#WindTurbines

[peeta333]

Ok am I the only one who thinks these are just wonderful and amazing ? When I see them they make me smile and I have to shoot them!! Lol today we have #blackandwhite of the #windturbines These are new to me. I have not seen them till we went to #alberta these are located south west of #oyen on highway 570. Which much to my surprise now has cell service. That highway had nothing before. Soooo awesome. I surely enjoy seeing these. I know people hate them. But I absolutely love them! #explorealberta #winter #wind #snow #landscape #raw_country #raw_bnw #raw_canada #ipulledoverforthis #meanwhileinalberta https://www.instagram.com/p/CnV7aneu2sk/?igshid=NGJjMDIxMWI=

[deeplyeco]

How to Use Renewable Energy at Home

Imagine standing on your porch, looking up at the sky. You see the sun's power could light up your home. For many, using renewable energy is more than a trend—it's a journey to a sustainable life. It's about making choices that help our planet.Choosing renewable solutions at home means more than just saving money. It's about hope for the future and taking care of our planet. With rising electricity costs and climate change, we need clean energy solutions. This path leads to a sustainable lifestyle that can inspire others.Key Takeaways The use of renewable technology in homes is growing, thanks to reduced costs and governmental incentives. - Homeowners can choose energy providers utilizing renewable sources in deregulated markets. - Solar energy is a popular choice, with options like panels and water heaters available. - Geothermal and air source heat pumps harness external temperatures for efficient heating. Read the full article

[victoriaanisa]

More Details: Title: International Research Awards on High Energy Physics and Computational Science by ScienceFather. Website: physics.sciencefather.com Visit Our Award Nomination : https://hep-conferences.sciencefather.com/award-nomination/?ecategory=Awards&rcategory=Awardee Contact us : Physicsinquiry@sciencefather.com

[technophili]

Why AI is the Missing Link in the Renewable Energy Transition

The global AI market for clean energy is expected to exceed $75.82 billion by 2030, and the industry's confidence in this transformative technology is undeniable according to Kyotu Technology. At the moment, the energies we currently use are going to disappear, which is why we need an energy transition via solar, wind or hydraulic energy.These are the ones that will help us find sustainable, environmentally-friendly solutions. And why is it so urgent to make this transition?We don't need to tell you! We can all see how climate change is becoming more and more worrying as fossil fuel reserves run out, not to mention the fact that we're trying to reduce carbon emissions at all costs.So what can we do? What if there was a technology called artificial intelligence that could help us? And... what if there was a technology that could help operators, even just a little, to improve the energy optimization capabilities of renewable energy infrastructures?And...what if there were other technologies that are useful in 

Predictive maintenance in renewable energies

Well, we want renewable energies, we demand them, we love them, and that's normal.On the other hand, there are a few things to sort out when it comes to maintenance. According to the FDM Group ,the way we do maintenance often means that we have to do inspections all the time, or react immediately to equipment failures.All this causes unnecessary downtime, messes up the scheduling of interventions, particularly in remote areas or at sea, not to mention increasing maintenance costs.And since renewable energies don't operate continuously, because wind speeds can vary or because there's no daylight, maintenance planning becomes more complicated. So what is AI's role in predictive maintenance According to the FDM Group, these algorithms learn from historical data, identifying patterns and correlations that can indicate whether there are equipment failures about to take place.If we now switch to renewable energies, AI would be very useful when it comes to analyzing data that comes from sensors embedded in the infrastructure, past performance records and environmental factors, so as to know what problem might occur, and how this will optimize maintenance schedules. To what extent is AI-driven predictive maintenance used?In a field like solar energy, it's used to identify potential problems with photovoltaic (PV) panels. For those who don't know, photovoltaic panels are the flat surface that captures solar radiation in order to produce photovoltaic energy in the form of electricity.If AI algorithms analyze data on how well each panel is performing, we'll be able to detect anomalies such as declining efficiency or deteriorating panels, and know when maintenance is required.At least, that's what the FDM Group says. And it's relevant in the sense that it will guarantee much better energy production and extend the lifespan of solar installations.There are also wind turbines that need predictive maintenance with AI and especially wind turbines that wear out very easily and not to mention the fact that other components like bearings and gears are not what they used to be over time.According to the FDM Group, AI can tell when there will be failures by analyzing data from sensors that monitor vibration, temperature and other indicators.If operators know when this or that component is going to fail, it's a piece of cake to schedule maintenance activities as if they were anticipating everything that's going to happen, so they can make downtime as insignificant as it is improbable, but on the other hand it would make energy production so... productive.Let's turn the page and tackle hydroelectric systems, where we really need the performance of turbines and generators.So, as the FDM group would like, we really do need to avoid technical problems such as cavitation (the formation of gas and vapour bubbles in a liquid subjected to negative pressure) or imbalance,so if we let AI take the lead, it will be able to predict these kinds of headaches if, of course, we let it access past performance data as well as real-time sensor information.The real benefit here is that we could avoid costly repairs and even more unnecessary downtime.Challenges and limits: let's talk If predictive maintenance is to be effective, data must also be available in large quantities and of good quality.According to Javaid et al (2022), if AI were given data that was not accurate or unreliable to train on, I can assure you that you would find it hard to believe its predictions.So, I get the impression that it's currently a problem for operators to invest in sensors, data infrastructure and AI technologies, because without that, there's no predictive maintenance.

Energy optimization in renewable energies

The three energy sources we've already mentioned (solar, wind and hydro) are currently what's needed if we want to talk about energy that defends the cause and sustainability.However, as I said earlier, these energies don't work continuously. Wind turbines can't operate in the same way all the time, when wind speeds are constantly changing, and solar panels depend on sunlight, so when there isn't any? They stop.So these little moments mean that we have problems when it comes to matching energy supply and demand.Let me tell you about energy optimization. In a nutshell, it's a process in which we make operational parameters better, maximizing efficiency and output. And why do we talk about it? Because it's the central point between the reliability of renewable energies and their ability to compete successfully.Why is energy optimization so important?The FDM Group defines energy optimization as the art and science of maximizing the efficiency and output of renewable energy systems.It involves ensuring that energy production is aligned with demand, adapting to the fact that energies don't work all the time and that their conditions can change, and ensuring that the energy we produce meets quality standards.If we go back to our renewable energies, it's still very important to do so to cope, as I said earlier, with the fact that energies don't work continuously, so we now have other, more reliable choices and they last longer than what we're used to using if we think economically.What's more, its importance goes beyond the simple fact that it increases efficiency. According to the FDM Group, it has a direct impact on the economic viability of renewable energy projects, making them more competitive in the wider energy market.In addition, optimizing energy production contributes to the overall stability and reliability of the power grid, and thus fosters a stronger ecosystem for the integration of renewable energies.

Benchmarking AI techniques

The integration of AI techniques, including deep learning, neural networks and predictive analytics, in predictive maintenance and energy optimization, highlights their distinct strengths and applications.Deep learning Deep learning is adept at automatically learning the most relevant features from datasets, making it suitable for scenarios where manual feature engineering is difficult.According to Mansouri et al. (2021), deep learning models, in particular multi-layer neural networks, are capable of capturing complex non-linear relationships within data.Deep learning models can be computationally intensive, requiring powerful hardware and processing resources. The question is, why? Why are depp learning models so complex? In fact, it's often because we can't explain or interpret certain results, and that's what makes the decision-making process so difficult to understand.Maybe you didn't understand this part, but that's okay, just remember that deep learning is used to study a wide range of data which, let's not forget, are not eternal, and it actually comes from wind turbines, so it's easy to know when you're facing potential faults or things that are unclear or abnormal in performance, and all this by detecting subtle patterns.Image recognition tasks, such as identifying anomalies in solar panels through image analysis, illustrate the capability of deep learning in solar energy applications (Mansouri et al., 2021).Neural networksVersatile neural networks excel at recognizing complex patterns in data, making them suitable for fault detection and prognosis in predictive maintenance. According to Chen et al (2021), neural networks adapt to changing conditions, enabling them to learn continuously and adjust predictions in line with evolving data patterns.The effectiveness of neural networks is highly dependent on the quality and quantity of labeled data available for training. Neural network training can be complex and time-consuming, requiring careful tuning of hyperparameters.Neural networks are effective in fault detection applications, analyzing sensor data to identify deviations from normal turbine performance, enabling proactive maintenance. In wind energy, neural networks help predict the remaining useful life of critical components, facilitating maintenance planning (Chen et al., 2021).Predictive analysisPredictive analysis, based on statistical modeling, provides interpretable information on the factors influencing maintenance forecasts, offering transparency in decision-making.According to Sri Preethaa et al (2023), the use of statistical techniques provides a robust framework for understanding the relationships between variables and predicting future events.Predictive analysis may struggle to adapt to highly dynamic or non-linear systems, where traditional statistical models may fail to capture complex patterns. The effectiveness of predictive analysis is highly dependent on the availability of historical data, and sudden changes in operating conditions can impact on its accuracy.Predictive analysis can be applied to estimate the probability of inverter failure based on historical data and environmental conditions.In wind energy, predictive analysis can be used to efficiently schedule maintenance activities based on historical performance and weather forecasts (Sri Preethaa et al., 2023).The choice of AI technique depends on specific use cases, data characteristics and operational requirements. Deep learning and neural networks are good in scenarios where complex patterns and non-linear relationships need to be identified.Predictive analytics, with its interpretive capability and statistical modeling, may be preferred when less dynamic systems are involved and a transparent decision-making process is crucial.Challenges and opportunitiesThe fusion of AI and renewable energies has opened up new frontiers in the search for sustainable and efficient energy solutions.However, this integration comes with its own set of challenges that need to be addressed to unlock the full potential of this transformative partnership.Data security and privacyWith AI applications in renewable energy relying heavily on the collection and analysis of large amounts of data, ensuring data security and privacy has become a paramount issue. According to Shateri et al (2020), the interconnected nature of energy systems and the transmission of sensitive information pose risks that require vigilant attention.Growing dependence on interconnected devices and smart grids increases vulnerability to cyber-attacks. Malicious actors may attempt to disrupt energy infrastructures, with potential economic and environmental repercussions.Granular data collection, particularly from smart meters and sensors, raises privacy concerns (Shateri et al., 2020).Developing and implementing robust encryption methods and secure communication protocols can protect data during transmission, reducing the risk of unauthorized access.According to Seth et al. (2022), advances in privacy-preserving AI techniques such as federated learning and homomorphic encryption make it possible to extract valuable information from data without compromising privacy.Interoperability challengesThe heterogeneous nature of renewable energy systems, combined with various AI technologies, poses interoperability challenges.According to Rane (2023), the lack of standardized frameworks can hinder seamless communication between different components and systems, thus undermining the scalability and efficiency of AI applications.The coexistence of various AI models, each developed using different technologies, poses difficulties in creating interoperable systems capable of exchanging information effortlessly.The lack of universally accepted standards for data formats, communication protocols and interfaces complicates the integration of AI solutions across different renewable energy platforms (Rane, 2023).Collaborative efforts to establish industry-wide standards for AI applications in renewable energy can streamline interoperability and facilitate the exchange of information between various systems.Promoting the use of open-source platforms and tools can encourage the development of interoperable solutions, fostering a collaborative ecosystem (Rane, 2023).Difficulties of integration into existing infrastructuresIntegrating AI into existing renewable energy infrastructures poses challenges due to the need to modernize them and ensure compatibility.According to Yaqoob et al (2023), many renewable energy systems were not initially designed with AI integration in mind, making the adaptation process complex.Adapting AI solutions to older renewable energy systems, which were not initially designed to accommodate advanced technologies, requires careful planning to avoid disruption and inefficiencies.Implementing AI solutions can involve high initial costs for infrastructure upgrades, new equipment acquisition and staff training, posing financial challenges for some operators (Yaqoob et al., 2023).Phased implementation of AI solutions, starting with specific components or subsystems, enables a gradual integration process that minimizes disruption and spreads costs over time.Designing renewable energy systems with adaptability in mind makes it easier to integrate AI technologies in the future, fostering a more responsive and efficient energy infrastructure.

Opportunities for further research and development

While challenges exist, they serve as catalysts for further research and development, offering exciting opportunities to advance the application of AI in renewable energy. Key areas of opportunity include1. Developing AI-driven predictive maintenance models that can accurately anticipate equipment failures, optimize maintenance schedules and reduce downtime in renewable energy systems (Ahmad et al., 2021).2. Research into AI algorithms for real-time grid management, enabling a better balance between energy supply and demand, the integration of intermittent renewable sources and efficient energy distribution (Hannan et al., 2020).3. Investigating AI techniques to optimize energy storage systems, ensuring efficient charging and discharging cycles and maximizing the utilization of stored energy (Li et al., 2023).4. Explore AI solutions to manage decentralized energy systems, such as microgrids, to improve energy resilience, reliability and self-sufficiency (Şerban and Lytras, 2020).5. Advance AI-powered decentralized energy exchange platforms, where individuals and organizations can sell surplus energy back to the grid or trade it with each other, making clean energy more affordable according to Forbes 6. Bridge the expertise gap by encouraging collaboration between AI experts and renewable energy professionals to develop tailored solutions that meet the unique requirements of the energy sector according to Forbes.7. Improve the quality and diversity of data sources to increase the accuracy and reliability of AI-driven predictive maintenance and energy optimization models according to Forbes.8. Explore innovative techniques, such as federated learning and homomorphic encryption, to address data security and privacy concerns in the integration of AI and renewable energy (SETH ET AL., 2022).9. Develop standardized frameworks and protocols to facilitate interoperability between various AI technologies and renewable energy systems (rane, 2023).10. Design renewable energy infrastructures with inherent adaptability to enable easier integration of AI solutions in the future, creating a more responsive and efficient energy ecosystem (yaqoob et al., 2023).

Conclusion

The symbiosis between AI and renewable energies holds enormous promise for a sustainable and technologically advanced future.By harnessing the power of AI in predictive maintenance and energy optimization, the renewable energy sector can improve the reliability, efficiency and competitiveness of clean energy solutions.AI-powered tools, combined with human expertise and ingenuity, can optimize complex hybrid generation projects, seamlessly integrating renewable sources into the power grid according to Forbes.The integration of AI and renewables offers a future where decentralized energy exchange platforms, powered by AI algorithms, can predict prices, optimize the timing of exchanges and ensure efficient redistribution of energy, making clean energy more affordable and accessible (Forbes).However, the journey is not without its challenges. Data security and privacy, interoperability issues and difficulties integrating into existing infrastructure require collaborative efforts, standardization and ongoing research.By answering the call to action, researchers, practitioners and policy-makers can collectively contribute to a paradigm shift in the renewable energy sector.Through Read the full article

[retops]

you can't even hear them while they work

[cheetomussolini]

Leave it in the ground!

By Richard on March 30, 2017 at 5:36 pm

Posted In: Political Cartoons

During Trump's term in office:

Coal production declined 26.5%

coal-mining jobs dropped by 16.7%.

Carbon emissions from energy consumption dropped 11.5%

Remember he said he'd bring back Coal jobs

[indiaartndesign]

Thermodynamic Wind Turbine Chapel and Club | Margot Krasojević Architects

Known for an architectural approach seeped in dynamic engineering, and purposefully driven to harnessing natural resources, Dr. Margot Krasojević undertakes a cliffside project in Montenegro with careful consideration for the region’s natural beauty; equally diligent to its tough and inhospitable landscape. Her design, thus, focusses on the pilgrimage to Ostrog – to one of its cliffside churches, addressing the overarching concept of generating energy from humans.  https://www.indiaartndesign.com/thermodynamic-wind-turbine-chapel-and-club-margot-krasojevic-architects/

[wilsonneate]

Cabazon, CA. May 2024.

[enrego]

Enrego Energy - Erneuerbare Energien: Projekte, Bürgerbeteiligungen, An- & Verkauf

Erneuerbare Energien Projekte, Bürgerbeteiligungen, An- und Verkauf von Energieprojekten, Projektentwicklung – Ihr Partner für Kooperationen und nachhaltige Investitionen.

[its-vishnu-stuff]

Wind Turbine Engine Failure Prediction Model  - Innodatatics

A state-of-the-art computational method, the Wind Turbine Engine Failure Prediction Model, predicts potential issues with wind turbine engines. By analyzing environmental factors, performance indicators, and historical data, the model anticipates problems before they occur.

[usnewsper-business]

5 Exciting Companies to Invest in for a Bright Future! #artificialintelligence #CloudComputing #consumergoodscompany #digitalpaymentsolutions #fintechcompany #healthcarecompany #householditems #rarediseases #renewableenergycompany #solarpanels #windturbines

[generatorsandcontrolpanels]

A New Wave Of Sustainability: Electrical Solutions At Sea.

Introduction.

The maritime industry is undergoing a profound transformation, driven by a growing commitment to environmental sustainability. Gone are the days when ships solely relied on fossil fuels; today, the industry is embracing renewable energy sources like solar power and wind energy. This shift towards cleaner energy not only benefits the environment but also presents innovative solutions for powering vessels and reducing carbon emissions. Here, let’s explore the adoption of solar and wind energy in the maritime sector, the challenges it faces and the promising trends shaping a more sustainable maritime future.

Harnessing Renewable Energy Sources.

In today's world, where we care a lot about the environment, the shipping industry is changing. It used to use only fossil fuels to power ships, but now it's using clean energy sources. Instead of just using dirty fuels ships are using the power of the sun and the wind. Let’s see about the two main types of clean energy for ships: solar power and wind energy. Solar Power on the High Seas. The sun, a very powerful star in the sky, is now being used to make energy on the ocean. This is helping the ocean become more eco-friendly. Here's how solar power is making boats and ships more sustainable. Solar Panels on Maritime Vessels. Solar panels on ships are like special energy-capturing devices that soak up sunlight and turn it into electricity. This electricity helps power the ship and makes it move while also being kinder to the environment. These solar panels are tough and placed carefully on the ship to get as much sunlight as possible. Having solar panels on ships is great because it means they don't need as much fuel which is better for the planet and cheaper for the ship. Additionally, these panels provide a steady supply of extra power for things like lights, navigation and other important stuff on board. Power Generation and Storage. Solar energy collected during the day is only part of the solution. To make sure to always have power vessels use big batteries to store extra energy from the sun when it's sunny. These batteries act like a backup so the ships can use the stored energy at night or on cloudy days when the sun isn't shining. This way the marine vessels can keep things running without using fossil fuels. Meanwhile, it can also use the extra energy from the sun to charge electric vehicles like ferries that carry people across water. This helps the environment because it reduces pollution. Wind Energy: Sails and Turbines. During the day, the sun provides a lot of energy but at night the wind steps into help ships be more eco-friendly. New sail and wind turbine technology is changing how ships travel on the ocean. Innovative Sail Technologies. Sails used to be for moving boats but now they're super smart. They have sensors and fancy materials to catch wind energy. They don't just push the boat; they also make electricity and store it in batteries. So, the boat doesn't need to use regular engines as much. Wind Turbines on Ships. Picture a ship with tall masts covered in modern wind turbines. This might sound like science fiction but it's happening now. These turbines are put in just the right spots to catch the strong sea winds and turn them into electricity. Putting wind turbines on ships is a big step forward for eco-friendly boat tech. They work quietly and well in making clean power that helps the regular power on the ship. Sometimes they make extra power that can be sent back to the power grid which help in renewable energy grow even more.

But what challenges and complexities lie on the path to fully harnessing these renewable energy sources at sea?

Energy Storage Efficiency Storing energy efficiently is really important when we use solar panels and wind turbines to make power. We need better batteries that can save the extra energy these sources make even when the sun isn't shining or the wind isn't blowing. For things like boats, it's extra important to have batteries that can hold a lot of energy but don't weigh too much or take up too much space. Weather-Dependent Energy. Solar and wind power rely on good weather. If it's cloudy or stormy for a long time these energy sources may not work well. People who design and use ships need to think about this when they decide how to use energy on sea journeys. Space Constraints. Space on ships is very valuable, especially on cargo ships. It's tricky to add green energy systems while keeping enough room for cargo. We need smart designs and small equipment to solve this problem. Maintenance and Durability. Renewable energy setups in the tough ocean conditions face problems like rust from salty water and always moving around. To keep these systems working well, it needs strong materials and regular maintenance plans. Integration with Existing Systems Adding renewable energy systems to existing ships can be tricky. Engineers have to make sure these new systems work well with the ship's regular power, navigation and communication systems to keep the ship safe and working properly. The maritime industry is determined to use clean energy, like solar and wind power, even though it's tough. Governments and groups around the world are supporting this by making rules and giving rewards. In the future, ships can use both the sun and the wind for power. And they're getting better at storing energy and making new designs. This means ships will be more eco-friendly. Even though it's not easy, we're getting closer to a time when ships can sail silently and cleanly with the help of nature and smart ideas.

In this progressive march towards a more sustainable maritime future, these trends further underscore the maritime industry's commitment to harnessing renewable energy sources at sea:

Research and Innovation: Maritime researchers and industry leaders are working hard to make renewable energy better and cheaper. They're using new technology to do this. Collaborative Initiatives: More and more often, countries, groups and businesses are teaming up to work together on renewable energy projects for ships and boats. They share what they know, use the best methods and agree on how to make renewable energy work well in the maritime industry. Hybrid Propulsion Systems: Using both regular engines and renewable energy sources together in vehicles is becoming more popular. These hybrid systems can work in different situations and help cut down on pollution. Electrification of Ports: Ports are important places for ships. Hence, they are working to use clean energy. Some ports are putting up solar panels, wind turbines and power sources on the shore to give ships clean energy when they stop there. Regulatory Support: International groups such as International Maritime Organization (IMO), overseeing ships and boats are making rules to encourage the use of clean energy in the industry. These rules are making it easier for sustainable practices to be used. Renewable Energy-Powered Ferries: Ferries that travel short distances are using cleaner energy sources more and more. They are using electricity and a mix of electricity and something called hydrogen fuel cells to power their engines. This is happening in places near the coast. Environmental Certification: Groups like Green Marine evaluate and reward shipping companies for being eco-friendly. These certifications make companies show how they use clean energy and be more honest about it.

Conclusion.

The maritime industry's shift towards harnessing renewable energy sources represents a significant stride towards a more sustainable future. Solar power and wind energy have emerged as viable alternatives with innovative technologies and collaborative efforts driving progress. Overcoming challenges related to energy storage, weather-dependency, space constraints, maintenance and system integration remains pivotal. Nevertheless, ongoing research, hybrid propulsion systems, electrification of ports, regulatory support, renewable energy-powered ferries and environmental certifications are promising trends that underline the industry's commitment to eco-friendly practices. As we navigate these waters of change, the prospect of cleaner, more efficient and environmentally responsible maritime transportation draws nearer. Read the full article

[michaelkelso2]

I nearly died when I... Now I guard windmills and I’m not sure if I’ll ...