MESHKAT: Modelling and Evaluation of Solar Hubs in Qatar – A Customer-Driven AI Platform for Sustainable Arid Cities

The MESHKAT solar energy optimisation platform is an interdisciplinary initiative led by the College of Science and Engineering (CSE) at HBKU, designed to accelerate Qatar’s transition to a sustainable and decentralised energy future. Developed in response to Kahramaa’s net billing policy and the national BeSolar strategy, MESHKAT reduces barriers to solar adoption by providing personalised, data-driven insights for households, businesses, farms, and industrial users. At its core, MESHKAT integrates high-resolution weather and irradiance datasets, real electricity consumption records, and advanced forecasting and optimisation models to deliver tailored assessments of solar photovoltaic (PV) feasibility. The platform generates user-specific reports covering solar potential, financial returns, and environmental benefits, while also enabling policy simulation and incentive testing. This dual function makes MESHKAT both a consumer tool and a strategic decision-support system for regulators and policymakers. The project builds on HBKU’s ongoing research in machine learning, reinforcement learning, and game-theoretic approaches to energy optimisation, combined with QEERI’s expertise in solar resource modelling, forecasting, and privacy-preserving data management. It also draws on the College of Public Policy’s experience in sustainability governance and stakeholder engagement to develop pragmatic energy pricing, subsidy, and demand-side management policies.

Hamad Bin Khalifa University (HBKU)