CN109492809B - Wind power plant value evaluation method based on node electricity price - Google Patents

Wind power plant value evaluation method based on node electricity price Download PDF

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CN109492809B
CN109492809B CN201811329845.XA CN201811329845A CN109492809B CN 109492809 B CN109492809 B CN 109492809B CN 201811329845 A CN201811329845 A CN 201811329845A CN 109492809 B CN109492809 B CN 109492809B
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江岳文
温步瀛
郭丽云
林建新
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Abstract

The invention relates to a wind power plant value evaluation method based on node electricity prices. The method is characterized by considering the network value of wind power integration, integrating the network value into node electricity prices, and establishing a specific value model for evaluating a certain wind power plant by utilizing the thought of trend tracking, the change of the load node electricity prices before and after wind power integration and the standby cost caused by wind power so as to optimize the operation of a power system and the wind power plant.

Description

Wind power plant value evaluation method based on node electricity price
Technical Field
The invention relates to the field of optimized operation of power systems, in particular to a wind power plant value evaluation method based on node electricity prices.
Background
Wind power is used as a renewable energy source which is pollution-free and extremely low in marginal cost, and the wind power is incorporated into a power grid to directly influence the original configuration of power resources, so that the energy consumption cost of a conventional unit can be reduced, the system operation cost can be reduced, and the line transmission margin of the power grid can be improved. On the other hand, due to the uncertainty of wind power, more spare cost is caused to the system. The method is particularly necessary for providing a favorable reference for the acceptance, the wind abandonment and the construction of a wind power plant of the wind power. The existing wind power value evaluation basically reflects the total value of all wind power plants from the whole system, the value of a single wind power plant is difficult to measure specifically, the value measurement is not comprehensive, the value is mainly reflected only in the energy consumption value and the standby cost, and the influence of wind power grid connection on the line transmission margin is not considered. If the wind power can provide reverse power flow and the transmission margin of some lines in the power grid is increased, the positive network value is generated for the transmission capability available for the system, particularly for heavy load lines; on the contrary, if the transmission power of some lines is increased by the wind power integration, so that the transmission margin of some lines, particularly heavy load lines, is reduced, the wind power generates negative network value.
The node electricity price can reflect the values of the electric energy at different times at different geographical positions in the system, reflect the scarcity degree of the electric power resources, improve the use efficiency of the electric power resources, optimize the configuration of the electric power resources, and provide useful information for producers, consumers, investors and managers of the electric power. Node electricity prices before and after wind power integration generally change, and the change is just the value reflection of wind power. Therefore, the method considers the change of the transmission margin of the line before and after the wind power integration, particularly the change of the margin of the heavy load line, establishes a node electricity price model, compares the changes of the node electricity prices before and after the wind power integration, and forms the evaluation of the energy consumption value and the network value of a certain wind power plant; in addition, in order to comprehensively measure the value of a certain wind power plant, the standby cost brought to the system operation is considered, and the value of the wind power plant on a certain node is comprehensively obtained.
Disclosure of Invention
The invention aims to provide a wind power plant value evaluation method based on node electricity prices, which is based on the node electricity prices considering the energy consumption and the network value after wind power integration, calculates the standby cost of wind power, comprehensively measures the value of a certain wind power plant, provides a powerful reference for planning and running the wind power plant, and provides a reference for the optimized running of a power system containing the wind power.
In order to achieve the purpose, the technical scheme of the invention is as follows: a wind power plant value evaluation method based on node electricity prices comprises the following steps:
step S1, extracting system information, operating parameters, and network parameters:
step S2: the optimal power flow objective function operates the optimal power flow of the power system without wind power with the lowest system operation cost, obtains the electricity price of each node, the serial number of the heavy-load line and the transmission capacity of the heavy-load power transmission line by using a primary-dual interior point method, and calculates the transmission margin r of each line without wind powerlI.e. by
Figure BDA0001859601710000021
Wherein h islFor tide on line lA stream; fl maxMaximum transmission capacity on line l; r islThe transmission margin of a heavy load line l when wind power is not contained; when r islWhen the load is less than or equal to alpha, the line l is considered as a heavy load line, and the value of alpha is taken according to the actual operation condition of the power grid;
step S3: calculating the value of wind power grid-connected transmission margin:
when the wind power is connected to the grid, the transmission margin of the original heavy load line l is rl W，
If rl W-rlIf the wind power is more than or equal to 0, the wind power generates positive network value on the line l; to simplify the analysis problem, let:
Vl W,T,+＝rl W-rl
in the formula, Vl W,T,+The positive network value of the wind power on the line l is obtained;
on the contrary, if rl W-rlIf the wind power generation rate is less than or equal to 0, the wind power generation generates negative network value V on the line ll W,T,-Let us order
Vl W,T,-＝γl(rl W-rl)
γlA proportionality coefficient greater than 1 indicates that the negative value should be greater if the overload of the line continues to be aggravated under a heavily loaded line;
if a new heavy load line l, namely r appears in the wind power integrationl WIf the value is less than or equal to alpha, the negative network value generated on the line l by the wind power is Vl W,T,N,-Let us order
Vl W,T,N,-＝rl W-α
If the wind power integration does not make the original heavy load line load shedding and loading or the new heavy load line appears, the network value is 0;
in conclusion, the transmission margin value of the line l after wind power integration is as follows:
Vl W,T＝al(rl W-rl)+blγ(rl W-rl)+cl(rl W-α)
wherein, al、bl、clVariables 0, 1, for line l, at most one is not 0;
step S4, establishing an optimal power flow model considering wind power grid connection transmission margin value:
wind power is merged into a power system, and the main purpose is to reduce the energy consumption level of non-renewable energy sources as far as possible and keep the sustainable development of the power system on the premise of ensuring the safe operation of the power system; therefore, the optimal power flow objective function is the lowest system operating cost, i.e. the optimal power flow objective function is
Figure BDA0001859601710000031
ai、biAnd ciRespectively, a cost function of the conventional generator set i; pi GGenerating output of a conventional generator set i; n is a radical ofGThe number of conventional generator sets;
step S5, solving the node electricity price containing wind power:
in order to calculate the node electricity price containing wind power, the model established in the step S4 is converted into a Lagrange function, and lambda is defined1、λ2l、λ3lLagrange coefficient constrained by equation, and1≥0、λ2l≥0、λ3lnot less than 0; definition of mu1l、μ2l、τ1l，g1i、g2i、
Figure BDA0001859601710000032
Lagrange coefficients constrained by inequality, and mu1l≥0、μ2l≥0、τ1l≥0、g1i≥0、g2i≥0、
Figure BDA0001859601710000033
Figure BDA0001859601710000034
According to the KKT condition, at the optimum point:
Figure BDA0001859601710000035
Figure BDA0001859601710000036
from the above formula, one can obtain:
λ3l＝-τ1l(al+blγ+cl)
Figure BDA0001859601710000037
the node electricity price for embodying the wind power grid connection adequacy value is as follows:
Figure BDA0001859601710000041
when the network value is fused into the node electricity price, the improved node electricity price comprises 4 components: energy consumption, network loss, congestion, and line transmission margin; wherein,
Figure BDA0001859601710000042
the transmission margin caused by wind power integration is reflected in the node electricity price;
step S6, evaluating the energy consumption value and the network value of the wind power plant based on the node electricity price:
the energy consumption value of the wind power is embodied in the node electricity price lambda1、
Figure BDA0001859601710000043
Of the two components; the wind power integration reduces the energy consumption of the conventional generator set of the system, so that lambda is enabled1Descending; meanwhile, the grid-connected operation of the wind power plant changes the original systemThe power supply layout and the output level of the network are obviously changed under the condition that the load demand is relatively unchanged, and the change of the branch power flow inevitably causes the change of the network loss, thereby causing the change of the network loss energy consumption, namely the change of the network loss energy consumption
Figure BDA0001859601710000044
A change in (b); the network value of wind power is embodied in that reverse power flow can be provided after wind power is connected to the grid, so that the original line blockage is reduced or eliminated, and the transmission margin of a heavy load line is increased, which is positive network value; of course, it is also possible to reduce or overload the line transmission margin, resulting in a negative network value; according to the node electricity price model containing the wind power, the energy consumption value and the network value of the wind power can be reflected in the node electricity price; if the marginal power supply cost of the node is reduced by admitting wind power, and the electricity price level on the node is reduced, the value of the wind power is fully embodied, so the energy consumption value and the network value of the wind power plant on the node k can be expressed as follows:
Figure BDA0001859601710000045
Pi W,Ithe sum of the wind power output injected by each wind power plant on the node i;
Figure BDA0001859601710000046
injecting power into a kth wind power plant at a node i, wherein the power can be obtained by using power flow tracking; lambda [ alpha ]iThe price of the node i before wind power access only comprises three components of energy consumption, network loss and blocking; lambda [ alpha ]i WThe price of a node i containing wind power comprises four components of energy consumption, network, blockage and adequacy;
step S7, taking the standby cost caused by wind power uncertainty into consideration:
due to uncertainty of wind power, the increase of standby cost is caused and called as uncertainty cost; in order to highlight the increase of spare capacity and the rise of spare cost caused by wind power integration, load prediction errors are ignored;
the reserve price of the system tends to increase as the reserve capacity increases, so the reserve price is written as a linear function related to the wind power admission level:
Figure BDA0001859601710000051
wherein, aS、bSA price factor for the reserve capacity cost due to wind power; eta is a wind power prediction error coefficient;
the spare capacity required by the equipment is in direct proportion to the wind power prediction error, and the total spare cost caused by the wind power prediction error is as follows:
Figure BDA0001859601710000052
the standby cost caused by the wind farm on node k is:
Figure BDA0001859601710000053
step S8, wind power plant value evaluation:
according to the above analysis, the wind power value at node k is
Figure BDA0001859601710000054
In an embodiment of the present invention, in step S4, an optimal power flow model considering a wind power grid-connected transmission margin value is established, where the constraint conditions include:
(1) general constraints are:
(1.1) system power balance constraint:
Figure BDA0001859601710000055
Figure BDA0001859601710000056
is the load on the node j and,
Figure BDA0001859601710000057
wind power output on a node k; plossThe total system network loss; n is a radical ofLThe number of load nodes; n is a radical ofWThe number of the wind power nodes is;
(1.2) upper and lower limits of line transmission capacity constraint:
Figure BDA0001859601710000058
-Fl max≤hl≤Fl max
Rl-m、Tl-iand Hl-jRespectively wind power, a conventional generator set and the sensitivity of a load to the transmission capacity of a line l;
(1.3) unit output constraint:
Pi G,min≤Pi G≤Pi G,max
Pi G,minand Pi G,maxThe minimum and maximum output of a conventional generator set i;
(1.4) node wind power output constraint
Figure BDA0001859601710000061
Figure BDA0001859601710000062
The maximum wind power output on the node k is obtained;
(2) transmission margin constraint after newly increased wind power integration
Figure BDA0001859601710000063
βl≤Vl W,T
In the formula, betal(-γlα≤βlLess than or equal to 1) is a threshold value set according to the actual running condition of the power grid.
Compared with the prior art, the invention has the following beneficial effects: the method and the system take the node electricity price of the energy consumption and the network value after the wind power integration into consideration, calculate the standby cost of the wind power, comprehensively measure the value of a certain wind power plant, provide a powerful reference for planning and running the wind power plant, and provide a reference for the optimized running of the power system containing the wind power.
Drawings
Fig. 1 is a structural diagram of a microgrid system used in the method of the present invention.
Fig. 2 shows the node load distribution.
FIG. 3 shows the electricity price change of the nodes before and after the wind power is connected.
Detailed Description
The technical scheme of the invention is specifically explained below with reference to the accompanying drawings.
The invention provides a wind power plant value evaluation method based on node electricity prices, which comprises the following steps:
step S1, extracting system information, operating parameters, and network parameters:
step S2: the optimal power flow objective function operates the optimal power flow of the power system without wind power with the lowest system operation cost, obtains the electricity price of each node, the serial number of the heavy-load line and the transmission capacity of the heavy-load power transmission line by using a primary-dual interior point method, and calculates the transmission margin r of each line without wind powerlI.e. by
Figure BDA0001859601710000064
Wherein h islIs the current on line l; fl maxMaximum transmission capacity on line l; r islThe transmission margin of a heavy load line l when wind power is not contained; when r islWhen the value of alpha is less than or equal to alpha, the line l is considered as a heavy load line, and alpha can be different values according to the actual operation condition of the power grid, for example, alpha is 0.2,when the line transmission margin reaches 80% of the line transmission capacity, the line is considered as a heavy load line;
step S3: calculating the value of wind power grid-connected transmission margin:
if the wind power can provide reverse power flow and the transmission margin of some lines in the power grid is increased, the positive network value is generated for the transmission capability available for the system, particularly for heavy load lines; on the contrary, if the transmission power of some lines is increased by the wind power integration, so that the transmission margin of some lines, particularly heavy load lines, is reduced, the wind power generates negative network value. Of course, whether the network value is positive or negative, the consideration of the heavy load line has more practical significance and operation value.
When the wind power is connected to the grid, the transmission margin of the original heavy load line l is rl W，
If rl W-rlIf the wind power is more than or equal to 0, the wind power generates positive network value on the line l; to simplify the analysis problem, let:
Vl W,T,+＝rl W-rl
in the formula, Vl W,T,+The positive network value of the wind power on the line l is obtained;
on the contrary, if rl W-rlIf the wind power generation rate is less than or equal to 0, the wind power generation generates negative network value V on the line ll W,T,-Let us order
Vl W,T,-＝γl(rl W-rl)
γlA proportionality coefficient greater than 1 indicates that the negative value should be greater if the overload of the line continues to be aggravated under a heavily loaded line;
if a new heavy load line l, namely r appears in the wind power integrationl WIf the value is less than or equal to alpha, the negative network value generated on the line l by the wind power is Vl W,T,N,-Let us order
Vl W,T,N,-＝rl W-α
If the wind power integration does not make the original heavy load line load shedding and loading or the new heavy load line appears, the network value is 0;
in conclusion, the transmission margin value of the line l after wind power integration is as follows:
Vl W,T＝al(rl W-rl)+blγ(rl W-rl)+cl(rl W-α)
wherein, al、bl、clVariables 0, 1, for line l, at most one is not 0;
step S4, establishing an optimal power flow model considering wind power grid connection transmission margin value:
wind power is merged into a power system, and the main purpose is to reduce the energy consumption level of non-renewable energy sources as far as possible and keep the sustainable development of the power system on the premise of ensuring the safe operation of the power system; therefore, the optimal power flow objective function is the lowest system operating cost, i.e. the optimal power flow objective function is
Figure BDA0001859601710000081
ai、biAnd ciRespectively, a cost function of the conventional generator set i; pi GGenerating output of a conventional generator set i; n is a radical ofGThe number of conventional generator sets;
the constraint conditions include:
(1) general constraints are:
(1.1) system power balance constraint:
Figure BDA0001859601710000082
Figure BDA0001859601710000083
is the load on node j, Pk WWind power output on a node k; plossIs a complete systemSystem loss; n is a radical ofLThe number of load nodes; n is a radical ofWThe number of the wind power nodes is;
(1.2) upper and lower limits of line transmission capacity constraint:
Figure BDA0001859601710000084
-Fl max≤hl≤Fl max
Rl-m、Tl-iand Hl-jRespectively wind power, a conventional generator set and the sensitivity of a load to the transmission capacity of a line l;
(1.3) unit output constraint:
Pi G,min≤Pi G≤Pi G,max
Pi G,minand Pi G,maxThe minimum and maximum output of a conventional generator set i;
(1.4) node wind power output constraint
Figure BDA0001859601710000085
Figure BDA0001859601710000086
The maximum wind power output on the node k is obtained;
(2) transmission margin constraint after newly increased wind power integration
Figure BDA0001859601710000087
βl≤Vl W,T
In the formula, betal(-γlα≤βlLess than or equal to 1) is a threshold value set according to the actual running condition of the power grid; according to the tidal current state of a system before wind power integration, if the load rate of some lines is too high, the transmission limit is approached, and the system is improvedThe safety stability margin of the system is that beta is beta when the grid-connected wind power is expected to provide reverse power flow on the lineslThe value of (b) can be set to be greater than or equal to zero, then the network value of the wind power on these lines is positive; conversely, betalMay be less than zero, allowing the net value of wind power on these lines to be negative.
Step S5, solving the node electricity price containing wind power:
in order to calculate the node electricity price containing wind power, the model established in the step S4 is converted into a Lagrange function, and lambda is defined1、λ2l、λ3lLagrange coefficient constrained by equation, and1≥0、λ2l≥0、λ3lnot less than 0; definition of mu1l、μ2l、τ1l，g1i、g2i、
Figure BDA0001859601710000091
Lagrange coefficients constrained by inequality, and mu1l≥0、μ2l≥0、τ1l≥0、g1i≥0、g2i≥0、
Figure BDA0001859601710000092
Figure BDA0001859601710000093
According to the KKT condition, at the optimum point:
Figure BDA0001859601710000094
Figure BDA0001859601710000095
from the above formula, one can obtain:
λ3l＝-τ1l(al+blγ+cl)
Figure BDA0001859601710000096
the node electricity price for embodying the wind power grid connection adequacy value is as follows:
Figure BDA0001859601710000101
when the network value is fused into the node electricity price, the improved node electricity price comprises 4 components: energy consumption, network loss, congestion, and line transmission margin; wherein,
Figure BDA0001859601710000102
the transmission margin caused by wind power integration is reflected in the node electricity price;
step S6, evaluating the energy consumption value and the network value of the wind power plant based on the node electricity price:
the energy consumption value of the wind power is embodied in the node electricity price lambda1、
Figure BDA0001859601710000103
Of the two components; the wind power integration reduces the energy consumption of the conventional generator set of the system, so that lambda is enabled1Descending; meanwhile, the grid-connected operation of the wind power plant changes the original power supply layout and output level of the system, the power flow distribution in the network is obviously changed under the condition that the load demand is relatively unchanged, and the change of the branch power flow inevitably causes the change of the network loss, thereby causing the change of the network loss energy consumption, namely the change of the network loss energy consumption
Figure BDA0001859601710000104
A change in (b); the network value of wind power is embodied in that reverse power flow can be provided after wind power is connected to the grid, so that the original line blockage is reduced or eliminated, and the transmission margin of a heavy load line is increased, which is positive network value; of course, it is also possible to reduce or overload the line transmission margin, resulting in a negative network value; according to the node electricity price model containing wind power, the energy consumption value and the network value of the wind power can be embodied in the node electricityIn price; if the marginal power supply cost of the node is reduced by admitting wind power, and the electricity price level on the node is reduced, the value of the wind power is fully embodied, so the energy consumption value and the network value of the wind power plant on the node k can be expressed as follows:
Figure BDA0001859601710000105
Pi W,Ithe sum of the wind power output injected by each wind power plant on the node i;
Figure BDA0001859601710000106
injecting power into a kth wind power plant at a node i, wherein the power can be obtained by using power flow tracking; lambda [ alpha ]iThe price of the node i before wind power access only comprises three components of energy consumption, network loss and blocking;
Figure BDA0001859601710000107
the price of a node i containing wind power comprises four components of energy consumption, network, blockage and adequacy;
step S7, taking the standby cost caused by wind power uncertainty into consideration:
due to the uncertainty of wind power, the backup cost is increased, which is called uncertainty cost. In a conventional power system, due to a load prediction error, forced shutdown and the like, a certain rotation reserve capacity needs to be maintained to ensure safe and reliable operation of the system. The model mainly highlights the increase of spare capacity and the rise of spare cost caused by wind power integration, and therefore load prediction errors are ignored temporarily.
The reserve price of the system tends to increase as the reserve capacity increases, so the reserve price is written as a linear function related to the wind power admission level:
Figure BDA0001859601710000111
wherein, aS、bSA price factor for the reserve capacity cost due to wind power; eta is wind power predictionAn error coefficient;
the spare capacity required by the equipment is in direct proportion to the wind power prediction error, and the total spare cost caused by the wind power prediction error is as follows:
Figure BDA0001859601710000112
the standby cost caused by the wind farm on node k is:
Figure BDA0001859601710000113
step S8, wind power plant value evaluation:
according to the above analysis, the wind power value at node k is
Figure BDA0001859601710000114
The following is a specific example of the present invention.
A certain 14-node micro-grid system is taken as an example to analyze node electricity prices containing wind power grid-connected transmission margin values, and a system structure diagram is shown in figure 1. A micro gas turbine (MT) is connected to each of the nodes 3 and 11, a Fuel Cell (FC) and a diesel generator (DE) are connected to each of the nodes 6 and 12, and a Wind Turbine (WT) is connected to the node 7. The capacity of the wind turbine is assumed to be large enough. The upper limit of the line transmission capacity is 100 kW. The parameters of the distributed power supply are shown in table 1, the distribution of the load at each node is shown in fig. 2, the network parameters are shown in table 2, and the distribution of the load at each node is shown in fig. 2. Spare cost factor aSand bSRespectively accounting for 0.08$/kW and 0.0002 $/(kW)2). The transmission margin calculation results are shown in table 3, and the node electricity prices are shown in fig. 3.
TABLE 1 parameters of distributed power supplies
Type (B) Pmin/kW Pmax/kW kom/($/kW)
MT1 15 200 0.025
MT2 5 100 0.025
FC 5 100 0.026
DE 5 100 0.016
TABLE 2 microgrid system network parameters
Figure BDA0001859601710000115
Figure BDA0001859601710000121
Table 3 line transmission flow without wind power and line transmission flow with wind power (with and without transmission margin)
Figure BDA0001859601710000122
As can be seen from Table 3, the heavy load lines without wind power access include lines 2-3 and 6-7, the heavy load lines without considering the transmission margin of the lines are lines 2-3, 5-6, 2-10 and 10-11, while the heavy load lines with considering the transmission margin of the lines become 2-3 and 2-10, and the degree of heavy load is reduced.
As can be seen in FIG. 3, the value of the wind farm is $ 6.7904, which is a $ 0.183 reduction from the wind value without consideration of the line transmission margin constraints.
The above are preferred embodiments of the present invention, and all changes made according to the technical scheme of the present invention that produce functional effects do not exceed the scope of the technical scheme of the present invention belong to the protection scope of the present invention.

Claims (2)

1. A wind power plant value evaluation method based on node electricity prices is characterized by comprising the following steps:
step S1, extracting system information, operating parameters, and network parameters:
step S2: the optimal power flow objective function operates the optimal power flow of the power system without wind power with the lowest system operation cost, obtains the electricity price of each node, the serial number of a heavy load circuit and the transmission capacity of the heavy load circuit by using a primary-dual interior point method, and calculates the transmission margin r of each circuit without wind powerlI.e. by
Figure FDA0003068514150000011
Wherein h islIs the current on line l; fl maxMaximum transmission capacity on line l; r islFor a line l without wind powerThe transmission margin of (a); when r islWhen the load is less than or equal to alpha, the line l is considered as a heavy load line, and the value of alpha is taken according to the actual operation condition of the power grid;
step S3: calculating the value of wind power grid-connected transmission margin:
when wind power is connected to the grid, the transmission margin of the original heavy load line l is changed into rl W，
If rl W-rlIf the wind power is more than or equal to 0, the wind power generates positive network value on the line l; to simplify the analysis problem, let:
Vl W,T,+＝rl W-rl
in the formula, Vl W,T,+The positive network value of the wind power on the line l is obtained;
on the contrary, if rl W-rlIf the wind power generation rate is less than or equal to 0, the wind power generation generates negative network value V on the line ll W,T,-Let us order
Vl W,T,-＝γl(rl W-rl)
γlThe proportionality coefficient is greater than 1, which indicates that the negative network value is greater when the overload of the line is continuously intensified under the heavy-load line;
if a new heavy load line l, namely r appears in the wind power integrationl WIf the value is less than or equal to alpha, the negative network value generated on the line l by the wind power is Vl W,T,N,-Let us order
Vl W,T,N,-＝rl W-α
If the wind power integration does not make the original heavy load line load shedding and loading or the new heavy load line appears, the network value is 0;
in conclusion, the transmission margin value of the line l after wind power integration is as follows:
Vl W,T＝al(rl W-rl)+blγ(rl W-rl)+cl(rl W-α)
wherein, al、bl、clVariables 0, 1, for line l, at most one is not 0;
step S4, establishing an optimal power flow model considering wind power grid connection transmission margin value:
wind power is merged into a power system, and the main purpose is to reduce the energy consumption level of non-renewable energy sources as far as possible and keep the sustainable development of the power system on the premise of ensuring the safe operation of the power system; therefore, the optimal power flow objective function is the lowest system operating cost, i.e. the optimal power flow objective function is
Figure FDA0003068514150000021
ai、biAnd ciRespectively, a cost function of the conventional generator set i; pi GGenerating output of a conventional generator set i; n is a radical ofGThe number of conventional generator sets;
step S5, solving the node electricity price containing wind power:
in order to calculate the node electricity price containing wind power, the model established in the step S4 is converted into a Lagrange function, and lambda is defined1、λ2l、λ3lLagrange coefficient constrained by equation, and1≥0、λ2l≥0、λ3lnot less than 0; definition of mu1l、μ2l、τ1l，g1i、g2i、
Figure FDA0003068514150000022
Lagrange coefficients constrained by inequality, and mu1l≥0、μ2l≥0、τ1l≥0、g1i≥0、g2i≥0、
Figure FDA0003068514150000023
Figure FDA0003068514150000024
According to the KKT condition, at the optimum point:
Figure FDA0003068514150000025
Figure FDA0003068514150000026
from the above formula, one can obtain:
λ3l＝-τ1l(al+blγ+cl)
Figure FDA0003068514150000031
the node electricity price for reflecting the wind power grid-connected transmission margin value is as follows:
Figure FDA0003068514150000032
and integrating the wind power grid-connected transmission margin value into the node electricity price, wherein the improved node electricity price comprises 4 components: energy consumption, network loss, congestion, and line transmission margin; among which, in node electricity prices
Figure FDA0003068514150000033
The wind power grid-connected transmission margin value is embodied;
step S6, evaluating the energy consumption value and the network value of the wind power plant based on the node electricity price:
the energy consumption value of the wind power is embodied in the node electricity price lambda1、
Figure FDA0003068514150000034
Of the two components; the wind power integration reduces the energy consumption of the conventional generator set of the system, so that lambda is enabled1Descending; meanwhile, the grid-connected operation of the wind power plant changes the original power supply of the systemThe layout and output level, under the condition of relatively unchanged load demand, the power flow distribution in the network will also obviously change, and the change of the branch power flow inevitably causes the change of the network loss, thereby causing the change of the energy consumption of the network loss, namely
Figure FDA0003068514150000035
A change in (b); the network value of wind power is embodied in that reverse power flow can be provided after wind power is connected to the grid, so that the original line blockage is reduced or eliminated, and the transmission margin of a heavy load line is increased, which is positive network value; of course, it is also possible to reduce or overload the line transmission margin, resulting in a negative network value; according to the node electricity price model containing the wind power, the energy consumption value and the network value of the wind power can be reflected in the node electricity price; if the marginal power supply cost of the node is reduced by admitting wind power, and the electricity price level on the node is reduced, the value of the wind power is fully embodied, so the energy consumption value and the network value of the wind power plant on the node k can be expressed as follows:
Figure FDA0003068514150000036
Pi W,Ithe sum of the wind power output injected by each wind power plant on the node i;
Figure FDA0003068514150000037
injecting power into a kth wind power plant at a node i, wherein the power can be obtained by using power flow tracking; lambda [ alpha ]iThe price of the node i before wind power access only comprises three components of energy consumption, network loss and blocking; lambda [ alpha ]i WThe price of a node i containing wind power comprises four components of energy consumption, network loss, blockage and line transmission margin;
step S7, taking the standby cost caused by wind power uncertainty into consideration:
due to uncertainty of wind power, the increase of standby cost is caused and called as uncertainty cost; in order to highlight the increase of spare capacity and the rise of spare cost caused by wind power integration, load prediction errors are ignored;
the reserve price of the system tends to increase as the reserve capacity increases, so the reserve price is written as a linear function related to the wind power admission level:
Figure FDA0003068514150000041
wherein, aS、bSA price factor for the reserve capacity cost due to wind power; eta is a wind power prediction error coefficient;
the spare capacity required by the equipment is in direct proportion to the wind power prediction error, and the total spare cost caused by the wind power prediction error is as follows:
Figure FDA0003068514150000042
the standby cost caused by the wind farm on node k is:
Figure FDA0003068514150000043
step S8, wind power plant value evaluation:
according to the above analysis, the wind power value at node k is
Figure FDA0003068514150000044
2. The method for evaluating the value of the wind power plant based on the node electricity price according to claim 1, wherein in the step S4, an optimal power flow model considering the value of the wind power grid-connected transmission margin is established, and the constraint conditions include:
(1) general constraints are:
(1.1) system power balance constraint:
Figure FDA0003068514150000045
Figure FDA0003068514150000046
is the load on the node j and,
Figure FDA0003068514150000047
wind power output on a node k; plossThe total system network loss; n is a radical ofLThe number of load nodes; n is a radical ofWThe number of the wind power nodes is;
(1.2) upper and lower limits of line transmission capacity constraint:
Figure FDA0003068514150000048
-Fl max≤hl≤Fl max
Rl-m、Tl-iand Hl-jRespectively wind power, a conventional generator set and the sensitivity of a load to the transmission capacity of a line l;
(1.3) unit output constraint:
Pi G,min≤Pi G≤Pi G,max
Pi G,minand Pi G,maxThe minimum and maximum output of a conventional generator set i;
(1.4) node wind power output constraint
Figure FDA0003068514150000051
Figure FDA0003068514150000052
The maximum wind power output on the node k is obtained;
(2) transmission margin constraint after newly increased wind power integration
Figure FDA0003068514150000053
βl≤Vl W,T
In the formula, betal，-γlα≤βlLess than or equal to 1, which is a threshold value set according to the actual running condition of the power grid.
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