Solar Powered Data

Solar Powered Data delves into the intersection of energy consumption, climate technology, and data analytics, focusing on practical means to reduce carbon footprints through residential solar energy, electric vehicles (EVs), and carbon accounting. It emphasizes the importance of data in optimizing and understanding the impact of green technologies.

Solar Energy Electric Vehicles Carbon Accounting Renewable Energy Technologies Carbon Emission Reduction Strategies Hydrogen Production Data Analytics in Climate Tech Educational Courses on Climate

The hottest Substack posts of Solar Powered Data

And their main takeaways
19 implied HN points 01 Jul 23
  1. Exploring personal solar energy data can start with simple steps like getting quotes from platforms like EnergySage.
  2. Solar panel energy production can vary due to factors like weather conditions and time of year, impacting electricity consumption offset and savings.
  3. Net metering and understanding energy consumption patterns are crucial for optimizing the benefits of residential solar energy systems.
0 implied HN points 02 Dec 23
  1. Installing residential solar panels can significantly reduce carbon emissions associated with electricity consumption, offering a positive impact on environmental sustainability.
  2. Using hourly emissions data provides a more accurate assessment of the emissions reduced by solar panels, highlighting the importance of understanding the timing of energy production and consumption.
  3. Marginal emissions play a crucial role in evaluating the real-world impact of energy decisions, showing that the environmental benefits of solar panels may vary based on when electricity is generated and consumed.
0 implied HN points 26 Nov 23
  1. Electricity from the grid is largely generated by burning fossil fuels, contributing to greenhouse gas emissions. Using residential solar panels can help shift to clean, renewable energy from the sun.
  2. Even with solar panels, the production and consumption of electricity are not always aligned, leading to times when homes pull from the grid. Solar tends to overproduce during the day and underproduce at night.
  3. The demand for electricity varies by time of day and year, affecting the carbon intensity of the overall grid. Cheap renewable energy can reduce the use of dirtier coal and gas plants, making the grid cleaner.
0 implied HN points 21 Nov 23
  1. The Terra.do Carbon Accounting course covers a range of topics from climate fundamentals to action plan development, making it a comprehensive learning experience.
  2. The course workload included readings, homework assignments, and Q&A sessions, providing a structured and manageable approach to learning about carbon accounting.
  3. The course projects involved analyzing real-world companies' climate plans and calculating carbon emissions, offering practical applications of the learned concepts.
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0 implied HN points 12 Sep 23
  1. The average American needs to reduce their carbon contribution to avoid a 2 degree Celsius temperature increase by 2050. Personal actions like going solar and electrifying everything help, but difficult-to-electrify industries may rely on hydrogen for decarbonization.
  2. Traditional hydrogen production is not clean, emitting large amounts of CO2. New methods like 'blue' and 'green' hydrogen offer cleaner alternatives to help meet net zero goals.
  3. The cost of clean hydrogen production is decreasing, with major investments from companies driving a shift towards blue and green hydrogen. Despite challenges like varying emissions from different production methods, green hydrogen from renewable sources is seen as a key in reducing carbon emissions.
0 implied HN points 30 Apr 24
  1. The course on Software Stacks in Climate Tech from Terra.do can be beneficial for software engineers interested in climate change
  2. The course content included topics like public data sources, energy modeling, and hardware/software interfaces
  3. The course assignments were challenging, appealing to a wide range of technical backgrounds, and encouraged participants to push themselves to learn and grow
0 implied HN points 21 Aug 23
  1. Measuring carbon emissions is challenging and involves various frameworks like the GreenHouse Gas Protocol and Science-Based Targets.
  2. Just like baseball teams aim to score more runs by balancing offense and defense, individuals in carbon accounting also strive to reduce emissions while enhancing carbon removal.
  3. In both baseball and carbon accounting, accurately attributing individual contributions is complex, and there is a need for improved methods to credit and analyze performance.
0 implied HN points 09 Jul 23
  1. The correlation between weather data like solar radiation and solar energy with solar production is high, indicating a predictive relationship.
  2. By using historical and forecasted weather data, it's possible to project solar energy production up to two weeks in advance, offering insights for planning.
  3. Accuracy of solar energy predictions from sources like Visual Crossing is crucial for reliable projected energy production outcomes.
0 implied HN points 26 Aug 23
  1. To measure success in preventing carbon emissions, a relevant baseline is crucial. This could be individual company goals or industry standards, similar to evaluating a baseball player against a replacement level baseline.
  2. Achieving net zero carbon emissions requires collaboration throughout the supply chain, akin to how in baseball, run prevention involves both the pitcher and fielders.
  3. Accounting for context, such as location, role, and timing, is essential in both baseball and carbon emissions measurement to accurately assess contributions and impacts.
0 implied HN points 20 Dec 23
  1. Participated in a Utility Data Hackathon focused on energy insights and placed 2nd out of 9 teams.
  2. Found a solution that leverages utility data API and Shovels API to help electrify households efficiently.
  3. Collaborated effectively with a software engineer to build a demo app that provides energy-saving recommendations based on electricity data patterns.