Power & Utilities
Orbital Vegetation Monitor
Using machine-learning to monitor vegetation height and cover, and other environmental impacts, of operations using data from active and passive sensors in orbit.
Field of Expertise
Power (wind, solar, thermal generation, transmission & distribution networks, smart grids, storage), Gas (transmission and distribution networks), energy markets and regulation and whole system planning.
Expertise
DNV-GL’s relevant expertise • Advisory – full suite of technical and techno-economic advisory services across the entire power and gas value chain from policy to use • Data and analytics – From developing comprehensive power and gas data analytics implementation road-maps to turn-key analytics services • Software – Solutions to improve asset management and operation for power & renewables and gas and electric transmission & distribution networks. Consumers and asset owners benefit from our expertise and solutions through: • Improved accuracy in short term demand forecasting using demand and weather data • Improved demand behaviour modelling • Improved system resilience and operation by market and network modelling including network constraints. • Cost savings through efficient operation Examples of recent projects that have delivered value to UK gas and power consumers: 1. Real Time Networks Innovation project This is a large-scale, real-time demand modelling project, which was delivered successfully and included a wide range of innovations that give value to the customer. These included dramatic improvements in demand estimation accuracy for network modelling, from the single load to the full LDZ level, and a novel diversity method that for the first time allows demand diversity to be calculated correctly at all levels across complex looped networks, from source to extremity. The demand estimation improvements from the project will allow better validation and operational decisions to be made, and in particular the improvement in modelling accuracy of large load groups leads to a reduction of up to 30% in peak load at network source, reducing open-cut replacement and avoiding the need for unnecessary reinforcement. The focus of Real Time Networks is the gas network, but many of the techniques developed are applicable to the Real Time Operations project and the electricity market. This provides an excellent foundation for the work, with methods in place whose accuracy has been proven when applied to energy networks. Whilst the initial phase of the Real Time Operations work is specific to electricity demands and the need for gas generation, the wider project is in effect an extension of the Real Time Networks concepts to the full energy market (gas plus electricity). Expanding real time concepts to cover energy as a combined entity completes the loop, and DNV GL’s experience with successfully delivering Real Time Networks puts us in a unique position to deliver the Real Time Operations Challenge. 2. Electricity DNO – review of MV network performance Strategic review of entire MV network to study the current and future performance of its 350 circuits and identify where future investment will be required. The study involved running load flow analysis and contingency analysis on each circuit to establish where there are capacity or voltage constraints. This study also looked at the current performance of the network and the impact of future demand growth. The results of the review are being used in discussions on future investment plans with the industry regulator as part of the current price review. Critical to the discussions were the investment plans to invest in areas where capacity or voltage constraints were identified by the project. Operationally the results of the study are available for planning areas to prioritise work on the circuits that are most stressed ensuring risks to end consumers are minimised in an economic and efficient manner. 3. Scottish Power Energy Networks – Project FUSION DNV-GL is a leading Project Partner in SPEN’s Network Innovation Competition (NIC) funded Project FUSION. FUSION looks to apply the Universal Smart Energy Framework (USEF) to the GB electricity market context to explore how the value of demand and generation flexibility within the distribution networks can be unlocked more quickly than it otherwise would. FUSION seeks to establish a local flexibility market based on the rules and protocols within USEF to investigate how local flexibility can be unlocked to manage constraints on SPEN’s networks as a viable alternative to refurbishment and/or replacement of assets. FUSION hopes to demonstrate that accelerating the unlocking of local flexibility can deliver multiple benefits to consumers, particularly new revenue streams for demand fluctuation in response to DNO/DSO requirements and overall reductions in the cost of operating the system resulting in lower consumer bills. 4. Demand Forecasting DNV-GL provides short-term demand forecasting software and consultancy to the UK gas transmission and distribution networks (including WWU). DNV-GL also provides short-term energy forecasting services for effective management of renewable (wind and solar) assets. Synergi Forecaster is a solution based on over 20 years of gas demand forecasting expertise and uses the latest statistical and neural network based algorithms. It generates accurate short-term gas demand forecasts 24/7 which are vital in supporting the efficient operation of the UK gas transmission and distribution networks. Synergi Forecaster is deployed operationally to receive live network flow and weather data to provide the most accurate forecast possible for network control room staff. Accurate forecasts provide benefits through more efficient network operation, improved trading decisions and through the current forecasting incentives schemes. Synergi Forecaster is already used by the UK gas transmission control room to predict the gas demand from the aggregate NTS connected power station load. This is based on historic demand patterns and weather but also uses additional publicly available data such as generation by fuel type. DNV-GL believe there is significant scope to improve forecasts by utilising additional data shared such as actual flows, notifications and capacity constraints. Summary of Expertise In summary, DNV-GL can add valuable expertise and solutions to the Real Time Operations Innovation Challenge goals of: • Improved data sharing • Shared information on network constraints. • Shared short term forecasting. These goals will deliver clear benefits to gas and electricity customers and stakeholders through: • Cost, CO2 and efficiency savings through improved forecasting • Whole system operation, supporting future hybrid heating systems, flexible and intermittent renewable generation • Improved transparency, use and sharing of data We propose delivering these goals through an innovation project, described at high level in the Vetting section.