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Modeling distributed energy resource aggregations in security constrained unit commitment and economic dispatch

The Federal Energy Regulatory Commission (FERC) recently issued Order 2222, which requires all wholesale electricity markets in the US to allow distributed energy resources (DERs) to participate in the market as aggregated resources. These DER aggregations may be composed of many individual resources that are offered and dispatched by the market as a single entity. We present here a model of a distributed energy resource aggregator (DERA) that is scheduled by a market operator’s security constrained unit commitment (SCUC) and security constrained economic dispatch (SCED). The DERA model includes constraints for battery energy storage systems (BESSs), demand response resources (DRRs), and a simple distributed energy resource (DER). This paper describes a model for each resource type and presents two methods for the DERA to generate market offer curves: a profit-maximizing optimization to compute cost curves and a direct cost algorithm to determine dispatch costs for each resource and combine into cost curves. Once all participating DERAs are scheduled in SCUC/SCED, the model is then modified to dispatch individual DERs to maximize profit or minimize schedule deviation of the DERAs. A simulation of a representative day illustrates the DERA offers, the scheduled generation, and the DERA dispatch. Findings show the potential for unavoidable schedule deviations due to internal DER constraints and due to economic incentives to deviate from the SCUC/SCED schedules. This highlights the importance of DERA offer construction on market efficiency and system reliability. Novel aspects of our approach include: (1) We consider the asymmetry of price incentives impacting DERAs from the wholesale market compared to those impacting consumers from the retail market, as imposed by current regulations and laws. (2) We model aggregate consumer response through statistically parameterizable utility functions rather than a potentially impractical approach of modeling each individual consumer. (3) We show how to use the DERA operational dispatch model to create offers into the wholesale electricity market. (4) We show how DERAs may fail to meet their scheduled dispatch because the market offer format may not permit them to fully express their operational features such as intertemporal costs and constraints to the market.

aggregations↗

Frozen storage of proteins: Use of mannitol to generate a homogenous freeze-concentrate

Therapeutic proteins may be subjected to several freeze–thaw cycles throughout manufacturing and storage. The protein solution composition and the freezing conditions may lead to incomplete ice crystallization in the frozen state. This can also result in freeze-concentrate heterogeneity characterized by multiple glass transition temperatures and protein destabilization. The overall objective was to investigate the potential advantages of including a crystallizing excipient (mannitol) along with a sugar (sucrose or trehalose) for frozen storage. Here, this study showed that the addition of mannitol, a readily crystallizing excipient, facilitated ice crystallization. Inclusion of an isothermal hold during cooling (annealing) maximized the mannitol crystallization and resulted in a homogenous freeze-concentrate of a constant composition characterized by a single glass transition temperature. The role of freezing rate and annealing on both mannitol and ice crystallization were discerned using high intensity synchrotron radiation. The addition of sucrose or trehalose, at an appropriate concentration, stabilized the protein. The mannitol to sugar ratio (3:1 or 1:1, 5 % w/v) was optimized to selectively cause maximal crystallization of mannitol while retaining the sugar amorphous. Human serum albumin (1 mg/mL) in these optimized and annealed compositions did not show any meaningful aggregation, even after multiple freeze–thaw cycles. Thus, in addition to a sugar as a stabilizer, the use of a crystallizing excipient coupled with an annealing step can provide an avenue for frozen storage of proteins.

59 BASIC BIOLOGICAL SCIENCES↗

Optimal experimental design for prediction based on push-forward probability measures

Incorporating experimental data is essential for increasing the credibility of simulation-aided decision making and design. This paper presents a method which uses a computational model to guide the optimal acquisition of experimental data to produce data-informed predictions of quantities of interest (QoI). Many strategies for optimal experimental design (OED) select data that maximize some utility that measures the reduction in uncertainty of uncertain model parameters, for example the expected information gain between prior and posterior distributions of these parameters. In this paper, we seek to maximize the expected information gained from the pushforward of an initial (prior) density to the push-forward of the updated (posterior) density through the parameter-to-prediction map. The formulation presented is based upon the solution of a specific class of stochastic inverse problems which seeks a probability density that is consistent with the model and the data in the sense that the push-forward of this density through the parameter-to-observable map matches a target density on the observable data. While this stochastic inverse problem forms the mathematical basis for our approach, we develop a one-step algorithm, focused on push-forward probability measures, that leverages inference-for-prediction to bypass constructing the solution to the stochastic inverse problem. A number of numerical results are presented to demonstrate the utility of this optimal experimental design for prediction and facilitate comparison of our approach with traditional OED.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Evaluation of the economic implications of varied pressure drawdown strategies generated using a real-time, rapid predictive, multi-fidelity model for unconventional oil and gas wells

Experience has suggested that pressure maintenance in hydraulically fractured reservoirs via lower, more sustained production drawdowns may offer improved cumulative recovery and overall resource extraction efficiency compared to more rapid drawdown approaches aimed at generating high initial production. However, given the inherent variability of oil and natural gas markets, operators pursue production strategies that maximize profitability over resource extraction efficiency. This study focuses on evaluating the implications of contrasting pressure drawdown strategies on the long-term production and resulting economics for a real, producing unconventional gas well in the Marcellus Shale of the Appalachian Basin using a techno-economic analysis approach. Our research combines elements of well-specific horizontal well design, production forecasting, equipment sizing and capital cost estimation, operating cost estimation, and revenue and tax calculations. Gas production forecast outlook scenarios were generated under varying pressure drawdowns using two approaches: 1) a novel physics-informed machine learning workflow and 2) traditional reservoir simulation. A discounted cash flow model was used to evaluate the resulting economic implications for each drawdown scenario—generating output for exploring the coupled effect of factors like the timing and volume of gas production, prevailing economic and market conditions for natural gas, and overall estimated ultimate recovery on profitability metrics such as internal rate of return and net present value. Results show that there is potential to maximize the cumulative gas produced in the specific case study well by employing a lower pressure drawdown. Conversely, the greatest profitability is achieved using rapid drawdown as signified by a small, specific subset of our outlook scenarios. On an averaging basis, we find that the combinations of highest cumulative producing and most profitable scenarios occur under lower drawdowns with long (>40 years) producing timeframes, but require higher relative gas price and lower discounting considerations. Further, the machine learning predictive outlooking capability proved effective for enabling rapid generation of a multitude of scenario forecasts. As a result, a variety of prominent example cases could be generated to strike the balance of greater productivity and economic return given their associated producing features and economic conditions when compared to similar producing scenarios—critical insight that offers improved decision support for unconventional oil and gas operations.

42 ENGINEERING↗

Converting polycarbonate and polystyrene plastic wastes intoaromatic hydrocarbons via catalytic fast co-pyrolysis

Thermochemical conversion of plastic wastes is a promising approach to produce alternative energy-based fuels. Herein, we conducted catalytic fast co-pyrolysis of polycarbonate (PC) and polystyrene (PS) to generate aromatic hydrocarbons using HZSM-5 (Zeolite Socony Mobil-5, hydrogen, Aluminosilicate) as a catalyst. The results indicated that employing HZSM-5 in the catalytic conversion of PC facilitated the synthesis of aromatic hydrocarbons in comparison to the non-catalytic run. A competitive reaction between aromatic hydrocarbons and aromatic oxygenates was observed within the studied temperature region, and catalytic degradation temperature of 700 °C maximized the competing reaction towards the formation of targeted aromatic hydrocarbons at the expense of phenolic products. Catalyst type also played a vital role in the catalytic decomposition of PC wastes, and HZSM-5 with different Si/Al molar ratios produced more aromatic hydrocarbons than HY (Zeolite Y, hydrogen, Faujasite). Regarding the effect of Si/Al molar ration in HZSM-5 on the distribution of monocyclic aromatic hydrocarbons (MAHs), a Si/Al molar ratio of 38 maximized benzene formation with an advanced factor of 5.1. Catalytic fast co-pyrolysis of PC with hydrogen-rich plastic wastes including polypropylene (PP), polyethylene (PE), and polystyrene (PS) favored the production of MAHs, and PS was the most effective hydrogen donor with a ~2.5-fold increase. The additive effect of MAHs increased at first and then decreased when the PC percentage was elevated from 30 % to 90 %, achieving the maximum value of 32.4 % at 70 % PC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reducing t1 noise through rapid scanning

The so-called t 1 noise, which arises due to random instabilities in the spectrometer hardware, remains the primary source of noise that limits the sensitivity of most 2D NMR experiments, particularly in the expanding group of solid-state NMR methods that utilize dipolar-recoupling. Here in this communication we revisit the relationship between the signal intensity and the t 1 noise produced. It is shown that since the latter scales linearly with the signal strength, the use of a conventional relaxation delay of 1.3T 1 may prove far from optimal. In cases where the fluctuations occur on a shorter timescale than the recycle delay, a considerably faster repetition rate should be used to maximize the time sensitivity in a 2D experiment than what is used to maximize the sensitivity in 1D. This is demonstrated with the acquisition of 1 H{ 13 C} Dipolar-mediated Heteronuclear Multiple-Quantum Correlation (D-HMQC) type spectra in which the sensitivity could be nearly doubled by choosing a very short relaxation delay corresponding to 0.2T 1 .

2D NMR↗

The effect of helium on cavity swelling in dual-ion irradiated Fe and Fe-10Cr ferritic alloys

We report Ferritic-martensitic (FM) steels for in-vessel components in proposed fusion reactors are expected to suffer from high levels of displacement damage and helium (He) generation by neutron transmutation. However, a thorough understanding of the He synergistic effects on the cavity swelling in FM steels is still not well established. To gain fundamental insights into the He effect on cavity swelling, high purity Fe and Fe-10 wt.% Cr ferritic model alloys were irradiated with 8 MeV Ni ions and co-implanted He ions at 400 to 550 °C up to 30 displacements per atom (dpa) with He implantation rates of 0.1, 10 and 50 appm He/dpa. The current study focuses on the 50 appm He/dpa, 500 °C behavior vs. 0.1 and 10 appm He/dpa. Irradiation-induced defects, including cavities, dislocation loops, and dislocation networks were characterized using transmission electron microscopy (TEM). In the grain interior, a bimodal cavity size distribution was observed in the 10 and 50 appm He/dpa samples, but not for 0.1 appm He/dpa. Cavity swelling was maximized at intermediate He implantation rates of ~10 appm He/dpa for both ion-irradiated Fe and Fe-10Cr alloys. The cavity swelling behavior as a function of He implantation rate appears to be controlled by the He/dpa-dependent variation of cavity sink strengths. Treating small bubbles as biased sinks for interstitial absorption can significantly increase the ratio of biased to unbiased sink strengths (Q) and results in maximized cavity swelling for a Q ratio close to one.

36 MATERIALS SCIENCE↗

India National Gas Hydrate Program Expedition 02 Summary of Scientific Results: Numerical Simulation of Reservoir Response to Depressurization

The India National Gas Hydrate Program Expedition 02 (NGHP-02) discovered gas hydrate at high saturation in sand reservoirs at several sites in the deepwater Bay of Bengal. To assess the potential response of those deposits to scientific depressurization experiments, comprehensive geologic models were constructed to enable numerical simulation for two sites. Both sites (NGHP-02-09 and NGHP-02-16) feature thick sequences of thinly-interbedded reservoir and non-reservoir facies at sub-seafloor depths less than 300m and sub-sea depths of 2400m or more. These settings pose significant challenges to current modeling capabilities. First, the thinly-interbedded reservoir architecture complicates the determination of basic reservoir parameters from both log and core data due to measurement resolution issues. Secondly, the fine scale variation in sediment properties imparts great contrasts in key parameters over very short distances, creating high gradients at multiple scales and varying orientations that necessitate careful design of high-definition simulation grids. Thirdly, the deposits include internal sources of water, as well as a range of complex boundary conditions, including variable permeability within the overlying mud-rich “seals,” that complicate reservoir depressurization. Lastly, because of the unique combination of great water depth and relatively shallow sub-seafloor depth: models designed to maximize the dissociation rate impose large pressure drawdowns on relatively low-strength sediments. This condition renders the proper evaluation and integration of the geomechanical response to hydrate dissociation critical. In this report, we review the history of gas hydrate reservoir simulation, discuss methods for creating geologic input models, and summarize the key findings and implications of the collaborative NGHP-02 numerical simulation effort. Together, the studies confirm the viability of the modeled accumulations for scientific testing and identify key challenges related to the selection of specific test sites and the design of test wells.

Boswell, Ray↗

Meta-equilibrium transition microstructure for maximum austenite stability and minimum hardness in a Ti-stabilized supermartensitic stainless steel

We report that the maximization of stable reverted austenite at room temperature through inter-critical tempering is a widely used method to reduce hardness in supermartensitic stainless steels. Nevertheless, partial martensitic transformation might occur due to insufficient compositional stabilization. In this work, we conducted a time-resolved triple-step inter-critical tempering, specially designed to obtain maximum austenite stability and minimum hardness through the progressive suppression of the martensitic transformation. The mechanism behind the progressive increase in stable reverted austenite was the generation of a meta-equilibrium state, which imposed a limit in both high temperature austenite reversion and room temperature austenite stabilization. Such limit corresponded to the high temperature volume fraction of austenite, obtained right before cooling from the first cycle. Additionally, this effect was associated to the Ni-rich fresh martensite laths acting as local Ni compositional pockets, providing site-specific austenite reversion; and to the suppression of any additional nucleation at the Ni-poor matrix as the T0 temperature for austenite reversion was strongly increased. The softening mechanism was mainly controlled by the carbon arrest effect by the precipitation of Ti (C, N), which was completed after the first tempering cycle. Nevertheless, maximizing reverted austenite and suppressing fresh martensite at room temperature did not result in additional hardness reductions.

36 MATERIALS SCIENCE↗

Parametric study and speciation analysis of rare earth precipitation using oxalic acid in a chloride solution system

Oxalic acid precipitation is a common step in the purification of rare earth elements (REE) from a concentrated pregnant leach solution (PLS). However, the presence of contaminants such as Al, Fe, and Ca in given amounts decreases the REE precipitation efficiency and product purity while also increasing the amount of oxalic acid needed to maximize recovery. As such, a statistically designed test program was performed to identify the optimal conditions necessary for a relatively low REE content PLS containing elevated concentrations of contaminant ions. The performance objective was maximization of REE precipitation efficiency while minimizing the oxalic acid dosage. A central composite design was utilized to quantify performance impacts and identify the ultimate set of parameter values for oxalic acid dosage, Fe(III) contamination concentration, solution pH, and reaction temperature. The resultant model suggested that oxalic acid dosage and reaction pH are the most significant factors for the REE precipitation efficiency, followed by the interaction of oxalic dosage and Fe concentration. Test results indicate that increasing the oxalic acid concentration from 0 g/L to 80 g/L improved the REE precipitation efficiency from approximately 4.2% to 95.0%. Furthermore, raising the solution pH from 0.5 to 2.5 considerably enhanced the precipitation efficiency from 0.0% to 98.9%. A solution temperature elevation decreased REE recovery, which indicated an exothermic reaction between REEs and oxalate anions. Finally, a high level of Fe contamination adversely impacted REE precipitation efficiency. Here, to further the understanding of the REE-oxalate system, a fundamental solution chemistry study was performed using the equilibrium constants of the reactions. The study resulted in the development of oxalate speciation diagrams and provided an analysis of the REE precipitation characteristics at various oxalate anion concentrations and Fe(III) contamination levels using MINTEQ software. The dominant Fe(III) species in the solution system were found to be Fe-(C 2 O 4 ) 3 3- , Fe-(C 2 O 4 ) 2- , and Fe-(C 2 O 4 ) + , which consume the majority of the oxalate anions. The simulated model was found to be in agreement with the experimental findings and helped to explain the adverse impact of increased iron concentrations on REE precipitation efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crowded electrolytes containing redoxmers in different states of charge: Solution structure, properties, and fundamental limits on energy density

Nonaqueous redox flow batteries use liquid electrolytes containing redox-active organic molecules (redoxmers) as their energy storage medium. To maximize energy density, the redoxmer concentration needs to be maximized while maintaining low viscosity and high ionic conductivity. During charge, a redoxmer molecule pairs with an ion in the electrolyte while another ion migrates across the membrane to maintain electric neutrality. In a crowded electrolyte, this reconstitution changes physical and chemical properties of the solution. To explore these behaviors, a phenothiazine redoxmer fully miscible with acetonitrile was used, and electrochemical charge was mimicked by chemical oxidation. The solutions were examined using small-angle X-ray scattering, nuclear magnetic resonance, and conductometry and modeled using classical molecular dynamics. Overall, our study indicates that physical and structural properties of redoxmer solutions in both states of charge make it exceedingly difficult to increase the redoxmer concentrations over 2 M at any temperature without compromising dynamic properties of such solutions. The cause for this limitation is proximity to a gel-like regime in which fluidity, diffusivity, and ionic conductivity exponentially decrease with increasing concentration. This tendency is compounded by non-Arrhenius behavior of the electrolyte: a small increase in the concentration outruns gains in fluidity and conductivity at a higher temperature. Thus the properties of crowded electrolytes generally make it impossible to operate when gel-like behavior sets in. Pushing the redoxmer concentration to 2.5-3 M might be possible for small redoxmer molecules, but it would require the use of ionic liquid electrolytes at 340-360 K. (C) 2021 Elsevier B.V. All rights reserved.

25 ENERGY STORAGE↗

Structural dynamics of first-order phase transition in giant magnetocaloric La(Fe,Si) 13 : The free energy landscape

Maximizing the performance of magnetic refrigerators and thermomagnetic energy harvesters is imperative for their successful implementation and can be done by maximizing their operation frequency. One of the features delimiting the frequency and efficiency of such devices is the phase transition kinetics of their magnetocaloric/thermomagnetic active material. While previous studies have described the magnetic component governing the kinetics of the magnetovolume phase transition in La(Fe,Si) 13 giant magnetocaloric materials, a comprehensive description of its structural component has yet to be explored. In this study, in situ synchrotron X-ray diffraction is employed to describe the structural changes upon magnetic field application/removal. Long magnetic field dependent relaxation times up to a few hundred seconds are observed after the driving field is paused. The phase transition is found to be highly asymmetric upon magnetic field cycling due to the different Gibbs energy landscapes and the absence of an energy barrier upon field removal. An exponential relationship is found between the energy barriers and the relaxation times, suggesting the process is governed by a non-thermal activation over an energy barrier process. Such fundamental knowledge on first-order phase transition kinetics suggests pathways for materials optimization and smarter design of magnetic field cycling in real-life devices.

36 MATERIALS SCIENCE↗

Performance of neutron spectrum unfolding using deuterated liquid scintillator

The performance of the maximum likelihood expectation maximization method for unfolding neutron energy spectra using deuterated liquid scintillator is evaluated for future utilization with rare isotope beams. High-resolution neutron energy spectra as well as the detector response matrix were measured at the Edwards Accelerator Laboratory at Ohio University. Maximum-likelihood expectation maximization (MLEM) unfolded neutron spectra are compared with spectra from neutron time-of-flight. In conclusion, the effects of the MLEM stopping criteria and spectrum statistics are also investigated.

47 OTHER INSTRUMENTATION↗

A monolithic antineutrino detector for non-intrusive reactor monitoring

Recent advances in organic detection media have found applications in reactor antineutrino physics. One example is the Precision Oscillation and Spectrum Experiment (PROSPECT), which leveraged pulse-shape sensitivity to enable a successful surface deployment at the High Flux Isotope Reactor (HFIR), achieving a signal to background of 4:1. PROSPECT utilized almost 4 tonnes of 6 Li-doped pulse-shape sensitive liquid scintillator in a two-dimensional segmented array. It used a combination of pulse-shape sensitivity and position sensitivity via segmentation to reduce the most prominent form of correlated background for surface detectors — cosmogenic fast neutrons. These new liquids may enable detector designs that bring additional tools for reducing backgrounds while reducing engineering complexity. In this paper, we present an investigation into a detector design that exploits properties of these liquids by maximizing spectral and pulse-shape sensitivity via highly efficient photon detection. The detector utilizes photomultiplier tubes (PMTs) placed at the top and bottom of a right cylinder, with highly reflective white walls. This design sacrifices some position sensitivity for maximal photon efficiency. In conclusion, the design choice has consequences for the identification of the background and antineutrino sensitivity, which we examine.

Pulse shape↗

Filament-induced breakdown spectroscopy signal enhancement using optical wavefront control

Filament-induced breakdown spectroscopy (FIBS) is an analytical method that holds significant promise for remote sensing. In FIBS, it is desirable to maximize the intensity and improve the reproducibility of a selected spectroscopic feature. Here, we demonstrate the use of wavefront control in conjunction with a genetic algorithm in FIBS of metallic copper and show that this approach can increase the efficacy of filament-induced breakdown signal production. Through wavefront optimization, we enhance the intensity of a chosen characteristic spectroscopic feature of copper by a factor of approximately 3 when performing filamentation over a 1-meter distance. The relative standard deviation of signal intensity is reduced from ~17% to ~12% after optimization. We find that modification of the wavefront by introduction of astigmatism and coma maximizes the signal intensity, and these aberrations appear in two distinct trials of the genetic algorithm. We compare these findings to previous work on multiple filament control and discuss the possible mechanisms that lead to signal enhancement associated with both the beam amplitude and phase profile. A broader use of wavefront control with feedback may improve the performance of FIBS in remote sensing applications.

42 ENGINEERING↗

Cascading from $\mathscr{N}$ = 2 supersymmetric Yang–Mills theory to confinement and chiral symmetry breaking in adjoint QCD

We argue that adjoint QCD in 3 + 1 dimensions, with any SU(N) gauge group and two Weyl fermion flavors (i.e. one adjoint Dirac fermion), confines and spontaneously breaks its chiral symmetries via the condensation of a fermion bilinear. We flow to this theory from pure $\mathscr{N}$ = 2 SUSY Yang–Mills theory with the same gauge group, by giving a SUSY-breaking mass M to the scalars in the $\mathscr{N}$ = 2 vector multiplet. This flow can be analyzed rigorously at small M, where it leads to a deconfined vacuum at the origin of the $\mathscr{N}$ = 2 Coulomb branch. The analysis can be extended to all M using an Abelian dual description that arises from the N multi-monopole points of the $\mathscr{N}$ = 2 theory. At each such point, there are N −1 hypermultiplet Higgs fields h$^{i=1,2}_m$, which are SU(2) R doublets. We provide a detailed study of the phase diagram as a function of M, by analyzing the semi-classical phases of the dual using a combination of analytic and numerical techniques. The result is a cascade of first-order phase transitions, along which the Higgs fields h i m successively turn on, and which interpolates between the Coulomb branch at small M, where all h$^{i}_m$ = 0, and a maximal Higgs branch, where all h$^{i}_m$ ≠ 0, at sufficiently large M. We show that this maximal Higgs branch precisely matches the confining and chiral symmetry breaking phase of two-flavor adjoint QCD, including its broken and unbroken symmetries, its massless spectrum, and the expected large-N scaling of various observables. The spontaneous breaking pattern SU(2) R → U(1) R , consistent with the Vafa–Witten theorem, is ensured by an intricate alignment mechanism for the h$^{i}_m$ in the dual, and leads to a CP 1 sigma model of increasing radius along the cascade.

D’Hoker, Eric [Univ. of California, Los Angeles, C↗

The Cell Utilized Partitioning Model as a Predictive Tool for Optimizing Counter-Current Chromatography Processes

Counter-current chromatography (CCC) is capable of unique elution modes that isolate analytes using the movement of the stationary phase in addition to moving the mobile phase. These modes include elution-extrusion CCC (EECCC) and dual-mode CCC (DM CCC) that are not possible in traditional solid-liquid chromatography systems. Although EECCC and DM CCC are widely used to recover highly retained components, to our knowledge, optimizing the elution process in these modes with predictive models has not been reported. To address this gap, we developed a predictive model for CCC dubbed the Cell Utilized Partitioning (CUP) model. The CUP model accurately predicts the effluents of multicomponent separations in EECCC and DM CCC modes when compared to experimental data. Furthermore, CUP model simulations were extended to investigate the influence of operating and intrinsic parameters on the yield and productivity, and to compare the separation performances of EECCC and DM CCC in various conditions. The results demonstrate that low distribution constants, usually a KD less than 1, and a selectivity > 1.3, under specific flowrate ranges, increase both productivity and yield. From these results, generalized optimization and scaleup guidelines are proposed that can apply to research settings and to industrial processes to maximize preparative CCC performance.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗

Steady-state off-design modeling of the supercritical carbon dioxide recompression cycle for concentrating solar power applications with two-tank sensible-heat storage

Concentrating solar power researchers are evaluating the potential of the supercritical carbon dioxide recompression cycle to improve the thermal efficiency and decrease the capital costs of next-generation systems. This analysis investigates the steady-state off-design performance of a recompression cycle integrated with two-tank sensible-heat thermal energy storage as the ambient temperature and heat-transfer fluid (HTF) inlet conditions to the cycle change. This paper presents off-design component models and then cycle convergence and control models to maximize net cycle power output while constraining the high-side pressure and air-cooler fan power to their respective design values and fixing the cycle HTF outlet temperature to its design value. Results show that inventory control and air-cooler fan power are important control parameters that can be optimized to maximize off-design power output as the ambient temperature and HTF mass flow rate diverge from design. The high-side pressure and fan power constraints cause the cycle net power to degrade when the ambient temperature is warmer than the design value, and this study calculates a maximum mass flow rate for hot days above which the cycle cannot achieve the design HTF outlet temperature. Finally, the analysis shows that optimizing compressor shaft speeds can improve cold-day performance by around 1.5 percentage points and part-load performance by up to 2.5 percentage points versus a baseline case with no active compressor control.

14 SOLAR ENERGY↗