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Power fluctuation smoothening method based on optimum control of energy storage and virtual energy storage

An optimal control and virtual energy storage technology, which is applied in the direction of AC network load balancing, etc., can solve problems such as high cost, small capacity of energy storage equipment, and restrictions on large-scale applications

Active Publication Date: 2016-02-24
TIANJIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the small capacity and high cost of energy storage equipment, its large-scale application is restricted.

Method used

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  • Power fluctuation smoothening method based on optimum control of energy storage and virtual energy storage
  • Power fluctuation smoothening method based on optimum control of energy storage and virtual energy storage
  • Power fluctuation smoothening method based on optimum control of energy storage and virtual energy storage

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0035] A method for smoothing power fluctuations of microgrid tie-lines based on optimal control of virtual energy storage, see figure 1 , figure 2 and Figure 4 , the method includes the following steps:

[0036] 101: Obtain the scheduling reference value of the tie line power on the day through the power prediction value of new energy power generation, uncontrollable load and controllable equipment consumption without control

[0037] Firstly, get the power prediction value of new energy power generation, uncontrollable load and controllable equipment consumption without control in the day before, and then get the dispatching reference value of the tie line power on the day

[0038] 102: Obtain the power generated by new energy at time t of the day (starting from time t=1) to calculate the total power y that needs to be stabilized by the energy storage battery and electric heat pump at that time ref,t ;

[0039] 103: According to the state equation in the optimal co...

Embodiment 2

[0044] The scheme in step 103 in Embodiment 1 is described in detail below in conjunction with specific calculation formulas and examples, see below for details:

[0045] 201: Use the KiBaM (KineticBatteryModel) energy storage battery model to describe the operation of the energy storage battery;

[0046] Among them, use Indicates the target power of the energy storage battery, and the required discharge current I at this moment d for: V rated Indicates the rated voltage of the energy storage battery, N s Indicates the number of energy storage batteries connected in series.

[0047] Suppose at the end of each step q 1 =0, the maximum discharge current I of the energy storage battery d,max for:

[0048] I d , m a x = kq 1 , 0 ...

Embodiment 3

[0092] The following specific experiments are used to verify the feasibility of a method for smoothing power fluctuations of microgrid tie-lines based on virtual energy storage optimal control provided by the present invention. See the following description for details:

[0093] In order to verify the effect of this method, 1000 electric heat pump models were established, and the response characteristic curve of a single electric heat pump is as follows figure 1 As shown, the temperature set point of each electric heat pump is 21°C, the dead zone range is 4°C, and its thermodynamic dynamic parameters C, R, and Q are set to 3599.3J / °C, 0.1208°C / W, and 400W, respectively. The average daily outdoor temperature is 5°C. 100 energy storage battery units are established, and the number of energy storage batteries in each unit is 80, and its rated voltage V rated , the maximum capacity q max , the capacity ratio c of the KBM model, the proportionality constant k of the KBM model, an...

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Abstract

The invention discloses a power fluctuation smoothening method based on optimum control of energy storage and virtual energy storage. The method comprises: ascheduling reference value of a day tie-line power is obtained according to power prediction values consumed by new-energy power generation, an uncontrollable load, and controllable equipment on the uncontrolled condition; a power of the ew-energy power generation at the day t time is obtained, and a total power, needed to be smoothened, of an energy storage battery and an electric heating pump at the time is calculated; according to a state equation in an optimum control model, optimization distribution is carried out on the total power under constraint conditions and objective functions of the energy storage battery and the electric heating pump in the optimum control model, thereby obtaining objective functions of the energy storage battery and the electric heating pump; and actual response powers of the energy storage battery and the electric heating pump are calculated. According to the invention, cluster demand response controlling is carries out on lots of electric heating pumps in a micro grid of the urban park and a load curve is adjusted to form a virtual energy storage effect; and with coordination and control with the energy storage battery, the power fluctuation of the tie-line of the micro grid is smoothened.

Description

technical field [0001] The invention relates to the fields of smart grid, user-side demand response and hybrid energy storage, in particular to a power fluctuation suppression method based on optimal control of energy storage and virtual energy storage. Background technique [0002] With the increasingly prominent energy and environmental issues, the use of new energy has attracted widespread attention. The installed capacity of wind power and other new energy power generation systems is increasing, and its proportion in the power grid is also increasing. However, due to the high randomness and volatility of new energy power generation, the connection of new energy to the grid will pose challenges to the balance of power supply and demand and the security of the power system. The use of energy storage equipment is currently an effective way to solve the above problems. The current energy storage technologies are mainly divided into four types: physical energy storage, electr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/32
CPCH02J3/32
Inventor 王丹陈沼宇贾宏杰王伟亮王冉卫文婷
Owner TIANJIN UNIV
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