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Company profile

Power Enable Solutions Limited

Light Touch, Big Impact - REOptimize Systems

Utilising machine learning and analysis of high resolution data, Reoptimize Systems offer the elegant, data-driven way to optimise renewables assets for stronger performance, longer life and lower costs.

CRN
SC578800
Founded
2017
Age
8

Overview

Legal name
POWER ENABLE SOLUTIONS LIMITED
Region
Scotland
Registered address
SUMMIT HOUSE
4-5 MITCHELL STREET
EDINBURGH
SCOTLAND
EH6 7BD
Insolvency history
No

Latest accounts

Financial period: 1 Nov 2023 to 31 Oct 2024

FILLETEDACCOUNTS
Turnover
Unknown
Profit / Loss
Unknown
Employees
6

Company events

Reference milestones and recent Companies House filing stream events.

8 events
26 Oct
2026

Confirmation statement due

Confirmation Due

Next confirmation statement due date

31 Jul
2026

Accounts due

Accounts Due

Next accounts due date

23 Jun
2026

Accounts With Accounts Type Micro Entity

Accounts Analysed

AA | Transaction MzUyNzkyNTU0NmFkaXF6a2N4

Published 23 Jun 2026 17:07

27 Mar
2026

Capital Allotment Shares

Capital

SH01 | Transaction MzUxMzAyMjUwM2FkaXF6a2N4

Published 27 Mar 2026 18:17

12 Oct
2025

Confirmation statement filed

Confirmation

Last confirmation statement made up date

31 Oct
2024

Accounts filed

Accounts

Last accounts made up date

24 Oct
2024

Confirmation Statement With No Updates

Confirmation-statement

CS01 | Transaction MzQ0MDgxNDA4NWFkaXF6a2N4

Published 24 Oct 2024 09:26

13 Oct
2017

Incorporated

Inception

Company registered at Companies House

Public funding

2 awards
First funded
2018
Funded years
2018, 2020
Age at first award
1 years

Projects

2020 Small Business Research Initiative Lead participant

Advanced AI for Integrated Financial Optimization of Wind Energy Assets

1 Oct 2020 to 31 Dec 2020

Awarded
£59,911
Total cost £59,911

REOptimize Systems (REOS), was formed to exploit research developed at University of Edinburgh, which has implemented a unique approach to increasing the efficiency of wind turbines. Through advanced modelling and the application of novel machine learning techniques the algorithms minimise the end-to-end losses in the system. This technique has patents pe...

2018 Study Lead participant

Autonomous Wind Turbine Optimisation Software - AWTOS

1 Nov 2018 to 31 Jan 2020

Awarded
£111,916
Total cost £159,880

"Current WT control systems do not optimise the end to end system and are set up with factory default settings to optimise individual elements of the drive train such as the generator and inverter. Factory settings are not optimal due to site specific wind turbulence and machine to machine variability caused by wear and tear. Non-optimised control leads n...

Product types

Small Business Research Initiative Study