Technical management of renewable portfolios: from data to maturity score

A consultant with eight ongoing projects — three wind turbines, four solars, one hybrid — accumulates, at the end of a cycle of studies, eight folders with files, eight PDFs, eight accompanying spreadsheets and no integrated vision. The question that comes from the manager is always the same: which project is more mature? Where is the greatest risk? In which can we advance this week?

The answer usually lives in a presentation mounted on the eve, with numbers copied from different reports, in different formats, produced by different engineers, without standardization of criteria between them. It is not lack of competence — it is lack of infrastructure for multi-active technical consolidation.

What fragmented consolidation hides

When each engineer defines "data quality" in their own way, comparing projects involves comparing different methodologies under the same column. One project with 88% availability validated by IEC 61400-12-1 and another with 91% calculated ad hoc on data without QA/QC appears the same in the status table — but they are not comparable.

Technical traceability in portfolios, discussed in NT.05It deals with the chain of custody within an individual project. Portfolio management adds a different dimension: standardization between projects. Indicators need to be defined with the same methodology in all assets in order for the comparison to be valid — and this standardization needs to be automatic, not dependent on the individual engineer who delivered the study.

Standard indicators for mixed portfolios

Portfolios with solar and wind assets cannot compare resource directly: GHI in kWh/m2 is not comparable with wind speed in m/s. What is comparable are standardized indicators that reflect the quality and completeness of the analysis, regardless of the technology:

The operational rule is simple: when the objective is Compare technical priority between assets, use only the standard indicators. When the objective is Analyze the resource of a specific asset, use the physical indicators of the campaign study (NT.09 for wind, NT.10 To mix the two contexts is the origin of the most common prioritization errors in portfolio management.

The technical maturity score

A single score per asset allows to sort priorities and identify blocks immediately, without depending on the complete reading of individual reports. The weighted formulation combines the five standardized indicators:

readiness_score = data_quality   × 0,35
                + availability    × 0,25
                + metadata_completeness  × 0,15
                + low_uncertainty    × 0,15
                + report_readiness   × 0,10

The weights reflect a technically conservative hierarchy. Data quality has the highest weight (35%) because an asset with poor quality data — even with good availability, complete metadata and documented uncertainty — is not ready for decision: the fundamental numbers are suspicious. Availability (25%) comes next because it determines the statistical representativeness of the period. Metadata and uncertainty (15% each) are checks of completeness and methodological rigour. Report ready (10%) is the least because it is the natural consequence of the others — when the previous four are in order, the report tends to be ready too.

The resulting classification follows four tracks:

A fundamental aspect: the score needs to be explainable. Presenting a number 74 without showing which components pulled the result down is useless for decision making. The value of the composite indicator is in decomposition — the manager needs to know if the problem is data quality (recess or new campaign requires), availability (extend period requires) or simply the report has not been completed (requires engineer's agenda, not new measurement).

Architecture of the suite: BORA and SOLANO as an input

The separation of responsibilities is deliberate. BORA and SOLANO do the physics: they process raw time series, apply QA/QC, calculate Weibull/TI/POA, generate detailed technical reports. The Portfolio does not repeat this analysis — it only imports Summaries campaign files: period, availability, quality score, uncertainty, P50/P90 when available, open pendings and report status.

This separation has an important consequence: the Portfolio can open even if the files - .bora - and - .solano Originals have changed folders or have been archived. It stores a Snapshot of the indicators imported into the file itself - .rnwn, maintaining a stable and auditable portfolio view regardless of the state of individual campaigns.

The decision matrix in practice

The matrix reading is immediate: Wind Serra is ready for investment decision (score 91), Sun Aurora can advance with documented qualifications (score 78), Sun Sertão requires technical review before any step (score 62), and Wind East is blocked — should not advance without direct intervention in the data (score 43).

The question that the manager makes next — What is the specific problem of the East Wind? It is answered by the same system: the components that pulled the score down (low availability: 61%, data quality: 48%, pending report) point to the necessary action. The difference between a useful portfolio score and an ornamental number is precisely in this explanatory decomposition.

Executive report versus technical report

The portfolio report does not replace the individual SOLANO and BORA reports — it points to them. This distinction is operationally important because the two documents have different audiences:

The individual technical report contains raw data, time series, detailed graphs, component uncertainty analysis, IEC compliance and audit trail. It is the bankable document — dense, complete, with decades of service life in the project file.

The Executive Portfolio Report is for the manager, the investment committee and the client. It contains the asset matrix, priority ranking, critical alerts and recommendations for next steps. It is short, visual, with focus on decision. Reference individual reports when the reader needs to deepen.

Production of the executive report from it as it generated the reports — rather than manually consolidating it into a presentation — ensures that the numbers are consistent between the two documents. The annual GHI of the Aurora Sun in the executive report is the same as shown in Section 5 of the SOLANO report because it comes from the same file - .solano.

Implications for due diligence and risk management

In processes of due diligence portfolio technical, the auditor needs to respond quickly: which assets have sufficient quality data to base an investment decision? Without a standardized consolidated view, this survey consumes days of analysis — in each individual report, verifying criteria that vary from engineer to engineer.

A portfolio with an automatic and auditable maturity score reduces this time drastically: the auditor knows in minutes which assets are available below the threshold, which are uncertain outside the acceptable range, which do not have an approved report. The traceability chain goes from the consolidated indicator to the gross field data, via campaign file — exactly the audit trail discussed in NT.05.

For portfolios with wind assets, the maturity score connects directly to the gap P50–P90 discussed in NT.06: an asset with low data quality score has, almost by definition, high uncertainty of AEP — which means gap P50–P90 greater and more pressured DSCR. Portfolio score is not a decorative indicator; it is a proxy of the technical financial exposure of each asset.