SWITCH

SWITCH

Stabilizing weak grids through machine learning: empowering farmers in end‐of‐ line‐communities in North Africa through artificial neural networks

Coordinator of the project:

Technische Hochschule Ingolstadt Prof. Dr.‐Ing. Wilfried Zörner

Partners list :

• Technische Hochschule Ingolstadt (THI), Institute of new Energy Systems (InES) – Germany
• Women engage for a common future (WECF) – Germany
• University Ain Temouchent (UAT) – Algeria
• University of Adrar (UA) – Algeria
• Al Akhawayn University (AUI) – Morocco
• University Mohammed Premier (UMP)– Morocco
• Institut National des Postes et Télécommunications (INPT) – Morocco
• Aitown S.R.L. – Italy

Overall Objectives

SWITCH aims at developing an innovative and holistic solution to stabilize weak grids and enhance security of supply in such rural ‘end-of-line’ communities in North Africa.

Context: why is this action necessary?

For several decades, the increase in electricity demand worldwide has become a concern as it strains existing power generation and transmission capacities. North Africa is one of the regions, where gird face critical technical and economic challenges due to the rising demand of a rapidly growing population, limited growth in power generation capacities and the transition to fluctuating renewable

energies (RE). Especially regional distribution grids are facing severe challenges with reliable supply. Such so-called ‘weak grids’ are characterized by unstable frequencies and are prone to outages. Rural farming communities are particularly affected and have to shift to costly, non-sustainable fuels (i.e., diesel generators) during power outages. A stabilized grid and distributed energy resources can provide reliable access to energy as well as mitigate the intensive use of non-sustainable practices in rural communities. However, there is a lack of science-based solutions and methods for ensuring reliable supply in such situations on a community level considering the local boundary conditions.

What are the concrete actions that will be implemented?

A multi-disciplinary team will investigate how the electricity supply in ‘end-of-line’ communities in Morocco (MAR) and Algeria (DZA), suffering from frequent power outages, can be improved through integration of smart RE systems, Artificial Intelligence (AI)-driven prediction methods and optimal Agri-PV solutions for islanding on the local level, while at the same time increasing local revenues. SWITCH aims to provide a flexible approach to address the challenges for end-of-line communities through temporary islanding of distributed renewable energy generators. This will be directed by a novel and openaccess AI-driven tool based on predictions of power outages, solar power availability and local demand. It will guide local operators/ users to operate their smart decentralized energy supply system (Agri-PV) in a way that such Agri-PV systems can support a weak grid during regular operation and supply electricity to key consumers in ‘end-of-line’ communities autonomously in case of power outages through islanding.

What is the expected impact of the project?

Based on the comprehensive training and the dissemination activities, the short- to mid-term impacts of the project include that both involved grid operators use and promote the AI-driven decision support tool and that the designed Agri-PV blueprints are fully rolled-out in the pilot communities. Both of these aspects will significantly contribute to reduction of power outages in the local rural grids. The long-term impacts od SWITCH outline that the tool is being introduced throughout the North African region to various grid and system operators (private and public) and 20 more smart Agri-PV systems have been installed in rural communities. As a result, the local grids in the pilot regions in DZA & MAR are functioning without relevant outages and stakeholders in neighbouring countries start formulating similarly favourable conditions for REs.

In resume, SWITCH will increase energy access in rural areas and the use of REs, while giving access to affordable energies to the largest number of beneficiaries and maximizing the socio-economic impacts. The project will also contribute to behavioural change as far as energy usages are concerned, as well as improving economic development and promoting both job creation and income generating activities in the local context.