Optical storage system for compensating water hammer effect of water turbine and its cooperative frequency modulation method

Patent metadata

Field	Value
Publication number	US-12355246-B1
Application number	US-202519026524-A
Country	US
Kind code	B1
Filing date	Jan 17, 2025
Priority date	Jul 25, 2024
Publication date	Jul 8, 2025
Grant date	Jul 8, 2025

Abstract

An optical storage system designed to compensate for the water hammer effect in hydropower turbines and its cooperative frequency modulation method are provided. The method involves detecting the water hammer effect and utilizing a pre-established system model integrating a hydropower unit, photovoltaic system, and hybrid energy storage system. Through model predictive control combined with a whale optimization algorithm, the governor parameters of the hydropower unit are optimized. The system then obtains the photovoltaic active power output and the battery's state of charge (SOC) within the hybrid energy storage system. Based on these parameters, a collaborative control strategy for the photovoltaic and hybrid energy storage systems is determined and executed. This strategy enables effective control of the photovoltaic system and/or hybrid energy storage to compensate for reverse power adjustments in the hydropower unit, addressing the water hammer effect and ensuring stable power grid operation.

First claim

What is claimed is:

1. A method for compensating a water hammer effect of a turbine by a photovoltaic storage system and performing a collaborative frequency modulation of the turbine, applied to a hydropower system, wherein the hydropower system comprises a hydropower unit, a photovoltaic system and a hybrid energy storage system, and the method comprises the following steps:
when an occurrence of the water hammer effect is detected, based on a pre-established system model composed of the hydropower unit, the photovoltaic system and the hybrid energy storage system, optimizing governor parameters of the hydropower unit by using a whale optimization algorithm based on model predictive control;
obtaining a photovoltaic active power output by the photovoltaic system and a state of charge (SOC) of a battery in the hybrid energy storage system;
according to the photovoltaic active power and the state of charge of the battery, determining a target coordinated control strategy of the photovoltaic system and the hybrid energy storage system; and
invoking the target coordinated control strategy to control the photovoltaic system and/or the hybrid energy storage system in response to a power inversion of the hydropower unit;
wherein the state of charge of the battery comprises a lead-carbon battery state of charge and a super capacitor battery state of charge, and the target coordinated control strategy of the photovoltaic system and hybrid energy storage system comprises at least one of the following:
determine whether the photovoltaic active power is greater than a preset power threshold, and in response to being so, multiply a load shedding coefficient by the photovoltaic active power to obtain an active power output by the photovoltaic system after the load shedding:

d
=

K
f

(

1
-

Δ
⁢
f

f
0

)

wherein K f is a rated load reducing rate, Δf is an electric network frequency deviation, and f 0 is an electric network frequency rated value;
determine whether the super capacitor battery state of charge is in a first battery state of charge interval, and in response to being so, determine whether the lead-carbon battery state of charge is in a second battery state of charge interval, and in response to being so, use a product of a sagging coefficient of a lead-carbon battery, a charging and discharging power coefficient and a frequency deviation of a power grid as a charging and discharging power of the lead-carbon battery, and a product of a virtual inertia coefficient of a super capacitor, the charging and discharging power coefficient and a frequency change rate of the frequency deviation of the power grid as a charging and discharging power of the super capacitor; and
determine whether the super capacitor battery state of charge is in the first battery state of charge interval, and in response to being so, determine whether the lead-carbon battery state of charge is in the second battery state of charge interval, and in response to being not, use the product of the virtual inertia coefficient of the super capacitor, the charge-discharge power coefficient, and the frequency change rate of the frequency deviation of the power grid as the charge-discharge power of the super capacitor.

2. The method according to claim 1 , wherein a discharge power coefficient of the lead-carbon battery and the super capacitor satisfies the following constraints:

K

bess
⁢
_
⁢
d

=

{

0
,

0
<
SOC
<

SOC
min

K
max

⁢

P
0

⁢

e

n
⁡
(

SOC
-

SOC
min

)

0.25

K
max

+

P
0

(

e

n
⁡
(

SOC
-

SOC
min

)

0.25

-
1

)

,
else

K
max

,

SOC
max

Assignees

• Univ Kunming Science & Technology

Inventors

• Shu Hongchun
• Wang Guangxue
• He Yefu
• Tang Yutao
• Shi Botao
• Han Yiming

Classifications

• H02J2101/24

  Photovoltaics · CPC title

• H02J2101/20

  Dispersed power generation using renewable energy sources · CPC title

• H02J3/0014 Primary

  for preventing or reducing power oscillations in networks · CPC title

• H02J3/00142

  Oscillations concerning frequency · CPC title

• H02J15/10

  using storage of hydraulic energy · CPC title