Abstract

In the present study, a novel approach to dynamic economic dispatch for power systems spanning multiple regions is introduced, utilizing the alternating direction multiplier method (ADMM) as its computational foundation. The proposed economic scheduling model is designed to optimize the operational costs of the system comprehensively, while adhering to a spectrum of operational constraints. Employing the ADMM, the study achieves a distributed resolution of the model by severing the inter-regional interconnections, thereby partitioning the overarching optimization challenge into manageable sub-problems specific to each region. This methodology facilitates the attainment of the system’s global optimum through the iterative resolution of these regional sub-problems. Furthermore, the algorithm obviates the necessity for a centralized data repository for multiplier updates, thereby endorsing a fully distributed scheduling paradigm. Concurrently, the study incorporates a multi-period optimization technique within the economic scheduling model to accommodate the inherent temporal dependencies of the power system. The culmination of this research is the empirical analysis of a tri-regional interconnected system, predicated on the IEEE standard test system, which substantiates the efficacy of the proposed economic dispatch strategy.

Abstract

In the present study, a novel approach to dynamic economic dispatch for power systems spanning multiple regions is introduced, utilizing the alternating direction multiplier method (ADMM) as its computational foundation. The proposed economic scheduling model is designed to optimize the operational costs of the system comprehensively, while adhering to a spectrum of operational constraints. Employing the ADMM, the study achieves a distributed resolution of the model by severing the inter-regional interconnections, thereby partitioning the overarching optimization challenge into manageable sub-problems specific to each region. This methodology facilitates the attainment of the system’s global optimum through the iterative resolution of these regional sub-problems. Furthermore, the algorithm obviates the necessity for a centralized data repository for multiplier updates, thereby endorsing a fully distributed scheduling paradigm. Concurrently, the study incorporates a multi-period optimization technique within the economic scheduling model to accommodate the inherent temporal dependencies of the power system. The culmination of this research is the empirical analysis of a tri-regional interconnected system, predicated on the IEEE standard test system, which substantiates the efficacy of the proposed economic dispatch strategy.