Title

Modeling State Transition and Head-Dependent Efficiency Curve for Pumped Storage Hydro in Look-Ahead Dispatch

Abstract

As the most widely installed storage device, pumped storage hydro (PSH) plays an essential role in providing flexibility for power systems worldwide. Thus, to accurately quantify the flexibility of PSH units in operational optimization problems is important. The conventional PSH models in the literature rarely consider state transition time due to their hourly-based settings. However, it becomes imperative for operational optimization on short-term intervals, especially with increasing shares of renewable energy in power systems. To this end, this paper presents a novel deterministic PSH model that considers the transition time and trajectory between three states of PSH units in look-ahead dispatch. Moreover, to better characterize the varying efficiency of PSH units with water head and flow rate, this paper proposes to model detailed head-dependent efficiency curves (hereafter called input-output curves) in look-ahead dispatch, which encounters heavy computational burdens when short time intervals are applied. In this work, a zig-zag piece-wise linear approximation method is used for input-output curve modeling. This can enable an accurate quantification for variable efficiency and head dependence in a computationally effective manner. Numerical results are presented to show performances of the proposed PSH model in both flexibility quantification and computation time.

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Generators; Inputoutput Curve; Linear Approximation; Look-Ahead Dispatch; Optimization; Power Systems; Pumped Storage Hydro; Reservoirs; State Transition; Trajectory; Wind Farms

International Standard Serial Number (ISSN)

0885-8950; 1558-0679

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2021 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Jan 2021

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