The network constraint stochastic energy sharing method for integration of energy storages and RESs in the interconnected energy microgrid

The high penetration of renewable energy sources (RESs) improves the sustainability of distribution-level energy systems, but their uncertain output creates operational challenges for coupled electricity and natural gas networks. To address this issue, this paper proposes a stochastic network-constrained peer-to-peer (P2P) energy-sharing framework for an integrated energy system (IES). The proposed framework coordinates PRs, flexible consumers, fixed loads, photovoltaic units, wind turbines (WNs), micro gas turbines (MGTs), power-to-gas (P2G) units, energy storage systems, and gas compressors (GRs) under distribution system operator supervision. Uncertainties in wind speed, solar irradiance, electricity demand, and natural gas demand are represented by 1000 generated scenarios, reduced using Kantorovich distance, and statistically validated through the T-test. The resulting mixed-integer nonlinear programming problem is solved using an outer approximation/equality relaxation/augmented penalty decomposition method. The framework is tested on the IEEE 33-bus distribution system coupled with a 15-node natural gas network. Numerical results show that the proposed method reduces PRs’ and flexible consumers’ operating cost by about 25%, increases the revenues of micro MGTs, WNs, and photovoltaic units by about 140%, 40%, and 80%, respectively, and decreases the GR supply cost by 10.3% compared with the benchmark without P2P trading. The proposed method also maintains voltage and gas-pressure feasibility and reduces solving time by about 61% compared with DICOPT.