Two-Stage Stochastic Energy Scheduling for Multi-Energy Rural Microgrids With Irrigation Systems and Biomass Fermentation

Multi-energy rural microgrids (MERMs) hold both economic potential and multi-energy coordination ability, emerging as a promising energy management paradigm in rural areas. In this paper, an energy scheduling method is investigated for a MERM with renewable energy and biomass resources, aiming to satisfy the rural electrical, thermal, natural gas, and irrigation demands economically. Mathematically, biomass flows are formulated by adopting a differential dynamics model of anaerobic biomass fermentation. The irrigation system is accurately formulated by fully taking into account meteorological information such as ambient temperature and precipitation. To handle the uncertainties in precipitation, reservoir inflows, renewable power generation as well as electrical and thermal load demands, a two-stage stochastic optimization method is employed, and the proposed model is then reformulated into a stochastic mixed integer quadratic programming (SMIQP) problem. To mitigate the computational burden arising from integer variables and enhance the solution efficiency, a scenario decomposition algorithm, progressive hedging (PH), is used to decompose the SMIQP into scenario-wise subproblems, which are then solved in parallel. Finally, the simulation results demonstrate the effectiveness of the proposed MERM scheduling method and the efficiency of the PH algorithm.