Unified Data Pipeline for Renewable Energy Assets

Client Overview

The client is a USA-based renewable energy company managing a portfolio of utility-scale solar, onshore wind and grid-connected battery storage assets across multiple sites and two market regions. Each site reports equipment telemetry through SCADA, while separate grid meters track electricity delivered for settlement, giving the business the data it needs to verify generation, understand asset performance and forecast future output.

TL;DR

A renewable energy company needed a clearer way to bring together data from solar, wind and battery assets across multiple sites. We built a unified telemetry data pipeline that made generation reporting, performance analysis and forecasting easier to manage from one place.

Challenges

As the client’s renewable portfolio expanded, data was being generated across multiple solar, wind and battery sites, along with separate SCADA and settlement systems. Since each source followed its own structure and reporting frequency, building a single, consistent view of performance took extra effort.

The team needed a better way to bring this data together so they could compare actual generation with expected output, understand the reasons behind performance changes and prepare cleaner inputs for forecasting.

They also needed the flexibility to handle the differences between solar, wind and battery assets without losing important site-level details. The goal was to create a reliable data foundation that made reporting and analysis simpler while still supporting the needs of each asset type.

Solution

Lucent designed a unified data pipeline that brought SCADA telemetry, grid meter readings and site-level operational data into one consistent flow. Through its Data Engineering Services, Lucent Innovation consolidated these fragmented data sources into a scalable architecture that made renewable energy data easier to manage, analyse, and use for forecasting.

The solution focused on four key areas:

Unified data collection: Brought telemetry, settlement meter data and operational records together from multiple sites and market regions.
Consistent data processing: Cleaned, aligned and checked incoming data so teams could work with a dependable view of generation and performance.
Performance analysis: Connected generation data with factors such as weather, asset availability, curtailment and operating events to help explain changes in output.
Forecast-ready data: Structured historical generation and operational data so it could be used more consistently for future production forecasting.

This gave the client a clearer flow of information from individual assets through to reporting and analysis. Teams could compare actual generation with expectations, investigate performance variations more efficiently and work from the same underlying dataset.

The pipeline was also designed with future growth in mind, making it easier to bring additional renewable sites and new data sources into the same reporting framework.

Technologies and Tools

Platform

Databricks Lakehouse

Storage Format

Delta Lake (time travel retained across the settlement dispute window)

Field Telemetry

OPC-UA and Modbus TCP collectors at each site, bridged to MQTT

Streaming Ingestion

Apache Kafka + Databricks Auto Loader (Structured Streaming)

Reference Data

Meter data management exports, asset register, numerical weather prediction feeds

Transformation

PySpark + Delta MERGE (idempotent upsert on asset, signal and event time)

Signal Normalisation

Versioned vendor tag mapping table — canonical signal names, units and scaling factors

Orchestration

Databricks Workflows, with a separate backfill path for late site data

Analytics & Reporting

Databricks SQL + Power BI (availability, performance ratio, curtailment attribution)

Governance

Unity Catalog — lineage and column-level access control on settlement tables

Results

45% faster reporting cycles by reducing the manual effort needed to prepare site and settlement data.
30% reduction in data reconciliation time across SCADA and grid meter records.
25% faster investigation of performance issues by bringing operational, weather and generation data into one view.
18% improvement in forecast accuracy for short-term generation planning.
40% less manual data preparation for recurring operational and management reports.
Faster onboarding of new sites, with new assets added to the common data framework without creating separate reporting workflows.

Words of Appreciation

"Our data problem was never really about volume. It was that every vendor described the same reading differently, half our sites reported late, and the settlement numbers kept moving underneath us. Lucent Innovation took that seriously rather than treating it as a straightforward ingestion job. We can now show exactly what we filed and why it changed, and our operations and commercial teams have stopped arguing about whose figure is right."

Daniel Reyes

Head of Asset Performance

Future Scalability

The pipeline was built to scale as the client adds new solar, wind or battery assets. New sites and data sources can be connected without rebuilding the existing setup. It also creates room for future use cases such as advanced forecasting, predictive maintenance and automated performance alerts.

Building a Unified Data Pipeline for Renewable Energy Operations

Industry

Core Technologies