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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Ensemble Learning Based Convex Approximation of Three-Phase Power Flow

Though the convex optimization has been widely used in power systems, it still cannot guarantee to yield a tight (accurate) solution to some problems. To mitigate this issue, this paper proposes an ensemble learning based convex approximation for alternating current (AC) power flow equations that differs from the existing convex relaxations. The proposed approach is based on three-phase quadratic power flow equations in rectangular coordinates. To develop this data-driven convex approximation of power flows, the polynomial regression (PR) is first deployed as a basic learner to fit convex relationships between the independent and dependent variables. Then, ensemble learning algorithms such as gradient boosting (GB) and bagging are introduced to combine learners to boost model performance. Based on the learned convex approximation of power flow, optimal power flow (OPF) is formulated as a convex quadratic programming problem. The simulation results on IEEE standard cases of both balanced and unbalanced systems show that, in the context of solving OPF, the proposed data-driven convex approximation outperforms the conventional semi-definite programming (SDP) relaxation in both accuracy and computational efficiency, especially in the cases that the conventional SDP relaxation fails

Convex approximation↗
DOE OSTI2021

Hybrid Analytics Solution to Improve Coal Power Plant Operations

This project focused on developing advanced methods for thermal performance monitoring of a coal-fueled power plant. The specific goal was to develop and demonstrate a new thermal performance monitoring approach using a hybrid model that integrates a physics-based heat balance model with a machine learning-based pattern recognition model. The hybrid model enables increased accuracy and scope of the thermal analysis and an improved ability to monitor and detect changes in plant operation. This new approach takes full advantage of the individual model capabilities and creates an important new set of capabilities not previously possible using the two types of models separately. Using the heat balance model, a rich set of derived parameters (virtual sensors) are calculated from the measured plant operating data at each time point. The combined measured and derived data values are used by machine learning algorithms to create pattern recognition models over the range of normal unit operation. To create the monitoring models, historical data from normal operation of the plant is first processed by the heat balance model to compute the derived parameter data. The result is a greatly expanded set of normal operating data that can be used as input to create the pattern recognition model. Once the models are calibrated for normal operation, the hybrid model is suitable for use in continuous online monitoring. During online monitoring, new plant operating data is processed first by the heat balance model and then by the pattern recognition model. Results from the pattern recognition model quantify the deviation of each measured or derived parameter from its expected value in normal operation. The hybrid models can detect abnormal changes in plant operating data with very high accuracy and sensitivity. When abnormal behavior is detected, alerts are generated automatically for evaluation by the plant monitoring staff. The new hybrid solution product was developed and verified in the performance of the project. The hybrid solution was tested first in a simulation environment that mimicked the plant data systems and infrastructure used by U.S. power generating plants and utilities. The hybrid solution was then deployed for real-time, online monitoring of an operating coal-fueled power plant at a field test site. Field testing demonstrated that all hybrid solution development objectives were accomplished. The project work was based on combining the capabilities of two existing software products to create the new hybrid solution product. One of these was the existing MapEx® heat balance product and the other was the existing SureSense® advanced pattern recognition product. Each of these separate products was assessed to be at a Technology Readiness Level (TRL) of 9 at the start of the effort. The hybrid solution product was assessed to be at a TRL of 2 at the start of the project based on early feasibility work by the project team. At completion of the field testing performed in the project, the hybrid solution product was assessed to be at a TRL of 7. The project team expects that the hybrid solution product will be deployed commercially and will achieve a TRL of 9 within one year after completion of the project.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Design and optimization of flexible decoupled high-temperature gas-cooled reactor plants with thermal energy storage

Advanced nuclear power plants are well-positioned for future zero-carbon grids, however, the need for flexible power generation will be required over the traditional emphasis on baseload generation for meeting historical demands. To achieve such flexibility, this work examines viable configurations for coupling nuclear energy production with thermal energy storage. Previous designs on nuclear-thermal energy storage configurations for advanced reactor designs, which utilized reactor steam as the heat source for charging the thermal energy storage, are restricted by the heat diversion ratio and efficiency losses, thus their impacts can be limited. In this context, this study proposes configurations for fully decoupling the nuclear reactor from the power cycle and positioning the storage as an intermediate loop, thereby achieving an unconstrained heat diversion ratio and improved efficiency. Compared with a standard high-temperature gas-cooled reactor’s power cycle, steady-state thermodynamic modeling and dispatch optimizations quantify the benefits of a steam reheat cycle within the fully decoupled thermal energy system to separate the plant cycle from the high-pressure primary side. These benefits are further detailed, compatible with required high-temperature and high-pressure conditions, through (1) open-source dynamic transient models that examine the impact of off-design operation on the systems, (2) the investigation of components design and costing and finally (3) sizing and dispatch optimization. The fully-decoupled design achieves a cycle efficiency of 43.1%, an enhancement over the vendor’s standard efficiency of 42.2% (Xe-100 design). Here, the proposed design offers strengthened physical barriers from the nuclear island as well as superior operational flexibility and power boosting. Dispatch optimization and market analysis reveal that thermal energy storage size is highly dependent on the peak patterns of electricity prices and the minimum generation level constraint imposed on the balance of plant. Evaluation of off-design operation demonstrates that the full decoupling design with the suggested fail-safe control mechanisms ensures a minimal impact on reactor parameters, even during rapid power ramping.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

A resource adequacy assessment of correlated wide-area outages in the power grid

As the power grid is undergoing rapid transformations, numerous questions are emerging about its vulnerability to wide-area extreme events (WAEE), which could influence its operations. Relatively few analyses have been conducted to date regarding the impact of correlated outages during WAEEs on the grid’s ability to balance resources with demand. This study addresses this gap by conducting a resource adequacy analysis for a hurricane-inspired WAEE on a 2035 synthetic power grid system for the United States. A sensitivity analysis was also conducted to characterize the relative impact of weather on unserved energy. Our results indicate that although the magnitude and duration of the shortfalls vary depending on weather conditions, persistent shortfalls are observed in some regions. Initial explorations indicate a strong correlation between transmission-constrained regions and regions with persistent shortfalls. Future work could generate empirically-grounded representations for generator outages as well as conduct causal analyses of these shortfalls to improve understanding of drivers as well as possible mitigation strategies. Continued exploration of extreme weather impacts on the grid is important to develop more robust understanding of the reliability and resilience of our power systems, especially as they undergo rapid transformations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Multiphysics Modeling of Microreactors with NEAMS codes, and Validation Based on KRUSTY Reactivity Insertion

The NEAMS Multiphysics Applications team continues to assess code usability and functionality for microreactor design and safety analyses, while demonstrating that NEAMS tools capture both steady-state and transient behavior across distinct microreactor concepts. In FY2025, the team advanced full-core, high-fidelity, multiphysics models that solve more complex problems and strengthen verification/validation for several microreactor systems: heat-pipe microreactor (HPMR), gas-cooled microreactor (GCMR), and the KRUSTY experiment. These models employ the MOOSE MultiApp/Transfers architecture with Griffin for neutronics, BISON for heat conduction/thermomechanics, Sockeye for heat pipes, SAM/THM for coolant channels and loops, and SWIFT for hydride behavior, with meshes generated via the MOOSE Reactor Module. The graphite models available in the Grizzly code were also investigated for future analyses. For the HPMR, a Na-HPMR variant was constructed to align with recently validated heat-pipe experiments and Sockeye’s LCVF capability, enabling mechanistic heat-pipe transients and startup modeling. The Na-HPMR will serve as the primary model for HPMR investigations in upcoming tasks. The load-following and single heat-pipe failure scenarios (Griffin/BISON/Sockeye), which were previously modeled for the K-HPMR, were replicated for the Na-HPMR, showing strong negative temperature feedback and highly localized thermal effects, respectively, while the startup case captured vapor-front progression and heat-removal activation. Solid mechanics was added to the previously built K-HPMR full-core model in BISON, showing minimal impact on steady-state reactivity yet enabling stress-field predictions that prepare the path for full-core TRISO performance analyses. For the GCMR, automated steady-state and four transient scenarios were executed using Griffin/BISON/SAM/SWIFT. Results confirm robust inherent safety: power collapses promptly in loss-of-cooling events, the inlet-temperature drop settles to a new equilibrium, and a single-channel blockage yields only a ~30 K local fuel-temperature rise with <0.4% power decrease. SWIFT-predicted hydrogen redistribution affects reactivity during both steady-state and transient conditions, underscoring its importance. A Brayton-cycle balance of plant (BOP) model in SAM/THM demonstrated stable startup behavior, and xenon-driven reactivity during load following was analyzed. To improve TRISO-compact temperature fidelity, a fast multiscale Heat Source Decomposition (HSD) treatment was implemented. Against heterogeneous benchmarks, HSD reduces underprediction of kernel temperatures and lowers predicted peak powers in reactivity-insertion transients compared to previous homogenized models. KRUSTY warm-critical validation progressed from FY2024 baselines: the 15Ȼ insertion shows excellent agreement in peak power (~2% high) and temperature trends, and the 30Ȼ case was automated via a feedback controller that maintained power near 3 kW for ~150 s with close agreement to data. The successful modeling of the warm critical tests has laid a strong foundation for simulating more complex nuclear system tests in the years ahead. Throughout FY2025, developer feedback was provided (e.g., MOOSE batch mesh generation, distributed pre-split meshes, Griffin sweeper on displaced meshes), several new models were contributed to the Virtual Test Bed, and an OECD-NEA WPRS multiphysics benchmark based on the HPMR was initiated to enable broader cross-comparison and best-practice development with the nuclear community at large.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Hybrid Analytics Solution for Power Plant Operations

Expert Microsystems, Inc., MapEx Software Inc. and XMPLR Energy LLC have teamed to submit a proposal to the US Department of Energy’s Office of Fossil Energy to improve the efficiency, reliability and flexibility of existing coal-based power plants. The project, titled Hybrid Analytics Solution to Improve Coal Power Plant Operations (the “Hybrid Analytics” project), will develop, demonstrate and commercialize a novel approach that integrates two proven real-time monitoring techniques. The Hybrid Analytics approach integrates into a single, integrated solution: a) an established, advanced data-driven analytics solution that includes artificial intelligence, advanced pattern recognition and machine-learning techniques and b) a well-proven, first principle thermal heat balance model solution. The future role of coal plants will depend on the ability to cycle and follow loads to meet marginal power demands, accommodate renewables and support the grid. Essential to success in this new role is a plant’s ability to maintain high reliability, efficiency and flexibility. However, these changing operational demands put significant stresses on power plant components that directly impact the ability to deliver these requirements. In the past, plants have independently monitored performance using physics-based solutions (heat rate, boiler losses, etc.) and reliability using data-driven analytics (advanced pattern recognition). The Hybrid Analytics solution integrates both approaches to enhance fault detection, provide automated diagnostics and estimates of remaining time to act, and provide critical, enhanced and accurate real-time information to coal plant operators. As a result, coal plants can improve efficiency, reliability, and flexibility and can cost-effectively maintain their key role in the power delivery system.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Midwest Nuclear-based Net-Zero Carbon Steelmaking Demonstration

Globally, the iron and steel industry accounts for around a quarter of GHG emissions from the manufacturing sector , which is about 7% of the 33 gigatonnes (Gt) of global CO 2 emissions . Thus, globally, the steel industry is a 2-3 Gt CO 2 per year emissions challenge. The steel industry is important to the U.S. economy with output equal to $0.5 trillion and domestic production capacity is critical to national defense, infrastructure, energy production, and transportation. President Biden’s executive order on climate identifies actions and policies to put the Nation on a path to achieve net-zero carbon emissions, economy-wide, by no later than 2050. To achieve this, deep carbon reductions in the power, transportation, buildings and capital-intensive industrial manufacturing segments such as steel, cement and chemicals need to be addressed. In its recent “Accelerating Decarbonization of the U.S. Energy System” report , the National Academy of Sciences (NAS) stated that, “while technology exists to decarbonize all parts of the energy system, some sectors remain at precommercial or first-of-a-kind demonstration stages and require significant improvement in cost and performance to become commercially viable.” The NAS goes on to state that these hard to decarbonize sectors include “aviation, shipping, and industrial subsectors such as steel, cement, and chemicals manufacturing .” The Administration has proposed a timeline to decarbonize energy, transportation and then industry and manufacturing. From a life-cycle approach, decarbonizing steel and other large industrial inputs are necessary to decarbonize transformations in energy and transportation. DOE’s TRI-Lab Consortium’s Integrated Energy Systems (IES) program is a collaboration amongst DOE’s three applied energy laboratories: the National Energy Technology Laboratory; National Renewable Energy Laboratory and Idaho National Laboratory. The IES approach looks at more tightly integrating low-carbon nuclear energy, renewable electricity, energy storage, load/demand balancing, and biomass (including plastics and other wastes) with one or more industrial processes that utilize heat and/or power from these clean and waste energy sources to produce a low-carbon commodity-scale product.

08 HYDROGEN↗
DOE OSTI2020

Evaluating the Potential for Tidal Phase Diversity to Produce Smoother Power Profiles

Although tidal energy conversion technologies are not yet commercially available or cost-competitive with other renewable energy technologies like wind turbines and solar panels, tides are a highly predictable resource. Tidal energy’s predictability indicates that the resource could introduce less volatility into balancing the electric grid when compared to other renewables, a fundamentally desirable attribute for the electric system. More specifically, tidal energy resources are unique in that they have the potential to produce relatively smoother power profiles over time through aggregation. In order to generate smooth power profiles from tidal resources, sufficient complexity within the timing of tides is necessary within electrical proximity. This study evaluates the concept of aggregating diverse tides for the purpose of reducing periods of no and low energy production and creating smoother power profiles in regions around Alaska and Washington by calculating cross-correlations of tidal current velocity time series. Ultimately, study results show limited potential to exploit the resources for this purpose and describe the institutional mechanisms necessary to realize the benefits in practice.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Per-Phase Control for CHB Converters with Negative-Sequence Current and DC Voltage Balancing Control

This paper presents a per-phase controller for a grid-connected Cascaded H-Bridge (CHB) converter featuring negative sequence current regulation and DC bus voltage balancing capabilities. Unlike conventional three-phase controllers, each phase of the CHB can be separately and controlled to regulate the DC voltage and reactive power flow. per-phase negative sequence current control strategy is incorporated into the proposed controller to ensure compliance with IEEE Standard 2800-2022, which requires the absorption of negative-sequence reactive current during grid voltage disturbances. Furthermore, a feed-forward control-based DC bus voltage balancing method is employed, which eliminates the need for the integrator commonly used in traditional approaches. The performance of the proposed controller is validated under various unbalanced grid scenarios and DC bus voltage imbalances through electromagnetic transient (EMT) simulation using a three-phase, three-level grid-connected CHB–Dual Active Bridge (DAB) converter testbed developed on MATLAB/Simulink. Additionally, the performance of the negative-sequence current regulation is investigated through simulation under different unbalanced grid voltage scenarios.

negative sequence current↗
DOE OSTI2020

A Tradeoff Analysis of Series / Parallel Three-Phase Converter Topologies for Wireless Extreme Chargers

In this paper, extreme fast charging (XFC) technology is studied considering the charge rates of 300 kW for wireless power transfer (WPT) applications. Tradeoff analysis of series and parallel connection of three-phase WPT system are presented by comparisons of voltage and current stresses on power electronics active / passive components. In addition, star (Y) / delta (Δ) connection configurations for three-phase wireless power transfer coupling coils are analyzed with series and LCC resonant compensation circuits. The system series and parallel connection controllability is also reviewed considering voltage and current balance techniques with output control. In a conclusion of evaluation analysis, it is revealed that each component of 300 kW wireless charging network must be designed for high fast charging system and the overall system operation need to be strategically planned for high power charging and infrastructure deployment.

Asa, Erdem↗
NASA NTRS1973

Intelligibility improvement of analog communication systems using an amplitude control technique.

An amplitude control technique has been employed for use with analog voice communication systems, which improves low-level phoneme reception and eliminates the received noise between words and syllables. Tests were conducted on a narrow-band frequency-modulation simplex voice communication channel employing the amplitude control technique. Presented for both the modified rhyme word tests and the phonetically balanced word tests are a series of graphical plots of the tests' score distribution, mean, and standard deviation as a function of received carrier-to-noise power density ratio. At low received carrier-to-noise power density ratios, a significant improvement in the intelligibility was obtained. A voice intelligibility improvement of more than 2 dB was obtained for the modified rhyme test words, and a voice intelligibility improvement in excess of 4 dB was obtained for the phonetically balanced word tests.

Wishna, S.↗
NASA NTRS1993

Miniature Long-life Space Cryocoolers

TRW has designed, built, and tested a miniature integral Stirling cooler and a miniature pulse tube cooler intended for long-life space application. Both efficient, low-vibration coolers were developed for cooling IR sensors to temperatures as low as 50 K on lightsats. The vibrationally balanced nonwearing design Stirling cooler incorporates clearance seals maintained by flexure springs for both the compressor and the drive displacer. The design achieved its performance goal of 0.25 W at 65 K for an input power to the compressor of 12 W. The cooler recently passed launch vibration tests prior to its entry into an extended life test and its first scheduled flight in 1995. The vibrationally balanced, miniature pulse tube cooler intended for a 10-year long-life space application incorporates a flexure bearing compressor vibrationally balanced by a motor-controlled balancer and a completely passive pulse tube cold head.

Tward, E.↗
NASA NTRSDate not supplied

New Developments in Retropropulsion Testing for Mars Entry, Descent and Landing

NASA’s plans for landing human-scale payloads on Mars in the next decade require that retrorockets be used to decelerate the atmospheric entry vehicle continuously from supersonic conditions through soft touchdown. Conventional Mars entry vehicle architectures that include a single parachute for supersonic-to-subsonic descent are not scalable to the sizes needed to land humans on Mars (~20 metric tons). The major aerosciences risks are the uncertainties in predicting aerodynamic stability and performance during powered free-flight and landing. These risks are influenced partially by current limitations in relevant data and testing methods. Consequently, trajectory simulations currently depend on unvalidated powered descent and landing aerodynamics models. NASA engineers have identified gaps in testing methods that, if addressed, would improve the ability to validate these models. There are gaps in capabilities to test multi-engine hot-gas retropropulsion systems in US wind tunnels. This is partially due to the successful use of parachutes as decelerators for human spaceflight at Earth and for the entire Mars lander program to date. Retropulsion test data historically and to this day are limited to using high pressure air jets, at comparatively low temperatures,as engine plume simulants on subscale wind tunnel models. Additionally, the ability to directly measure aerodynamic interference force and moments is limited by existing flow-through balance capabilities. This paper briefly covers historical and recent test data, and identifies new ground test techniques as a means to provide more relevant test data for powered flight and landing aerodynamic model validation.These techniques include using heated inert gases as a substitute for combustion products, additively manufactured 6-component flow-through force and moment balances, and off-body quantitative diagnostic measurements.

Retropropulsion↗
DOE OSTI2026

Design of a SMART Valve Testbed for Nuclear Thermal Dispatch

By the year 2050, the United States aims to achieve net-zero carbon emissions. To achieve this target, the licensing of the Light Water Reactor (LWR) fleet has been extended for 20 more years. To stay economically competitive with other power sources such as renewable and fossil-fuel power plants, the U.S. Department of Energy has introduced a plan to modernize the existing LWR fleet and diversify the revenue stream. One of the plans is to dispatch thermal energy to endothermic industrial processes. SMART valves will play an important role in this initiative by efficiently balancing the load by regulating valves in a coordinated manner while monitoring the thermal-hydraulic systems to enhance safety and maintain the integrity of the power plant. This research aims to develop a facility to test the coordinated control algorithm and produce various test results for training the monitoring system. The constructed facility is capable of simulating various operational and accidental scenarios by coordinating all the valves (positions) and pump (flowrate). The facility is developed with an Internet of Things (IoT)-based custom system and a python-based valve position control and coordination mechanism. It has achieved stable sensor outputs, pump control, and coordinated valve regulation in all three valves with minimum obstruction in the system.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Balancing Doses of EL222 and Light Improves Optogenetic Induction of Protein Production in Komagataella phaffii

ABSTRACT Komagataella phaffii, also known asPichia pastoris, is a powerful host for recombinant protein production, in part due to its exceptionally strong and tightly controlled P AOX1 promoter. MostK. phaffiibioprocesses for recombinant protein production rely on P AOX1 to achieve dynamic control in two‐phase processes. Cells are first grown under conditions that repress P AOX1 (growth phase), followed by methanol‐induced recombinant protein expression (production phase). In this study, we propose a methanol‐free approach for dynamic metabolic control inK. phaffiiusing optogenetics, which can help enhance input tunability and flexibility in process optimization and control. The light‐responsive transcription factor EL222 fromErythrobacter litoralisis used to regulate protein production from the P C120 promoter inK. phaffiiwith blue light. We used two system designs to explore the advantages and disadvantages of coupling or decoupling EL222 integration with that of the gene of interest. We investigate the relationship between EL222 gene copy number and light dosage to improve production efficiency for intracellular and secreted proteins. Experiments in lab‐scale bioreactors demonstrate the feasibility of the outlined optogenetic systems as potential alternatives to conventional methanol‐inducible bioprocesses usingK. phaffii.

Biotechnology & Applied Microbiology↗
DOE OSTI2020

The Minos Computing Library: Efficient Parallel Programming for Extremely Heterogeneous Systems

Hardware specialization has become the silver bullet to achieve efficient high performance, from Systems-on-Chip systems, where hardware specialization can be ``extreme'', to large-scale HPC systems. As the complexity of the systems increases, so does the complexity of programming such architectures in a portable way. This work introduces the Minos Computing Library (MCL), as system software, programming model, and programming model runtime that facilitate programming extremely heterogeneous systems. MCL supports the execution of several multi-threaded applications within the same compute node, performs asynchronous execution of application tasks, efficiently balances computation across hardware resources, and provides performance portability. We show that code developed on a personal desktop automatically scales up to fully utilize powerful workstations with 8 GPUs and down to power-efficient embedded systems. MCL provides up to 17.5x speedup over OpenCL on NVIDIA DGX-1 systems and up to 1.88x speedup on single-GPU systems. In multi-application workloads, MCL dynamically resource allocation provides up to 2.43x performance improvement over manual, static allocation of computing resources.

Gioiosa, Roberto↗
DOE OSTI2022

Temporal complementarity of marine renewables with wind and solar generation: Implications for GB system benefits

Wave and tidal energy have the potential to provide benefits to power systems with high proportions of stochastic renewable generation. This is particularly applicable with wind and solar photovoltaics, as the offsetting of these renewable resources results in more reliable renewable generation. This study utilises ten metrics to quantify the temporal complementarity and supply-demand balancing requirements of the energy mix in Great Britain, to investigate the potential magnitude of these system benefits. Wave and tidal generation profiles are created using historical resource data and hydrodynamic models. The results show that the inclusion of wave and tidal generation creates a renewable energy mix which is more available under multiple conditions: throughout a year of operation; at times of peak demand; for multiple consecutive hourly time periods; and at times when wind and solar generation are not available. Three regional case studies also show that the inclusion of marine energy allows for improved regional supply-demand matching, reducing instances of energy shortage and excess and potentially relieving transmission congestion at particularly constrained locations within GB. Finally, the implications of these findings are discussed in terms of GB wholesale market operation, system balancing and system security.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

TPCPF: Three-Phase Continuation Power Flow Tool for Voltage Stability Assessment of Distribution Networks With Distributed Energy Resources

This article presents a three-phase unbalanced continuation power flow algorithm for voltage stability assessment of distribution systems with high penetration of distributed energy resources (DERs). Analyzing distribution system voltage stability with DER will allow high penetration of renewable energy necessary for the sustainability goals. The developed algorithm can analyze voltage stability for both the meshed and radial systems and the balanced and unbalanced three-phase distribution systems. The developed tool allows the voltage stability analysis to facilitate the planning, operation, control, and distribution system management. The impact of DER on the voltage stability of several test cases has been analyzed considering constant power (P Q) and regulated-voltage (P V ) modes of operation for DER units. Moreover, different voltage stability case studies are presented to demonstrate the impact of unbalance, load increment, and network topology on the maximum loading capacity. Finally, results using the IEEE 13-node feeder, the 18-bus balanced shipboard system, the 13-node CIGRE benchmark system, and the 136-bus redial distribution feeder demonstrate that the developed continuation power flow tool can efficiently perform voltage stability analysis for active distribution systems.

42 ENGINEERING↗