CN112564109B - Frequency modulation optimization operation method based on participation of energy storage system in large-scale offshore wind power - Google Patents
Frequency modulation optimization operation method based on participation of energy storage system in large-scale offshore wind power Download PDFInfo
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Abstract
The invention provides a method for participating in frequency modulation optimization operation containing large-scale offshore wind power based on an energy storage system, which comprises the following steps: selecting an offshore wind power plant with an energy storage system configured in a certain coastal region, acquiring an offshore wind power prediction output value and relevant parameters of the energy storage system, and acquiring an energy market price by using a scene analysis method; constructing an energy storage system participating frequency modulation auxiliary service optimization operation model containing large-scale offshore wind power with the goal that the maximum combined income of the offshore wind power and the energy storage system is the maximum; considering the uncertainty of the offshore wind power output, establishing fuzzy opportunity constraint of the offshore wind power output; and (4) performing optimized operation by adopting a method that an offshore wind power and energy storage system participates in an energy market and frequency modulation auxiliary service, and solving the model based on an MATLAB optimization tool box. The invention optimizes the output of the offshore wind power and the energy storage system, can effectively reduce the wind abandon amount of the offshore wind power, improves the overall income and social benefit of the combined operation of the offshore wind power and the energy storage system, and shortens the investment recovery period of the energy storage system.
Description
Technical Field
The invention relates to the field of electric power auxiliary service, in particular to a method for participating in frequency modulation optimization operation containing large-scale offshore wind power based on an energy storage system.
Background
In recent years, with increasing energy crisis problems and environmental problems, renewable energy sources such as offshore wind power have received much attention. China's coastline is as long as 1.8 kilometers, has the natural advantages of developing offshore wind power, coastal provinces represented by Fujian, Guangdong, Zhejiang, Jiangsu and the like have abundant offshore wind power resources, and offshore wind power resources are being vigorously developed by the coastal provinces. Compared with onshore wind power, offshore wind power has the characteristics of being close to an electrical load center, no land resource occupation of an offshore wind turbine, small output fluctuation, higher efficiency of the offshore wind turbine and the like. The large-scale application of offshore wind power can effectively solve the energy crisis problem and the environmental problem, but the large-scale offshore wind power consumption still has problems.
Aiming at the problem of large-scale offshore wind power consumption, the energy storage system is one of effective methods for solving the problem, and stores electric energy at the stage of offshore wind power output peak and releases the electric energy at the stage of output valley so as to obtain more electric energy benefits. However, the investment cost of the current energy storage system is still high, especially for a large-scale energy storage system, the method only depends on the energy storage system to participate in the electric energy transaction to improve the economic benefit, the cost recovery year limit of the energy storage system is long, and the utilization rate of the energy storage system is low. The energy storage system can effectively participate in the frequency modulation auxiliary service due to the characteristics of quick adjustment and the like, and becomes a high-quality frequency modulation resource. At present, the research aiming at the participation of the energy storage system in frequency modulation mainly aims at the participation of the energy storage system in the frequency modulation of the traditional thermal power generating unit, and relatively few researches about the participation of the energy storage system in the frequency modulation auxiliary service by depending on large-scale new energy sources are available. Related researches of the energy storage system which depends on large-scale new energy to participate in frequency modulation auxiliary services do not consider the problems of loss cost of the energy storage system, uncertainty of electricity price of an energy market and uncertainty of the new energy. Therefore, a method considering the problem of loss cost of the energy storage system, the problem of uncertainty of electricity price of an energy market and the problem of uncertainty of new energy is urgently needed, so that the energy storage system can effectively depend on large-scale offshore wind power to participate in frequency modulation auxiliary service.
Disclosure of Invention
The technical problem to be solved by the invention is how to combine an energy storage system and large-scale offshore wind power to participate in frequency modulation auxiliary service, and simultaneously consider the loss cost problem, the price uncertainty problem of an energy market and the uncertainty problem of new energy, and the problems are solved according to the initial investment cost, a scene method and fuzzy chance constraint of the energy storage system.
The technical scheme adopted by the invention is a method for participating in frequency modulation optimization operation containing large-scale offshore wind power based on an energy storage system, which comprises the following steps:
(1) selecting an offshore wind power plant with an energy storage system configured in a certain coastal region, acquiring a predicted power value of offshore wind power and related parameters of the energy storage system, and inputting the predicted power value and the related parameters of the energy storage system into original parameters of the energy storage system participating in frequency modulation optimization operation containing large-scale offshore wind power;
(2) generating a typical electricity price scene by applying a scene method according to the historical electricity price data of the PJM market, and calculating the average electricity price in the same time period under each scene as the electricity price in the time period;
(3) establishing various profit models, including a profit model of the offshore wind power and energy storage system in an energy market, an energy storage system frequency modulation profit model, an environmental benefit model and an energy storage system loss cost model;
(4) constructing an optimized operation model of the energy storage system participating in the frequency modulation auxiliary service containing large-scale offshore wind power, wherein the maximum combined operation yield of the offshore wind power and the energy storage system is an objective function;
(5) establishing model constraint conditions including charge and discharge state constraint, charge and discharge power constraint and capacity constraint of the energy storage system, wherein the energy storage system participates in frequency modulation auxiliary service power constraint and the offshore wind power combined energy storage system participates in total power constraint of an energy market;
(6) establishing fuzzy opportunity constraints of offshore wind power output;
(7) and (4) carrying out optimized operation by adopting a method that an offshore wind power and energy storage system participates in an energy market and frequency modulation auxiliary service according to the optimized operation model established in the steps (3), (4), (5) and (6), and solving the model based on an MATLAB optimization tool box.
(8) And outputting the offshore wind power output value and the output value of the offshore wind power combined energy storage system under different scenes.
Preferably, the scene method in step (2) is specifically expressed as:
an autoregressive-moving average model (ARMA model) is adopted for scene generation, and the model is specifically represented as follows:
wherein p and q are the order of the model,
and theta j Respectively, the undetermined coefficient, x, of the model t Represents a time series, a t Representing the error, i.e. the running average of a white noise sequence.
Adopting backward reduction method to reduce scene, the concrete process is as follows:
1) the generated scenes are numbered and a reservation set A is generated as S 0 ,…,S i ,…S n Discarding the collection B ═ B 0 Making k equal to 0 for the empty set;
2) determining the scene alpha needing to be eliminated in the kth iteration k And the removed scene alpha k Moving to a abandon collection J; modifying and culling a scene alpha k Nearest scene S m The probability of (c) is:
P(S' m )＝P(S m )+P(α k )
in the formula (II), P (S' m ) As a scene S m The probability after the change;
3) and repeating the process 2) continuously until the final needed scene number is obtained by iteration.
Preferably, each profit model in the step (3) is specifically expressed as:
the revenue of offshore wind power and energy storage systems in the energy market:
F 1 ＝f 11 -f 12
the offshore wind power and energy storage system participates in the income obtained by the energy market trading:
f 11 ＝ρ t P wc,t Δt
P wc,t ＝P w,t +P dis,t -P ch,t
wind storage output deviation penalty cost caused by offshore wind power output uncertainty, offshore wind power output power limitation, participation of an energy storage system in frequency modulation and the like:
in the formula, ρ t Electricity prices for the energy market at time t; p wc,t The total output value of the offshore wind power and energy storage system at the moment t of the energy market is obtained; p w,t Actual output of the offshore wind farm at the moment t; p is wp,t The planned output of the offshore wind farm at the time t is provided; p is ch,t 、P dis,t Charging power and discharging power of the energy storage system at the moment t; alpha (alpha) ("alpha") 1 、α 2 And punishment coefficients of the wind storage combined system when the output is excessive and insufficient are respectively.
The energy storage system frequency modulation benefit comprises capacity compensation and mileage compensation:
F 2 ＝f 21 +f 22
capacity compensation:
in the formula, n is the total daily transaction time period number of the energy storage system participating in the power auxiliary service; m is a group of 1 The commissioning rate of the energy storage system; p fm,t Reporting power for the energy storage system when participating in frequency modulation at a time t; p r,t The capacity compensation standard is the capacity compensation standard of the energy storage system when the energy storage system participates in frequency modulation at the time t;
mileage compensation:
frequency modulation mileage:
in the formula, M 2 Is an adjustment factor; k t Is the comprehensive performance index of the energy storage system in the t period；D t The frequency modulation mileage of the energy storage system in the time period t is obtained; q d,t Compensating a standard for the frequency modulation mileage of the energy storage system in a time period t; beta is a variable of 0 and 1; p is c,t And charging or discharging the energy storage power value.
Environmental benefits:
in the formula, Q N The electric quantity which can be generated by burning one ton of domestic standard coal; w dis,t The discharge electric quantity is the discharge electric quantity of the energy storage system participating in the electric power auxiliary frequency modulation at the moment t; lambda [ alpha ] i The unit environmental value of the i-th polluted gas; m is a unit of cf The emission amount of pollution gas generated by burning one ton of coal by a conventional thermal power coal-fired frequency modulation unit.
Energy storage system loss cost:
initial construction cost of the energy storage system for the entire life cycle:
C＝C P P N +C e E N
discharge capacity of the energy storage system in the delta t period:
E Δt ＝(P dis,t +P fm,t -P ch,t )Δt
in the formula, C P 、C e Is the cost per unit power and per unit capacity of the energy storage system; p N 、E N Rated power and rated capacity of the energy storage system are respectively; a. and b is an energy storage cost loss calculation coefficient.
Preferably, the optimal operation model with the maximum combined operation yield of the offshore wind power and energy storage system in the step (4) is expressed as follows:
maxF＝F 1 +F 2 +F 3 -F 4
preferably, the constraint condition of the optimized operation model in step (5) is specifically expressed as:
and (3) restricting the charge and discharge states of the energy storage system:
in the formula, beta ch 、β dis Respectively, a charge-discharge state variable, beta, of the energy storage system dis ＝1、β ch 1 indicates that the energy storage system is charging and conversely discharging; beta is a beta dis ＝0、β ch 0 means that the energy storage system is neither charging nor discharging.
And (3) charge and discharge power constraint of the energy storage system:
in the formula (I), the compound is shown in the specification,
and the maximum charging and discharging power values are respectively of the energy storage system.
Capacity constraint of energy storage system:
in the formula, E soc,t The capacity state value of the energy storage system at the moment t; eta ch 、η dis Respectively the charge and discharge efficiency of the energy storage system;
respectively a minimum capacity state value and a maximum capacity state value within an allowed range of the energy storage system; SOC (system on chip) min 、SOC max Respectively a minimum state of charge and a maximum state of charge of the energy storage system;
the initial and final capacity state values in one charge-discharge cycle period are respectively.
And (3) power constraint of the energy storage system participating in frequency modulation auxiliary service:
in the formula (I), the compound is shown in the specification,
maximum power for charging or discharging the stored energy.
The total power constraint of the offshore wind power combined energy storage participating in the day-ahead market is as follows:
in the formula (I), the compound is shown in the specification,
the maximum value of the combined output of the offshore wind power and energy storage system at the moment t.
Preferably, the fuzzy opportunity constraint of offshore wind power output in the step (6) is specifically expressed as follows:
fuzzy chance constraint based on credibility measure:
Cr{g(x,ζ)≤0}≥γ
in the formula, Cr {. cndot.. is credibility under the constraint condition {. cndot. cndot. -; g {. is a constraint event set; γ represents the confidence level.
Two functions are defined:
then, when the confidence level γ < 0.5, the fuzzy chance constrains the clear equivalent:
when the confidence level gamma is more than or equal to 0.5, the fuzzy chance constrains a clear equivalent form:
in the formula " ∨ "represents a big operator" ∧ "means a small operator; r is a radical of hydrogen k1 、r k2 、r k3 Is a triangle membership parameter.
According to the definition process of fuzzy opportunity constraint, the relation between the triangular fuzzy expression of offshore wind power output and the membership parameter is as follows:
in the formula (I), the compound is shown in the specification,
the output of the offshore wind power is in a fuzzy expression form; p w,pre Predicting the output of the offshore wind power; omega 1 P w,pre 、P w,pre 、ω 2 P w,pre Membership degree parameters of offshore wind power output; coefficient of proportionality omega 1 、ω 2 。
Fuzzy opportunity constraint of offshore wind power output:
in the formula, P w,t The output power value of the offshore wind farm at the moment t;
the output is the upper limit of the offshore wind power adjustable output.
And performing clear class equivalent transformation on the fuzzy opportunity constraint of the offshore wind power output according to the fuzzy opportunity constraint clear equivalent form.
Preferably, the offshore wind power and energy storage system in step (7) participates in energy market and frequency modulation auxiliary service, and comprises:
1) scene one: the energy storage system can participate in energy market transaction by matching with offshore wind power, can also participate in frequency modulation auxiliary service by using the idle time period, follows relevant operation constraints by using an optimized operation model with the maximum combined operation yield of the offshore wind power and the energy storage system as an objective function, and solves to obtain an offshore wind power output value and an offshore wind power combined energy storage system output value under the scene.
2) Scene two: the energy storage system is only matched with offshore wind power to participate in energy market trading, does not participate in frequency modulation auxiliary service, complies with relevant operation constraints and solves to obtain an offshore wind power output value and an offshore wind power combined energy storage system output value under the scene by using an optimized operation model with the maximum combined operation yield of the offshore wind power and energy storage system as an objective function.
The invention has the beneficial effects that: the method comprises the steps of considering the cost of an energy storage system, the uncertainty of the electricity price of an energy market and the uncertainty of the output of offshore wind power, establishing a frequency modulation optimization operation model based on the participation of the energy storage system in large-scale offshore wind power, solving the model by adopting an MATLAB optimization tool box to obtain the most economical optimization operation scheme, reducing the wind abandoning amount of the offshore wind power, improving the overall income and social benefits of the combined operation of the offshore wind power and the energy storage system, and shortening the investment recovery period of the energy storage system.
Drawings
FIG. 1: a flow chart of a method for participating in frequency modulation optimization operation containing large-scale offshore wind power based on an energy storage system;
FIG. 2 is a schematic diagram: expressing the triangular membership function of the offshore wind power output;
FIG. 3: energy market electricity price result graph;
FIG. 4: a scene I is a diagram of an optimization result of wind power output and wind combined output on the sea;
FIG. 5: a scene two, a sea wind power output and wind combined output optimization result graph;
FIG. 6: and (5) a frequency modulation capacity optimization result diagram of the energy storage system in the first scene.
Detailed description of the preferred embodiments
The following detailed description is given to a method for participating in frequency modulation optimization operation including large-scale offshore wind power based on an energy storage system, with reference to embodiments and drawings.
As shown in fig. 1, the method for participating in frequency modulation optimization operation including large-scale offshore wind power based on the energy storage system of the invention comprises the following steps:
(1) selecting an offshore wind power plant with an energy storage system configured in a certain coastal region, acquiring a predicted power value of offshore wind power and related parameters of the energy storage system, and inputting the predicted power value and the related parameters of the energy storage system into original parameters of the energy storage system participating in frequency modulation optimization operation containing large-scale offshore wind power;
(2) generating a typical electricity price scene by applying a scene method according to the historical electricity price data of the PJM market, and calculating the average electricity price in the same time period under each scene as the electricity price in the time period;
the scene method is specifically expressed as follows:
an autoregressive-moving average model (ARMA model) is adopted for scene generation, and the model is specifically represented as follows:
wherein p and q are the order of the model,
and theta j Respectively, the undetermined coefficient, x, of the model t Represents a time series, a t Representing the error, i.e. the running average of a white noise sequence.
Adopting backward subtraction method to reduce scene, the concrete process is as follows:
1) the generated scenes are numbered and a reservation set A is generated as S 0 ,…,S i ,…S n Discarding the collection B ═ B 0 Making k equal to 0 for the empty set;
2) determining the scene alpha to be eliminated in the k iteration k And the removed scene alpha k Moving to a abandon set J;modifying and culling a scene alpha k Nearest scene S m The probability of (c) is:
P(S' m )＝P(S m )+P(α k )
in the formula (II), P (S' m ) As a scene S m The probability after the change;
3) and repeating the process 2) continuously until the final needed scene number is obtained by iteration.
(3) Establishing various profit models, including a profit model of the offshore wind power and energy storage system in an energy market, an energy storage system frequency modulation profit model, an environmental benefit model and an energy storage system loss cost model;
the revenue of offshore wind power and energy storage systems in the energy market:
F 1 ＝f 11 -f 12
the offshore wind power and energy storage system participates in the income obtained by the energy market trading:
f 11 ＝ρ t P wc,t Δt
P wc,t ＝P w,t +P dis,t -P ch,t
wind storage output deviation penalty cost caused by offshore wind power output uncertainty, offshore wind power output power limitation, participation of an energy storage system in frequency modulation and the like:
in the formula, ρ t Electricity prices for the energy market at time t; p wc,t The total output value of the offshore wind power and energy storage system at the moment t of the energy market is obtained; p w,t Actual output of the offshore wind farm at the moment t; p wp,t The planned output of the offshore wind farm at the time t is provided; p is ch,t 、P dis,t Charging power and discharging power of the energy storage system at the moment t; alpha is alpha 1 、α 2 And punishment coefficients of the wind storage combined system when the output is excessive and insufficient are respectively.
The energy storage system frequency modulation benefit comprises capacity compensation and mileage compensation:
F 2 ＝f 21 +f 22
capacity compensation:
in the formula, n is the total daily transaction time period number of the energy storage system participating in the power auxiliary service; m is a group of 1 The commissioning rate of the energy storage system; p fm,t Reporting power for the energy storage system when participating in frequency modulation at a time t; p r,t The capacity compensation standard is used for the energy storage system when the energy storage system participates in frequency modulation at the time t;
mileage compensation:
frequency modulation mileage:
in the formula, M 2 Is an adjustment factor; k t The comprehensive performance index of the energy storage system in the time period t is obtained; d t The frequency modulation mileage of the energy storage system in the time period t is obtained; q d,t Compensating the standard for the frequency modulation mileage of the energy storage system in the time period t; beta is a variable of 0 and 1; p c,t And charging or discharging the energy storage power value.
Environmental benefits:
in the formula, Q N The electric quantity which can be generated by burning one ton of domestic standard coal is provided; w is a group of dis,t The discharge electric quantity is the discharge electric quantity of the energy storage system participating in the electric power auxiliary frequency modulation at the moment t; lambda [ alpha ] i The unit environmental value of the i-th polluted gas; m is cf The emission amount of the pollution gas generated by burning one ton of coal by the conventional thermal power coal-fired frequency modulation unit.
Energy storage system loss cost:
initial construction cost of the energy storage system for the full life cycle:
C＝C P P N +C e E N
discharge capacity of the energy storage system in the delta t period:
E Δt ＝(P dis,t +P fm,t -P ch,t )Δt
in the formula, C P 、C e Is the cost per unit power and per unit capacity of the energy storage system; p is N 、E N Rated power and rated capacity of the energy storage system are respectively; a. and b is an energy storage cost loss calculation coefficient.
(4) Constructing an optimized operation model of the energy storage system participating in the frequency modulation auxiliary service containing large-scale offshore wind power, wherein the maximum combined operation yield of the offshore wind power and the energy storage system is an objective function;
the maximum combined operation yield of the offshore wind power and energy storage system is an optimized operation model of an objective function, and the optimized operation model is specifically expressed as follows:
maxF＝F 1 +F 2 +F 3 -F 4
(5) establishing model constraint conditions including charge and discharge state constraint, charge and discharge power constraint and capacity constraint of the energy storage system, wherein the energy storage system participates in frequency modulation auxiliary service power constraint and the offshore wind power combined energy storage system participates in total power constraint of an energy market;
and (3) restricting the charge and discharge states of the energy storage system:
in the formula, beta ch 、β dis Are respectively the charge-discharge state variable, beta, of the energy storage system dis ＝1、β ch 1 indicates that the energy storage system is in operationCharging, and conversely discharging; beta is a dis ＝0、β ch 0 means that the energy storage system is neither charging nor discharging.
And (3) charge and discharge power constraint of the energy storage system:
in the formula (I), the compound is shown in the specification,
and the maximum charging and discharging power values of the energy storage system are respectively.
Capacity constraint of energy storage system:
in the formula, E soct The capacity state value of the energy storage system at the moment t; eta ch 、η dis Respectively the charge and discharge efficiency of the energy storage system;
respectively a minimum capacity state value and a maximum capacity state value within an allowed range of the energy storage system; SOC min 、SOC max Respectively a minimum state of charge and a maximum state of charge of the energy storage system;
the initial and final capacity state values in a charge-discharge cycle period are respectively.
And (3) power constraint of the energy storage system participating in frequency modulation auxiliary service:
in the formula (I), the compound is shown in the specification,
maximum power for charging or discharging the stored energy.
The offshore wind power combined energy storage participates in the total power constraint of the market in the day ahead:
in the formula (I), the compound is shown in the specification,
and the maximum value of the combined output of the offshore wind power and energy storage system at the moment t.
(6) Establishing fuzzy opportunity constraints of offshore wind power output;
fuzzy chance constraint based on credibility measure:
Cr{g(x,ζ)≤0}≥γ
in the formula, Cr {. is credibility under a constraint condition {. The } is Cr {. The credibility is determined; g {. is a constraint event set; γ represents the confidence level.
Two functions are defined:
then, when confidence level γ < 0.5, the fuzzy opportunity constrains the clear equivalent:
when the confidence level gamma is more than or equal to 0.5, the fuzzy chance constrains a clear equivalent form:
in the formula, V represents taking a large operator, and A represents taking a small operator; r is a radical of hydrogen k1 、r k2 、r k3 As a parameter of degree of membership of the triangle。
As shown in fig. 2, according to the definition process of the fuzzy chance constraint, the relationship between the triangular fuzzy expression of the offshore wind power output and the membership parameter is as follows:
in the formula (I), the compound is shown in the specification,
the output of the offshore wind power is in a fuzzy expression form; p w,pre The output power of the offshore wind power is predicted value; omega 1 P w,pre 、P w,pre 、ω 2 P w,pre The output membership parameter of the offshore wind power is obtained; coefficient of proportionality omega 1 、ω 2 。
Fuzzy opportunity constraint of offshore wind power output:
in the formula, P w,t The output power value of the offshore wind farm at the moment t;
the output is adjustable for the upper limit of offshore wind power.
And performing clear class equivalent transformation on the fuzzy opportunity constraint of the offshore wind power output according to the fuzzy opportunity constraint clear equivalent form.
(7) And (4) carrying out optimized operation by adopting a method that an offshore wind power and energy storage system participates in an energy market and frequency modulation auxiliary service according to the optimized operation model established in the steps (3), (4), (5) and (6), and solving the model based on an MATLAB optimization tool box.
Offshore wind and energy storage systems participate in energy markets and frequency modulation ancillary services, including:
1) scene one: the energy storage system can participate in energy market transaction by matching with offshore wind power, can also participate in frequency modulation auxiliary service by using the idle time period, follows relevant operation constraints by using an optimized operation model with the maximum combined operation yield of the offshore wind power and the energy storage system as an objective function, and solves to obtain an offshore wind power output value and an offshore wind power combined energy storage system output value under the scene.
2) Scene two: the energy storage system is only matched with offshore wind power to participate in energy market trading, does not participate in frequency modulation auxiliary service, follows relevant operation constraints by using an optimized operation model with the maximum combined operation yield of the offshore wind power and the energy storage system as an objective function, and solves to obtain an offshore wind power output value and an offshore wind power combined energy storage system output value under the scene.
(8) And outputting the offshore wind power output value and the output value of the offshore wind power combined energy storage system under different scenes.
Specific examples are given below:
for the embodiment, 15 minutes is taken as a transaction period for calculation, a predicted output value of a wind power plant at sea at a certain place within 1 day in a 96-period is selected, a 20MW/50MW & h lithium iron phosphate energy storage system is configured for the wind power plant at sea, and basic parameters of a frequency modulation optimization operation model participating in large-scale wind power at sea based on the energy storage system are input. Fig. 3 is energy electricity prices for three typical days acquired according to the scene method, the average electricity price of the three typical days is obtained as the energy market electricity price in the day ahead, and the electricity prices in the same hour take the same value.
FIG. 4 shows the results of the offshore wind power output and the wind storage combined output under the scene, except that the wind storage combined output cannot completely track the offshore wind power planned output in the period of 12 to 24, and the wind storage combined output can completely track in other periods; FIG. 5 shows a scenario II that offshore wind power output and wind storage combined output exist, except for the interval of 12-24, wind storage combined output in a plurality of time periods cannot completely track offshore wind power planned output; compared with the two graphs, no matter the actual offshore wind power output or the wind storage combined output in the scene one is compared with that in the scene two, the planned output of the offshore wind power can be better tracked in the operation stage in the day, the output punishment cost is less, and the offshore wind power consumption rate is improved. Fig. 6 shows a frequency modulation capacity optimization result of the energy storage system in a scene, and according to the optimization result, the energy storage system can be arranged to participate in the frequency modulation auxiliary service at a corresponding stage, so that the profit of the energy storage system is increased, the investment and recovery period of the energy storage system is shortened, the total profit of the offshore wind power combined energy storage system can be increased, in addition, the environmental pollution caused by the fact that the energy storage system replaces a conventional thermal power generating unit to participate in frequency modulation can be reduced, and the social benefit is improved.
The foregoing merely represents preferred embodiments of the invention, which are described in some detail and detail, and therefore should not be construed as limiting the scope of the invention. It should be noted that, for those skilled in the art, various changes, modifications and substitutions can be made without departing from the spirit of the present invention, and these are all within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (5)
1. A frequency modulation optimization operation method based on an energy storage system for participating in large-scale offshore wind power is characterized by comprising the following steps:
step 1, selecting an offshore wind farm with an energy storage system configured in a certain coastal region, acquiring a marine wind power prediction output value and related parameters of the energy storage system, and inputting original parameters of the energy storage system participating in frequency modulation optimization operation containing large-scale marine wind power;
step 2, generating a typical electricity price scene by applying a scene method according to the historical electricity price data of the PJM market, and calculating the average electricity price in the same time period in each scene as the electricity price in the time period;
the scene method described in step 2 is specifically expressed as:
an autoregressive-moving average model is adopted for scene generation, and the model is specifically expressed as follows:
wherein p and q are the order of the model,
and theta j Respectively, the undetermined coefficient, x, of the model t Represents a time series, a t Represents the error, i.e., the running average of a white noise sequence;
adopting backward reduction method to reduce scene, the concrete process is as follows:
1) the generated scenes are numbered and a reservation set a is generated { S ═ S 0 ,…,S i ,…S n Discarding the collection B ═ B 0 Making k equal to 0 for the empty set;
2) determining the scene alpha to be eliminated in the k iteration k And the removed scene alpha k Moving to a abandon collection J; modifying and culling a scene alpha k Nearest scene S m The probability of (c) is:
P(S' m )＝P(S m )+P(α k )
wherein P (S' m ) As a scene S m The probability after the change;
3) repeating the process 2) until the number of the final required scenes is obtained by continuous iteration;
step 3, establishing various profit models, including a profit model of the offshore wind power and energy storage system in an energy market, an energy storage system frequency modulation profit model, an environmental benefit model and an energy storage system loss cost model;
each profit model described in the step 3 is specifically expressed as:
the revenue of offshore wind power and energy storage systems in the energy market:
F 1 ＝f 11 -f 12
the offshore wind power and energy storage system participates in the income obtained by the energy market trading:
f 11 ＝ρ t P wc,t Δt
P wc,t ＝P w,t +P dis,t -P ch,t
wind storage output deviation penalty cost caused by offshore wind power output uncertainty, offshore wind power output power limitation, participation of an energy storage system in frequency modulation and the like:
in the formula, ρ t Electricity prices for the energy market at time t; p wc,t The total output value of the offshore wind power and energy storage system at the moment t of the energy market is obtained; p is w,t Actual output of the offshore wind farm at the moment t; p is wp,t The planned output of the offshore wind farm at the time t is provided; p ch,t 、P dis,t Charging power and discharging power of the energy storage system at the moment t; alpha (alpha) ("alpha") 1 、α 2 Punishment coefficients of the wind storage combined system when the output is excessive and insufficient are respectively;
the energy storage system frequency modulation benefit comprises capacity compensation and mileage compensation:
F 2 ＝f 21 +f 22
capacity compensation:
in the formula, n is the total daily transaction time period number of the energy storage system participating in the power auxiliary service; m 1 The commissioning rate of the energy storage system; p fm,t Reporting power for the energy storage system when participating in frequency modulation at a time t; p r,t The capacity compensation standard is used for the energy storage system when the energy storage system participates in frequency modulation at the time t;
mileage compensation:
frequency modulation mileage:
in the formula, M 2 Is an adjustment factor; k t The comprehensive performance index of the energy storage system in the time period t is obtained; d t The frequency modulation mileage of the energy storage system in the time period t is obtained; q d,t Compensating a standard for the frequency modulation mileage of the energy storage system in a time period t; beta is a variable of 0 and 1; p c,t A charging or discharging power value for the stored energy;
environmental benefits:
in the formula, Q N The electric quantity which can be generated by burning one ton of domestic standard coal; w dis,t The discharge electric quantity is the discharge electric quantity of the energy storage system participating in the electric power auxiliary frequency modulation at the moment t; lambda [ alpha ] i The unit environmental value of the i-th polluted gas; m is a unit of cf The emission amount of pollution gas generated by burning one ton of coal by a conventional thermal power coal-fired frequency modulation unit;
energy storage system loss cost:
initial construction cost of the energy storage system for the entire life cycle:
C＝C P P N +C e E N
discharge capacity of the energy storage system in the delta t period:
E Δt ＝(P dis,t +P fm,t -P ch,t )Δt
in the formula, C P 、C e The cost per unit power and per unit capacity of the energy storage system; p is N 、E N Rated power and rated capacity of the energy storage system are respectively; a. b is an energy storage cost loss calculation coefficient;
step 4, constructing an optimized operation model of which the energy storage system participates in the frequency modulation auxiliary service containing large-scale offshore wind power, and the combined operation yield of the offshore wind power and the energy storage system is maximum to be an objective function;
step 5, establishing model constraint conditions, including charge-discharge state constraint, charge-discharge power constraint and capacity constraint of the energy storage system, wherein the energy storage system participates in frequency modulation auxiliary service power constraint and the offshore wind power combined energy storage system participates in total power constraint of an energy market;
step 6, establishing fuzzy opportunity constraints of offshore wind power output;
step 7, performing optimized operation by adopting a method that an offshore wind power and energy storage system participates in an energy market and frequency modulation auxiliary service according to the optimized operation model established in the steps 3, 4, 5 and 6, and solving the model based on an MATLAB optimization tool box;
and 8, outputting the offshore wind power output value and the output value of the offshore wind power combined energy storage system under different scenes.
2. The method for participating in frequency modulation optimization operation including large-scale offshore wind power based on the energy storage system according to claim 1, wherein the optimization operation model with the maximum combined operation yield of the offshore wind power and the energy storage system as an objective function in the step 4 is specifically expressed as follows:
maxF＝F 1 +F 2 +F 3 -F 4 。
3. the method for participating in frequency modulation optimization operation involving large-scale offshore wind power based on the energy storage system according to claim 1, wherein the constraint conditions of the optimization operation model in the step 5 are specifically expressed as follows:
and (3) restricting the charge and discharge states of the energy storage system:
in the formula, beta ch 、β dis Respectively, a charge-discharge state variable, beta, of the energy storage system dis ＝1、β ch 1 indicates that the energy storage system is charging and conversely discharging; beta is a dis ＝0、β ch 0 means that the energy storage system is neither charging nor discharging;
and (3) charge and discharge power constraint of the energy storage system:
in the formula (I), the compound is shown in the specification,
respectively the maximum charging and discharging power values of the energy storage system;
capacity constraint of energy storage system:
in the formula, E soc,t The capacity state value of the energy storage system at the moment t; eta ch 、η dis Respectively the charge and discharge efficiency of the energy storage system;
respectively a minimum capacity state value and a maximum capacity state value within an allowed range of the energy storage system; SOC min 、SOC max Respectively a minimum state of charge and a maximum state of charge of the energy storage system;
respectively is the initial and final capacity state value in a charge-discharge cycle period;
the energy storage system participates in the power constraint of the frequency modulation auxiliary service:
in the formula (I), the compound is shown in the specification,
maximum power to charge or discharge the stored energy;
the offshore wind power combined energy storage participates in the total power constraint of the market in the day ahead:
in the formula (I), the compound is shown in the specification,
the maximum value of the combined output of the offshore wind power and energy storage system at the moment t.
4. The method of claim 1, wherein the fuzzy opportunity of offshore wind power output constraint in step 6 is specifically expressed as:
fuzzy chance constraint based on credibility measure:
Cr{g(x,ζ)≤0}≥γ
in the formula, Cr {. is credibility under a constraint condition {. The } is Cr {. The credibility is determined; g {. is a constraint event set; γ represents the confidence level;
two functions are defined:
then, when the confidence level γ < 0.5, the fuzzy chance constrains the clear equivalent:
when the confidence level gamma is more than or equal to 0.5, the fuzzy chance constrains a clear equivalent form:
in the formula, V represents taking a large operator, and A represents taking a small operator; r is k1 、r k2 、r k3 A triangle membership parameter;
according to the definition process of fuzzy chance constraint, the relation between the triangular fuzzy expression of offshore wind power output and the membership parameter:
in the formula (I), the compound is shown in the specification,
the output of the offshore wind power is in a fuzzy expression form; p is w,pre Predicting the output of the offshore wind power; omega 1 P w,pre 、P w,pre 、ω 2 P w,pre The output membership parameter of the offshore wind power is obtained; coefficient of proportionality omega 1 、ω 2 ；
Fuzzy opportunity constraint of offshore wind power output:
in the formula, P w,t The output power value of the offshore wind farm at the moment t;
the upper limit of the output can be adjusted for offshore wind power;
and performing clear class equivalent transformation on the fuzzy opportunity constraint of the offshore wind power output according to the fuzzy opportunity constraint clear equivalent form.
5. The method of claim 1, wherein the step 7 of participating in energy market and frequency modulation assisted services comprises:
1) scene one: the energy storage system can participate in energy market transaction by matching with offshore wind power, can also participate in frequency modulation auxiliary service by using the idle time period, follows relevant operation constraints by using an optimized operation model with the maximum combined operation income of the offshore wind power and the energy storage system as an objective function, and solves to obtain an offshore wind power output value and an offshore wind power combined energy storage system output value under the scene;
2) scene two: the energy storage system is only matched with offshore wind power to participate in energy market trading, does not participate in frequency modulation auxiliary service, complies with relevant operation constraints and solves to obtain an offshore wind power output value and an offshore wind power combined energy storage system output value under the scene by using an optimized operation model with the maximum combined operation yield of the offshore wind power and energy storage system as an objective function.
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