Application of modified progressive hedging for stochastic unit commitment in electricity-gas coupled systems

The increasing number of gas-fired units has significantly intensified the coupling between electric and gas power networks. Traditionally, nonlinearity and nonconvexity in gas flow equations, together with renewable-induced stochasticity, resulted in a computationally expensive model for unit commitment in electricity-gas coupled integrated energy systems (IES). To accelerate stochastic day-ahead scheduling, we applied and modified Progressive Hedging (PH), a heuristic approach that can be computed in parallel to yield scenario-independent unit commitment. Through early termination and enumeration techniques, the modified PH algorithm saves considerable computational time for certain generation cost settings or when the scale of the IES is large. Moreover, an adapted second-order cone relaxation (SOCR) is utilized to tackle the nonconvex gas flow equation. Case studies were performed on the IEEE 24-bus system/Belgium 20-node gas system and the IEEE 118-bus system/Belgium 20-node gas system. The computational efficiency when employing PH is 188 times that of commercial software, and the algorithm even outperforms Benders Decomposition. At the same time, the gap between the PH algorithm and the benchmark is less than 0.01% in both IES systems, which proves that the solutions produced by PH reach acceptable optimality in this stochastic UC problem.