In the energy market, uncertainty shocks such as price fluctuations and policy changes often occur, resulting in top-down negative effects to energy consumers. To promote a more robust, efficient and sustainable European energy economy, the MoCEGS project proposes a multi-level top-down energy planning approach incorporating data-driven process integration, process network analysis and chemometrics as core components. MoCEGS project aims to optimize energy trading, improve system circularity, mitigate uncertainty shocks, and exploit chemical utilization via a unique energy planning framework. The difficulty of developing such a modelling framework is the necessary computational resources and the multidisciplinary expertise involved. The MoCEGS project is planned with high-performance computational facilities and multi-disciplinary training, which also includes a secondment to a different European country. The advantage of proposed approach is that computational time is reduced and also enables high data-resolution. This approach also converts the traditionally linear economy consideration to circular economy consideration via multi-level process integration. The ultimate goal is to link collaborative minds of cross-disciplinary researchers in developing an integrative energy planning framework that will be widely-used to promote energy circularity, address epistemic uncertainty and achieve regional sustainability.