Smart Control and Real-time Operation of Photovoltaic Microgrids for Electricity Access in Africa

Framework: This PhD is part of the SOMSE project ‘Service-Oriented design and smart energy management of PV Microgrids for Sustainable rural Electrification’ which is led jointly by Imperial College London and the University of Paris-Saclay, CentraleSupélec, CNRS.

The PhD is fully funded, based at the University of Paris-Saclay, CentraleSupélec, GeePs laboratory and supervised by Dr Imen Bahri (Paris-Saclay, expert in energy management and control), Dr Simon Meunier (CentraleSupélec, Paris-Saclay, energy modelling) and Prof. Jenny Nelson (Imperial College London, photovoltaic systems). The PhD will start in Autum 2026.

The PhD will involve strong international collaborations. In addition to close interaction and regular meetings with the Imperial College London (UK) team, partners including the National Renewable Energy Agency (ANER) in Sénégal, the University of Nairobi in Kenya, and Lancaster University (UK) will contribute complementary expertise particularly in institutional frameworks and rural electricity uses. Regular interactions with companies, funders, and policymakers are also planned. The PhD student will benefit from research visits at Imperial College London and in Africa to work closely with local stakeholders.

Description: More than 500 million people in sub-Saharan Africa still lack access to electricity, which significantly constrains socio-economic development. The rapid decline in photovoltaic (PV) costs has enabled the deployment of standalone PV microgrids as a promising low-carbon solution for rural electrification. However, their long-term economic viability often remains limited, as they typically power low-revenue domestic loads and rely heavily on costly battery storage to address the mismatch between solar generation and demand.

Expanding PV microgrids to supply electricity for wider community services (e.g., water, health) and productive uses (e.g., milling, small-scale artisanal activities) introduces loads that better align with solar generation profiles. Many of these uses can also generate higher revenues, thereby improving the economic viability of PV microgrids. In addition, they are often compatible with demand-side strategies such as load shifting, enabling consumption to be scheduled during periods of high solar availability.

The development of real-time energy management strategies for PV microgrids is key to fully leveraging these new services, as it enables a better coordination between available solar generation and electricity demand. By dynamically scheduling flexible uses and anticipating solar resource variability, such approaches can reduce reliance on battery storage, improve overall system efficiency and lifetime and decrease the cost of electricity provision.

The aim of this PhD is to develop advanced control and energy management strategies for PV microgrids integrating communal and productive electricity uses in rural contexts. The project will combine machine-learning-based solar irradiance forecasting adapted to low-connectivity environments, advanced control techniques (such as robust and predictive control), and smart scheduling of electricity uses. The work will also explore service-level flexibility, leveraging physical buffers such as water tanks or cold storage to decouple energy use from service delivery.

A major challenge will be to ensure that the proposed methods remain robust to uncertainty (e.g., forecast errors, variable demand) while being implementable on low-cost, resource-constrained systems. The developed approaches will be experimentally validated in the laboratory and tested through case studies in Kenya and Senegal, demonstrating their impact on costs, performance, and service provision.

Additional information about the PhD will be provided during the interview.

 

Open science, Impact & Alignment with Sustainable Development Goals (SDGs) : To maximise accessibility, Python will be the primary computational tool used throughout the PhD, all developments will be shared in open-source and dissemination activities for local stakeholders will be carried out. The PhD will deliver openly available advances for PV microgrid planning and operation, provide actionable insights to microgrid designers and operators and support evidence-based decision-making for policymakers. The PhD directly contributes to UN SDG 7 (Affordable and Clean Energy) and supports associated goals, including SDG 6 (Clean Water), SDG 3 (Good Health) and SDG 13 (Climate Action), by enabling access to essential services through sustainable energy systems.

Some publications from the research team relevant to the PhD and the SOMSE project: [1] Opportunities for decentralised solar power to improve reliability, reduce emissions and avoid stranded assets, Nature Communications, 2025. [2] Carbon pricing and system reliability impacts on pathways to universal electricity access in Africa, Nature Communications, 2024. [3] CLOVER: A modelling framework for sustainable community-scale energy systems, Journal of Open Source Software, 2023 [4] An empirical assessment of direct and indirect effects of electricity access on food security, World Development, 2021. [5] Large-scale modeling of solar water pumps using machine learning, Applied Energy, 2026. [6] Microgrid sizing and energy management using Benders decomposition algorithm, Sustainable Energy, Grids and Networks, 2024. [7] Model predictive control and linear control of DC–DC boost converter in low-voltage DC microgrids: An experimental comparative study, Control Engineering Practice, 2023.

CentraleSupélec is a founding member of Université Paris-Saclay, a research-intensive university that spans all disciplines and is consistently ranked among the world's best universities (13th globally and 1st in continental Europe in the Academic Ranking of World Universities).

Candidates from a wide range of backgrounds are welcome to apply. A strong motivation to engage with energy systems and interdisciplinary research, and to develop skills beyond one’s initial field of training, is essential.