Optimal Integration of Power System Infrastructure through AI-based Spatial Planning (Opti-AI)

About

The EU’s vision for a climate-neutral economy by 2050 necessitates profound changes in the power system, especially with the shift towards renewable energy sources (RES) and distributed energy generation. This transformation is further propelled by the electrification of heating and transport sectors, leading to increased and variable power flows at the distribution network level, necessitating a robust reinforcement of the power network infrastructure.

While various solutions for network planning based on electrical properties have been proposed in the literature, spatial planning, which involves the placement of transformers, conductors, and other elements within a targeted geographic area, is still underexplored and remains a significant challenge. The current process of spatial power-system infrastructure planning is predominantly manual, slow, and requires extensive local geographical, demographic, and land-use knowledge. However, leveraging on public data on land use, land registry, spatial plans, existing infrastructure, and satellite imagery can automate and optimize this process to a significant extent, addressing the urgent need for efficient spatial planning in the evolving power system landscape.

Within the proposed fundamental research project “Optimal Integration of Power System Infrastructure through AI-based Spatial Planning (OPTI-AI)” we aim to develop an innovative approach to spatial planning of power system infrastructure, utilizing artificial intelligence (AI) and machine learning. The project will enhance the efficiency of low and medium voltage power networks by addressing the spatial planning challenges that arise from various characteristics of the targeted geographic area, ranging from the terrain topology, land ownership, long-term municipality plans and other similar factors. The project is being implemented around three key components, involving:

  • Network Development Scenarios: Defining scenarios that satisfy the required power transfer capacity in the selected geographical area.
  • Geographical Area Segmentation Using AI: Utilizing machine learning models to segment and categorize different parts of the geographical area for infrastructure installation. This component involves an AI-driven instance segmentation process leveraging data like land use, land registry, and satellite imagery.
  • Optimization Procedures for Spatial Planning: An optimization algorithm that considers both the electrical properties of the network and the characteristics of the geographical area to achieve optimal spatial planning with minimal costs and environmental impact.

The main tangible result of OPTI-AI will be a scalable and replicable framework for power system infrastructure planning, contributing to more efficient and environmentally sustainable power networks. This approach promises significant advancements in the field, potentially leading to widespread improvements in power system planning and management.

Opti-AI (ARIS: J2-60030) is a fundamental research project funded by the Slovenian Research and Innovation Agency (ARIS) in the period: 1.1.2025 – 31.12.2027 (1,31 FTE per year).

The Principal Investigator (PI) of Opti-AI is Prof. Vitomir Štruc, PhD.

Link to Sicris: TBA

Project Overview

Opti-AI is structured into 6 work packages:

  • WP1: State-of-the-art review
  • WP2: Network development scenarios
  • WP3: Instance segmentation of geographical areas using machine learning
  • WP4: Optimal spatial planning for the power system infrastructure
  • WP5: Communication, dissemination and exploitation of the results
  • WP6: Project management

Project Phases

  • Year 1: WP1, WP2, WP3, WP4, WP5, WP6
  • Year 2: WP3, WP4, WP5, WP6
  • Year 3: WP3, WP4, WP5, WP6

Partners

Participating Researchers

Funding Agency