Plant Digital Model

Production Without Precision

The organisation operated a diversified portfolio:

• wind farms across multiple geographies

• solar plants with varying irradiation profiles

• a mix of long-term PPAs and exposure to spot markets

Each asset generated data continuously:

• production curves (MWh)

• weather inputs (wind speed, irradiation)

• grid constraints and curtailment events

• pricing signals (spot, forward, contractual)

But this data was fragmented.

Stored across multiple systems — trading, asset management, forecasting tools — it could not be easily combined into a single operational view.

 

The Cost of Fragmentation

The consequences were structural rather than visible.

The organisation could not accurately answer:

• What is the real marginal cost of producing each MWh at a given moment?

• How does profitability vary across assets, contracts, and time windows?

• When should energy be allocated to spot markets versus contractual obligations?

• Where is value being lost due to curtailment or suboptimal dispatch?

Decisions were made.

But not optimised.

 

From Generation to Value Chain

At its core, the organisation was managing assets, not a system.

What was missing was a unified model capable of connecting:

• generation (wind/solar output)

• cost structure (CAPEX amortisation, OPEX, balancing costs)

• market dynamics (spot prices, volatility, demand curves)

• contractual constraints (PPAs, delivery commitments)

Without this, energy production remained disconnected from value optimisation.

 

Building an Energy Digital Twin

Cleohpatra implemented a platform that created a digital twin of the energy value chain.

The system integrated:

• asset-level production data

• weather and forecasting models

• market pricing (real-time and forward curves)

• contractual obligations and constraints

• grid and curtailment dynamics

Instead of interacting with isolated systems, operators could now engage with a real-world model of their entire portfolio.

 

From Reporting to Decision-Making

The digital twin enabled the creation of a granular profitability model, applied at the level of:

• individual assets

• time intervals (hourly / intra-day)

• market conditions

This allowed teams to:

• evaluate the true value of each MWh produced

• compare spot vs contracted allocation dynamically

• identify high-value windows for energy dispatch

• quantify the cost of curtailment and inefficiencies

Energy stopped being measured in volume alone.

It began to be measured in value per unit of production.

 

Optimising Dispatch and Revenue

With this foundation, new workflows were introduced:

1. Market Allocation Optimisation

• dynamic allocation between PPAs and spot markets

• identification of high-price windows

• improved capture of price volatility

2. Production Strategy Optimisation

• alignment of maintenance and downtime with low-value periods

• prioritisation of assets based on marginal profitability

• reduction of curtailment losses

3. Cost and Profitability Visibility

• real-time view of profitability across the portfolio

• understanding of cost per MWh under varying conditions

 

The Shift in Performance

The impact was not driven by increased capacity.

It was driven by better decisions.

• improved revenue capture from existing production

• reduction in value leakage due to suboptimal allocation

• faster decision cycles (from weeks to minutes)

• improved capital efficiency across assets

What had previously required manual analysis across multiple systems could now be evaluated in real time.

 

From Assets to System

The most significant change was conceptual.

Before, the organisation operated a collection of assets.

After, it operated a coordinated energy system.

Instead of asking:

• “How much are we producing?”

It could ask:

• “Where is value being created — and where is it being lost?”

 

Closing Reflection

In renewable energy, variability is inevitable.

But inefficiency is not.

The difference lies in whether generation is managed as output,
or as part of a system where production, cost, and market dynamics are continuously aligned.