Optimal planning of grid and charging infrastructure - WP4

Research Scientist

This WP will develop methods and a software framework for optimal planning of grid and charging infrastructure, with the aim of achieving higher utilisation of the total energy capacity in the existing and future grid. Within this WP, the changing role of the DSO from a traditional/passive DSO to an active DSO (actively managing grid participants) is considered. Thus, the traditional methods for grid planning of a DSO will be used as reference. More advanced planning and optimisation of active distribution systems will be evaluated on this basis, acknowledging that planning and operation can no longer be considered as separate tasks. The charging infrastructure may be considered as a new layer in such a framework, employing a multi-objective approach.

WP4 will focus on research question Q4 and will be based on the results obtained in WP1-WP3. The WP is divided into four subtasks:

Task 4.1 – Load models for active grid planning

Investigate how knowledge regarding charging profiles for different types of EVV can be incorporated in active grid planning (WP2), and how charging stations can be modelled on an aggregated level. Charging profiles and models for different types of EVV and knowledge about user behaviour (WP1-WP2), in combination with charging technology and control strategies for utilisation of available flexibility (WP3), will enable development of load models for EVV that will be used as input to an optimisation model.

Task 4.2 – Impact of EVV increase on traditional grid planning

Develop a reference scenario, where the DSO has no influence on sizing, allocation and operation of the EVV charging infrastructure and solves all arising issues with traditional grid expansion measures. The reference case will be developed in close cooperation with the DSOs.

Task 4.3 – Optimisation model for active grid planning

Develop an optimisation model for active grid planning, based on the knowledge, load models and control strategies developed in previous WPs and tasks, with the aim of achieving more optimal time and space distribution of charging demand. The framework of the optimisation model will be developed in the project, taking grid data developed in WP1 (synthetic grids or actual grid data), load models, costs and constraints as input. The optimisation model will consider the potential utilisation of flexibility in charging infrastructure (active and reactive power control), as well as the benefit of installing stationary battery storage (sizing, allocation). The aim is to optimise the utilisation of grid infrastructure and hence minimising total costs (social welfare perspective vs. DSO's perspective). This will be achieved using a (linear/non-linear) optimal power flow and/or combing it with other suitable optimisation algorithms (e.g. genetic algorithms, MILP). Cost-benefit analyses of different scenarios (outcome of a close cooperation with all the partners involved) will be performed and compared to the reference scenario developed in Task 4.2.

Task 4.4 – Impact of EVV increase on active grid planning and operation

Develop a methodology for optimal decision-making in active grid planning, considering charging profiles, charging infrastructure, costs (cost-benefit analyses) and different flexibility alternatives (based on previous tasks and WPs). This task will quantify the technical and economic results of the optimisation model developed in Task 4.3.