Pre-tender

Published

ENQEIR993: Market Consultation - Embedded PV sample data

8 suppliers have saved this notice.

Looks like a fit? Save this tender and qualify it in Stotles

Value

200,000 GBP

Close date

2026-07-23

Description

The objective of this Market Research is to search for suppliers capable of delivering a continuous feed of representative embedded PV generation data that meets the following outcomes: 1. Improve system visibility: Provide near real time insight into embedded PV output across Ireland and Northern Ireland. 2. Support operational forecasting: Enable EirGrid and SONI to better predict short term solar output changes by creating proxy forecasts for the locations of the data supplied by the tender winner(s) and then use the actual generation of the proxy sites to fine tune the actual forecast. 3. Provide a geographically representative dataset: Ensure broad dispersion and diversity of PV sites to reflect system-wide behaviour. 4. Deliver high data quality and reliability: Ensure data is accurate, validated, and free from distortions such as behind the meter battery interactions.

Unlock decision maker contacts.

Never miss a tender again

Get alerts, AI summaries and tools to qualify faster

Explore similar pre-tenders, open or awarded contracts

Browse open tenders, recent contract awards and upcoming contract expiries that match similar CPV codes.

Kent County Council

1,500,000,000 GBP

Published 5 days ago

West Berkshire Council

Published 12 days ago

Education Buying Group Ltd

80,000,000 GBP

Published 20 days ago

Warwickshire County Council

Published 21 days ago

Network Rail

125,000,000 GBP

Published a month ago

London Borough of Newham

2,200,000 GBP

Published a month ago

London Borough of Tower Hamlets

20,000,000 GBP

Published a month ago

London Borough of Barking and Dagenham

Published a month ago

Milton Keynes Council

12,000,000 GBP

Published a month ago

Sign up to the Stotles Tender Tracker for free

Find even more contracts with advanced search capability and AI powered relevance scoring.