Differentiable Simulator For Dynamic & Stochastic Optimal Gas & Power Flows

In many power systems, particularly those isolated from larger intercontinental grids, operational dependence on natural gas becomes pivotal, especially during fluctuations or unavailability of renewables coupled with uncertain consumption patterns. Efficient orchestration and inventive strategies are imperative for the smooth functioning of these standalone gas-grid systems. This paper delves into the challenge of synchronized dynamic and stochastic optimization for independent transmission-level gas-grid systems. Our approach's novelty lies in amalgamating the staggered-grid method for the direct assimilation of gas-flow PDEs with an automated sensitivity analysis facilitated by SciML/Julia, further enhanced by an intuitive linkage between gas and power grids via nodal flows. We initiate with a single pipe to establish a versatile and expandable methodology, later showcasing its effectiveness with increasingly intricate examples.Comment: 7 pages, 7 figures, submitted to PSCC 202

System-Wide Emergency Policy for Transitioning from Main to Secondary Fuel

Inspired by the challenges of running the Israel's power system -- with its increasing integration of renewables, significant load uncertainty, and primary reliance on natural gas -- we investigate an emergency scenario where there's a need to transition temporarily to a pricier secondary fuel until the emergency resolves. Our objective is to devise tools that can assist power system operators in making decisions during such critical periods. We frame this challenge as a Markov Decision Process (MDP) optimization, considering uncertainties like potential failures of dual-fuel generators during the transition, operator attentiveness under stress, available but finite amount of primary fuel (linepack available in the natural gas part of the system), power forecast (net demand after renewable production), and the cost implications of unavoidable load shedding. By solving the MDP in a simplified context, we identify viable policies through simulations of multiple parametrized Markov Processes (MPs). We verify our methodology using a realistic open-source model replicating Israel's power-gas infrastructure and outline next steps for refining and adapting this approach.Comment: 7 pages, 6 figure