Off-grid and decentralized hybrid renewable electricity systems data analysis platform (OSDAP)

highlights•Hybrid systems data handling, visualization, analysis, and forecasting tool.•Artificial neural networks application in irradiance forecasting for hybrid systems.•Developed Performance analysis methodology based on international standards.•Hybrid system including lead-acid and Lithium-ion hybrid battery storage.•Comprehensive approach based on contrastive case studies in Africa and Canada. Off-grid and decentralized Hybrid Renewable Electricity Systems (OHRES) play a promising role in providing sustainable energy access to 860 million people around the globe with no access to electricity. However, the diversity of global geographies, lack of performance analysis standardization, and modeling limitations hinder the scalability of OHRES. This study outlines the creation of a data analysis platform (OSDAP) and irradiance forecasting models for OHRES that can be used to support the provision of global energy access. The paper presents the technical layout of OHRES in two case studies in Canada and Uganda and outlines an assessment and modeling platform that can be used to assess OHRES performance across widely varying geographic locations. Two irradiance forecasting models are developed using artificial neural networks, which can be used to increase solar energy utilization in OHRES.