conditions Kevin J. Albrecht, Matthew L. Bauer, Clifford K. Ho ASME Energy and Sustainability July 16, 2019 Session 3-11: Integrated CSP Systems Two (ES2019-3893) SAND2019-8280C

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