Public procurement notice: Contract Notice
Published: 2022-07-06
Buyer: Sustainable Energy Authority of Ireland
Country: IE
Contract type: Services
Procedure: Open procedure
CPV classification: 38221000 | 71314000: Energy and related services | 71314300: Energy-efficiency consultancy services | 71356000 | 72212461
Estimated value: 16400000 EUR
Submission deadline: 2022-08-01
Award criteria: The most economic tender

Technical requirements: The objective of this RFT is to establish a framework for expert services in support of SEAI’s Research and policy Insights Directorate. This RFT is issued with the objective of to establish frameworks of experts comprising of the following: Lot 1: Sustainable energy policy research and advice. Lot 2: Energy model development and support. Lot 3: Sustainable Energy Finance and programme / policy impact evaluation (including Cost Benefit Analysis). Lot 4: Framework for the Provision of Market Research Services. Lot 5: Sustainable Energy Research. Lot 6: Behavioural Science, Experimental Design and Evaluation. Lot 7: Data Gathering and Quality Control. Lot 8: Decarbonised heat
Lot 9: Provision of Support to Public and Professional Bodies (in developing and adopting SEAI Best Practices in the electricity and wind energy sectors. Lot 10: Offshore renewables policy and research support. For further information please visit the RFT on www.etenders.gov.ie
SEAI will draw upon the appointed experts to undertake several diverse tasks to include (but not limited to) the following:
Policy research (including reviews of published literature and provision of expertise) with a focus on driving uptake for existing and emerging low carbon technologies (including wind, bioenergy technologies, solar PV, offshore, ocean, heat pumps, hydroelectric, district heating etc.) and energy efficiency measures.
SEAI do not require tenderers to be proficient in all of the above topics or associated key skills/knowledge, but they should clearly indicate relative strengths/weaknesses and suitability of each task/field indicated.
Subject to satisfactory performance, organisational needs and budget availability, may be extended for up to two consecutive periods of twelve months each on the same terms and conditions, depending on the project’s progression and subject to SEAI’s obligations at law.
SEAI will draw upon the appointed experts to undertake several diverse tasks to include (but not limited to) the following:
1.	Development of bespoke energy models and provision of technical analysis for informing sustainable energy policy making.
2.	Enhancement of existing energy models, modelling methodologies, data sources, data management and quality control/assurance (QAQC) practises, and policy assessment tools, including:
a.	Models for heat, energy efficiency, electricity (PLEXOS), transport, energy infrastructure, and cost-benefit analysis, which are integrated within the National Energy Modelling Framework (NEMF) – link to more detail at the footnote  .
b.	Renewable energy support schemes, such as the Support Scheme for Renewable Heat (SSRH), and Micro-Generation Support Scheme (MSS).
3.	Support the development and maintenance of the Python-based NEMF, including version control, program efficiency, documentation, training, feature enhancement, visualisation, QAQC, and user interface and inputs interaction.
a.	Model verification and in-depth review of model inputs, processes, calculations, algorithms and outputs.
b.	Data management and QAQC processes (including templates, protocols for filing, model development and utilisation, and data sourcing.
SEAI do not require tenderers to be proficient in all of the above topics or associated key skills/knowledge, but they should clearly indicate relative strengths/weaknesses and suitability of each task/field indicated. The complexity of the modelling work varies form bespoke excel based energy policy models, to the fully detailed energy system wide modelling framework referred to above and described in the footnote below as the National Energy Modelling Framework, (NEMF).


Award value: 16400000