Sustainability
Article | July 7, 2023
It all started about four years ago, when SUVs and pickup trucks drove uninvited onto their lands, remembers Olimpia Palmar, a member of the Indigenous Wayúu peoples, who historically have occupied the La Guajira desert in northern Colombia and Venezuela. "We started seeing these arijunas [Wayuúunaiki for non-native peoples] wearing construction helmets and boots and vests, getting out of the cars, checking the desert, and then leaving," she recalls.
Word soon began circulating across the Guajira Peninsula, from the rancherías — the community’s rural settlements — to the few urban centers: The arijunas were offering money to those who would let them plant tall, slim towers on their lands to measure the wind. On La Guajira’s dusty earth, where few things grow, towers began to sprout. By 2019, at least 30 wind-measuring towers had risen on Wayúu land, according to a report by Indepaz, a nonprofit research center.
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Solar+Storage, Strategy and Best Practices
Article | September 17, 2022
Machine learning and artificial intelligence (AI) are two of the most commonly used commercial phrases these days. As a result, companies across sectors are searching for methods to include them in order to optimize and automate their key operations. The energy sector is no exception!
Indeed, throughout the years, renewable energy industries (wind, solar, hydro, nuclear) have substantially gained from the potential of machine learning. They were able to reduce their expenses, make better projections, and raise the rate of return on their portfolio. And this tendency is just going to gain momentum. If your company is in the energy industry or utilizes a lot of power, machine learning and AI can help you improve your business performance. But how precisely? Let's get started.
Ways in Which AI and Machine Learning are Changing Energy Sector
There are a few methods that machine learning and AI can be applied to positively improve the energy industry. Here are a few popular applications currently under development.
Predictive Maintenance
AI helps match energy output with demand and ensure power grid stability and resilience.In 2003, a low-hanging high-voltage electricity line hit an overgrown tree in Ohio, causing a widespread blackout. There was no power system alarm and no sign of the incident. The electric company didn't notice until three additional power lines failed. This carelessness ultimately brought down the whole grid. The 50 million-person blackout lasted two days. Eleven individuals died, and $6 billion was lost.
Predictive maintenance can be implemented using machine learning and IoT
Sensors gather operational time series data from electricity lines, equipment, and stations (data accompanied by a timestamp).
Machine learning algorithms can then forecast when a component will fail (or n-steps). It can also anticipate machinery's remaining usable life or future breakdown. These algorithms detect machine failure, eliminate blackouts or downtimes, improve maintenance procedures, and reduce maintenance expenses.
Grid Management
Grid management is a promising AI application in energy. Complex networks distribute electricity to users (also known as the power grid). Generation and demand must always match in the electrical system. Other issues, like blackouts and system breakdowns, can occur.
Despite being ancient, pumped hydroelectric storage is the most common way to store energy. It operates by moving water upwards and letting it fall into turbines. Renewable energy makes predicting the grid's power generation challenging. After all, it is affected by a variety of things, like sunlight and wind.
Demand Response
Large demand shifts can be expensive for nations that depend on renewable energy. As nations migrate to green energy, it's harder to adapt to demand fluctuations. Germany plans to use 80% renewable energy by 2050.
Countries such as Germany will encounter two major challenges Demand fluctuations: On some days or times of the year, power consumption soars (on Christmas, for example) Weather volatility: Without wind or clear skies, it might be hard to meet electrical demand. In both circumstances, more stations or fossil fuel-powered facilities must meet demand
Solving demand response issues
Many nations are partnering with businesses to examine weather forecasts, power demand, etc. Germany's EWeLiNE project forecasts wind and solar energy at a specific moment. This enables the government to use non-renewable energy to meet additional power demand.
They utilize enormous historical data sets to train machine learning algorithms, as well as data from wind turbines or solar panels, to properly balance supply and demand.
Closing Lines
AI increases the potential of humans. Several renewable energy producers are investing in artificial intelligence to boost their businesses.There are numerous uses of artificial intelligence in renewable energy. The fundamental purpose of AI integrated systems is to reduce forecasting issues and incorporate renewable energy into the central energy grid as effectively as possible. AI can also assist renewable energy providers in developing successful plans and policies based on present energy consumption and demand.
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Energy
Article | July 16, 2022
To maintain the goals of the Paris Agreement and save the Earth from ecological breakdown, one of the most important things experts agree we need to do is transition to a renewable energy economy. While most of us may associate renewable energy with wind energy and solar energy, there are several other sources of clean energy that are growing in popularity. One such source is geothermal energy.
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Solar+Storage
Article | May 25, 2021
For anyone who has owned solar panels in the past, or even many considering solar power installation in the near future, it’s generally understood that direction is important in this field. Specifically, the ability of solar panels to point south, where they will receive the maximum possible sunlight and therefore create the maximum amount of energy, is vital for many solar panel installations – but it’s important to realize that the simple direction of the panels is not the only important variable here.
At Intermountain Wind & Solar, we’re happy to offer both commercial and residential solar panel installation services, including the utilization of the Tesla Powerwall battery backup. We assist our clients with every part of solar panel installation, including important directional and related themes that will play a role in how much sunlight your panels are able to soak up. Today we’ll focus on some of the important variables here, including why south-facing panels are the optimal approach plus several other basic factors to keep in mind when it comes to maximizing panel positioning and direction.
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