An energy storage capacity optimization method for large-scale wind farms considering ancillary service compensation

An ancillary service and energy storage capacity technology, applied in wind power generation, electrical components, circuit devices, etc., can solve the problems of poor enthusiasm for energy storage in wind farms, failure to consider ancillary service compensation, and low income from combined wind-storage operations

Active Publication Date: 2019-01-18
ZHENGZHOU UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is: the present invention provides a large-scale wind farm energy storage capacity optimization method that takes into account auxiliary service compensation, and solves the problem of

Method used

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  • An energy storage capacity optimization method for large-scale wind farms considering ancillary service compensation
  • An energy storage capacity optimization method for large-scale wind farms considering ancillary service compensation
  • An energy storage capacity optimization method for large-scale wind farms considering ancillary service compensation

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Embodiment 1

[0119] A method for optimizing the energy storage capacity of a large-scale wind farm considering ancillary service compensation, comprising the following steps:

[0120] Step 1: Take the quantified degree of mitigation to the system ancillary service costs before and after the addition of BESS as ancillary service compensation, and calculate the wind-storage combined operation benefit based on the ancillary service compensation and the obtained direct economic benefits of the wind farm’s configuration of energy storage;

[0121] Step 2: After the energy storage provides backup for the uncertainty of wind power, update the BESS constraints adapted to the dispatch plan;

[0122] Step 3: The updated BESS constraints are combined with other conventional constraints to form a set of constraints, and the objective function is obtained by maximizing the combined operation income of wind and storage, and the wind farm energy storage capacity optimization model is constructed according...

Embodiment 2

[0162] Based on embodiment 1, step 2 includes the following steps:

[0163] Step 2.1: On the premise of allowing wind curtailment, define the charge and discharge power and state of charge of the BESS, as shown in Equation 6:

[0164]

[0165] Among them, S t Represents the charging and discharging power of the battery at time t; P wind,t represents the forecast value of wind power at time t; P combined,t Represents the grid-connected power when the wind and storage are operating in combination at time t; P wloss,t Represents the wind abandonment value at time t; S soc,t-1 Represents the charge capacity of the BESS at time t; η s Represents the charging and discharging efficiency; Δt represents the scheduling time interval, 1h;

[0166] Step 2.2: According to the limitation of BESS rated charging and discharging power and energy storage capacity, express the BESS constraint at time t as shown in Equation 7:

[0167]

[0168] Among them, P cap Indicates the rated p...

Embodiment 3

[0174] Based on embodiment 1, step 3 includes the following steps:

[0175] Step 3 includes the following steps:

[0176] Step 3.1: The updated BESS constraints at time t are combined with other conventional constraints to form a set of constraints, as shown in Equation 9:

[0177]

[0178] Among them, P net,t represents the net load at time t; P load,t represents the system load demand at time t; P wind,t Represents the forecast value of wind power at time t; r t up / r t dn Indicates the upper / lower limit of the maximum ramp rate allowed by the online unit at time t; Ng Indicates the number of conventional units; Indicates the maximum / minimum output power allowed by conventional unit i; u i,t Indicates the start and stop state of unit i in the t period, 0-1 variable; Indicates the upper / lower deviation range of the wind power forecast value; R load,t Represents the standby demand of the load. Due to the high repeatability of the daily load curve, the standard ...

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Abstract

The invention discloses an energy storage capacity optimization method of a large-scale wind farm considering auxiliary service compensation, and relates to the energy storage capacity optimization method field of the wind farm. The method includes: S1, after quantifying the mitigation degree of the auxiliary service cost of the system, taking the auxiliary service compensation as the auxiliary service compensation, and calculating the wind storage combined operation income according to the economic benefit of the wind storage and the wind farm configuration energy storage; S2: Updating the BESS constraint adapted to the dispatching plan after the energy storage provides the reserve for the uncertainty of the wind power; S3: combining BESS constraint with other constraint to construct constraint set, and obtaining the objective function by maximizing revenue, constructing the wind farm energy storage capacity optimization model according to the them. S4, solving the collected power system parameter input model to obtain the optimal capacity; The invention solves the problems that the energy storage capacity optimization of the existing wind farm does not consider the auxiliary service compensation, which leads to the low combined operation income of the wind farm and the low enthusiasm of the wind farm for allocating energy storage, and achieves the effect of effectively encouraging the wind farm to allocate energy storage and realizing the friendly grid-connected absorption of the wind power.

Description

technical field [0001] The invention relates to the field of wind farm energy storage capacity optimization methods, in particular to a large-scale wind farm energy storage capacity optimization method that takes into account auxiliary service compensation. Background technique [0002] As a flexible and dispatchable power source, the energy storage system provides a new idea for coping with the grid connection of wind power. The configuration of the energy storage system in wind farms will become one of the modes of large-scale development of wind power in the future. Compared with other energy storage technologies, it has smaller requirements on geographical conditions and higher energy efficiency, and has the broadest application prospects in power systems. [0003] At present, the most direct benefit of deploying BESS in wind farms is that additional wind power can be connected to the grid and reduce the loss of wind abandonment; the deployment of BESS in wind farms requ...

Claims

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Application Information

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IPC IPC(8): H02J3/38H02J3/00
CPCH02J3/386H02J3/008H02J2310/64H02J2203/20Y02E10/76Y04S20/222Y02E40/10Y02B70/3225
Inventor 姜欣王天梁金阳
Owner ZHENGZHOU UNIV
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