考虑超碳需求响应及农业柔性负荷的乡村虚拟电厂低碳优化调度OA

Driven by carbon neutrality goals,rural virtual power plants face the dual challenges of insufficient flexible regulation capabilities and limited low-carbon pathways on the user side.In response to these challenges,this paper proposes an advanced low-carbon optimization method for rural virtual power plants that integrates multi-energy complementarity and flexible regulation.This method first constructs an agricultural flexible load model,introducing a daily cumulative temperature index for crops to achieve co-optimization of thermal load and crop growth cycles,and setting dynamic temperature range constraints for livestock farming to enable precise regulation of agricultural production loads.Second,it establishes an ultra-carbon demand response mechanism,using a dual-dimensional control model combining tiered carbon prices and price fluctuation coefficients to directly link carbon emission intensity with load transfer benefits on the user side,encouraging users to proactively adjust their energy consumption behavior.Based on this,the method considers the charging and discharging characteristics of agricultural machinery and electric vehicles,constructing a vehicle-grid interaction multi-scenario coordination model to achieve peak-shaving optimization of the distributed energy system.Finally,a case study of a specific agricultural high-tech zone in Shandong province demonstrates that this method can enhance system economic efficiency and achieve regional comprehensive carbon emissions reduction,demonstrating its potential for rural energy transition under carbon neutrality goals.