A. Load Scenarios with Electric Heat
- Generate baseline and future scenarios of ‘Grid and Primary’ load with initial improvements to method (summer 2015)
- Develop disaggregated domestic heat pump scenarios – moving on from the single domestic heat pump type in the ‘Transform’ model to up to ten heat pump / house type combinations, and modelling how load profiles are affected by both thermal load and supplier/ system operator incentives – working with DELTA EE and Imperial College (end 2015)
- Deliver an improved assessment of thermal and voltage constraints for the secondary networks including heat pump inputs (early 2016)
- Generate baseline and future scenarios of load at ‘Grid and Primary’ and secondary networks including various incremental improvements to inputs and method (summer 2016)
B. Commercial Capacity Options (based on Load Scenarios)
- Definition of a ‘real options’ approach and tool to support decisions on DSM versus various scales of ‘Grid and Primary’ reinforcement under demand uncertainty
- Identification and prioritisation of intervention options beyond the customer meter to address secondary networks constraints
This project is innovative because no other DNOs has developed this type of granular analysis of uncertain demand, or investigated these commercial approaches to capacity issues.
The financial benefits of the project will come from ensuring that load-related investment is well justified, and in particular by identifying where the Capacity to Customers DSM technique or customer interventions beyond the meter can be used to avoid or defer load-related investment. This will be done by more accurately and credibly representing current and future load, to minimise load-related expenditure to deliver only the justified capacity. It will also provide the foundation for future use of commercial solutions where these can be shown to provide an overall cost benefit. These commercial solutions also offer the opportunity to release capacity more quickly than traditional network solutions (customer service benefit), and with lower environmental impact e.g. reducing electricity demand, avoiding embedded carbon associated with new network assets. It is also expected that the project will streamline analysis of demand in the planning process, allowing our engineers to take a more sophisticated view of current and future demand, without an increase in planning engineer resource.
A. Load Scenarios with Electric Heat
- Appropriate methods implemented to correct observed past Grid & Primary peak demand for weather effects and distributed generation contribution, balancing accuracy with cost.
- Enhanced quantification of impact of growth of electric heating in 2022 and 2030 on the Electricity North West network under different scenarios – using analysis of different types of heat pumps in different housing types. High-level analysis of a provisional scenario to 2050.
- Quantification of how other electricity value chain players’ influence of electric heating operation will affect this impact (either reducing the impact and / or increasing the impact at different times) in 2022 and 2030, with high level view to 2050.
- Revised tools and methods available to generate credible Grid & Primary and secondary networks peak load scenarios by asset to 2030, reflecting the scale and sources of uncertainty in demand, with scenarios used for internal and external business requirements.
B. Commercial Capacity Options
- Created a ‘Real options’ decision approach with supporting Excel tool(s), supported by the University of Manchester’s analysis, which uses demand scenarios to make an economic assessment of whether to use the Capacity to Customers post-fault DSR method versus traditional reinforcement.
- Identification, initial assessment and ranking of ways that Electricity North West can mitigate (other than reinforcing the network) the impact that electric heating will have on their network (focusing on the customer side of the meter).
Internal / external dissemination of results from both aspects of project is detailed in the ‘potential for new learning’ section.