Modelling Energy & Finance

In Complex Requirements

Encast is a multi-source energy modelling platform for commercial & industrial locations to plan their energy resilience with confidence.

Our modelling design allows you to develop a digital twin before breaking ground to instantly compare 30+ year modelled scenarios, framed into 30-minute intervals for granular analysis.

We provide deep analysis of performance for phased financial investment and empower the user to optimise based on their criteria, rather than a hidden mathematical equation.

Building Your Projects and Energy Modules

Projects & Scenarios

Every single 30 minute frame is calculated procedurally, using a peer-reviewed physics based approach, allowing effects from conditional operation and externalities such as weather and energy prices to be fully seen and understood. Models can be built for over 30 years in real-time.

Unlimited scenarios to quickly compare performance requirements.

Multi-currency operation to ensure your financial model is accurate.

Alter your energy-generation modules for difference scenarios.

Set your model life, commissioning date  and reporting detail.

Incomer and export sizing to build-in capacity constraints.

Tariffs, Heat & Electrical Demand Data Input Analysis

Value Maps

Value maps are used to define tariffs, electrical & heat demand loads. Every value map uploaded has a statistics page to assess data quality and characteristics. This gives a value of dataset health and heat map to ensure more accurate calculations.

Electrical loads to define the energy required in kWh by the site.

Profit and Loss define a detailed cost or multiplier for a report.

Thermal loads to define the heat used in kWh.

Complex map creation for every 30 minutes of the entire model.

Manually generate your load profile or upload to the platform.

Detailed Reports For Project Comparison

Reports

Reporting granularity can be used to switch between yearly and monthly reporting for project life with editable units for energy and mass. If you do not need to see a total value for each statistic, you can turn this on or off with a simple selection.

4 Reporting Areas: Financial, Carbon, Levelised Cost, Downtime.

Summary financial reports for a single look project assessment.

NPV, IRR, Cashflows, Income, Expenditure and TAX calculations.

Display all Levelised Cost of Energy (LCoE) entries for each scenario.

Carbon Report profit & loss entries can be viewed here.

Fine-tuning Optimisation

Detailed Analysis

Our detail viewing system allows you to individually inspect the state and performance of every component of an energy solution down to every half hour (at standard frame length) across the project life. Allowing the effects from conditional operation and externalities, such as energy prices and weather, to be understood. Enterprise users may model on shorter frames to increase fidelity. For total project performance analysis.

Performance inspection of every module for every half hour.

Any period of 28 days or less for every installation.

Select scenario and view each module, demand and headless.

Module panes only if active installations in selected period.

Aggregated chart if multiple installations in module.

Visualising The Project Performance

Dashboards

Visualising your modelling forecast in dashboards allow you to compare the different elements together. You have control over the chart type, what is presented and how. You may create multiple dashboards for a project comparing scenarios.

Breakdown by energy module type or each installation instance.

Profit & loss for all variable and value maps across the project.

Financial analysis in detail for all key analysis metrics.

Aggreged production or separate load and heating output.

Stack data, format display, axis and series ordering.

Ready to Model at the Speed of Thought?

Join the community of project owners, analysts and energy consultants who are already using Encast to deliver faster, more accurate energy resilience planning for themselves, their investments and their customers.
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