1,720,987 research outputs found
Dynamic economic dispatch using complementary quadratic programming
No full textEconomic dispatch for micro-grids and district energy systems presents a highly constrained non-linear, mixed-integer optimization problem that scales exponentially with the number of systems. Energy storage technologies compound the mixed-integer or unit-commitment problem by necessitating simultaneous optimization over the applicable time horizon of the energy storage. The dispatch problem must be solved repeatedly and reliably to effectively minimize costs in real-world operation. This paper outlines a method that greatly reduces, and under some conditions eliminates, the mixed-integer aspect of the problem using complementary convex quadratic optimizations. The generalized method applies to grid-connected or islanded district energy systems comprised of any variety of electric or combined heat and power generators, electric chillers, heaters, and all varieties of energy storage systems. It incorporates constraints for generator operating bounds, ramping limitations, and energy storage inefficiencies. An open-source platform, EAGERS, implements and investigates this optimization method. Results demonstrate a >99% reduction in computational effort when comparing the newly minted optimization strategy against a benchmark commercial mixed-integer solver applied to the same combined cooling, heating, and power problem
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Complementary quadratic programming and artificial neural network for computationally efficient microgrid dispatch optimization with unit commitment
Full text linkMicrogrid infrastructures allow for a cleaner energy future by reducing transmission losses, enabling combined heat and power efficiency upgrades, employing onsite renewable generation, and providing power stability especially when paired with energy storage devices. Microgrid dispatch optimization allows wider implementation of microgrid infrastructures by lowering microgrid operations costs. The computational bottleneck of dispatch optimization is unit commitment, which is a mixed integer optimization problem. Three methods to reduce the computational effort of unit commitment and maintain satisfactory optimality are. Complementary Quadratic Programming (cQP), modified complementary Quadratic Programming (mcQP), and Artificial Neural Network (ANN) with dynamic economic dispatch. Both cQP and mcQP are capable of quickly optimizing receding horizon dispatches with storage, creating training sets which facilitates machine learning approaches such as method three. This thesis presents cQP and mcQP development as a means of training a neural network unit commitment solver, and compares all three approaches to solutions of the full mixed-integer problem using a commercial solver. Decision trees are employed for feature selection, and ANNs of varying depth are compared for ANN structure selection. The mcQP method is the most robust, and the ANN method is the most computationally efficient. All three methods outperform the commercial solver in computational efficiency, robustness, and dispatch cost
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Analysis of vortex tube applications in hydrogen liquefaction
Full text linkThermal and AC Power Systems Dispatch Optimization Incorporating Storage and Unit Commitment
Full text linkThesis (Ph.D.), Mechanical Engineering, Washington State UniversityReliable and efficient power system dispatch is of paramount importance for the increased incorporation of microgrid infrastructures and renewable and distributed energy resources. Operating costs of microgrids and distributed generation can be reduced when optimizer models include control for unit commitment, meeting thermal demands, energy storage devices, and AC power flow constraints, as opposed to a heuristic dispatch or a dispatch that only considers some of these aspects. Augmentations to conic programming (CP) implementations for power systems dispatch with unit commitment allow for the inclusion of thermal demands, energy storage, and AC power flow constraints. The computational demand for inclusion of all the elements of this problem is shown to be remediated with transfer learning of a neural network (NN) with sigmoid and linear activation functions initially trained from Complementary Quadratic Programming (cQP) real power dispatch solutions then trained from conic AC power solutions. The application of a neural network allows for rapid creation of dispatch solutions which can be used to better evaluate the applicability and cost of dispatch methods with higher computational demand, such as conic programming, across a wide range of scenarios. This dissertation evaluates the computational efficiency, dispatch cost, and reliability of neural networks with varying layers as trained by conic programming and cQP for solving the AC microgrid power flow optimization problem with unit commitment, storage, and combined heat and power. Three test cases are used to benchmark cQP, CP, and NNs: a hypothetical test case, a model of Washington State University’s Pullman campus, and a modified model of WSU’s campus to include higher levels of on-site generation from solar and combined heat and power gas turbines. This work provides the first known example of simultaneous solution of the AC optimal power flow problem in conjunction with the combined cooling heat and power unit commitment optimization with storage. This work also demonstrates the advantage of incorporating a sigmoid function for neural network replication of microgrid dispatches which include unit commitment.
Key Terms: dispatch, optimal power flow, energy storage, microgrid, quadratic programming, conic programming, neural network, decision tree, machine learningWashington State University, Mechanical Engineerin
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Steady state modeling and analysis of a reversible solid oxide fuel cell based energy storage system
Full text linkHigh variable renewable energy penetrations are infeasible due to the high rates of curtailment necessary to maintain grid stability with existing grid infrastructure. Electrical energy storage can be used to increase grid stability and decrease curtailment at high renewable energy penetrations by storing variable renewable power when it is not usable by the grid. This thesis introduces a design for a reversible solid oxide fuel cell (reSOFC) based energy storage system that utilizes indirect and direct internal reformation and methanation to operate at high electrical efficiencies. By selecting operating conditions conducive to steam reformation in fuel cell mode and methanation in electrolysis cell mode, benefits to thermal management and reactant composition within the reSOFC are achieved. Under steady state operation, these conditions are found to result in higher electrical efficiencies in a methane-based reSOFC than a hydrogen-based reSOFC while avoiding carbon deposition within the reSOFC. This thesis outlines the modeling methods and requirements for a reSOFC-based energy storage system and applies that model to the use of variable renewable energy within the Pacific Northwest. A high-level analysis compares the optimized levelized cost of electricity for a reSOFC-based energy storage system with a state-of-the-art grid-scale battery energy storage system and finds reSOFC-based energy storage to be a competitive option
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A novel de-coupled SOFC-GT hybrid system to power commercial all-electric aircraft
Full text linkThis study describes and evaluates two solid-oxide fuel cell/gas-turbine systems (SOFC-GT) capable of fully powering large-scale commercial all-electric aircraft (AEA) with zero emissions using liquid hydrogen fuel and superconducting electric motors driving ducted fans. The analysis departs from existing research integrating SOFCs into light-weight conceptual aircraft designs, or confining the scope to supporting roles generating supplemental electric power for existing aircraft, and instead focuses on a commercial scale AEA based on existing airframe specifications. Of the two systems analyzed, the first adheres closely standard SOFC-GT cycles with the variation that unreacted hydrogen is purified and recirculated rather than combusted to further heat the turbine inlet stream. The second system analyzed incorporates an oxygen separation membrane to decouple the fuel cell and turbomachinery sub-systems. The arrangement facilitates steady fuel cell operating pressure, high power density and improved efficiency over a broader range of operation. A detailed weight analysis describing a novel SOFC stack design identifies and addresses the challenges in meeting the required power-to-weight ratios. The resulting assessment illustrates how an SOFC based AEA can approach or exceed current jet engine performance, particularly in long range applications. Higher specific energy density of liquid hydrogen fuel, combined with the highly efficient energy conversion of SOFC and superconducting motors allows for a 10-21% increase in payload capacity for an Airbus A380 while maintaining the same range capability
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PRESSURIZED SOLID OXIDE ELECTROLYSIS MODELING SYSTEM PERFORMANCE AND DEMONSTRATING OPERATION
Full text linkThis work investigates high pressure solid oxide electrolysis (SOE) through fundamental thermodynamic analysis, system modeling, and experimentation with state of the art (SoA) materials and technology. Pressurized steam electrolysis can meet lifetime efficiency targets reducing the energy requirement for practical hydrogen production by 18% over non-pressurized electrolysis. A system thermoneutral point is determined to maximize lifetime fuel production and system efficiency. Operating conditions and system design tradeoffs are identified for lower cost hydrogen production. Commercial cell testing solutions meeting the demanding operating requirements of high pressure, temperature, oxidizing, and reducing environments are demonstrated for long duration with pressurized and steam conditions. Improved performance is shown with commercially manufactured cells in pressurized testing environments up to 10 barg, though these conditions are found to accelerate degradation of SoA solid oxide materials. The research presented here advances current SOE systems knowledge for renewable fuel production. The findings identify an alternative approach to solid oxide technology development for greater efficiency. Commercialization of this technology has the potential for large scale displacement of fossil fuels
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A HIGH-FIDELITY, CONTINUOUS ORTHO-PARAHYDROGEN MEASUREMENT AND CONVERSION SYSTEM
Full text linkProduction and consumption of liquid hydrogen is set to increase many orders of magnitude in the upcoming decades. Yet an entire liquid shipment can be boiled-off from the exothermic ortho-parahydrogen reaction if not performed during liquefaction. Measurements of ortho-parahydrogen composition have been historically challenging which hinders routine analysis. Included are experimental results of a continuous flow, in-situ Raman spectroscopy system for sampling ortho-parahydrogen composition. Correlation between Raman peak intensities and ortho-parahydrogen ratios demonstrates the actual number of molecules present in a given J mode is dependent on Boltzmann distribution, partition function, anisotropic polarizability, and scattering frequency. Consistent definitions of orthohydrogen percentage as related to Raman peak areas allow true orthohydrogen percentages to be obtained from sub 80K sample temperatures. The degeneracy of J mode populations as described by full statistical thermodynamics allows a correction to obtain true orthohydrogen percentages. This correction is completed with known experimental peak areas which correspond to confirmed equilibrium orthohydrogen percentage values. Simultaneous Raman measurement before and after catalytic packed bed and vortex tube ortho-parahydrogen conversion devices allow improved measurement to verify conversion performance. For example, a catalyzed dual outlet vortex tube produced a raw Raman measured para-orthohydrogen conversion of 6.3% from inlet to outlet. When calibrated to the true orthohydrogen percentage, it equates to 7.3% compared to the theoretical of 8.7% based off experimental temperature differentials. The results indicate application in optimizing liquefaction packed bed and reducing boil-off through vortex tube related heat exchangers applications. Together, these methods of orthohydrogen and parahydrogen conversion and measurement allow for increased liquid hydrogen storage optimization
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High Performance Microchannel Heat Exchanger Design
Full text linkNovel manufacturing methods allows for miniaturization of microchannel dimensions with the potential to enhance heat exchanger performance by increasing surface area per unit mass. In this thesis, microchannel heat exchanger design is analyzed to determine factors limiting effectiveness and power density. Ideal heat exchanger performance is characterized for one-pass counterflow heat exchangers with varying channel dimensions, flow regimes, and thermal conductivities. Smaller channel sizes lead to increased pressure drop and temperature gradients within the channel, necessitating low flow rates. Axial conduction is found to drive down effectiveness at low flow rates, with this effect more pronounced with decreased channel dimensions. Reducing the heat exchanger’s thermal conductivity to 1W/(m∙K) is found to reduce axial conduction. However, pressure drop still limits performance for existing designs, so optimized designs are necessary to create high performance microchannel heat exchangers. A multi-pass design consisting of stacked one-pass layers to keep pressure drop at an acceptable level is tested at various channel dimensions and flow regimes. The multi-pass design achieved an 11.2 times increase in power density and 1.08 times increase in maximum achievable effectiveness over leading commercial heat exchanger designs
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DEVELOPMENT OF HIGH PRESSURE SOFC TEST STAND AND IN-SITU CHARACTERIZATION OF ANODE SUPPORTED CELLS USING TIME DOMAIN IMPEDANCE SPECTROSCOPY
Full text linkIn this work a Solid Oxide Fuel Cell (SOFC) test stand was developed for testing commercially available anode supported cells with an active area of 81 cm2 under pressurized conditions up to 98 PSIG, with temperatures ranging from 600 °C – 750 °C. A custom stack architecture was developed utilizing disposable 430 S.S interconnect plates, and sealing is accomplished using only compressible gaskets. An in-situ technique was developed using impedance measurements during stack compression at room temperature to ensure proper compression of the stack is achieved.In house electrodeposited Co-Mn coatings were developed to prevent chrome evaporation at the cathode and increase conductivity. The cell performance with and without the coating was compared. The cells were characterized using polarization curves as well as in-situ impedance measurements with a subsequent Distribution of Relaxation Times (DRT) analysis. The results show a significant improvement in performance up to about 48 PSIG which can be attributed to reductions in activation and gas diffusion losses. Further increases in pressure after 48 PSIG show diminishing returns in performance.Additionally, a time domain impedance spectrometer was developed which utilizes Passive Load Excitation (PLE) to obtain the impedance spectrum of the cell. Custom MATLAB software was developed to transform the time domain response of the cell into the frequency domain via a carrier function Laplace transform. The MATLAB software was validated using a commercial circuit simulating software, which simulated an RC dummy cell in both a time transient analysis and frequency domain analysis. The MATLAB software correctly converted the time transient response of the simulated circuit into the frequency domain. The spectrometers hardware was validated by comparing its measured response of SOFC button cells and NiMH battery packs to measurements of the same cells using a commercially available AC impedance spectrometer
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