Frequently asked questions

There is a notable correlation between market electricity prices and carbon emissions, meaning that cheaper electricity often aligns with lower emissions. Thus, optimizing solely for reduced emissions alone can lead to cost savings. Considering both factors together can, however, further enhance the overall savings of carbon and costs for your customers.
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Access to granular carbon emissions data is key for a successful combined optimization strategy. Our API provides real-time and forecasted electricity insights to help you implement this strategy, allowing you to align consumption with low-cost and low-emission periods. For more information, read our blog post on co-optimizing for price and carbon with flexible electricity loads.

The potential for CO₂ reduction using our API is considerable, but varies depending on the specific application.
Optimization of electric vehicle charges can save up to 1 kilogram of CO₂ per charging session in certain European regions (read more in this blog). Moreover, the adoption of carbon-optimized smart charging can reduce total emissions by up to 16%, highlighting its significant potential for reducing the carbon footprint (FUSE study).
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Looking at customer cases, Monta’s smart charging feature powered by Electricity Maps has saved an average of 200 grams of CO₂ per charge since its launch in May 2023, leading to combined savings of over 15 tons across customers, demonstrating the impact of optimized EV charging. On an industrial scale, optimizing electricity use based on carbon intensity can also yield significant reductions, as seen in Salesforce’s AI-training data centers, which saved 105 tons of CO₂.

Both optimizing based on renewable energy and carbon emissions have their advantages, and the best approach depends on your specific goals.
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Optimizing based on hourly flow-traced carbon intensity provides a more precise measure of the emissions associated with electricity consumption. This approach considers all electricity on the grid, including local production and exchanges with neighboring grids, offering the most accurate representation of the carbon footprint. It effectively reflects the real-time environmental impact of your electricity use, making it a strong choice for reducing your overall carbon footprint.
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On the other hand, optimizing based on renewable energy is beneficial because it aligns electricity consumption with the availability of renewable resources like wind and solar. Focusing on renewable energy is intuitive and easily understandable for end-users, which can enhance user engagement and education about grid dynamics. The signal can also help address the intermittency of renewables and support grid stability by making consumption patterns more predictable.

For users with green electricity contracts, our API can add significant value by addressing some key limitations of these contracts.
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While green electricity contracts promise renewable energy, they often do not account for the location and time availability of green electricity, which can impact the actual environmental benefits. Sustainability features powered by Electricity Maps API addresses this mismatch. By optimizing users' electricity consumption to align it with times when the grid is greener, they can reduce real emissions and potentially save electricity costs as well. Providing insights on carbon intensity also allows users to understand and verify the impact of their green energy use.

Electricity Maps can play an important role in supporting the claim that electric vehicles are clean by helping users understand and reduce the environmental impact of their EVs. The environmental benefits of EVs are closely tied to the source of the electricity used to charge them. Our data helps ensure that EVs are not only cleaner in theory but also in practice, aligning their charging with the availability of cleaner electricity. A study found that the adoption of carbon-optimized smart charging can reduce total emissions by up to 16%, highlighting the significant potential for reducing the carbon footprint of EVs with our data (FUSE study).
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By integrating our real-time and forecasted electricity signals, you can empower end-users to maximize the potential for emissions reduction of EVs by charging them during periods of low carbon intensity. Thus, you help users understand and further reduce their environmental impact through smarter charging behavior.