Projects
Projects: Summary of Projects by RegionProjects in Region Scotland involving Scottish and Southern Energy plc : NIA_SSEN_0045 |
||
| Reference Number | NIA_SSEN_0045 | |
| Title | Future Fiscal Forecasting | |
| Status | Completed | |
| Energy Categories | Other Power and Storage Technologies(Electricity transmission and distribution) 10%; Other Cross-Cutting Technologies or Research(Energy Economics) 50%; Other Cross-Cutting Technologies or Research(Environmental, social and economic impacts) 40%; |
|
| Research Types | Applied Research and Development 100% | |
| Science and Technology Fields | SOCIAL SCIENCES (Economics and Econometrics) 50%; SOCIAL SCIENCES (Business and Management Studies) 40%; ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 10%; |
|
| UKERC Cross Cutting Characterisation | Systems Analysis related to energy R&D (Energy modelling) 100% | |
| Principal Investigator |
Project Contact No email address given Scottish and Southern Energy plc |
|
| Award Type | Network Innovation Allowance | |
| Funding Source | Ofgem | |
| Start Date | 01 March 2020 | |
| End Date | 01 December 2020 | |
| Duration | ENA months | |
| Total Grant Value | £131,500 | |
| Industrial Sectors | Power | |
| Region | Scotland | |
| Programme | Network Innovation Allowance | |
| Investigators | Principal Investigator | Project Contact , Scottish and Southern Energy plc (100.000%) |
| Industrial Collaborator | Project Contact , Scottish and Southern Energy plc (0.000%) |
|
| Web Site | https://smarter.energynetworks.org/projects/NIA_SSEN_0045 |
|
| Objectives | This project will look to implement a new forecasting model from USA to help inform future solutions across SSEN and the wider industry. This project will test the hypothesis that the use of GB Settlement sourced fiscal metering (referring to recording electrical energy flow for each half hour for Settlement (Half Hourly Metering Systems)) in combination with SCADA data and weather data will lead to more accurate forecasts for fiscal purposes.The project will utilise existing or readily available data sets (as mentioned in the above paragraph) in combination with an alternative to conventional forecasting techniques. This alternative technique is part of the new suggested in-house developed forecasting model that the supplier will use in this project. The project will primarily focus on the use of existing data sets currently available within the existing GB market, however, it will also develop insights to inform the use of data sets which may become available such as those from smart metering.The project will use a blind back-cast technique (a method that starts with defining a desirable future and then works backwards to identify policies and programs that will connect that specified future to the present) to allow comparisons between forecast and actual data sets.To accelerate analysis, the project will not implement enduring data exchange approaches and will instead adopt more adaptable and temporary methods (such as File Transfer Protocol) preserving all the necessary safeguards for GDPR etc. This project will use GB Settlements sourced fiscal metering in combination with SCADA data and weather data to: 1) forecast energy consumption for a Distribution Service Area and disaggregate this into the corresponding GSPs i.e. the SEPD DSA and 18 GSPs;2) Forecast energy consumption for a sample of HV feeders with a high uptake of demand or generation (two generation dominated, and two demand dominated) Project findings will be communicated in a written report and shared amongst GB DNO experts via a face to face workshop. The project objectives include: assessment of the availability and suitability of current and future data sources which could provide more detailed fiscal forecasting of energy volumes; an assessment of methodology to be used; and a quantitative evaluation of the level of accuracy of the new forecasting model | |
| Abstract | This project will use GB Settlements sourced fiscal metering in combination with SCADA data and weather data to: 1) forecast energy consumption for a Distribution Service Area and disaggregate this into the corresponding GSPs i.e. the SEPD DSA and 18 GSPs;2) Forecast energy consumption for a sample of HV feeders with a high uptake of demand or generation (two generation dominated, and two demand dominated)Project findings will be communicated in a written report and shared amongst GB DNO experts via a face to face workshop. | |
| Data | No related datasets |
|
| Projects | No related projects |
|
| Publications | No related publications |
|
| Added to Database | 02/11/22 | |
