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Projects: Projects for Investigator
Reference Number	NIA_NGET0177
Title	Solar PV Forecasting Phase 1
Status	Completed
Energy Categories	Renewable Energy Sources(Solar Energy, Photovoltaics) 75%; Other Power and Storage Technologies(Electricity transmission and distribution) 25%;
Research Types	Applied Research and Development 100%
Science and Technology Fields	PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics) 50%; ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 25%; ENVIRONMENTAL SCIENCES (Earth Systems and Environmental Sciences) 25%;
UKERC Cross Cutting Characterisation	Not Cross-cutting 100%
Principal Investigator	Project Contact No email address given National Grid Electricity Transmission
Award Type	Network Innovation Allowance
Funding Source	Ofgem
Start Date	01 April 2016
End Date	01 April 2018
Duration	24 months
Total Grant Value	£440,000
Industrial Sectors	Power
Region	London
Programme	Network Innovation Allowance
Investigators	Principal Investigator	Project Contact , National Grid Electricity Transmission (100.000%)
Web Site	http://www.smarternetworks.org/project/NIA_NGET0177
Objectives	The objectives of the project are to reduce demand forecast error attributable to embedded solar PV as a result of researching improvements in solar irradiance forecasting methods. In order to achieve the objectives, the following work packages will be pursued and delivered: Post Processing Work Packages: WP 1 - Refinements to the existing solar radiation forecasting capability to best suit National Grid’s requirements Clear evidence shows the Met Office Global and Regional Ensemble Prediction System (MOGREPS) UK ensemble has a tendency to be too cloudy, which has a particularly strong negative impact upon solar radiation forecasts. For Day +1 forecasts, the Met Office will test replacing MOGREPS-UK with the global MOGREPS-G (Global) ensemble output which demonstrably performs well from Day +2 onwards. They will also test replacing the MOGREPS-UK ensemble mean with a blended forecast using multi-model solar radiation, including output from the Met Office’s high resolution deterministic Numerical Weather Prediction (NWP). If testing demonstrates these changes are positive, the Met Office will implement these improvements by Summer 2016. WP 2 - Investigation and development of statistical post-processing techniques A number of techniques exist that can add value to raw forecasts through learning systematic error characteristics from making use of existing radiation observations. The Met Office currently deploys Kalman Filtering to temperature and wind speed. Application of a Kalman Filter; perhaps to normalised solar radiation, will be tested and assessed. The Met Office will also explore other techniques such as Model Output Statistics (MOS) and Neural Nets and potential combinations of techniques. Where these demonstrate added value, the aim will be to develop them into the Met Office operational environment by Summer 2017. A report of these methods will be published as part of the project deliverables. WP 3 - Development of a gridded solar radiation Nowcast Accuracy in the 4-6 hour period is operationally significant for National Grid. The Met Office have an hourly updating Nowcast capability that combines observational data from both weather stations and satellite imagery with the latest high resolution NWP for a number of key parameters. This work package would extend that capability to solar radiation, for which both station and satellite measurements offer the clear potential for improving the fit to reality in the earliest hours of the forecast. The Met Office would also explore whether real-time available PV readings could be reverse-engineered to give an additional observational source of solar radiation, with good spatial coverage, that could be integrated into the Nowcast. The aim would be to operationalise by Summer 2017. Core Science Work Package: WP 4 - Focussed development of core NWP cloud/radiation schemes This work package aims to: Perform research into model development that could lead to improvements in the forecasting of cloud and radiation at the surface. Deliver a report on research and development aimed at improving the representation of clouds, radiation and their interaction within the forecasting system. Provide a reference for future improvements in the MOGREPS forecasting system that would directly benefit the irradiance forecasts National Grid receive. This project’s aim is to drive improvement in the key climatological variable that feeds National Grid’s PV generation forecast model. These Improvements can be more accurately measured by comparing National Grid PV forecasts derived on project completion with the PV outturn data calculated using the method given by the NIA PV Monitoring Phase 2 project (NIA_NGET0170). Post Processing Work Packages Immediate improvement in National Grid’s operational PV power forecasts, including those published for industry visibility. Reduction of demand forecast error. This would lead to reduced balancing costs for managing the current level of solar PV on the system and reducing the costs to consumers of introducing further solar PV on the power system. Core Science Work Package: This work package would support and boost research and potential development in the fundamental cloud/radiation physics at the heart of our Numerical Weather Prediction (NWP) models. Where, as a result of this focus, the Met Office identify improvements, they will work to develop these into their operational capability as means to provide improved solar irradiance forecasting. However, the Met Office has to ensure that enhancements do not adversely affect other applications of NWP and for this reason cannot commit to specific timelines. A progress report will be provided in the research and development pertinent to solar radiation forecasting at appropriate intervals through the life of the project.
Abstract	There is approximately 8GW of solar photovoltaic generation in Great Britain as of November 2015, which consists of over 600,000 individual sites. The majority are 3. 3kW domestic installations which sit on the distribution networks. National Grid has no direct visibility of this generation as there is no obligation for National Grid to receive metering for such low level but numerous installations from the electricity distribution networks. The only visibility is in the indirect result of demand suppression seen in Grid Supply Point metering. This increasing capacity of weather dependent generation has led to an increasing demand forecast error and a need for higher reserve levels as a result. Improving solar PV power forecasts is one way in which the forecast error can be reduced which in turn will reduce the need for higher levels of reserve and hence balancing costs. The key weather variable that determines PV forecast model accuracy is irradiance. Sunshine is however subject to significant temporal and spatial variability, due to the complex and dynamic distribution of cloud. This makes it challenging to predict accurately. Innovations and further research in this area will help achieve improvements in the irradiance forecasts National Grid receives. Cloud is the principal source of error in solar radiation forecasts. This is because interception by cloud introduces significant variability into the amount of radiation reaching the ground. In order to estimate surface solar radiation, Numerical Weather Prediction (NWP) models need to correctly establish several factors related to clouds, such as whether there is cloud at all, the proportion of sky coverage and the optical thickness of the cloud, as well as how these factors evolve over time. Much of this variability operates at scales at which NWP cannot wholly resolve. Whilst there is scope to target improvement in the NWP, there is also strong potential to develop post-processing techniques and statistical correction tools to better handle the uncertainties that remain in the Numerical Weather Prediction (NWP) leading to improvement in the end solar radiation forecast supplied to National Grid from the radiation forecast provider.Note : Project Documents may be available via the ENA Smarter Networks Portal using the Website link above
Publications	(none)
Final Report	(none)
Added to Database	11/12/18