Multi-time scale identification for multi-energy system

TL;DR

This paper introduces a novel method for identifying multi-time scale dynamics in multi-energy systems, using signal pre-filtering and subtraction to separately identify high and low frequency components, improving modeling accuracy.

Contribution

The paper presents a new approach for two-time scale system identification in multi-energy systems, addressing the challenge of broad bandwidth and dynamic modeling complexity.

Findings

Method effectively separates high and low frequency components.

Case studies confirm the accuracy and effectiveness of the approach.

The approach enhances dynamic modeling of multi-energy systems.

Abstract

Multi-energy systems have been leaping forward for its various benefits, e.g., energy conservation and emission reduction. Coupling components are capable of transmitting energy from one time scale system to another time scale system, so the multi-energy system exhibits multi-time scale characteristic and broad bandwidth, thereby causing difficulties in dynamic modeling. In this work, two-time scale system identification is studied. A method is developed to solve the problem, which is uses signal pre-filtering and subtraction. The high and low frequency parts of the two-time scale system are identified separately and then combined to form the incorporated in parallel structure. The consistency of the method is proved and case studies are used to verify the effectiveness of the method.