Electricity prices are going up, which is pushing millions around the world into energy poverty and unable to meet necessities like heating, cooling, and cooking. As of late 2024, over 21 million U.S. households (roughly 16%) owed a staggering $15.4 billion in unpaid utility arrears. In Europe, retail electricity prices have almost doubled since the beginning of the energy crisis in 2021, affecting more than 46 million people across many countries.
The Great Decoupling: Renewables vs. Grid Reality
While some critics point to the "green agenda" as the primary driver of these costs, the data suggests a different story. In markets with high renewable penetration, wholesale prices tend to drop. Solar power is now roughly 41% cheaper than fossil fuel alternatives therefore, in the long run the demand for renewable energy will only grow as the world keeps moving for cheaper avenues of power.
The real culprit behind high electricity bills isn't the source of energy, it’s the power grid.
For instance, let’s look at U.S. power grid, it is one of the most complex machines which humanity has built. It comprises thousands of power plants, 600,000 miles of transmission lines, 55,000 substations and over 6 million miles of distribution lines. However, we are basically running a 21st-century economy on a machine that was designed in the 1880s.
- Then: Electricity was centrally generated, with a predictable, and a unidirectional flow.
- Now: Flows are bi-directional (think rooftop solar), generation is intermittent, and consumption patterns are increasingly volatile.
To lower costs, we need a more resilient, responsive, and "intelligent" grid.
Tredence is partnering with companies that generate, transmit and distribute electricity to close the gap between legacy infrastructure and current demand. We are leveraging vast data streams to enable affordability through four key pillars:
- Reliable Integration: Leveraging renewable energy to reduce dependency on expensive "peaker" plants.
- Grid Resilience: Using visual monitoring and health indexing to prevent costly failures.
- Smart Balancing: Recommending strategic investments in Battery Energy Storage Systems (BESS).
- Optimized Trading: Enabling more profitable energy exchange trades through advanced indexing.
Case in Point: We partnered with a client which owns and operates 28 GW utility scale solar power park on a 760 sq. km. The excess generation would cause revenue loss while deficient generation would incur government penalties. We developed solution which in its first stage assessed the historical accuracy and reliability of the weather forecasts to assign weights and merge data from multiple sources into a unified, high-quality input set.
In the next stage, the solution leverages past source data and actual generation records to normalize the inputs and feed it into gradient booster regression model which forecast the power generation for every 15-minute time span for T+1 day.
The forecast accuracy improvements delivered $280,000 in reduced penalty costs.
Tredence: 'Amper' Agentic Platform on Snowflake
To leapfrog the grid into the future, Amper operates across four sophisticated layers:
- Unified Energy Data Platform: Ingests structured data (inverter efficiency, gas pressure) and unstructured data (LiDAR vegetation scans, thermal imagery of hotspots) — using Openflow, dbt, Snowpark, and Streamlit.
- AI/ML Layer: Features customized supervised models for solar forecasting, computer vision for spotting rusted towers or missing bolts, and LSTM models for index forecasting built using the capabilities of Snowpark ML.
- Agentic Layer: Specialized autonomous agents built using Snowflake Cortex, interact with physical assets. These agents can isolate faults in milliseconds, trigger automated work orders for maintenance, and coordinate with battery storage to balance the intermittent nature of wind and solar.
- Governance Layer: The "master agent" that ensures all autonomous actions align with safety guardrails, optimization objectives, and consumer priorities (residential vs. industrial).
Tredence has combined its domain depth in the form of industry specific data models, pre-built ingestion pipelines and its technological prowess in the form of AI / ML model and agent orchestration to leapfrog humanity’s largest and most complex machine into the future.
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Aniket Aggarwal
Lead Consultant, Industrial & Energy
