A Tool to Plan and Optimize Your Solar Power for Energy Independence

Hacker News

Hi HN, I built PVBenchmark to help people understand how much solar power they can generate at their location and how their system compares to others. If you're looking to reduce reliance on the grid, plan a backup power setup, or just check whether your solar array is performing as expected, this might be useful. The site provides location-based forecasts based on panel orientation, tilt, and capacity, so you can get an idea of what to expect before installing a system. If you already have solar, you can compare your actual output with similar setups from other users to spot inefficiencies or confirm you're getting what you should. The goal is to move beyond generic estimates and provide real-world data from people actually generating their own power. It started out as a small project for Germany but now supports global forecasts and comparisons. Curious to hear what you think—what would make this more useful?

Visit product View on Hacker NewsFeb 19, 2025

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports, started · Missing: reddit linkedin, podcasting, created

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal

52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive

51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos

43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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