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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

SmartTransit.AI: A Dynamic Paratransit and Microtransit Application

New rideshare and shared mobility services have transformed urban mobility in recent years. Such services have the potential to improve efficiency and reduce costs by allowing users to share rides in high-capacity vehicles and vans. Most transit agencies already operate various ridepooling services, including microtransit and paratransit. However, the objectives and constraints for implementing these services vary greatly between agencies and can be challenging. First, off-the-shelf ridepooling formulations must be adapted for real-world conditions and constraints. Second, the lack of modular and reusable software makes it hard to implement and evaluate new ridepooling algorithms and approaches in real-world settings. We demonstrate a modular on-demand public transportation scheduling software for microtransit and paratransit services. The software is aimed at transit agencies looking to incorporate state-of-the-art rideshare and ridepooling algorithms in their everyday operations. We provide management software for dispatchers and mobile applications for drivers and users and conclude with results from the demonstration in Chattanooga, TN.

Pavia, Sophie↗
DOE OSTI2022

Materials Design using an Active Subspace-based Batch Bayesian Optimization Approach

Integrated computational materials engineering (ICME) calls for integrating simulation tools and/or experiments to develop new materials and materials systems. However, implementation of ICME approaches is challenging mainly due to the considerable computational expense of such frameworks and large dimensionality of the design space. Addressing these challenges is thus critical to the success of ICME initiatives. We present here a specific Bayesian optimization framework designed to address these two challenges. In particular, we propose an active subspace batch Bayesian optimization framework. The framework makes use of dimension reduction via the active subspace method and makes use of the ability to query in parallel via the batch Bayesian optimization approach. Here, the integration of these techniques leads to significant efficiency improvements while maintaining accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High Efficiency 2-Bladed Utility Wind Turbine Enhanced by CoFlow Jet Active Flow Control

The aerodynamic performance and power output of a high efficiency Co-Flow Jet (CFJ) 2-bladed Wind Turbine is studied in this paper. CFJ is a Zero-Net-Mass-Flux (ZNMF) active flow control method that dramatically increases airfoil lift coefficient and suppresses flow separation at a low energy expenditure. The 3D Reynolds Averaged Navier-Stokes (RANS) equations with one-equation Spalart-Allmaras (SA) turbulence model are solved to simulate the 3D flows of the wind turbines. The CFJ-Wind Turbine in this paper is modified from the NREL 3-bladed 3.4 MW reference wind turbine with the same RPM, blade length, distribution of chord, twist, and bending. The CFJ 2-bladed wind turbine utilizes the CFJ-NACA 64 series airfoils at most of the blade span from 31.88\% to the tip. The CFJ injection and suction slots are implemented along the full blade span to enhance the effectiveness and power output. The study shows that the 2-bladed CFJ turbine significantly increases power output compared with the 3-bladed baseline turbine at all wind speeds by 15.8\% at the wind speed of 9.8 m/s and by 25.9\% at 4 m/s respectively. The efficiency enhancement is substantially more at the low wind speed than at high wind speed. This would be very beneficial to increase the annual power output or capacity factor as wind turbines work at the speeds lower than the rated speed for most of the time. The results show that the flow field around the blade surface presents a significant enhanced suction peak near the blade leading edge, which results in a very high tangential force and thus increased wind turbine net power coefficient. Consistent with the previous study for the small NREL Phase VI research wind turbine, this paper demonstrates that CFJ 2-bladed wind turbine is an effective technology to extract more power from the wind at all speeds. This study is just an initial effort to demonstrate the advantage of the CFJ blade with no design optimization. It is believed that there is more potential to further enhance the efficiency improvement.

active flow control↗
DOE OSTI2022

Coupling a Lagrangian–Eulerian Spark-Ignition (LESI) model with LES combustion models for engine simulations

In the United States transportation sector, Light-Duty Vehicles (LDVs) are the largest energy consumers and CO 2 emitters. Electrification of LDVs is posed as a potential solution, but SI engines can still contribute to decarbonization. Car manufacturers have turned to unconventional engine operation to increase the efficiency of Spark-Ignition (SI) engines and reduce the carbon emissions of their fleets. Dilute, lean, and stratified-charge engine operation has the potential for engine efficiency improvements at the expense of increased cyclic variability and combustion instability. At such demanding engine conditions, the spark ignition event is key for flame initiation and propagation and for enhanced combustion stability. Reliable and accurate spark ignition models can help design ignition systems that reduce cyclic variability. Multiple computational spark-ignition models exist that perform well under conventional conditions, but the underlying physics needs to be expanded, for unconventional engine operation. In this paper, a hybrid Lagrangian–Eulerian Spark-Ignition (LESI) model is coupled with different turbulent flame propagation models for engine simulations. LESI relies on Lagrangian arc tracking and Eulerian energy deposition. The LESI model is coupled with the Well-Stirred Reactor (WSR), Thickened Flame Model (TFM), and g-equation model and used to simulate several cycles of a Direct-Injection Spark-Ignition (DISI) engine using a commercial Computational Fluid Dynamics (CFD) engine solver. The results showcase the successful coupling of LESI with the combustion models. Global engine metrics, such as pressure and Apparent Heat Release Rate (AHRR), for each simulation setup are compared to experimental engine results, for validation. In addition, results highlight the successful prediction of spark channel movement by comparing simulation images to experimental optical engine images. Finally, the successful coupling of LESI to combustion models, making it a usable model in the engine modeling community, is emphasized and future development details are discussed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Defining quantum-ready primitives for hybrid HPC-QC supercomputing: a case study in Hamiltonian simulation

As computational demands in scientific applications continue to rise, hybrid high-performance computing (HPC) systems integrating classical and quantum computers (HPC-QC) are emerging as a promising approach to tackling complex computational challenges. One critical area of application is Hamiltonian simulation, a fundamental task in quantum physics and other large-scale scientific domains. This paper investigates strategies for quantum-classical integration to enhance Hamiltonian simulation within hybrid supercomputing environments. By analyzing computational primitives in HPC allocations dedicated to these tasks, we identify key components in Hamiltonian simulation workflows that stand to benefit from quantum acceleration. To this end, we systematically break down the Hamiltonian simulation process into discrete computational phases, highlighting specific primitives that could be effectively offloaded to quantum processors for improved efficiency. Our empirical findings provide insights into system integration, potential offloading techniques, and the challenges of achieving seamless quantum-classical interoperability. We assess the feasibility of quantum-ready primitives within HPC workflows and discuss key barriers such as synchronization, data transfer latency, and algorithmic adaptability. These results contribute to the ongoing development of optimized hybrid solutions, advancing the role of quantum-enhanced computing in scientific research.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Stakeholder-driven carbon neutral pathways for Thailand and Bangkok: integrated assessment modeling to inform multilevel climate governance

Thailand has established a target of carbon neutrality by 2050. Reaching this goal will require coordination and collaboration between stakeholders spanning sectors and scales, including energy system decision makers, land managers, and city planners. Robust decarbonization scenarios incorporating current plans and targets, additional measures needed, and trade-offs between strategies can help stakeholders make informed decisions in the face of uncertainty. Through iterative engagement with decision makers at the city and national levels, we develop and analyze carbon neutral scenarios for Thailand that incorporate Bangkok’s role using a global integrated assessment model. We find that Thailand can reach carbon neutrality through power sector decarbonization, energy efficiency improvements, widespread electrification, and advanced technologies including carbon capture and storage and hydrogen. Negative emissions technologies will also be needed to offset Thailand and Bangkok’s hardest-to-abate CO 2 emissions. Bangkok, as a major population and economic center, contributes significantly to Thailand’s energy demand and emissions and can therefore play an important role in climate change mitigation. Accordingly, our results underscore the importance of subnational climate action in meeting Thailand’s carbon neutral goal. Our analysis also indicates that without sustained land-based carbon sequestration, much more mitigation effort will be needed in Thailand’s energy sector, including at the subnational scale, to reach carbon neutrality. These insights can help stakeholders identify priorities, consider tradeoffs, and make decisions that will impact Bangkok and Thailand’s long-term climate change mitigation potential. This analysis demonstrates how stakeholder engagement in integrated assessment modeling can facilitate and inform multilevel climate governance.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Carbon neutrality in Malaysia and Kuala Lumpur: Insights from stakeholder-driven integrated assessment modeling

Several cities in Malaysia have established plans to reduce their CO2 emissions, in addition to Malaysia submitting a Nationally Determined Contribution to reduce its carbon intensity (against GDP) by 45% in 2030 compared to 2005. Meeting these emissions reduction goals will require a joint effort between governments, industries, and corporations at different scales and across sectors. In collaboration with national and sub-national stakeholders, we developed and used a global integrated assessment model to explore emissions mitigation pathways in Malaysia and Kuala Lumpur. Guided by current climate action plans, we created a suite of scenarios to reflect uncertainties in policy ambition, level of adoption, and implementation for reaching carbon neutrality. Through iterative engagement with all parties, we refined the scenarios and focus of the analysis to best meet the stakeholders’ needs. We found that Malaysia can reduce its carbon intensity and reach carbon neutrality by 2050, and that action in Kuala Lumpur can play a significant role. Decarbonization of the power sector paired with extensive electrification, energy efficiency improvements in buildings, transportation, and industry, and the use of advanced technologies such as hydrogen and carbon capture and storage will be major drivers to mitigate emissions, with carbon dioxide removal strategies being key to eliminate residual emissions. This study highlights the participatory process in which stakeholders contributed to the development of the model and guided the analysis, as well as insights into Malaysia’s decarbonization potential and the role of multilevel governance.

cities↗
DOE OSTI2025

An Optimized H5 Hysteresis Current Control with Clamped Diodes in Transformer-Less Grid-PV Inverter

With the rise of renewable energy penetration in the grid, photovoltaic (PV) panels are connected to the grid via inverters to supply solar energy. Transformer-less grid-tied PV inverters are gaining popularity because of their improved efficiency, reduced size, and lower costs. However, they can induce a path for leakage currents between the PV and the grid due to the absence of galvanic isolation. This leads to serious electromagnetic interference, loss in efficiency, and safety concerns. The leakage current is primarily influenced by the nature of the common mode voltage (CMV), which is determined by the switching techniques of the inverter. In this paper, a novel inverter topology of Hysteresis Controlled H5 with Two Clamping Diodes (HCH5-D2) is derived. The HCH5-D2 topology helps decouple the AC part (Grid) and DC part (PV) during the freewheeling period to make the CMV constant, thereby reducing the leakage current. Additionally, the extra diodes help reduce voltage spikes generated during the freewheeling period and maintain the CMV at a constant value. Finally, a 2.2 kW grid-connected single-phase HCH5-D2 PV inverter system’s MATLAB simulation is presented, showing better results compared to a traditional H4 inverter.

42 ENGINEERING↗
DOE OSTI2022

Adoption Pathways for DC Power Distribution in Buildings

Driven by the proliferation of DC energy sources and DC end-use devices (e.g., photovoltaics, battery storage, solid-state lighting, and consumer electronics), DC power distribution in buildings has recently emerged as a path to improved efficiency, resilience, and cost savings in the transitioning building sector. Despite these important benefits, there are several technological and market barriers impeding the development of DC distribution, which have kept this technology at the demonstration phase. This paper identifies specific end-use cases for which DC distribution in buildings is viable today. We evaluate their technology and market readiness, as well as their efficiency, cost, and resiliency benefits while addressing implementation barriers. The paper starts with a technology review, followed by a comprehensive market assessment, in which we analyze DC distribution field deployments and their end-use characteristics. We also conduct a survey of DC power and building professionals through on-site visits and phone interviews and summarize lessons learned and recommendations. In addition, the paper includes a novel efficiency analysis, in which we quantify energy savings from DC distribution for different end-use categories. Based on our findings, we present specific adoption pathways for DC in buildings that can be implemented today, and for each pathway we identify challenges and offer recommendations for the research and building community.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A Theoretical Open Architecture Framework and Technology Stack for Digital Twins in Energy Sector Applications

Digital twin is often viewed as a technology that can assist engineers and researchers make data-driven system and network-level decisions. Across the scientific literature, digital twins have been consistently theorized as a strong solution to facilitate proactive discovery of system failures, system and network efficiency improvement, system and network operation optimization, among others. With their strong affinity to the industrial metaverse concept, digital twins have the potential to offer high-value propositions that are unique to the energy sector stakeholders to realize the true potential of physical and digital convergence and pertinent sustainability goals. Although the technology has been known for a long time in theory, its practical real-world applications have been so far limited, nevertheless with tremendous growth projections. In the energy sector, there have been theoretical and lab-level experimental analysis of digital twins but few of those experiments resulted in real-world deployments. There may be many contributing factors to any friction associated with real-world scalable deployment in the energy sector such as cost, regulatory, and compliance requirements, and measurable and comparable methods to evaluate performance and return on investment. Those factors can be potentially addressed if the digital twin applications are built on the foundations of a scalable and interoperable framework that can drive a digital twin application across the project lifecycle: from ideation to theoretical deep dive to proof of concept to large-scale experiment to real-world deployment at scale. This paper is an attempt to define a digital twin open architecture framework that comprises a digital twin technology stack (D-Arc) coupled with information flow, sequence, and object diagrams. Those artifacts can be used by energy sector engineers and researchers to use any digital twin platform to drive research and engineering. This paper also provides critical details related to cybersecurity aspects, data management processes, and relevant energy sector use cases.

Gourisetti, Sri, Nikhil Gupta (ORCID:0000000188778↗
DOE OSTI2023

Impact of Biofuel Blending on Hydrocarbon Speciation and Particulate Matter from a Medium-Duty Multimode Combustion Strategy

The U.S. Department of Energy’s Co-Optima initiative simultaneous focused on diversifying fuel sources, improving efficiency, and reducing emissions through using novel combustion strategies and sustainable fuel blends. For medium-duty/heavy-duty diesel engines, research in this area has led to the development of a multimode strategy that uses premixed charge compression ignition (PCCI) at low loads and conventional diesel combustion (CDC) at mid–high loads. The aim of this study was to understand how emissions were impacted when using PCCI instead of CDC at low loads and switching to an oxygenated biofuel blend. It provides a detailed speciation of the hydrocarbon (HC) and particulate matter (PM) emissions from a multimode medium-duty engine operating at low loads in PCCI and CDC modes and high loads in CDC. The effect of the oxygenated biofuel blend on emissions was studied at all three mode–load conditions using #2 ULSD and a bio-derived fuel (25% hexyl hexanoate (HHN)) blended in #2 ULSD. The PCCI mode effectively decreased NOx, total HC, and PM/PN emissions, with a substantial decrease in larger particles (≥50 nm). A PM/PN reduction was observed at high loads with the 25% HHN fuel. While the total HC emissions were not impacted by fuel type, the detailed HC analysis exposed changes in the HC’s composition.

09 BIOMASS FUELS↗
DOE OSTI2023

Gold Nanoparticles AuNP Decorated on Fused Graphene-like Materials for Application in a Hydrogen Generation

The search for a sustainable, alternative fuel source to replace fossil fuels has led to an increased interest in hydrogen fuel. This combustible gas is not only clean-burning but can readily be produced via the hydrolysis of sodium borohydride. The main drawback of this reaction is that the reaction occurs relatively slowly and requires a catalyst to improve efficiency. This study explored a novel composite material made by combining gold nanoparticles and fused graphene-like materials (AuFGLM) as a catalyst for generating hydrogen via sodium borohydride. The novel fused graphene-like material (FGLM) was made with a sustainable dextrose solution and by using a pressure-processing method. Imaging techniques showed that FGLM appears to be an effective support template for nanoparticles. Transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and Raman spectroscopy were used to characterize and determine the size, shape, and structure of nanoparticles and composites. The TEM study characterized the fused carbon backbone as it began to take on a rounder shape. The TEM images also revealed that the average diameter of the gold nanoparticle was roughly 23 nm. The FTIR study confirmed O-H, C-C, and C=O as functional groups in the materials. The EDS analysis showed that the composite contained approximately 6.3% gold by weight. The crystal structures of FGLM and AuFGLM were identified via P-XRD analysis. Various reaction conditions were used to test the catalytic ability of AuFGLM, including various solution pHs, temperatures, and doses of NaBH 4 . It was observed that optimal reaction conditions included high temperature, an acidic solution pH, and a higher dose of NaBH 4 . The activation energy of the reaction was determined to be 45.5 kJ mol -1 , and it was found that the catalyst could be used multiple times in a row with an increased volume of hydrogen produced in ensuing trials. The activation energy of this novel catalyst is competitive compared to similar catalysts and its ability to produce hydrogen over multiple uses makes the material an exciting choice for catalyzing the hydrolysis of NaBH 4 for use as a hydrogen fuel source.

08 HYDROGEN↗
DOE OSTI2022

Field Measurement of Central CO2 Heat Pump Water Heater for Multifamily Retrofit

Domestic hot water heating of multifamily buildings accounts for a substantial portion of the energy load of existing buildings. This load is made up of both the energy required to produce hot water and the energy needed to maintain the temperature of the heated water within a building’s distribution piping so that heat can be promptly delivered to building occupants as needed. Properly designed heat pump water heater (HPWH) systems have the ability to improve efficiency in both water heating and temperature control operations. Further, CO2 heat pump technology reflects a shift away from traditional refrigerants and toward refrigerants with low global warming potential (GWP). In this paper’s case study, a design consisting of multiple CO2 heat pump water heaters (commonly used in single-family homes) with a novel “swing tank” was proposed to meet the demand for domestic hot water heating and recirculation loop temperature maintenance. The proposed design was applied to the retrofit of a 60-unit, low-rise, multi-family building located in the Pacific Northwest of the United States. The purpose of this paper is to verify the performance of the system including the proposed “swing tank” in a centralized SHW system using CO2 HPWH. It also provides practical information and lessons learned from the retrofit project. Long-term monitoring data showed that the system had a coefficient of performance (COP) of three or greater and provided an average of 20 gallons of hot water per day per apartment. The results of this work indicate that residential-scale CO2 HPWH equipment and a “swing tank” design can efficiently provide domestic hot water heating and temperature maintenance for mid-sized multifamily buildings.

Banks, Adria↗
DOE OSTI2020

Knock Mitigation Effectiveness of EGR across the Pressure-Temperature Domain

Exhaust gas recirculation (EGR) has been shown to enable efficiency improvements in SI engines through multiple different mechanisms, including decreasing the knock propensity at high load, which allows higher compression ratio. While many of the benefits of EGR are applicable to both low and high power density engines, including reductions in pumping work and improved specific heat ratio, the knock benefits and corresponding compression ratio increases have been limited to low power density naturally aspirated engines primarily intended for hybrid vehicle architectures. An earlier study [1] indicated that there may be a kinetic limitation for the ability of EGR to mitigate knock under these conditions, but that study only considered a small number of conditions. In this investigation, we expand on that study while also providing data for model validation for the new light-duty combustion consortium from the U.S. Department of Energy: Partnership for Advancing Combustion Engines (PACE). In this investigation, the effectiveness of EGR to mitigate knock is studied with regards to the effect of engine speed (1,500 and 3,000 rpm), changing trajectory in the pressure-temperature domain by varying the intake manifold temperature (35, 60, and 90 deg C), and by considering the effect of minor species by studying the effect of untreated EGR vs. EGR that has been treated by an automotive three-way catalyst. Additionally, to increase the relevance of these data for future modeling studies, the performance of the full boiling range gasoline was compared relative to a surrogate formulation. The study found that the fuel surrogate performs well, confirmed the kinetic limitations of EGR to mitigate knock under boost, and showed improvements in EGR performance with catalyzed EGR.

42 ENGINEERING↗
DOE OSTI2022

Low Temperature Combustion Exploration with Negative Valve Overlap

Progressively stringent emission regulations and increasing regulatory demands on fuel economy have led to advanced combustion development. Low temperature combustion (LTC), specifically homogenous charge compression ignition (HCCI), is a promising technology for reducing exhaust emissions and improving efficiency. However, its operating range is limited to low load without boosting and EGR, due to low volumetric efficiency and high pressure rise rates. In addition, effectively controlling the combustion phasing is another challenge in realizing the associated combustion gains. In this work, advanced valve control mechanisms known as continuously variable valve duration (CVVD) and continuously variable valve timing (CVVT) were used for both intake and exhaust valvetrains to enable negative valve overlap (NVO) for trapping hot exhaust residuals and to promote multipoint simultaneous ignition. Heat release phasing was controlled by varying the fueling scheme and by adjusting the amount of NVO. Parametric studies on valve timing and duration, fueling strategy, lambda, spark assist, etc., were carried out first. Afterwards the LTC strategy was proposed and then LTC operation was explored at different engine speeds. Various approaches for extending load limits were summarized and discussed. Finally, combustion performance was compared to that of spark ignition combustion, demonstrating the combustion gains of LTC.

02 PETROLEUM↗
DOE OSTI2026

Techno-Economic Evaluation of Electrified Vehicle Options in Drayage Fleets

The electrification of drayage fleets offers potential economic and operational benefits, but the financial viability of electrified vehicles remains sensitive to battery cost, energy price, and fleet usage patterns. While total cost of ownership (TCO) is a useful benchmark, fleet operators and investors are equally concerned with investment performance metrics such as payback period (PB) and Internal Rate of Return (IRR), which better reflect financial risks and investment return timelines. This study develops a unified techno-economic framework that jointly evaluates TCO, PB, and IRR to determine when electrified trucks become cost-effective alternatives to diesel trucks. Building on a previously developed cost modeling tool and using real-world telematics data from a Class 8 drayage fleet at the Port of Savannah, the analysis incorporates projected battery cost trajectories, electricity and diesel price trends, vehicle efficiency improvements, and multiple battery capacities. Parameter ranges reflect widely cited projections and observed drayage-duty-cycle variability. A surrogate-modeling method approximates economic performance across thousands of battery cost–electricity price combinations, enabling high-resolution identification of conditions that achieve TCO parity, acceptable PB thresholds, and target IRR levels. Additionally, the study estimates the evolving share of the fleet that can feasibly electrify over time under multiple economic metrics. This integrated framework offers a novel, data-driven approach to inform risk-aware decision-making for fleet electrification and supports investment planning under evolving cost and operational conditions.

Sun, Ruixiao [ORNL] (ORCID:0000000341768676)↗
DOE OSTI2025

Artificial Intelligence for Smart Transportation

There are more than 7,000 public transit agencies in the U.S. (and many more private agencies), and together, they are responsible for serving 60 billion passenger miles each year. A well-functioning transit system fosters the growth and expansion of businesses, distributes social and economic benefits, and links the capabilities of community members, thereby enhancing what they can accomplish as a society. Since affordable public transit services are the backbones of many communities, this work investigates ways in which Artificial Intelligence (AI) can improve efficiency and increase utilization from the perspective of transit agencies. This book chapter discusses the primary requirements, objectives, and challenges related to the design of AI-driven smart transportation systems. We focus on three major topics. First, we discuss data sources and data. Second, we provide an overview of how AI can aid decision-making with a focus on transportation. Lastly, we discuss computational problems in the transportation domain and AI approaches to these problems.

Wilbur, Michael↗
DOE OSTI2023

Grand challenges in the digitalisation of wind energy

The availability of large amounts of data is starting to impact how the wind energy community works. From turbine design to plant layout, construction, commissioning, and maintenance and operations, new processes and business models are springing up. This is the process of digitalisation, and it promises improved efficiency and greater insight, ultimately leading to increased energy capture and significant savings for wind plant operators, thus reducing the levelised cost of energy. Digitalisation is also impacting research, where it is both easing and speeding up collaboration, as well as making research results more accessible. This is the basis for innovations that can be taken up by end users. But digitalisation faces barriers. This paper uses a literature survey and the results from an expert elicitation to identify three common industry-wide barriers to the digitalisation of wind energy. Comparison with other networked industries and past and ongoing initiatives to foster digitalisation show that these barriers can only be overcome by wide-reaching strategic efforts, and so we see these as “grand challenges” in the digitalisation of wind energy. They are, first, creating FAIR data frameworks; secondly, connecting people and data to foster innovation; and finally, enabling collaboration and competition between organisations. The grand challenges in the digitalisation of wind energy thus include a mix of technical, cultural, and business aspects that will need collaboration between businesses, academia, and government to solve. Working to mitigate them is the beginning of a dynamic process that will position wind energy as an essential part of a global clean energy future.

17 WIND ENERGY↗