This project will develop a comprehensive whole-system methodology, and a relevant prototype tool, to quantify, with high temporal and spatial resolution, the electricity transmission network infrastructure impacts of heat and transport decarbonisation scenarios. The method, which will consider multi-energy vector modelling of heat and transport, will be demonstrated with comprehensive case studies based on Greater Manchester. The project will also explore innovative solutions to meet future energy demands to deliver cost benefits to the consumers. It will review the traditional way of bottom-up electrical network reinforcement approach.
Objectives
1. Assess the impact of different solutions, for the decarbonisation of heating and transport, on the electricity transmission network infrastructure requirements by multi energy vector modelling.
2. Develop a prototype tool for whole system modelling with high spatial and temporal resolution.
Learnings
Outcomes
The key outcomes of the project include:
- Electricity profiles for demand and generation and aggregated annual demand and generation from (i) heating, (ii) cooking, (iii) transport and (iv) distributed generation for selected years (i.e. 2030, 2040 and 2050) at the primary substation, Bulk Supply Point (BSP) and Grid Supply Point levels.
- Beside the modelling of the energy mixture (e.g. integration of electric vehicles, use of heat pumps, etc.), the sizing and operation standards are also key factors which can have a significant impact on both the associated carbon emissions, peak electricity demand, and network reinforcement requirements, therefore affect the outcomes of the pathway.
- The large integration of low carbon technologies and DHN can further stress distribution networks and lead to costly reinforcements. A share of these reinforcements could be avoided, by connecting the most energy demanding technologies, such as DHN, at the transmission level.
- A prototype whole-system analysis tool in MATLAB is developed. The tool includes CBAs for the assessment and comparison of decarbonisation scenarios, as well as for the optimisation of the operation of flexible technologies such as storage. The tool also allows customisation of sizing and operation rules for heating technologies, DHN integration, population growth, building insulation improvements, and other settings, which are described in the user guide.
- Recommendation for further work on network models: The proposed prototype tool estimates energy consumption at the primary substation, BPS and GSP levels through aggregation. More accurate results, including detailed estimation of power losses and system constraints, and also capturing impacts at the transmission level could be achieved by including power flow studies in future. Furthermore, the use of integrated (power-gas/hydrogen) network models would be recommended to facilitate developing decarbonisation scenarios that minimise investments in new assets by better utilising existing multi-network infrastructures.
Lessons Learnt
It was found that access to proper data was challenge considering the level of data availability and consistency may vary across different region and type of energy in demand profile. In addition, due to the changes of the key energy scenarios FES and DFES over the last year, the outputs of the project had to be revised accordingly to reflect the change. It’d be helpful if the project can foresee impacts associated with changing of energy scenarios and address it during the development of the project scope or at the beginning of the project in the project plan.
Dissemination
Multi Energy Vector Modelling: investigating the impact of decarbonisation, Session Presentation, Energy Networks Innovation Conference, 9th December 2020.
