(59b) Energia - an Integrated Framework and Software Prototype for Multiscale Energy Systems Transition Modeling, Optimization and Scenario Analysis

De-carbonization of energy infrastructure, while meeting growing global energy demand, requires a shift in primary energy production and supply towards renewable technologies. Renewables, such as wind, solar and biofuels, are typically available intermittently, and are subject to seasonal variability and uneven geographical distribution. This necessitates the explicit consideration of spatiotemporal characteristics and variabilities in the analysis of proposed low-carbon energy scenarios. Future energy systems may further involve integrated value chains of multiple energy sectors with multiple technology options for sustainable energy generation, production of chemicals and synthetic fuels, and transportation [1]. A holistic, multiscale energy systems engineering approach [2] can provide a systematic framework to address these challenges toward assessing promising energy transition pathways, linking decisions at the process synthesis, scheduling, and supply chain level, and enabling trade-off analysis.

In this work, we present the developments of ENERGIA, a novel multi-scale energy systems transition modeling, optimization and scenario analysis framework and software prototype. ENERGIA integrates (i) energy supply chain and transportation considerations, (ii) detailed energy production aspects, and (iii) scheduling decisions for operation and inventory management of energy and resources storage. Its key features include (i) detailed data and models for the description of process alternatives and units and the corresponding supply chains, (ii) a detailed time-varying scheduling model [3], (iii) a library of surrogate modelling techniques, for both the nonlinear process models, as well as scheduling decisions, and (iv) an effective multi-period, multi-location mixed-integer optimization solution strategy, coupled with environmental, risk and uncertainty analysis. ENERGIA’s python-based environment allows users to visualize resource availabilities and demands at various temporal and geographic scales and resolutions, and compare competing objectives and renewable-based energy strategies. A hydrogen-economy energy transition problem is presented to highlight the potential and key capabilities of the proposed framework.

[1] Demirhan, C. D., Tso, W. W., Powell, J. B. & Pistikopoulos, E. N., A multi-scale energy systems engineering approach towards integrated multi-product network optimization. Applied Energy 281, 116020 (2021).

[2] Kakodkar, R., He, G., Demirhan, C. D., Arbabzadeh, M., Baratsas, S.G., Avraamidou, S., Mallapragada, D., Miller, I., Allen, R. C., Gençer, E & Pistikopoulos, E.N., A review of analytical and optimization methodologies for transitions in multi-scale energy systems. [Manuscript submitted, 2021]

[3] Allen, R. C., Baratsas, S.G., Kakodkar, R., Avraamidou, S., Powell, J. B., Heuberger, C.F., Demirhan, C. D. & Pistikopoulos, E.N., An optimization framework for solving integrated planning and scheduling problems for dense energy carriers. 11th IFAC International Symposium on Advanced Control of Chemical Processes (ADCHEM) (2021). [In press]