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Projects: Projects for Investigator
Reference Number NIA_NGTO016
Title WATTS – Weather Analytics for The Transmission System
Status Completed
Energy Categories Other Power and Storage Technologies(Electricity transmission and distribution) 50%;
Other Cross-Cutting Technologies or Research(Energy Economics) 25%;
Other Cross-Cutting Technologies or Research(Environmental, social and economic impacts) 25%;
Research Types Applied Research and Development 100%
Science and Technology Fields PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics) 10%;
PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 10%;
ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 50%;
ENVIRONMENTAL SCIENCES (Earth Systems and Environmental Sciences) 30%;
UKERC Cross Cutting Characterisation Systems Analysis related to energy R&D (Energy modelling) 100%
Principal Investigator Project Contact
No email address given
National Grid Electricity Transmission
Award Type Network Innovation Allowance
Funding Source Ofgem
Start Date 01 September 2018
End Date 01 May 2019
Duration ENA months
Total Grant Value £360,000
Industrial Sectors Power
Region London
Programme Network Innovation Allowance
Investigators Principal Investigator Project Contact , National Grid Electricity Transmission (100.000%)
  Industrial Collaborator Project Contact , National Grid plc (0.000%)
Web Site https://smarter.energynetworks.org/projects/NIA_NGTO016
Objectives This feasibility project will assess the impact of the weather on ET congestion, modelling a simplified representation of the GB transmission system. This research will focus on the following three areas:Focus 1 - Long-term statistics of weather-sensitive supply, demand and transmission congestion Focus 2 - The impact of future renewable generation deployment on transmission congestion Focus 3 - The attribution of constraint payments to specific weather regimes This feasibility project will be split into two primary phases. Phase 1 comprises data collection and processing, whereas Phase 2 is further sub-divided into sections addressing each of the focus points introduced in the method section above. Phase 1Weather modelling: 10+ years of hourly weather data of UK will be generated using a weather prediction model. Long-term weather data from global weather models will be extracted, resulting in 35+ years of hourly weather data Data pre-processing: NGETs GB transmission network will be split into several zones Weather-sensitive supply, demand and weather data will be zonally-aggregated Supply and Demand modelling: The total weather-sensitive generation and demand for each transmission zone will be determined as a function of the input weather conditions Flow model: A model will be developed to simulate flows between transmission zones based on the supply and demand in each zone, and the transmission capacity between zones This will operate on a time-step by time-step basis Further development of this model will continue in Phase 2 Phase 2Focus 1: Long-term statistics of weather-sensitive demand, supply and transmission congestion Determine long-term statistics of weather-sensitive supply and demand in each zone Apply the simplified electricity flow model to estimate long-term congestion statistics Assess the net impact of the weather on the observed long-term trends in supply and demand, and discuss the implications for transmission congestion Assess the severity of recent levels of congestion relative to the range that could occur given at least 10 years of weather data Focus 2: Impact of future renewable generation deployment Investigate the statistical co-dependence of supply and demand across the GB network, and its implications for transmission congestion Assess the impact of increasing levels of renewable supply on transmission congestion, based on the expected future deployment of renewables Focus 3: Attribution of constraint payments to specific weather regimes Identify recent constraint payment events using data provided by NGET Investigate the weather patterns associated with individual constraint events Use advanced data analytics techniques to identify the dominant weather regimes associated with weather-driven constraint payments Estimate the likelihood of weather-driven constraint payments occurring, based on a wide range of possible weather conditions, and place recent events into context Analyse the profiles of weather-sensitive demand and supply in different parts of the system Combine simulated weather data with the flow model to estimate the impact of weather on transmission congestion in different parts of GB Analyse the statistical co-dependence of weather-sensitive demand and supply in different parts of the GB transmission system Investigate the impact of planned renewable generator installations on transmission congestion Investigate the degree to which past constraint payment events can be attributed to the weather
Abstract Increasing amounts of renewable energy are creating new challenges for transmission system balancing. As both supply and demand in Great Britain become increasingly weather-sensitive, levels of congestion across transmission zone boundaries may experience increased variability. This could give rise to significant changes in the level of congestion from year to year, and changes in the likelihood of boundaries coming under stress due to extreme weather events. The weather adds complexity by introducing spatial and temporal relationships between weather-sensitive demand and generation across the transmission system. Limited transmission capacity between zones leads to varying levels of weather-induced congestion in different parts of the country. When excess supply in one transmission zone cannot be safely transported elsewhere, it incurs a cost. Understanding the impact of a wide range of possible weather scenarios on transmission congestion is important in order to manage the network cost effectively and provide the best service to consumers as reinforcements can be planned in advance and proactively.
Publications (none)
Final Report (none)
Added to Database 09/11/22