Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
184 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Model Predictive Control for a Medium-head Hydropower Plant Hybridized with Battery Energy Storage to Reduce Penstock Fatigue (2111.05004v3)

Published 9 Nov 2021 in eess.SY and cs.SY

Abstract: A hybrid hydropower power plant is a conventional HydroPower Plant (HPP) augmented with a Battery Energy Storage System (BESS) to decrease the wear and tear of sensitive mechanical components and improve the reliability and regulation performance of the overall plant. A central task of controlling hybrid power plants is determining how the total power set-point should be split between the BESS and the hybridized unit (power set-point splitting) as a function of the operational objectives. This paper describes a Model Predictive Control (MPC) framework for hybrid medium- and high-head plants to determine the power set-point of the hydropower unit and the BESS. The splitting policy relies on an explicit formulation of the mechanical loads incurred by the HPP's penstock, which can be damaged due to fatigue when providing regulation services to the grid. By filtering out from the HPP's power set-point the components conducive to excess penstock fatigue and properly controlling the BESS, the proposed MPC is able to maintain the same level of regulation performance while significantly decreasing damages to the hydraulic conduits. A proof-of-concept by simulations is provided considering a 230 MW medium-head hydropower plant.

Citations (15)

Summary

We haven't generated a summary for this paper yet.