CN113361117A - Distributed energy storage polymerization degree evaluation index model based on polymerization condition - Google Patents

Distributed energy storage polymerization degree evaluation index model based on polymerization condition Download PDF

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CN113361117A
CN113361117A CN202110667986.8A CN202110667986A CN113361117A CN 113361117 A CN113361117 A CN 113361117A CN 202110667986 A CN202110667986 A CN 202110667986A CN 113361117 A CN113361117 A CN 113361117A
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叶鹏
刘思奇
关多娇
屈科明
杨硕
王士元
王枫淇
李天岳
魏靖晓
张政斌
杨宏宇
王子赫
邵旸棣
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Abstract

The invention relates to a distributed energy storage polymerization evaluation model, in particular to a distributed energy storage polymerization degree evaluation index model based on a polymerization condition. The method provides technical basis and a practical method for the aggregation of distributed energy storage participating in auxiliary services in a large scale. The method comprises the following steps: building a structural framework of which distributed energy storage participates in polymerization under a polymerization condition; based on the established framework, acquiring operation parameters of all parts of the energy storage monomer; and setting the output/input power of each energy storage monomer based on the acquired operation parameters of each part of the energy storage monomer. Establishing a polymerization degree index of each energy storage monomer: calculating the energy storage polymerization degree of the energy storage monomer according to the extracted three polymerization degree index data, and calculating 40 energy storage polymerization degree data: and establishing a distributed energy storage polymerization degree evaluation index model based on the polymerization condition. And (4) carrying out example result analysis on the effectiveness of the distributed energy storage polymerization degree evaluation index model.

Description

Distributed energy storage polymerization degree evaluation index model based on polymerization condition
Technical Field
The invention relates to a distributed energy storage polymerization evaluation model, in particular to a distributed energy storage polymerization degree evaluation index model based on a polymerization condition.
Background
The distributed energy storage power and capacity are small, the access position is flexible, the distributed micro-grid and the medium-low voltage distribution network are generally concentrated on a user side, and the distributed micro-grid and the medium-low voltage distribution network can be used for peak regulation, frequency regulation and improvement of the power quality and reliability of power supply of the power grid. However, distributed energy storage is wide in dispersion and difficult to uniformly control, and waste of energy storage resources is easily caused. And large-scale distributed energy storage participating regional power auxiliary service compensation (market) work is promoted in various regions, and the convergence and integration of energy storage resources, namely the aggregation, becomes an important action for effectively regulating and controlling an energy storage object by a power grid.
At present, the research on distributed energy storage aggregation at home and abroad mainly focuses on two aspects: and aggregating the stored energy with similar regulation potential into groups or realizing the relative balance of the charge states of the stored energy. The method comprises the following steps that (1) experts focus on aggregation grouping, firstly, energy storage is clustered or evaluated and grouped through static indexes of energy storage operating characteristics based on an improved K-means algorithm and a panoramic theory, and then a grouped energy storage aggregation potential regulation and control model is constructed; experts pay attention to the realization of balance, firstly set energy storage parameters and charge-discharge balance functions, then aggregate all energy storage into a whole based on aggregation effect and a fully distributed control algorithm, and perform optimized regulation and control. However, the above studies are limited to a single aspect, and the effect is not good enough.
Disclosure of Invention
The invention aims at the defects in the prior art, and provides a distributed energy storage polymerization evaluation model, in particular to a distributed energy storage polymerization degree evaluation index model based on a polymerization condition. Aiming at the problems of wide distribution of distributed energy storage, resource dispersion, incapability of high-efficiency polymerization and the like, the method can realize the polymerization of each energy storage monomer from the energy storage monomer to the energy storage polymer through smaller in-vivo difference and higher in-vivo polymerization degree, and provides a technical basis and a practical method for the polymerization of the distributed energy storage participating in the auxiliary service on a large scale.
In order to achieve the purpose, the invention adopts the following technical scheme that the method comprises the following steps:
building a structural framework of which distributed energy storage participates in polymerization under a polymerization condition;
based on the established framework, acquiring operation parameters of all parts of the energy storage monomer;
setting the output/input power of each energy storage monomer i relative to the instant charge state s based on the operation parameters of each part of the obtained energy storage monomeriCharge and discharge function p(s)i)c、p(si)dThe following were used:
Figure BDA0003117681720000021
Figure BDA0003117681720000022
in the formula: p(s)i)c、p(si)dFor each output/input power of energy storage unit i with respect to instant state of charge siThe charge and discharge function of (2); ciThe rated capacity of the energy storage monomer i is set; c∑The total rated capacity of all the energy storage monomers entering the regulation layer is obtained; pi·ratedThe rated power of the energy storage monomer i is set; a. theiAn adaptation factor for it; a. thei0Adapting the elementary factor for it; diTo which the self-partition coefficient is applied; siIs an immediate state of charge; sshc0.4 is the shallow charge point; sshd0.6 is a shallow discharge charge point; smax0.9 is the maximum charge point; smin0.1 is the minimum charge point; smid0.5 is charge midpoint;
establishing a polymerization degree index of each energy storage monomer i: degree of regulation P of stored energy poweri(ii) a Energy storage adaptive equalization degree PiA first step of; energy storage capacity contribution degree Rdev；
Calculating the energy storage polymerization degree A of the energy storage monomer i according to the extracted three polymerization degree index dataiCalculating 40 energy storage polymerization degrees AiData:
Ai＝μ1·Pi+μ2·Pi*+μ3·Rdev
in the formula: mu.sxWeight representing polymerization degree index of three energy storage monomers is selected according to 9-level scaling method1＝0.5；μ2＝0.3；μ3＝0.2；
And establishing a distributed energy storage polymerization degree evaluation index model based on the polymerization condition.
Further, example result analysis is carried out on the effectiveness of the distributed energy storage polymerization degree evaluation index model, and efficient polymerization of energy storage resources can be realized by the distributed energy storage polymerization degree evaluation index model based on the polymerization condition.
Further, the operating parameters include the energy storage unitsRated capacity Ci(ii) a Rated power Pi·rated(ii) a Adaptive factor Ai(ii) a Adaptive elementary factor Ai0(ii) a Self-distribution coefficient di(ii) a Instantaneous state of charge si(ii) a Immediate area control offset ai。
Further, the establishing of the structural framework of the aggregation of the distributed energy storage under the aggregation condition comprises:
establishing an upper and a lower layers of distributed energy storage aggregation framework: the upper layer is a polymerization layer, and the lower layer is a response layer;
upper polymeric layer: based on a distributed energy storage polymerization degree evaluation index model under a polymerization condition, the distributed energy storage polymerization degree evaluation index model is used for polymerizing energy storage monomers with similar polymerization degrees into an energy storage polymer; to achieve efficient aggregation of energy storage resources.
The lower layer is a response layer and is used for the energy storage polymer to complete the demand response issued by the power grid.
Further, the established regulation degree P of the energy storage poweriThe characterization in the index of degree of polymerization is: the energy storage polymer assists the regulation capability of the output/input power of each energy storage monomer in the polymer along with the continuous change of the regulation degree during the operation of the power grid; piThe calculation method is as follows:
Figure BDA0003117681720000031
Figure BDA0003117681720000032
in the formula: p (a)i)c、p(ai)dControlling deviation a of storage release/absorption power relative to immediate area for area demand of each energy storage monomer i in adjusting processiThe adaptive equalization charge-discharge function of (1); pi·ratedThe rated power of the energy storage monomer i is set; a. theiAn adaptation factor for it; a. thei0Adapting the elementary factor for it; diTo which the self-partition coefficient is applied; a isiControlling the deviation for the immediate area; a ismax0.9 is an emergency action point; a ismin0.1 is the minimum action point; a ismid0.5 is the normal action point;
Figure BDA0003117681720000041
Figure BDA0003117681720000042
in the formula: p'(s)i)c、p′(si)dFor each energy storage monomer i output/input power after removing capacity factor with respect to instant charge state siThe charge and discharge function of (2); p(s)i)c、p(si)dFor each output/input power of energy storage unit i with respect to instant state of charge siThe charge and discharge function of (2); ciThe rated capacity of the energy storage monomer i is set; c∑The total rated capacity of all the energy storage monomers entering the regulation layer is obtained; piAdjusting the degree of energy storage power; p (a)i)c、p(ai)dControlling deviation a of storage release/absorption power relative to immediate area for area demand of each energy storage monomer i in adjusting processiThe adaptive equalization charge-discharge function of (1); siIs an immediate state of charge; smid0.5 is the charge midpoint.
Further, the characterization of the established energy storage adaptive equilibrium degree in the polymerization degree index is as follows: during the operation period of the energy storage polymer cooperating with the power grid, along with the continuous change of the adjustment degree, the self-adaptive balancing capacity of each energy storage monomer in the polymer is realized; the degree P of the energy storage power of the energy storage monomer i can be adjustediPerforming per-unit system representation based on the adaptive equalization technology; self-adaptive equalization degree P of energy storage monomer iiMay be represented as:
Figure BDA0003117681720000043
in the formula: piIs the adaptive equalization degree; piAdjusting the degree of energy storage power; pBIs a self-distribution coefficient d ═15; elementary adaptive factor A00.01; adaptive factor A is 10. A0/PratedDegree of regulation P of stored energy poweri。
Further, the established energy storage capacity contribution degree is characterized in the polymerization degree index as follows: during the operation period of the energy storage polymer cooperating with the power grid, along with the continuous change of the required capacity, the capacity contribution capacity of each energy storage monomer in the polymer is increased; therefore, the energy storage monomer i capacity contribution degree RdevExpressed as:
Figure BDA0003117681720000051
Figure BDA0003117681720000052
in the formula: ccThe schedulable capacity is changed along with the energy storage output; pt(si) For each output/input power of energy storage unit i with respect to instant state of charge siA function of (a); t is a scheduling period; rdevA capacity contribution degree; cdDemand capacity for the system;
after the polymerization degree indexes of all the energy storage monomers i are established, the three polymerization degree indexes are simulated by the energy storage monomers configured in a typical industrial park, and data are extracted.
Further, the establishing of the distributed energy storage polymerization degree evaluation index model based on the polymerization condition comprises: calculating 40 energy storage polymerization degree data AiAs cloud drop variables in the distributed energy storage polymerization degree evaluation index model, AiThe following distribution is satisfied:
Figure BDA0003117681720000053
using cloud expectation curve y (A)i) Geometric form, y (A), describing an index model for evaluating distributed storage polymerization degreesi) The expression is as follows:
Figure BDA0003117681720000054
the quantitative data y (A) formed in the previous step is processed by a reverse cloud generatori) Digital characteristic C (E) converted into distributed energy storage polymerization degree evaluation index modelAi,En,He)，(EAiEn, He) are expressed as follows:
Figure BDA0003117681720000055
Figure BDA0003117681720000056
Figure BDA0003117681720000057
wherein E isAiRepresenting the expectation of the polymerization degree evaluation index model, En representing the entropy of the polymerization degree evaluation index model, He representing the super-entropy of the polymerization degree evaluation index model, n representing the cloud drop number, and S representing the variance;
evaluating the numerical characteristics C (E) of the index model by the forward cloud generator with the distributed accumulation polymerization degreeAiEn, He) generates n-1500 cloud droplets, and continuously repeats the steps until enough operation results of the distributed storage polymerization degree evaluation index model are generated.
Furthermore, the distributed energy storage equipment which is taken as an independent object to participate in the regulation and control of the energy storage aggregator is called an energy storage monomer; the energy storage monomers complete the convergence and integration of self resource energy under the regulation and control of an energy storage polymer supplier, and the large-scale energy storage monomer object formed by the energy storage monomers through polymerization is called an energy storage polymer.
Further, AiAn adaptation factor for it; the value range is 0.01-1, and the value range is related to the type of the energy storage battery, and the nickel-cadmium, the all-vanadium liquid flow and the lithium battery are 0.01; taking 0.5 of sodium-sulfur and zinc-bromine batteries; taking a lead-acid battery as 1; a. thei0For its adaptive elementary factor, Ai0＝A·Prated/10；diTaking 13 sodium-sulfur and lithium batteries as self-distribution coefficients, wherein the value range of the self-distribution coefficients is 15-20, and the self-distribution coefficients are related to the types of the energy storage batteries; taking 15 parts of an all-vanadium redox flow battery; taking 18 nickel-cadmium and zinc-bromine batteries; the lead-acid battery is 20.
Further, the energy storage monomers configured in a typical industrial park are: lead-acid batteries, all-vanadium redox flow batteries, nickel-cadmium batteries, sodium-sulfur batteries, zinc-bromine batteries and lithium batteries; the configuration parameters are respectively as follows: 4MW/10MW · h, 50MW/100MW · h, 8MW/20MW · h, 25MW/80MW · h, 15MW/40MW · h, 30MW/60MW · h.
Specifically, the polymerization potential among the energy storage monomers is defined as the polymerization degree of the energy storage monomers, and three polymerization degree indexes are set under the energy storage polymerization degree and respectively: the energy storage power adjustment degree of the power adjustment factor is taken into account; the energy storage self-adaptive balance degree of the charge state adjusting factor is calculated; and the energy storage capacity contribution degree of the capacity regulating factor is taken into account.
Specifically, if the results of the distributed energy storage polymerization degree evaluation index model calculation examples of some energy storage monomers are closer, it is proved that the possibility of the energy storage polymer polymerized by the energy storage monomers is higher.
Specifically, the energy storage polymerization degree A of the energy storage monomer i is calculatediThree polymerization degree indexes Pi、Pi*、RdevThe data of the curve is the random extraction of the data on the operation curve, and the extracted data can be fitted with the dynamic trend of the curve to the maximum extent; and calculating corresponding polymerization degree data according to the extracted index data, and pre-generating 40 polymerization degree data by each energy storage monomer.
Compared with the prior art, the invention has the beneficial effects.
The method is based on the distributed energy storage polymerization degree evaluation index model under the polymerization condition, so that the difference in the energy storage monomer groups can be balanced to a greater extent, and the relative balance among the energy storage monomer groups can be realized. The traditional distributed energy storage aggregation evaluation model only considers single aggregation grouping or single aggregation regulation and control, and cannot effectively combine the single aggregation grouping and the single aggregation regulation and control, so that the difference in the energy storage monomer grouping and the unbalance among the energy storage monomer groupings are caused, and the condition of energy storage resource waste exists. The energy storage monomers with similar polymerization degrees are screened out through the model and polymerized into energy storage polymers, so that the energy storage monomers can be polymerized into the energy storage polymers through smaller in-vivo difference and higher in-vivo polymerization degrees, and the high-efficiency utilization of energy storage resources is realized.
The method is easy to implement, based on polymerization conditions, the energy storage polymerization degree is calculated by three innovative energy storage polymerization degree indexes, so that the polymerization potential among energy storage monomers can be more intuitively expressed, and the method is easy to implement from calculation; meanwhile, a distributed energy storage polymerization degree evaluation index model is adopted for solving, and the calculation result is easy to observe.
The method is convenient for commercial development, the large-scale distributed energy storage participation regional power auxiliary service compensation (market) work is promoted in various regions, the development of the distributed energy storage polymerization degree evaluation index model based on the polymerization condition has great demand inevitably, and the method has good commercial development prospect.
Drawings
The invention is further described with reference to the following figures and detailed description. The scope of the invention is not limited to the following expressions.
Fig. 1 is a structural framework of distributed energy storage participating in aggregation.
Fig. 2 is a flowchart of an index model for evaluating the degree of distributed storage polymerization based on polymerization conditions.
Figure 3 is a graph of energy storage cell parameters for a typical 6 industrial park configuration in the area of liaison province.
Fig. 4 is a simulated operating curve of the power adjustment degree of the 6 energy storage single bodies.
Fig. 5 is a simulation operation curve of the adaptive equalization degree of the 6 energy storage monomers.
Fig. 6 is a simulation operation curve of the capacity contribution degree of the 6 energy storage monomers.
Fig. 7 is a simulation operation result of the distributed energy storage polymerization degree evaluation index model.
Fig. 8 is a 10-time fitting residual error graph of a simulation evaluation result of the distributed energy storage polymerization degree evaluation index model.
FIGS. 9-15 show data extracted from three simulation curves of polymerization degree indexes of energy storage monomers configured in 6 typical industrial parks in Liaoning province and 40 calculated energy storage polymerization degrees AiAnd (4) data.
Detailed Description
The invention provides a distributed energy storage polymerization degree evaluation index model based on a polymerization condition. Energy storage monomers with similar polymerization degrees are screened out through the model and polymerized into energy storage polymers, so that the energy storage monomers can be polymerized into the energy storage polymers through smaller in-vivo difference and higher in-vivo polymerization degrees, and the energy storage resources can be efficiently utilized. The basic idea is as follows: the polymerization layer is based on a distributed energy storage polymerization degree evaluation index model under a polymerization condition and is used for polymerizing energy storage monomers with similar polymerization degrees into energy storage polymers. The idea of this layer is: and the high-efficiency aggregation of energy storage resources is realized. The idea of the whole model is as follows: the energy storage resources scattered in a wide area are aggregated and regulated, so that the power grid requirement and scheduling can be conveniently responded, and a realistic reference is provided for aggregation of distributed energy storage participating in auxiliary service in a large scale.
The specific technical scheme is as follows: based on a polymerization condition framework, three dynamic adjustment indexes of energy storage power adjustment degree, self-adaptive balance degree and capacity contribution degree are established, and the three dynamic adjustment indexes can fully represent the dynamic adjustment capacity of energy storage monomers when the energy storage monomers participate in regional power grid response, so that the energy storage monomers with similar dynamic adjustment capacity are grouped. And then, calculating the energy storage polymerization degree according to the three dynamic adjustment indexes, taking the energy storage polymerization degree as input data of a distributed energy storage polymerization degree evaluation index model, screening energy storage monomers with similar polymerization degrees through the model, and polymerizing the energy storage monomers into an energy storage polymer.
The distributed energy storage polymerization degree evaluation index model based on the polymerization condition is based on a polymerization condition framework, three dynamic adjustment indexes of energy storage power adjustment degree, self-adaptive balance degree and capacity contribution degree are firstly established, and the three dynamic adjustment indexes can fully represent the dynamic adjustment capacity of energy storage monomers when the energy storage monomers participate in regional power grid response, so that the energy storage monomers with similar dynamic adjustment capacity are grouped into one group. And then, calculating the energy storage polymerization degree according to the three dynamic adjustment indexes, taking the energy storage polymerization degree as input data of a distributed energy storage polymerization degree evaluation index model, screening energy storage monomers with similar polymerization degrees through the model, and polymerizing the energy storage monomers into an energy storage polymer.
A distributed energy storage polymerization degree evaluation index model based on polymerization conditions comprises the following steps:
1. a distributed energy storage polymerization degree evaluation index model based on a polymerization condition is based on a polymerization condition framework, and three dynamic adjustment indexes of energy storage power adjustment degree, self-adaptive balance degree and capacity contribution degree are established firstly. And then, selecting energy storage monomers configured in 6 typical industrial parks in the Liaoning province, carrying out simulation verification on the polymerization degree indexes of the energy storage monomers configured in the 6 typical industrial parks in the Liaoning province, randomly extracting data from the operation curves of the indexes, and enabling the extracted data to be in accordance with the dynamic trend of the curves to the maximum extent. And calculating corresponding polymerization degree data according to the extracted index data, pre-generating 40 polymerization degree data by each energy storage monomer, using the polymerization degree data as input data of a distributed energy storage polymerization degree evaluation index model, screening energy storage monomers with similar polymerization degrees through the model, and polymerizing the energy storage monomers into an energy storage polymer. The method is characterized in that: the method comprises the following steps:
step 1) firstly, establishing a structural framework of the distributed energy storage participating in polymerization under a polymerization condition;
(1) establishing an upper and a lower layers of distributed energy storage aggregation framework: the upper layer is a polymerization layer, and the lower layer is a response layer.
(2) And the upper polymerization layer is based on a distributed energy storage polymerization degree evaluation index model under the polymerization condition and is used for polymerizing energy storage monomers with similar polymerization degrees into an energy storage polymer. The purpose of this layer is: and the high-efficiency aggregation of energy storage resources is realized.
(3) The lower layer is a response layer which is mainly used for the energy storage polymer to complete the demand response issued by the power grid.
Step 2) acquiring operation parameters of each part of energy storage monomers configured in 6 typical industrial parks in the Liaoning province based on the established frame, wherein the operation parameters comprise: rated capacity C of each energy storage monomeri(ii) a Rated power Pi·rated(ii) a Adaptive factor Ai(ii) a Adaptive elementary factor Ai0(ii) a Self-distribution coefficient di(ii) a Instantaneous state of charge si(ii) a Immediate area control offset ai；
Step 3) setting the output (input) power of energy storage monomers configured in 6 typical industrial parks in the Liaoning province about the instant state of charge s based on the acquired operation parametersiCharge and discharge function p(s)i)c、p(si)dThe following were used:
Figure BDA0003117681720000101
Figure BDA0003117681720000102
in the formula: p(s)i)c、p(si)dFor each energy storage cell i output (input) power with respect to the instantaneous state of charge siThe charge and discharge function of (2); ciThe rated capacity of the energy storage monomer i is set; c∑The total rated capacity of all the energy storage monomers entering the regulation layer is obtained; pi·ratedThe rated power of the energy storage monomer i is set; a. theiAn adaptation factor for it; a. thei0Adapting the elementary factor for it; diTo which the self-partition coefficient is applied; siIs an immediate state of charge; sshc0.4 is the shallow charge point; sshd0.6 is a shallow discharge charge point; smax0.9 is the maximum charge point; smin0.1 is the minimum charge point; smid0.5 is the charge midpoint.
Step 4) establishing the polymerization degree indexes of the energy storage monomers configured in 6 typical industrial parks in the Liaoning province based on the set charge and discharge functions of the energy storage monomers: degree of regulation P of stored energy poweri(ii) a Energy storage adaptive equalization degree PiA first step of; energy storage capacity contribution degree Rdev。
(1) Established degree of regulation P of stored energy poweriThe characterization in the index of degree of polymerization is: energy storage polymer assistAnd during the operation of the power grid, along with the continuous change of the adjustment degree, the adjustment capability of the output (input) power of each energy storage monomer in the polymer is realized. PiThe calculation method is as follows:
Figure BDA0003117681720000111
Figure BDA0003117681720000112
in the formula: p (a)i)c、p(ai)dControl deviation a of the storage release (absorption) power with respect to the immediate area for the area demand of each energy storage cell i during the regulation processiThe adaptive equalization charge-discharge function of (1); pi·ratedThe rated power of the energy storage monomer i is set; a. theiAn adaptation factor for it; a. thei0Adapting the elementary factor for it; diTo which the self-partition coefficient is applied; a isiControlling the deviation for the immediate area; a ismax0.9 is an emergency action point; a ismin0.1 is the minimum action point; a ismidAnd 0.5 is the normal action point.
Figure BDA0003117681720000113
Figure BDA0003117681720000114
In the formula: p'(s)i)c、p′(si)dOutput (input) power of each energy storage monomer i after capacity factor removal is related to instant charge state siThe charge and discharge function of (2); p(s)i)c、p(si)dFor each energy storage cell i output (input) power with respect to the instantaneous state of charge siThe charge and discharge function of (2); ciThe rated capacity of the energy storage monomer i is set; c∑The total rated capacity of all the energy storage monomers entering the regulation layer is obtained; piFor regulating power of stored energyDegree of saving; p (a)i)c、p(ai)dControl deviation a of the storage release (absorption) power with respect to the immediate area for the area demand of each energy storage cell i during the regulation processiThe adaptive equalization charge-discharge function of (1); siIs an immediate state of charge; smid0.5 is the charge midpoint.
(2) The characterization of the energy storage self-adaptive equilibrium degree in the polymerization degree index is as follows: and during the operation period of the energy storage polymer cooperating with the power grid, along with the continuous change of the adjustment degree, the self-adaptive balancing capacity of each energy storage monomer in the polymer is realized. The degree P of the energy storage power of the energy storage monomer i can be adjustediAnd (4) performing per-unit system representation based on the adaptive equalization technology. Self-adaptive equalization degree P of energy storage monomer iiMay be represented as:
Figure BDA0003117681720000121
in the formula: piIs the adaptive equalization degree; piAdjusting the degree of energy storage power; pBIs self-distribution coefficient d is 15; elementary adaptive factor A00.01; adaptive factor A is 10. A0/PratedDegree of regulation P of stored energy poweri。
(3) The characterization of the energy storage capacity contribution degree in the polymerization degree index is as follows: during the operation period of the energy storage polymer cooperating with the power grid, along with the continuous change of the required capacity, the capacity contribution capacity of each energy storage monomer in the polymer is increased. Therefore, the energy storage monomer i capacity contribution degree RdevIs represented as;
Figure BDA0003117681720000122
Figure BDA0003117681720000123
in the formula: ccThe schedulable capacity is changed along with the energy storage output; pt(si) For each energy storage monomer i output (input) power with respect to instant chargeState siA function of (a); t is a scheduling period; rdevA capacity contribution degree; cdCapacity is required for the system.
(4) Based on the established polymerization degree index of the energy storage monomer: the three polymerization degree indexes are simulated and data are extracted by using energy storage monomers configured in 6 typical industrial parks in the area of Liaoning province, and the extracted data are shown in figure 9.
Step 5) calculating the energy storage polymerization degree A of the energy storage monomers configured in 6 typical industrial parks in the Liaoning province according to the extracted three polymerization degree index dataiCalculating 40 energy storage polymerization degrees AiData, as shown in fig. 9:
Ai＝μ1·Pi+μ2·Pi*+μ3·Rdev
in the formula: mu.sxWeight representing polymerization degree index of three energy storage monomers is selected according to 9-level scaling method1＝0.5；μ2＝0.3；μ3＝0.2。
Step 6) establishing a polymerization degree evaluation index model of energy storage monomers configured in 6 typical industrial parks in the Liaoning province based on polymerization conditions;
(1) calculating 40 energy storage polymerization degree data AiAs a cloud drop variable in a polymerization degree evaluation index model of energy storage monomers configured in 6 typical industrial parks in the Liaoning province, AiThe following distribution is satisfied:
Figure BDA0003117681720000131
(2) using cloud expectation curve y (A)i) Describing the geometric form of an index model for evaluating the polymerization degree of energy storage monomers configured in 6 typical industrial parks in the Liaoning province, y (A)i) The expression is as follows:
Figure BDA0003117681720000132
(3) by means of the reverse cloud generator,quantitative data y (A) formed in the previous stepi) Converting the digital characteristic C (E) into a polymerization degree evaluation index model of energy storage monomers configured in 6 typical industrial parks in the Liaoning provinceAi,En,He)，(EAiEn, He) are expressed as follows:
Figure BDA0003117681720000133
Figure BDA0003117681720000134
Figure BDA0003117681720000135
wherein E isAiRepresenting the expectation of the polymerization degree evaluation index model, En representing the entropy of the polymerization degree evaluation index model, He representing the super-entropy of the polymerization degree evaluation index model, n representing the cloud drop number, and S representing the variance.
(4) Through a forward cloud generator, evaluating the digital characteristic C (E) of an index model by the polymerization degree of energy storage monomers configured in 6 typical industrial parks in the Liaoning provinceAiEn, He) to generate n-1500 cloud drops, and continuously repeating the above steps until enough calculation results of the polymerization degree evaluation index model of the energy storage monomers configured in 6 typical industrial parks in the area of the liaison province are generated.
And 7) carrying out example result analysis on the effectiveness of the polymerization degree evaluation index models of the energy storage monomers configured in 6 typical industrial parks in the Liaoning province, and verifying that the distributed energy storage polymerization degree evaluation index models based on the polymerization condition can realize the high-efficiency polymerization of energy storage resources.
Fig. 1 is a structural framework of distributed energy storage participating in aggregation. The upper layer is a polymerization layer which is based on a distributed energy storage polymerization degree evaluation index model under a polymerization condition and is used for polymerizing energy storage monomers with similar polymerization degrees into energy storage polymers. The lower layer is a response layer which is mainly used for the energy storage polymer to complete the demand response issued by the power grid.
Fig. 2 is a flowchart of an index model for evaluating the degree of distributed storage polymerization based on polymerization conditions. A distributed energy storage polymerization degree evaluation index model based on a polymerization condition is based on a polymerization condition framework, and is characterized in that three dynamic adjustment indexes of energy storage power adjustment degree, self-adaptive balance degree and capacity contribution degree are established firstly, and the three dynamic adjustment indexes can fully represent the dynamic adjustment capacity of energy storage monomers when the energy storage monomers participate in regional power grid response, so that the energy storage monomers with similar dynamic adjustment capacity are grouped into one group. And then, calculating the energy storage polymerization degree according to the three dynamic adjustment indexes, taking the energy storage polymerization degree as input data of a distributed energy storage polymerization degree evaluation index model, screening energy storage monomers with similar polymerization degrees through the model, and polymerizing the energy storage monomers into an energy storage polymer.
FIG. 3 illustrates the energy storage cell parameters for 6 typical industrial parks in the Liaoning province.
Fig. 4 is a simulation operation curve of the energy storage power adjustment degree of 6 energy storage monomers. As can be seen from the figure, the adjustment depths of the energy storage power adjustment degrees of the 6 energy storage monomers are consistent (the longitudinal trend is located between [ -1,1 ]), the main adjustment ranges are different (the transverse trend), and the shorter the interval of the main adjustment ranges, the earlier the energy storage monomer participates in the adjustment is proved. Wherein, the energy storage 2 and 6 are mainly positioned in the early stage of regulation; the stored energy 4, 3 is mainly in the middle stage of regulation; the stored energy 5, 1 is mainly located in the later stages of regulation, corresponding to the explanation of fig. 2.
Fig. 5 is a simulation operation curve of the adaptive equalization degree of the 6 energy storage monomers. As can be seen from the figure, the adjustment range of the self-adaptive equalization degree of each energy storage unit is approximately locked between [0,0.5], and the range is the range of the self-adaptive equalization of each energy storage unit. When the adjustment requirement is urgent, the self-adaptive equalization degrees of the energy storage units 1, 3, 4 and 5 are slightly increased to break through the self-adaptive equalization range, which shows that the relative equalization of the adjustment capability is realized on the basis that the self-adjustment capability of each energy storage unit is not weakened.
Fig. 6 is a simulation operation curve of the capacity contribution degree of the 6 energy storage monomers. In the figure, when the required capacity is greater than zero, the required energy storage discharge (output) is represented; when the required capacity is less than zero, it represents the required energy storage charge (input). As can be seen from the figure, the magnitude of the capacity contribution of each energy storage cell is represented by the plane size when the value is equal to 1, and the magnitude of the capacity contribution of each energy storage cell is sequentially as follows: the energy storage units 2, 4, 6, 5, 3 and 1 correspond to the capacity of each energy storage unit.
Fig. 7 is a simulation operation result of the distributed energy storage polymerization degree evaluation index model. Fig. 8 is a 10-time fitting residual error graph of a simulation evaluation result of the distributed energy storage polymerization degree evaluation index model. As shown in fig. 7 and 8, the black dispersion point is characterized by: and estimating the polymerization degree of the energy storage monomer according to the input polymerization degree data. The red curve is characterized by: fitting ten times of fitting curves according to the polymerization degree data. The residual plot of each fitted curve is shown in fig. 8. As can be seen from the figure, the energy storage monomers 1, 2 and 3 have similar polymerization degree evaluation index models and fitting curves; the energy storage monomers 4, 5 and 6 have similar polymerization degree evaluation index models and fitting curves, and residual data of the energy storage monomers 1, 2 and 3 are close to each other; the residual data of the energy storage monomers 4, 5 and 6 are close. It can be seen that energy storage monomers 1, 2, 3 are suitable for polymerization to form polymer 1 and energy storage monomers 4, 5, 6 are suitable for polymerization to form polymer 2.
FIGS. 9-15 are data extracted from three polymerization degree index simulation curves of energy storage monomers configured in 6 typical industrial parks in Liaoning province and 40 calculated energy storage polymerization degrees AiAnd (4) data.
It should be understood that the detailed description of the present invention is only for illustrating the present invention and is not limited by the technical solutions described in the embodiments of the present invention, and those skilled in the art should understand that the present invention can be modified or substituted equally to achieve the same technical effects; as long as the use requirements are met, the method is within the protection scope of the invention.

Claims (10)

1. A distributed energy storage polymerization degree evaluation index model based on polymerization conditions is characterized by comprising the following steps:
building a structural framework of which distributed energy storage participates in polymerization under a polymerization condition;
based on the established framework, acquiring operation parameters of all parts of the energy storage monomer;
setting the output/input power of each energy storage monomer i relative to the instant charge state s based on the operation parameters of each part of the obtained energy storage monomeriCharge and discharge function p(s)i)c、p(si)dThe following were used:
Figure FDA0003117681710000011
Figure FDA0003117681710000012
in the formula: p(s)i)c、p(si)dFor each output/input power of energy storage unit i with respect to instant state of charge siThe charge and discharge function of (2); ciThe rated capacity of the energy storage monomer i is set; c∑The total rated capacity of all the energy storage monomers entering the regulation layer is obtained; pi·ratedThe rated power of the energy storage monomer i is set; a. theiAn adaptation factor for it; a. thei0Adapting the elementary factor for it; diTo which the self-partition coefficient is applied; siIs an immediate state of charge; sshc0.4 is the shallow charge point; sshd0.6 is a shallow discharge charge point; smax0.9 is the maximum charge point; smin0.1 is the minimum charge point; smid0.5 is charge midpoint;
establishing a polymerization degree index of each energy storage monomer i: degree of regulation P of stored energy poweri(ii) a Energy storage adaptive equalization degree PiA first step of; energy storage capacity contribution degree Rdev；
Calculating the energy storage polymerization degree A of the energy storage monomer i according to the extracted three polymerization degree index dataiCalculating 40 energy storage polymerization degrees AiData:
Ai＝μ1·Pi+μ2·Pi*+μ3·Rdev
in the formula: mu.sxWeight representing index of degree of polymerization of three energy storage monomers, according to 9Step scale method, selecting mu1＝0.5；μ2＝0.3；μ3＝0.2；
And establishing a distributed energy storage polymerization degree evaluation index model based on the polymerization condition.
2. The model of claim 1, wherein the index model is based on the evaluation of distributed accumulation polymerization degree under polymerization condition: and carrying out example result analysis on the effectiveness of the distributed energy storage polymerization degree evaluation index model, and verifying that the distributed energy storage polymerization degree evaluation index model based on the polymerization condition can realize the efficient polymerization of energy storage resources.
3. The model of claim 1, wherein the index model is based on the evaluation of distributed accumulation polymerization degree under polymerization condition: the operating parameters comprise rated capacity C of each energy storage uniti(ii) a Rated power Pi·rated(ii) a Adaptive factor Ai(ii) a Adaptive elementary factor Ai0(ii) a Self-distribution coefficient di(ii) a Instantaneous state of charge si(ii) a Immediate area control offset ai。
4. The model of claim 1, wherein the index model is based on the evaluation of distributed accumulation polymerization degree under polymerization condition: the building of the structural framework of the aggregation of the distributed energy storage participation under the aggregation condition comprises the following steps:
establishing an upper and a lower layers of distributed energy storage aggregation framework: the upper layer is a polymerization layer, and the lower layer is a response layer;
upper polymeric layer: based on a distributed energy storage polymerization degree evaluation index model under a polymerization condition, the distributed energy storage polymerization degree evaluation index model is used for polymerizing energy storage monomers with similar polymerization degrees into an energy storage polymer; to achieve efficient aggregation of energy storage resources.
The lower layer is a response layer and is used for the energy storage polymer to complete the demand response issued by the power grid.
5. The model of claim 1, wherein the index model is based on the evaluation of distributed accumulation polymerization degree under polymerization condition: established degree of regulation P of stored energy poweriThe characterization in the index of degree of polymerization is: the energy storage polymer assists the regulation capability of the output/input power of each energy storage monomer in the polymer along with the continuous change of the regulation degree during the operation of the power grid; piThe calculation method is as follows:
Figure FDA0003117681710000021
Figure FDA0003117681710000031
in the formula: p (a)i)c、p(ai)dControlling deviation a of storage release/absorption power relative to immediate area for area demand of each energy storage monomer i in adjusting processiThe adaptive equalization charge-discharge function of (1); pi·ratedThe rated power of the energy storage monomer i is set; a. theiAn adaptation factor for it; a. thei0Adapting the elementary factor for it; diTo which the self-partition coefficient is applied; a isiControlling the deviation for the immediate area; a ismax0.9 is an emergency action point; a ismin0.1 is the minimum action point; a ismid0.5 is the normal action point;
Figure FDA0003117681710000032
Figure FDA0003117681710000033
in the formula: p'(s)i)c、p′(si)dFor each energy storage monomer i output/input power after removing capacity factor with respect to instant charge state siThe charge and discharge function of (2); p(s)i)c、p(si)dFor each output/input power of energy storage unit i with respect to instant state of charge siCharging and discharging ofA function; ciThe rated capacity of the energy storage monomer i is set; c∑The total rated capacity of all the energy storage monomers entering the regulation layer is obtained; piAdjusting the degree of energy storage power; p (a)i)c、p(ai)dControlling deviation a of storage release/absorption power relative to immediate area for area demand of each energy storage monomer i in adjusting processiThe adaptive equalization charge-discharge function of (1); siIs an immediate state of charge; smid0.5 is the charge midpoint.
6. The model of claim 1, wherein the index model is based on the evaluation of distributed accumulation polymerization degree under polymerization condition: the characterization of the established energy storage self-adaptive equilibrium degree in the polymerization degree index is as follows: during the operation period of the energy storage polymer cooperating with the power grid, along with the continuous change of the adjustment degree, the self-adaptive balancing capacity of each energy storage monomer in the polymer is realized; the degree P of the energy storage power of the energy storage monomer i can be adjustediPerforming per-unit system representation based on the adaptive equalization technology; self-adaptive equalization degree P of energy storage monomer iiMay be represented as:
Figure FDA0003117681710000041
in the formula: piIs the adaptive equalization degree; piAdjusting the degree of energy storage power; pBIs self-distribution coefficient d is 15; elementary adaptive factor A00.01; adaptive factor A is 10. A0/PratedDegree of regulation P of stored energy poweri。
7. The model of claim 1, wherein the index model is based on the evaluation of distributed accumulation polymerization degree under polymerization condition: the characterization of the established energy storage capacity contribution degree in the polymerization degree index is as follows: during the operation period of the energy storage polymer cooperating with the power grid, along with the continuous change of the required capacity, the capacity contribution capacity of each energy storage monomer in the polymer is increased; therefore, the energy storage monomer i capacity contribution degree RdevExpressed as:
Figure FDA0003117681710000042
Figure FDA0003117681710000043
in the formula: ccThe schedulable capacity is changed along with the energy storage output; pt(si) For each output/input power of energy storage unit i with respect to instant state of charge siA function of (a); t is a scheduling period; rdevA capacity contribution degree; cdDemand capacity for the system;
after the polymerization degree indexes of all the energy storage monomers i are established, the three polymerization degree indexes are simulated by the energy storage monomers configured in a typical industrial park, and data are extracted.
8. The model of claim 1, wherein the index model is based on the evaluation of distributed accumulation polymerization degree under polymerization condition: the establishment of the distributed energy storage polymerization degree evaluation index model based on the polymerization condition comprises the following steps: calculating 40 energy storage polymerization degree data AiAs cloud drop variables in the distributed energy storage polymerization degree evaluation index model, AiThe following distribution is satisfied:
Figure FDA0003117681710000044
using cloud expectation curve y (A)i) Geometric form, y (A), describing an index model for evaluating distributed storage polymerization degreesi) The expression is as follows:
Figure FDA0003117681710000051
the quantitative data y (A) formed in the previous step is processed by a reverse cloud generatori) Is converted intoDigital characteristic C (E) of distributed energy storage polymerization degree evaluation index modelAi,En,He)，(EAiEn, He) are expressed as follows:
Figure FDA0003117681710000052
Figure FDA0003117681710000053
Figure FDA0003117681710000054
wherein E isAiRepresenting the expectation of the polymerization degree evaluation index model, En representing the entropy of the polymerization degree evaluation index model, He representing the super-entropy of the polymerization degree evaluation index model, n representing the cloud drop number, and S representing the variance;
evaluating the numerical characteristics C (E) of the index model by the forward cloud generator with the distributed accumulation polymerization degreeAiEn, He) generates n-1500 cloud droplets, and continuously repeats the steps until enough operation results of the distributed storage polymerization degree evaluation index model are generated.
9. The model of claim 1, wherein the index model is based on the evaluation of distributed accumulation polymerization degree under polymerization condition: the distributed energy storage equipment which is taken as an independent object to participate in the regulation and control of the energy storage polymer is called as an energy storage monomer; the energy storage monomers complete the convergence and integration of self resource energy under the regulation and control of an energy storage polymer supplier, and the large-scale energy storage monomer object formed by the energy storage monomers through polymerization is called an energy storage polymer.
10. The model of claim 1, wherein the index model is based on the evaluation of distributed accumulation polymerization degree under polymerization condition: a. theiAn adaptation factor for it; the value range is between 0.01 and 1, and the type of the energy storage batteryTaking 0.01 percent of nickel-cadmium, all-vanadium liquid flow and lithium battery; taking 0.5 of sodium-sulfur and zinc-bromine batteries; taking a lead-acid battery as 1; a. thei0For its adaptive elementary factor, Ai0＝A·Prated/10；diTaking 13 sodium-sulfur and lithium batteries as self-distribution coefficients, wherein the value range of the self-distribution coefficients is 15-20, and the self-distribution coefficients are related to the types of the energy storage batteries; taking 15 parts of an all-vanadium redox flow battery; taking 18 nickel-cadmium and zinc-bromine batteries; taking 20 lead-acid batteries;
the energy storage monomers configured in a typical industrial park are: lead-acid batteries, all-vanadium redox flow batteries, nickel-cadmium batteries, sodium-sulfur batteries, zinc-bromine batteries and lithium batteries; the configuration parameters are respectively as follows: 4MW/10MW · h, 50MW/100MW · h, 8MW/20MW · h, 25MW/80MW · h, 15MW/40MW · h, 30MW/60MW · h.
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