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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Objective and algorithm considerations when optimizing the number and placement of turbines in a wind power plant

Abstract. Optimizing turbine layout is a challenging problem that has been extensively researched in the literature. However, optimizing the number of turbines within a given boundary has not been studied as extensively and is a difficult problem because it introduces discrete design variables and a discontinuous design space. An essential step in performing wind power plant layout optimization is to define the objective function, or value, that is used to express what is valuable to a wind power plant developer, such as annual energy production, cost of energy, or profit. In this paper, we demonstrate the importance of selecting the appropriate objective function when optimizing a wind power plant in a land-constrained site. We optimized several different wind power plants with different wind resources and boundary sizes. Results show that the optimal number of turbines varies drastically depending on the objective function. For a simple, one-dimensional, land-based scenario, we found that a wind power plant optimized for minimal cost of energy produced just 72 % of the profit compared to the wind power plant optimized for maximum profit, which corresponded to a loss of about USD 2 million each year. This paper also compares the performance of several different optimization algorithms, including a novel repeated-sweep algorithm that we developed. We found that the performance of each algorithm depended on the number of design variables in the problem as well as the objective function.

17 WIND ENERGY↗
DOE OSTI2016

Maximization of the annual energy production of wind power plants by optimization of layout and yaw-based wake control: Maximization of wind plant AEP by optimization of layout and wake control

This paper presents a wind plant modeling and optimization tool that enables the maximization of wind plant annual energy production (AEP) using yaw-based wake steering control and layout changes. The tool is an extension of a wake engineering model describing the steady-state effects of yaw on wake velocity profiles and power productions of wind turbines in a wind plant. To make predictions of a wind plant's AEP, necessary extensions of the original wake model include coupling it with a detailed rotor model and a control policy for turbine blade pitch and rotor speed. This enables the prediction of power production with wake effects throughout a range of wind speeds. We use the tool to perform an example optimization study on a wind plant based on the Princess Amalia Wind Park. In this case study, combined optimization of layout and wake steering control increases AEP by 5%. The power gains from wake steering control are highest for region 1.5 inflow wind speeds, and they continue to be present to some extent for the above-rated inflow wind speeds. The results show that layout optimization and wake steering are complementary because significant AEP improvements can be achieved with wake steering in a wind plant layout that is already optimized to reduce wake losses.

17 WIND ENERGY↗
DOE OSTI2020

Black-Box Optimization for Design of Concentrating Solar Power and Photovoltaic Hybrid Systems with Optimal Dispatch Decisions

The hybridization of concentrating solar power (CSP) and photovoltaics (PV) can enable dispatchable renewable electricity generation at a lower price than current stand-alone CSP systems. However, designing a CSP-PV hybrid system can be challenging because of the many degrees of freedom in design that affect the internal and external system interactions and trade-offs. We develop a methodology to determine optimal designs for CSP-PV hybrids by implementing NLopt's derivative-free, or “black-box,” algorithms around pre-existing CSP-PV hybrid simulation software that utilizes the National Renewable Energy Laboratory’s System Advisor Model (SAM); we then employ a dispatch optimization model to determine operational decisions that maximize a plant’s profits. We present optimal designs for CSP-PV hybrid systems dispatching against four time-of-delivery (ToD) pricing structures. NLopt’s algorithms can improve the base case design’s power purchase agreement (PPA) price by 15% to 21%, depending on the ToD pricing structure. In addition, we present the resulting optimal CSP-PV hybrid design’s annual performance metrics, which tend to have capacity factors between 50% and 62%, but are able to generate electricity during the year’s highest-valued periods about 90% of the time. Lastly, we investigate the trade-offs between capacity factor and PPA price using Pareto fronts and demonstrate that, for some ToD pricing structures, the system capacity factor can increase by 20% but at the expense of a 2% increase in PPA price.

black-box↗
NASA NTRS1983

An approach to optimization of low-power Stirling cryocoolers

A method for optimizing the design (shape of the displacer) of low power Stirling cryocoolers relative to the power required to operate the systems is described. A variational calculation which includes static conduction, shuttle and radiation losses, as well as regenerator inefficiency, was completed for coolers operating in the 300 K to 10 K range. While the calculations apply to tapered displacer machines, comparison of the results with stepped displacer cryocoolers indicates reasonable agreement.

Sullivan, D. B.↗
NASA NTRS2004

Design of Ultra-High-Power-Density Machine Optimized for Future Aircraft

The NASA Glenn Research Center's Structural Mechanics and Dynamics Branch is developing a compact, nonpolluting, bearingless electric machine with electric power supplied by fuel cells for future "more-electric" aircraft with specific power in the projected range of 50 hp/lb, whereas conventional electric machines generate usually 0.2 hp/lb. The use of such electric drives for propulsive fans or propellers depends on the successful development of ultra-high-power-density machines. One possible candidate for such ultra-high-power-density machines, a round-rotor synchronous machine with an engineering current density as high as 20,000 A/sq cm, was selected to investigate how much torque and power can be produced.

Choi, Benjamin B.↗
DOE OSTI2025

Optimal design of power constrained bipolar membrane electrodialysis over a wide brine range

Bipolar membrane electrodialysis enables the in-situ production of high value products (e.g., acid and base) from clean brine, which is essential for a sustainable future. A technoeconomic assessment (TEA) was conducted on extraction of value from brine using the WaterTAP framework to identify optimal cost across a wide design space. Here, in the power constrained regime, increasing supplied salt concentration does not necessarily result in reduced cost or increased NaOH concentration. A detailed analysis elucidates the critical roles of water dissociation, limiting currents, and sodium diffusion play in shaping the landscape of levelized cost. Among these, water splitting predominantly influences the TEA outcomes across most of the optimal design space. Sensitivity analysis further demonstrates that membrane properties controlling water dissociation significantly impact the unit cost. The results indicate that innovations targeting improvements in water disassociation should be prioritised to effectively reduce the levelized cost of product production.

Bipolar membrane electrodialysis↗
DOE OSTI2023

Data-driven quantum approximate optimization algorithm for power systems

Abstract Quantum technology provides a ground-breaking methodology to tackle challenging computational issues in power systems. It is especially promising for Distributed Energy Resources (DERs) dominant systems that have been widely developed to promote energy sustainability. In those systems, knowing the maximum sections of power and data delivery is essential for monitoring, operation, and control. However, high computational effort is required. By leveraging quantum resources, Quantum Approximate Optimization Algorithm (QAOA) provides a means to search for these sections efficiently. However, QAOA performance relies heavily on critical parameters, especially for weighted graphs. Here we present a data-driven QAOA, which transfers quasi-optimal parameters between weighted graphs based on the normalized graph density. We verify the strategy with 39,774 expectation value calculations. Without parameter optimization, our data-driven QAOA is comparable with the Goemans-Williamson algorithm. This work advances QAOA and pilots its practical application to power systems in noisy intermediate-scale quantum devices.

Jing, Hang (ORCID:0000000256343489)↗
DOE OSTI2014

TAS: 89 0227: TAS Recovery Act - Optimization and Control of Electric Power Systems: ARRA

The name SuperOPF is used to refer several projects, problem formulations and soft-ware tools intended to extend, improve and re-define some of the standard methods of optimizing electric power systems. Our work included applying primal-dual interior point methods to standard AC optimal power flow problems of large size, as well as extensions of this problem to include co-optimization of multiple scenarios. The original SuperOPF problem formulation was based on co-optimizing a base scenario along with multiple post-contingency scenarios, where all AC power flow models and constraints are enforced for each, to find optimal energy contracts, endogenously determined locational reserves and appropriate nodal energy prices for a single period optimal power flow problem with uncertainty. This led to example non-linear programming problems on the order of 1 million constraints and half a million variables. The second generation SuperOPF formulation extends this by adding multiple periods and multiple base scenarios per period. It also incorporates additional variables and constraints to model load following reserves, ramping costs, and storage resources. A third generation of the multi-period SuperOPF, adds both integer variables and a receding horizon framework in which the problem type is more challenging (mixed integer), the size is even larger, and it must be solved more frequently, pushing the limits of currently available algorithms and solvers. The consideration of transient stability constraints in optimal power flow (OPF) problems has become increasingly important in modern power systems. Transient stability constrained OPF (TSCOPF) is a nonlinear optimization problem subject to a set of algebraic and differential equations. Solving a TSCOPF problem can be challenging due to (i) the differential-equation constraints in an optimization problem, (ii) the lack of a true analytical expression for transient stability in OPF. To handle the dynamics in TSCOPF, the set of differential equations can be approximated or converted into equivalent algebraic equations before they are included in an OPF formulation. In Chapter 4, a rigorous evaluation of using a predefined and fixed threshold for rotor angles as a mean to determine transient stability of the system is developed. TSCOPF can be modeled as a large-scale nonlinear programming problem including the constraints of differential-algebraic equations (DAE). Solving a TSCOPF problem can be challenging due to (i) the differential-equation constraints in an optimization problem, (ii) the lack of a true analytical expression for transient stability constraint in OPF. Unfortunately, even the current best TSCOPF solvers still suffer from the curse of dimensionality and unacceptable computational time, especially for large-scale power systems with multiple contingencies. In chapter 5, thse issues will be addressed and a new method to incorporate the transient stability constraints will be presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1993

Optimal cooperative power-limited rendezvous between neighboring circular orbits

A minimum-fuel rendezvous of two power-limited spacecraft is investigated. Both vehicles are active and provide thrust to complete the rendezvous. Total propellant consumption is minimized. Analytical solutions are obtained for cooperative rendezvous in the linearized Hill-Clohessy-Wiltshire gravity field. The optimal solutions depend in a complicated way on the power-to-mass ratios of the spacecraft, the initial orbits, and the specified transfer time. For comparison purposes, analytical solutions for active-passive rendezvous in the linearized gravity field are also determined. Cooperative rendezvous requires smaller total propellant consumption, resulting in greater payload capability.

Coverstone-Carroll, Victoria↗
DOE OSTI2019

Power quality of service optimization for microgrids

Various examples are provided for power quality of service optimization for microgrids. In one example, among others, a microgrid includes a smart meter configured to control supply of electric power to loads based at least in part upon energy consumption scheduling of the loads, which is based at least in part upon an effective electric generation capacity associated with the microgrid. The energy consumption scheduling can be based at least in part upon estimated power output of a sustainable energy resource of the microgrid and a load demand characterization of the loads. In another example, a system comprises a plurality of microgrids and an advanced metering infrastructure (AMI) configured to monitor operations of the microgrids and to control supply of electric power from sustainable energy resources and energy storage systems to loads of the microgrids via smart meters based at least in part upon energy consumption scheduling of the loads.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Numerical Analysis on Hydraulic Power Take-Off for Wave Energy Converter and Power Smoothing Methods: Preprint

One of the primary challenges for wave energy converter (WEC) systems is the fluctuating nature of wave resources, which require the WEC components to be designed to handle loads (i.e., torques, forces, and powers) that are many times greater than the average load. This approach requires a much greater power take-off (PTO) capacity than the average power output and indicates a higher cost for the PTO. Moreover, additional design requirements, such as battery storage, are needed, particularly for practical electrical grid connection, and can be a problem for sensitive equipment (e.g., radar, computing devices, and sensors). Therefore, it is essential to investigate potential methodologies to reduce the overall power fluctuation while trying to optimize the power output from WECs. In this study, a detailed hydraulic PTO model was developed and coupled with a time-domain hydrodynamics model (WEC-Sim) to evaluate the PTO efficiency for WECs and the trade-off between power output and fluctuation using different power smoothing methods, including energy storage, pressure relief mechanism, and a powerbased setpoint control method. The study also revealed that the maximum power fluctuation for WECs can be significantly reduced by one order of magnitude when these power smoothing methods are applied.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Frequency Analysis of Solar PV Power to Enable Optimal Building Load Control

In this paper, we present a flexibility estimation mechanism for buildings’ thermostatically controlled loads (TCLs) to enable the distribution level consumption of the majority of solar photovoltaic (PV) generation by local building TCLs. The local consumption of PV generation provides several advantages to the grid operation as well as the consumers, such as reducing the stress on the distribution network, minimizing voltage fluctuations and two-way power flows in the distribution network, and reducing the required battery storage capacity for PV integration. This would result in increasing the solar PV generation penetration levels. The aims of this study are twofold. First, spectral (frequency) analyses of solar PV power generation together with the power consumption of multiple building TCLs (such as heating, ventilation, and air conditioning (HVAC) systems, water heaters, and refrigerators) are performed. These analyses define the bandwidth over which these TCLs can operate and also describe the PV generation frequency bandwidth. Such spectral analyses, in frequency domain, can help identify the flexible components of PV generation that can be consumed by the various TCLs through optimal building load utilization. Second, a quadratic optimization problem based on model predictive control is formulated to allow consuming most of the low and medium frequency content of the PV power locally by building TCLs, while maintaining occupants’ comfort and TCLs’ physical constraints. The solution to the proposed optimization problem is achieved using optimal control strategies. Numerical results show that most of the low and medium frequency content of the PV generation can be consumed locally by building TCLs. The remaining high-frequency content of the PV generation can then be stored/offset using energy storage systems.

14 SOLAR ENERGY↗
DOE OSTI2011

Hybrid robust predictive optimization method of power system dispatch

A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Optimal mitigation and control over power system dynamics for stochastic grid resilience

Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the western system coordinating council 9-bus test system using synthetic multi-device outage scenarios.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Fast yaw optimization for wind plant wake steering using Boolean yaw angles

Abstract. In wind plants, turbines can be yawed into the wind to steer their wakes away from downstream turbines and achieve an overall increase in plant power. Mathematical optimization is typically used to determine the best yaw angles at which to operate the turbines in a plant. In this paper, we present a new heuristic to rapidly determine the yaw angles in a wind plant. In this method, we define the turbine yaw angles as Boolean – either yawed at a predefined angle or nonyawed – as opposed to the typical methods of defining yaw angles as continuous or with fine discretizations. We then optimize which turbines should be yawed with an algorithm that sweeps through the turbines from the most upstream to the most downstream. We demonstrate that our new Boolean optimization method can find turbine yaw angles that perform well compared to a traditionally used gradient-based optimizer for which the yaw angles are defined as continuous. There is less than 0.6 % difference in the optimized power between the two optimization methods for randomly placed turbine layouts and less than a 0.6 % difference in the optimal annual energy production between the two optimization methods for a real wind farm. Additionally, we show that our new method is much more computationally efficient than the traditional method. For plants with nonzero optimal yaw angles, our new method is generally able to solve for the turbine yaw angles 50–150 times faster, and in some extreme cases up to 500 times faster, than the traditional method.

17 WIND ENERGY↗