Advanced Energy Modelling Tool

Evolved energy modelling

Find the optimal energy strategy using the best technologies that science has to offer, improve accuracy, reduce risk and generate a business case in hours, not weeks…

Data ingestion & transformation

Features

Transform NEM12 and interval data

Benefits

Prepare time-series data for modelling with ease, and process millions of records with a few clicks.

Value

Avoid manual data handling, tedious and repetitive calculations, improve accuracy, and reduce time to analysis, error and risk.

Data ingestion & transformation

Transform NEM12 and interval data

Prepare time-series data for modelling with ease, and process millions of records with a few clicks.

Avoid manual data handling, tedious and repetitive calculations, improve accuracy, and reduce time to analysis, error and risk.

Client asset register

Easily add and edit client data: sites, buildings and equipment to accurately aggregate time-series data in an automated manner.

Realise a source of truth for slow-changing client data to avoid tedious manual data entry and repetition.

Baseline as-built and identify flexible loads

Easily disaggregate time-series data to identify flexible loads such as HVAC used to estimate benefits of demand response, peak demand management and load shifting functions.

Avoid the need for complex spreadsheet models that require date-time matching from internal engineering and operating requirements.

Modelling engines

Technology options evaluation

Find the best technology mix, quickly. Easily discover optimal equipment based on type, cost, operating and regulatory variables using inbuilt optimisation algorithms.

Avoid the hype, find the optimal technology mix quickly and improve the quality of advice to clients.

Model the wholesale spot price (WSP)

Accurately model the benefit of wholesale pass-through contracts with one-click time-series calculations between client and WSP data.

Modelling the WSP requires 100,000+ calculations per electricity meter p.a. (not possible to do with spreadsheets).

Model the benefit of smart buildings

One-click template scenarios that simulate model predictive control algorithms from a baseline, taking into account internal control goals, energy optimisation, peak demand management, thermal comfort, and the WSP.

Show clients how they can improve thermal comfort, and energy productivity, reduce emissions, save money, and potentially generate income with smart building control algorithms.

Model a tariff change

One-click tariff change to quantify the benefits of a change in energy tariffs or create your own time-of-use (TOU) tariffs via the web-form.

Leverage a tariffs library of predefined tariffs. Model an unlimited number of electricity tariffs without the need for manual calculations.

Emissions and net zero

NGERs and carbon calculations are automated from the generation of time-series data.

Demonstrate how potential scenarios will achieve sustainability goals without the need for manual calculations.

Analysis tool-set

Flexibility and scalability

Create unlimited assumptions and scenarios, copy, edit and apply them to other sites or clients. Apply sensitivities, best, likely and worse case scenarios at the assumption or scenarios level with ease.

Avoid tedious aggregation and calculations in building scenarios or in applying scenarios to other projects, improve efficiency, and reduce time-to-analysis, error and risk.

Dynamic assumptions

Create and apply projection curves to assumptions, such as CPI or equipment degradation. Projection curves are stored in a library for application across scenarios and projects.

Accurately model the effect of changing costs and operating conditions over time. Improve efficiency and reduce time-to-analysis.

Financial calculations and charts

Model outputs <=50-year BCR and NVP in line with Treasury Guidelines and produce charts that communicate costs, benefits and ROI in your presentations.

Calculations and charts are created automatically with validation rules to ensure quality output.

Modelling tool workflow

Create a source of truth for client data

Easily add and edit client data: sites, buildings, and equipment to accurately aggregate time-series data in an automated manner.

Automated data processing and transformations

Prepare time-series data for modelling with ease, and process millions of records with a few clicks – NEM12, interval and common retailer formats.

Simulate baseline and unlimited what-if scenarios

Disaggregate controllable loads to determine a source of truth baseline. Evaluate optimal equipment sizing, model demand response, and the WSP and other what-if scenarios as per need.

Generate output cashflow, profit & loss, BCR, and NPV calculations with ease

Create dynamic projection curves that calculate the effect of changing operational and market conditions over time and produce a report to meet financial requirements and treasury guidelines.

Background

The modelling tool was created by consultants in an ARENA-funded R&D, i-Hub Data Clearing House (DCH6.1) project. The project evaluated the benefits of demand response of solar, batteries, and smart controls with exposure to the wholesale spot price (WSP).

The problem

Modelling the WSP against variable equipment loads in 15-minute intervals results in +100 000 calculations per electricity meter per yearly modelled period. The scale of calculations coupled with the complexity of equipment variables was simply not possible to achieve with traditional desktop/spreadsheet modelling.

The solution

A team of domain experts and software devs worked on a database-driven computer-science approach capable of transforming data at scale, binding variables, and non-linear assumptions to model inputs and automate calculations. The modelling tool was born. A system of polyglot architecture and software that enables the user to make changes to model inputs verbatim, run algorithms to simulate equipment operation and generate financial calculations with improved accuracy and speed.