About / Co-founder
Dr Tolulope Falope
Renewable energy · Energy forecasting · Machine learning · Energy management
Biography
Tolulope Falope is an energy-systems specialist working across solar energy, intelligent energy management, machine learning and distributed energy systems. His work focuses on how renewable-energy resources can be more effectively forecast, integrated and managed to improve the performance, flexibility and sustainability of modern energy systems.
His research has particular expertise in solar photovoltaic forecasting and integrated energy management, spanning data processing, machine-learning prediction, demand-side management and supply-side control. His doctoral research at Cranfield University developed an integrated energy-management framework combining solar forecasting, weather-data processing, time-of-use strategies, direct load control and generator management. The work included applications across rooftop photovoltaic systems, controlled electrical loads and off-grid solar configurations.
Tolulope's broader expertise lies in connecting data-driven methods with practical energy-system challenges. His work examines how forecasting, intelligent control and system integration can support renewable-energy deployment, improve energy efficiency and demand flexibility, and strengthen the economic and environmental performance of distributed and hybrid energy systems.
Specialist expertise
Solar energy, intelligent energy management, machine learning and distributed energy systems.
Research interests
Solar photovoltaic forecasting and integrated energy management, with particular interests in artificial intelligence (AI), machine learning, demand-side management and intelligent control. His research examines how data-driven forecasting and system integration can improve the performance, flexibility and sustainability of distributed and hybrid energy systems.
Selected projects & outputs
- Data preprocessing techniques for statistical photovoltaic forecasting modelsMeasurement, 282, 121997, 2026Publication
- Development of an integrated energy management system for off-grid solar applications with advanced solar forecasting, time-of-use tariffs, and direct load controlSustainable Energy, Grids and Networks, 39, 101449, 2024Publication
- A Three-Step Weather Data Approach in Solar Energy Prediction Using Machine LearningRenewable Energy Focus, 50, 100615, 2024Publication
- Hybrid energy system integration and management for solar energy: A reviewEnergy Conversion and Management: X, 21, 100527, 2024Publication