基于最优可调负荷模型的工业生产过程用电可行域建模方法OA

Industrial users possess significant potential to provide flexibility for the power system through demand-side regulation.Although industrial production processes involve complex energy consumption mechanisms,existing general models such as the state-task network(STN)can effectively model the energy constraints of certain types of industrial processes.However,the STN model involves a large number of discrete variables and requires extensive parameters,making it difficult to directly embed into economic dispatch for massive demand-side flexibility resources.This hinders the full utilization of industrial user flexibility.To address this,a modeling method for the feasible region based on the optimal adjustable load model(OALM)is proposed for industrial users whose production processes can be modeled using STN.First,the integer variables of the STN model are eliminated by leveraging the demand response timescale,thereby linearizing the model.Then,considering the electricity consumption characteristics of industrial users,the adjustable load model is employed to approximate the linearized STN model.Robust optimization method is used to solve its parameters to maximize the volume of the feasible region,and power-energy coupling constraints are added to resolve the unbounded issue in current feasible region parameter optimization.Case studies demonstrate that,compared to the high-dimensional and integer-variable-based original STN model,the low-dimensional and linear OALM maintains high accuracy and stability under different production plans,timescales,and electricity price scenarios.This provides a new approach to addressing the curse of dimensionality faced by large-scale integration of industrial users into load-side regulation.