Input Parameter Dataset for Stochastic Multi-Carrier SSCEE Scheduling with Electric-Drone Mobility

Abstract

Input Parameter Dataset for Stochastic Multi-Carrier SSCEE Scheduling with Electric-Drone Mobility This dataset provides a structured numerical input specification for a stochastic multi-carrier energy scheduling benchmark incorporating carbon-emission trading (CET), renewable portfolio standards (RPS), peer-to-peer (P2P) electricity trading, hydrogen conversion, and electric-drone mobility. The accompanying Microsoft Excel workbook contains 27 numerical parameter tables corresponding to Appendix C of the supplementary material. The dataset covers the following subsystems and modeling components: Multi-carrier distribution networks: IEEE 33-bus electrical distribution system, 7-node natural-gas network, 14-node district-heating network, and 20-node hydrogen distribution network, including branch characteristics, operating limits, and network parameters. Energy conversion and storage: Input specifications for combined heat and power units, gas boilers, electrolyzers, hydrogen fuel cells, methanation, and stationary energy storage. P2P electricity trading: Participant configurations, bilateral trading connections, and associated operating parameters. Electric-drone mobility: Fleet characteristics, battery parameters, charging and discharging limits, mobility-distribution parameters, and stochastic scenario inputs. Scheduling and learning parameters: Hourly demand and renewable-generation profiles, electricity tariffs, scenario-generation settings, and deep reinforcement learning configuration parameters. The benchmark adopts a 24-hour scheduling horizon with hourly resolution. Its mobility-scenario specification comprises 1,000 initial realizations and 10 representative scenarios, with scenario probabilities assigned according to the prescribed reduction procedure. The workbook includes separate machine-readable worksheets for the numerical tables and selected structured input categories.