A large-scale wind farm energy storage capacity optimization method considering ancillary service compensation

A technology for auxiliary services and energy storage capacity, applied in wind power generation, electrical components, circuit devices, etc., can solve the problems of poor enthusiasm for energy storage in wind farms, not considering compensation for auxiliary services, and low income from combined operation of wind and storage, etc. Reasonable, balanced cost and effect of translation effects

Active Publication Date: 2022-04-01
ZHENGZHOU UNIV
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  • 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 low wind-storage combined operation income caused by the existing wind farm energy storage capacity optimization without consideration of auxiliary service compensation. Poor enthusiasm for deploying energy storage in wind farms

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  • A large-scale wind farm energy storage capacity optimization method considering ancillary service compensation
  • A large-scale wind farm energy storage capacity optimization method considering ancillary service compensation
  • A large-scale wind farm energy storage capacity optimization method considering ancillary service compensation

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Embodiment 1

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

[0120] Step 1: Take the quantified degree of mitigation of system auxiliary service costs before and after the addition of BESS as auxiliary service compensation, and calculate the combined operating income of wind storage according to the auxiliary service compensation and the obtained direct economic benefits of wind farm configuration energy storage;

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

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

Embodiment 2

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

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

[0164]

[0165] Among them, S t Indicates the charging and discharging power of the battery at time t; P wind,t Indicates the predicted value of wind power at time t; P combined,t Indicates the grid-connected power of wind storage combined operation at time t; P wloss,t Indicates the wind curtailment value at time t; S soc,t-1 Indicates the charging capacity of BESS at time t; η s Indicates the charging and discharging efficiency; Δt indicates the scheduling time interval, 1h;

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

[0167]

[0168] Among them, P cap Indicates the rated power of the energy storage...

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 constraint at time t is combined with other conventional constraints to form a set of constraint conditions, as shown in formula 9:

[0177]

[0178] Among them, P net,t Indicates the net load at time t; P load,t Indicates the system load demand at time t; P wind,t Indicates the wind power forecast value at time t; Indicates the upper limit / 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 on-off status of unit i in the t period, 0-1 variable; Indicates the upper / lower deviation range of wind power forecast value; R load,t Represents the spare demand of the load. Since the daily load curve is highly repeatable, the standard deviation of its forecast err...

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Abstract

The invention discloses a large-scale wind farm energy storage capacity optimization method considering auxiliary service compensation, and relates to the field of wind farm energy storage capacity optimization methods; it includes S1: After quantifying the mitigation degree of system auxiliary service costs, use it as an auxiliary Service compensation, calculate the joint operation income of wind storage according to the economic benefits of configuring energy storage in wind farms; S2: after the energy storage provides backup for the uncertainty of wind power, update the BESS constraints to adapt to the dispatch plan; S3: combine BESS constraints with other constraints Set up a set of constraint conditions, obtain the objective function by maximizing revenue, and construct an optimization model of wind farm energy storage capacity based on the two; S4: input the collected power system parameters into the model to obtain the optimal capacity; the present invention solves the problem of existing wind farm energy storage Capacity optimization does not take into account the problems of low wind-storage joint operation income and poor enthusiasm for wind farm deployment of energy storage due to auxiliary service compensation.

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 taking into account auxiliary service compensation. Background technique [0002] As a flexible and schedulable power source, the energy storage system provides a new way of thinking to deal with the problem of wind power grid connection. The deployment of energy storage systems in wind farms will become one of the models for large-scale development of wind power in the future. Battery energy storage (Battery Energy storage system, BESS) Compared with other energy storage technologies, it has less 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 it can obtain additional wind power grid-connected capacity and redu...

Claims

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Application Information

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Patent Type & Authority Patents(China)
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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