Morshed leads the company's research activities. His field is intelligent grid systems, covering renewable energy, microgrids and battery energy storage, with artificial intelligence as the unifying tool across them.
His background spans electrical and electronic engineering, electronics engineering and specialist power-system training in protection, renewable energy engineering, distributed generation and stability analysis. This foundation ensures that our forecasting and optimisation models reflect the behaviour of real networks.
- Energy consumption and generation forecasting
- Integration of distributed generation
- Energy management and optimisation, including home energy management systems
- Integration of artificial intelligence in the smart grid
- Supervised, unsupervised and deep-learning modelling with Scikit-learn, TensorFlow and Keras
- Time-series forecasting and electrical fault detection schemes
- Python, MATLAB/Simulink and Arduino for modelling, simulation and prototyping
- Time-series forecasting of energy consumption and generation
- Electrical fault detection schemes
- Edge AI server and software deployed on an operating PV site
- National-scale electric vehicle demand forecasting and power-sector readiness study — EV adoption and charging scenarios, generation adequacy and grid readiness assessment, and an interactive scenario dashboard