CN110783957A - Wind power system-containing rotating standby optimal configuration method considering demand response - Google Patents
Wind power system-containing rotating standby optimal configuration method considering demand response Download PDFInfo
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Abstract
The invention discloses a wind power-containing power system rotation standby optimal configuration method considering demand response. The method comprises the following steps of 1: carrying out modeling analysis and calculation according to the uncertainty of the wind power output and the load to obtain the initial rotation reserve capacity of the power system; step 2: calculating to obtain the load side reduction rotation reserve capacity according to the interruptible load model and the translatable load model; and step 3: the optimized spinning reserve capacity is determined by analyzing the initial spinning reserve capacity and the curtailed spinning reserve capacity. And 4, step 4: and solving the optimized spinning reserve demand by adopting a Matlab tool box YALMIP programming solving method to obtain the optimal configuration of the spinning reserve demand. According to the wind power system rotating standby optimal configuration method considering demand response, provided by the invention, on the premise of ensuring stable operation of a power grid, the economical efficiency of operation of the power system can be improved, the rotating standby capacity is provided, wind power consumption is promoted, and the method has high engineering applicability.
Description
Technical Field
The invention relates to the technical field of power automation, in particular to a wind power system-containing rotating standby optimal configuration method considering demand response.
Background
The inherent randomness, volatility and other characteristics of wind power seriously affect the stable operation of the system. With the continuous expansion of the new energy grid-connected power generation scale, the rotating standby demand on the system increases suddenly, and the new energy power generation absorption capacity is seriously insufficient. Under the power grid intelligent background, the flexible controllable load and the power grid interactivity are enhanced, and the controllable load participates in scheduling, so that the reliability and the economy of the system are improved. In order to ensure the safe and stable operation of the power system and promote the wind power consumption, the original operation mode needs to be improved, a proper amount of rotary standby is equipped, and the controllable load is brought into a dispatching plan so as to deal with the uncertainty of the wind power output and the load.
Researchers at home and abroad mostly study the rotating standby optimal configuration problem of the wind power-containing power system from the aspects of reliability, economy, risk and the like of system operation. At present, the problem of the optimal configuration of the rotating standby of the wind power system is mainly researched from the following aspects: (1) and researching the system rotation standby optimization problem from three aspects of source network load. (2) From the source perspective, the wind power supply rotation standby in the wind power high-permeability power grid and the optimal configuration of the system rotation standby by improving the wind power prediction precision are respectively researched. (3) And (3) from the perspective of a network, considering network constraint and the interruption probability of a transmission line, and providing a new rotating standby model of the power system for optimizing the transmission line fault. (4) And introducing a sequence operation theory from the load angle to accurately represent the discrete sequence of the probability density function of the net load of each time interval, thereby optimizing the configuration of the positive and negative rotation standby. However, the problem of rotating standby configuration needs to be solved in a source network load three-aspect coordination mode, and it is difficult to guarantee that a system optimal solution is obtained only from a certain aspect. (5) By apportioning the rotating standby cost of the wind power-containing power system, the system is guided to reduce the standby requirement and improve the system economy. (6) Rotating standby demand is optimized based on economics at different confidence levels. (7) The maximum benefit and the minimum risk of the expected rotary reserve are taken as optimization targets, the obtained positive and negative rotary reserve capacity is optimized, and the reliability and the economical efficiency of the system are considered. The above studies, while taking system economy into account when determining spinning reserve capacity, do not take into account user-side schedulable resources and are not globally optimal solutions. (8) And (4) establishing a rotary reserve optimization model by considering user side demand response, and researching the influence of implementation of time-of-use electricity price and interruptible load on rotary reserve benefit to obtain the optimal rotary reserve capacity of the system. But the impact of demand response on spinning reserve capacity configuration is not analyzed in depth.
Disclosure of Invention
The invention provides a wind power system-containing rotating standby optimal configuration method considering demand response, which can improve the economical efficiency of the operation of a power system, enhance the capacity of a conventional unit for providing rotating standby, promote wind power consumption and have higher engineering applicability on the premise of ensuring the stable operation of a power grid.
In order to achieve the purpose, the invention provides the following scheme:
a wind power system-containing rotating standby optimal configuration method considering demand response comprises the following steps:
step 1: carrying out modeling analysis and calculation according to the uncertainty of the wind power output and the load to obtain the initial rotation reserve capacity of the power system;
step 2: calculating to obtain the load side reduction rotation reserve capacity according to the interruptible load model and the translatable load model;
and step 3: the optimized spinning reserve capacity is determined by analyzing the initial spinning reserve capacity and the curtailed spinning reserve capacity.
And 4, step 4: and solving the optimized spinning reserve demand by adopting a Matlab tool box YALMIP programming solving method to obtain the optimal configuration of the spinning reserve demand.
Optionally, the step 1: carrying out modeling analysis and calculation according to the uncertainty of the wind power output and the load to obtain the initial rotation reserve capacity of the power system, and specifically comprising the following steps:
(2a) wind farm output uncertainty modeling
Wind turbine generator output power p
wThe wind turbine generator set predicted output can be obtained by using the piecewise function representation of the wind speed v
Considering the uncertainty of wind power output, the wind power output is predicted
On the basis of the superposition of the prediction error Delta epsilon
wTo obtain the actual wind power output P
wComprises the following steps:
in the formula: v. of
iIndicating cut-in wind speed, v
rIndicating rated wind speed, v
oIndicating cut-out wind speed, P
rIndicating rated power, k, of the wind turbine
0、k
1And k
2Is a constant, Δ ε
wObedience mean of 0 and variance of
Normal distribution, standard deviation σ
w,tWind power output predicted value and wind power total installed capacity R are used
zIs shown as
(2b) Load uncertainty modeling
Setting the predicted load value at t as p
l,tAnd the load prediction deviation follows normal distribution to obtain:
in the formula: Δ p
lFor load prediction error, σ
2The variance of the error is predicted for the load.
Optionally, step 2: and calculating to obtain the load side reduction rotation reserve capacity according to the interruptible load model and the translatable load model, wherein the method specifically comprises the following steps:
(3a) interruptible load modeling
The power of the load i in the time period t after scheduling is
The compensation charge given to the user i after scheduling is
Interrupt time and frequency constraints
And
in the formula:
power usage before scheduling for load i at time t, α
i0 < α for load interruption factor
i≤1，α
i1 means that load i is completely interrupted;
a penalty fee for interrupting the unit power load;
the maximum duration of the load interruption in the scheduling period;
for the number of times the interruptible load i is actually invoked,
for maximum number of load interruptions allowed in a scheduling period, u
i,tIndicating an interruptible load state, u
i,t1 represents an interrupt;
(3b) translatable load modeling
The time-of-day power rate-responsive translatable load is
The translation amount constraint is:
an equivalent scheduling cost of
In the formula:
the predicted t-period load for the day-ahead schedule,
respectively load transferred into the t time period and load transferred out of the t time period; p
y,j(t-1) power after the load capable of rotating horizontally responds in the t-1 time period;
maximum allowable power variation for the load; p
y0(t) is the initial power usage of the load during the time period t; c
y0(t) is the original electricity price at time t; c
y(t) is the time-of-use electricity price at time t, P
y,j(t) is the actual power of the translatable load j at time t, and Δ t is the sampling time.
Optionally, the step 3: the method comprises the following steps of determining the optimized rotating reserve capacity by analyzing the initial rotating reserve capacity and the reduced rotating reserve capacity, and specifically comprises the following steps:
the minimum total generating cost C of the system is solved according to the system generating cost, the positive and negative rotation standby cost of the generating side, the wind abandoning cost and the response cost of the demand side
minAnd establishing an objective function, wherein the objective function is as follows:
in the formula: f (t) is the total economic cost of the thermal power generating unit at the moment t, P
G,i(t) is the output of the generator i at time t, P
G,j(t) is the output of generator j at time t, a
i，b
i，c
iIs the unit output coal consumption coefficient of the thermal power generating unit, F
wcPenalizing cost for wind abandon, C
wcPrice penalized for wind abandonment, F
SRFor spinning reserve costs α
i,uAnd α
i,dRespectively are up-down rotating standby prices,
and
R i，trespectively for up-and-down rotationCapacity; f
loadIn order to meet the demand response cost,
to represent the compensation charge given to the user i by the power system after the interruptible load has participated in the scheduling, S
jRepresenting a translatable load equivalent scheduling cost;
in order to obtain the optimal optimization effect of the objective function, the objective function is constrained, and the constraint conditions are as follows: according to active power balance constraints; according to power plant output constraints; according to a transmission power constraint of the transmission line; according to the climbing rate constraint of the conventional unit; according to positive and negative rotation standby constraints.
Optionally, the step 4: solving the optimized spinning reserve demand by adopting a Matlab tool box YALMIP programming solving method to obtain the optimal configuration of the spinning reserve demand, which specifically comprises the following steps:
(5a) inputting wind power output and output prediction data of each time period of 24 hours in the future of the load;
(5b) setting parameters of a conventional unit, parameters of a demand response model and constraint conditions;
(5c) solving the unit combination by using a GUROBI solver to determine the output plan and the rotary standby capacity of each unit;
(5d) adjusting the predicted value of each time interval of the translatable load according to the time-of-use electricity price, and repeating the step (5 c);
(5e) and (5) adjusting the interruptible load electricity utilization condition according to the set wind power and load fluctuation case, and repeating the step (5 c).
Compared with the prior art, the technology has the following beneficial effects:
the invention provides a rotating standby optimal configuration method for a wind power system considering demand response, which is used for providing a rotating standby optimal configuration strategy considering demand response from the source network load coordination perspective on the basis of the existing research aiming at the problems of thin-weak peak regulation capability and low wind power consumption level of the wind power system. The strategy considers the uncertainty of wind power output and load prediction and models according to the demand response characteristics. And further establishing a rotary standby constraint model and solving by adopting a GUROBI solver. The correctness and the effectiveness of the strategy are verified through example analysis.
The implementation of large-scale wind power grid connection, time-of-use electricity price and interruptible load brings new challenges and opportunities for the configuration of the rotary standby on the power generation side. The invention considers the influence of time-of-use electricity price and interruptible load on the rotary standby optimal configuration for research, and the conclusion is as follows:
1) the time-of-use electricity price changes the electricity consumption habit of residents, part of loads can be translated to respond to scheduling excitation, electricity consumption is advanced or delayed, the electricity consumption requirement during the electricity consumption peak is dispersed, the peak regulation pressure of a conventional unit is reduced, the unit combination is optimized, the rotating standby requirement of the system is reduced, the rotating standby capacity of the conventional unit is equivalently improved, and the power supply cost of the system is further reduced on the premise of meeting the power supply reliability.
2) The interruptible load is quick in response, and when the system has short-time power unbalance, the interruptible load responds in advance of the conventional unit, so that fluctuation can be stabilized in time, the stability of the power system is improved, part of the rotating reserve capacity provided by the conventional unit is offset, and the economic benefit of the overall operation of the system is greatly improved. But the interruptible load scale is small, and intelligent transformation and source expansion of a power grid are urgently needed.
3) The load can be translated only by predicting the trend but not establishing an accurate model under the influence of the inertia of the electricity utilization habit of the user; the power load has high proportion of cold and hot loads, long power duration and thermal inertia, and the heat accumulation/cold device can be additionally arranged to disperse power scale and time period or replace part of the power load through a heat source and an air source, so that the multiple sources are complemented, and the overall economy and reliability are improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flowchart illustrating a method for optimally configuring a rotating standby power system including wind power generation in accordance with an embodiment of the present invention;
FIG. 2 is a diagram of a day spin standby configuration plan, in accordance with an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a wind power system-containing rotating standby optimal configuration method considering demand response, which can improve the economical efficiency of the operation of a power system, enhance the capacity of a conventional unit for providing rotating standby, promote wind power consumption and have higher engineering applicability on the premise of ensuring the stable operation of a power grid.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Fig. 1 is a flowchart of a method for optimally configuring a rotating standby power system including wind power according to an embodiment of the present invention, and as shown in fig. 1, the method for optimally configuring a rotating standby power system including wind power according to a demand response includes the following steps:
step 101: carrying out modeling analysis and calculation according to the uncertainty of the wind power output and the load to obtain the initial rotation reserve capacity of the power system;
step 102: calculating to obtain the load side reduction rotation reserve capacity according to the interruptible load model and the translatable load model;
step 103: the optimized spinning reserve capacity is determined by analyzing the initial spinning reserve capacity and the curtailed spinning reserve capacity.
Step 104: and solving the optimized spinning reserve demand by adopting a Matlab tool box YALMIP programming solving method to obtain the optimal configuration of the spinning reserve demand.
The step 101: carrying out modeling analysis and calculation according to the uncertainty of the wind power output and the load to obtain the initial rotation reserve capacity of the power system, and specifically comprising the following steps:
wind farm output uncertainty modeling
Wind turbine generator output power p
wThe wind turbine generator set predicted output can be obtained by using the piecewise function representation of the wind speed v
Considering the uncertainty of wind power output, the wind power output is predicted
On the basis of the superposition of the prediction error Delta epsilon
wTo obtain the actual wind power output P
wComprises the following steps:
in the formula: v. of
iIndicating cut-in wind speed, v
rIndicating rated wind speed, v
oIndicating cut-out wind speed, P
rIndicating rated power, k, of the wind turbine
0、k
1And k
2Is a constant, Δ ε
wObedience mean of 0 and variance of
Normal distribution, standard deviation σ
w,tWind power output predicted value and wind power total installed capacity R are used
zIs shown as
Load uncertainty modeling
Setting the predicted load value at t as p
l,tAnd the load prediction deviation follows normal distribution to obtain:
in the formula: Δ p
lFor load prediction error, σ
2The variance of the error is predicted for the load.
Demand response modeling
When the installed capacity of new energy power generation is increased, the load structure is remarkably changed, the peak load is rapidly increased, and the load peak-valley difference is increased year by year. When the power dispatching peak regulation capacity is insufficient, measures such as switching off and power limiting are generally adopted to meet power balance, and the power utilization satisfaction degree of users is seriously influenced. The intelligent transformation of the power grid enables the power utilization flexibility of the user load to be continuously improved. The orderly utilization of the load can greatly improve the dispatching capability of the system and improve the economical efficiency of the system operation. The invention mainly models two types of controllable loads to research the influence of demand response on the rotary standby configuration.
Interruptible load modeling
The interruptible load may be partially or fully interrupted depending on the system power balance. The interruptible load has high response speed, can replace part of thermal power generating units to provide rotary standby auxiliary service, and is favorable for guaranteeing the power balance of the system. The interruption state of the interruptible load in time t is represented by a variable 0-1, u
i,t1 indicates that the load i is interrupted during the period t.
The power of the load i in the time period t after scheduling is
The compensation charge given to the user i after scheduling is
Interrupt time and frequency constraints
And
in the formula:
power usage before scheduling for load i at time t, α
i0 < α for load interruption factor
i≤1，α
i1 means that load i is completely interrupted;
a penalty fee for interrupting the unit power load;
the maximum duration of the load interruption in the scheduling period;
for the number of times the interruptible load i is actually invoked,
for maximum number of load interruptions allowed in a scheduling period, u
i,tIndicating an interruptible load state, u
i,t1 represents an interrupt;
translatable load modeling
The translatable load is a controllable load for which the user seeks a minimum electricity usage cost in response to the time-of-use electricity prices. The method has the advantages of low response speed, large scale, mainly changing load power utilization trend, smoothing load power utilization curve, fundamentally reducing the rotary standby requirement of the conventional unit, and being frequently applied to day-ahead scheduling.
The time-of-day power rate-responsive translatable load is
The translation amount constraint is:
an equivalent scheduling cost of
In the formula:
the predicted t-period load for the day-ahead schedule,
respectively load transferred into the t time period and load transferred out of the t time period; p
y,j(t-1) power after the load capable of rotating horizontally responds in the t-1 time period;
maximum allowable power variation for the load; p
y0(t) is the initial power usage of the load during the time period t; c
y0(t) is the original electricity price at time t; c
y(t) is the time-of-use electricity price at time t, P
y,j(t) is the actual power of the translatable load j at time t, and Δ t is the sampling time.
Rotary standby optimization model
The minimum total generating cost C of the system is solved according to the system generating cost, the positive and negative rotation standby cost of the generating side, the wind abandoning cost and the response cost of the demand side
minAnd establishing an objective function, wherein the objective function is as follows:
in the formula: f (t) is the total economic cost of the thermal power generating unit at the moment t, P
G,i(t) is the output of the generator i at time t, P
G,j(t) is the output of generator j at time t, a
i，b
i，c
iIs the unit output coal consumption coefficient of the thermal power generating unit, F
wcPenalizing cost for wind abandon, C
wcPrice penalized for wind abandonment, F
SRFor spinning reserve costs α
i,uAnd α
i,dAre respectively rotated up and downThe price is used for the purpose of,
and
R i，trespectively up-down rotating reserve capacity; f
loadIn order to meet the demand response cost,
to represent the compensation charge given to the user i by the power system after the interruptible load has participated in the scheduling, S
jRepresenting a translatable load equivalent scheduling cost;
in order to obtain the optimal optimization effect of the objective function, the objective function is constrained, and the constraint conditions are as follows: according to active power balance constraints; according to power plant output constraints; according to a transmission power constraint of the transmission line; according to the climbing rate constraint of the conventional unit; according to positive and negative rotation standby constraints.
The constraint conditions of the conventional optimized power flow model mainly comprise:
1) active power balance constraint
In the formula: p
W,tWind power grid-connected power at the moment t; p
L,tThe total power load at time t.
2) Power plant output constraints
P
imin≤P
i,t≤P
imax
In the formula: p
imax、P
iminThe upper and lower limits of the output of the conventional unit;
the output power of the wind turbine generator is the upper limit and the lower limit of the output power of the wind turbine generator.
3) Transmission power constraint for power transmission lines
In the formula (I), the compound is shown in the specification,
the upper limit of the active power transmitted for line l.
4) Conventional unit ramp rate constraint
In the formula, R
i,upAnd R
i,downAnd the unit i is the limit value of the climbing power and the descending power in unit time.
5) Positive and negative rotational back-up constraints
In the formula:
R trespectively up-regulation standby and down-regulation standby values which are satisfied by the load and wind wave fluctuation at the time t.
The step 104 is that: solving the optimized spinning reserve demand by adopting a Matlab tool box YALMIP programming solving method to obtain the optimal configuration of the spinning reserve demand, which specifically comprises the following steps:
(1) inputting wind power output and output prediction data of each time period of 24 hours in the future of the load;
(2) setting parameters of a conventional unit, parameters of a demand response model and constraint conditions;
(3) solving the unit combination by using a GUROBI solver to determine the output plan and the rotary standby capacity of each unit;
(4) adjusting the predicted value of each time interval of the translatable load according to the time-of-use electricity price, and repeating the step (3);
(5) and (4) adjusting the interruptible load power utilization condition according to the set wind power and load fluctuation case, and repeating the step (3).
The simulation analysis method adopts a power system consisting of 6 thermal power generating units and 5 wind power plants to perform simulation analysis. The parameters of the thermal power generating units are shown in table 1, and the wind power plant comprises 200 wind power generating units with installed capacity of 1.5 MW. The operation cost of the thermal power generating unit is 252 yuan/MW & h, and the rotating standby cost is 130 yuan/MW & h. The wind abandon penalty cost is 180 yuan/MW & h. And defining the system rotation standby capacity as the ratio of the capacity of the thermal engine assembling machine to the load of each time interval.
TABLE 1 thermal power generating unit parameters
Table1 Thermal power unit parameters
The load and wind power output prediction data are shown in table 2. Taking the time period of 8: 00-22: 00 as a peak section, and executing the peak time electricity price of 0.57 yuan/kW.h; the power rate of the rice is 0.29 yuan/kW.h when the rice is executed, wherein the power rate is 22: 00-8: 00 every day. The original price of electricity is 0.5 yuan/kW.h. The scheduling cost of interruptible load is 225 yuan/MW · h. The interruptible load capacity is 50 MW.
TABLE 2 load and wind power output prediction data
Table2 Load and wind power output forecast data
Due to uncertainty of wind power output, if the total installed capacity of a conventional unit is close to the daily maximum load, the rotating standby capacity of the system is insufficient, and the load shedding risk exists. The data analysis of the examples shows that the spare capacity at 16 points is insufficient, the rotating spare capacity is 104%, the load peak-valley difference reaches 1061MW, and if the output of a conventional unit is increased, the marginal cost is too high, and the economical efficiency is poor. Power system scheduling is encumbered with dilemma. And the power utilization trend of the translatable load can be changed by the excitation of the time-of-use power price, such as the data in the table 3. It can be seen from table 3 that the peak load is reduced to 1084MW, which is much smaller than the total output of the conventional thermal power generating unit, and the peak-to-valley difference is reduced to 484 MW. The number of the thermal power generating units with high power generation cost can be reduced by adjusting the unit combination and the output distribution, and the economical efficiency of system operation is greatly improved. The rotating standby requirement of the system is reduced by 27.7%, the running economy of the system is improved, and the rotating standby capacity of the system reaches 121.8%. The electric charge expenses of the power consumers before and after the time-of-use electricity price are 10520000 yuan and 10061080 yuan respectively, and the electricity cost is saved by about 4.4% when the electricity load of the residents responds to the time-of-use electricity price.
TABLE 3 load data before and after time of use of electricity price
Table3 Time-of-use electricity price before and after load data
Fig. 2 is a diagram of a day-spin standby configuration plan implemented by the present invention, and as shown in fig. 2, for the day-spin standby configuration plan after time-of-use electricity price execution, two cases, accounting for interruptible load and not including interruptible load, are considered and an interruptible load plan calling curve is given. The cost of the conventional unit for providing the rotary standby is divided into capacity cost and calling cost, and only the compensation cost is called for calling the interruptible load, so that the system economy can be further improved by preferentially calling the interruptible load on the premise of meeting the constraint condition. Through computational analysis, a configuration plan that accounts for interruptible load saves approximately 24.6% in cost over a plan that does not account for interruptible load. Compared with the rotary standby provided by a conventional unit, the interruptible load serving as an equivalent rotary standby has the characteristics of high response speed, low cost, small capacity and the like, when the load or wind power output fluctuates for a short time, the interruptible load is preferentially adjusted to ensure power balance in time, and when the fluctuation scale is too large, the rotary standby of the conventional unit is called, so that the requirement on system reliability is met, the rotary standby capacity is reduced, and the economical efficiency of system operation is improved.
The invention provides a rotating standby optimal configuration method for a wind power system considering demand response, which is used for providing a rotating standby optimal configuration strategy considering demand response from the source network load coordination perspective on the basis of the existing research aiming at the problems of thin-weak peak regulation capability and low wind power consumption level of the wind power system. The strategy considers the uncertainty of wind power output and load prediction and models according to the demand response characteristics. And further establishing a rotary standby constraint model and solving by adopting a GUROBI solver. The correctness and the effectiveness of the strategy are verified through example analysis. The implementation of large-scale wind power grid connection, time-of-use electricity price and interruptible load brings new challenges and opportunities for the configuration of the rotary standby on the power generation side. The invention considers the influence of time-of-use electricity price and interruptible load on the rotary standby optimal configuration for research, and the conclusion is as follows: 1) the time-of-use electricity price changes the electricity consumption habit of residents, part of loads can be translated to respond to scheduling excitation, electricity consumption is advanced or delayed, the electricity consumption requirement during the electricity consumption peak is dispersed, the peak regulation pressure of a conventional unit is reduced, the unit combination is optimized, the rotating standby requirement of the system is reduced, the rotating standby capacity of the conventional unit is equivalently improved, and the power supply cost of the system is further reduced on the premise of meeting the power supply reliability. 2) The interruptible load is quick in response, and when the system has short-time power unbalance, the interruptible load responds in advance of the conventional unit, so that fluctuation can be stabilized in time, the stability of the power system is improved, part of the rotating reserve capacity provided by the conventional unit is offset, and the economic benefit of the overall operation of the system is greatly improved. But the interruptible load scale is small, and intelligent transformation and source expansion of a power grid are urgently needed. 3) The load can be translated only by predicting the trend but not establishing an accurate model under the influence of the inertia of the electricity utilization habit of the user; the power load has high proportion of cold and hot loads, long power duration and thermal inertia, and the heat accumulation/cold device can be additionally arranged to disperse power scale and time period or replace part of the power load through a heat source and an air source, so that the multiple sources are complemented, and the overall economy and reliability are improved. The invention provides a wind power-containing power system rotation standby optimal configuration method considering demand response, and wind power large-scale grid connection influences stable operation of a power system and has difficulty in absorption. In order to ensure the reliability of a wind power-containing power system, a rotating standby optimal configuration strategy considering demand response is provided. According to the method, on the premise of analyzing wind power output and load prediction errors, controllable load demand response capacity is considered, and a power supply optimization combination model is established by taking the minimum total power generation cost of a system as a target. And (5) optimizing and solving the model by adopting a GUROBI solver. According to simulation verification, on the premise of ensuring stable operation of a power grid, the strategy can improve the economical efficiency of operation of a power system, enhance the capacity of a conventional unit for providing rotary standby, promote wind power consumption and have high engineering applicability.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (5)
1. A wind power system-containing rotating standby optimal configuration method considering demand response is characterized by comprising the following steps:
step 1: carrying out modeling analysis and calculation according to the uncertainty of the wind power output and the load to obtain the initial rotation reserve capacity of the power system;
step 2: calculating to obtain the load side reduction rotation reserve capacity according to the interruptible load model and the translatable load model;
and step 3: the optimized spinning reserve capacity is determined by analyzing the initial spinning reserve capacity and the curtailed spinning reserve capacity.
And 4, step 4: and solving the optimized spinning reserve demand by adopting a Matlab tool box YALMIP programming solving method to obtain the optimal configuration of the spinning reserve demand.
2. The wind power system rotating standby optimal configuration method considering demand response of claim 1, wherein the step 1: carrying out modeling analysis and calculation according to the uncertainty of the wind power output and the load to obtain the initial rotation reserve capacity of the power system, and specifically comprising the following steps:
(2a) wind farm output uncertainty modeling
Wind turbine generator output power p
wThe wind turbine generator set predicted output can be obtained by using the piecewise function representation of the wind speed v
Considering the uncertainty of wind power output, the wind power output is predicted
On the basis of the superposition of the prediction error Delta epsilon
wTo obtain the actual wind power output P
wComprises the following steps:
in the formula: v. of
iIndicating cut-in wind speed, v
rIndicating rated wind speed, v
oIndicating cut-out wind speed, P
rIndicating rated power, k, of the wind turbine
0、k
1And k
2Is a constant, Δ ε
wObedience mean of 0 and variance of
Normal distribution, standard deviation σ
w,tWind power output predicted value and wind power total installed capacity R are used
zIs shown as
(2b) Load uncertainty modeling
Setting the predicted load value at t as p
l,tAnd the load prediction deviation follows normal distribution to obtain:
in the formula: Δ p
lFor load prediction error, σ
2The variance of the error is predicted for the load.
3. The wind power system rotating standby optimal configuration method considering demand response of claim 1, wherein the step 2: and calculating to obtain the load side reduction rotation reserve capacity according to the interruptible load model and the translatable load model, wherein the method specifically comprises the following steps:
(3a) interruptible load modeling
The power of the load i in the time period t after scheduling is
The compensation charge given to the user i after scheduling is
Interrupt time and frequency constraints
And
in the formula:
power usage before scheduling for load i at time t, α
i0 < α for load interruption factor
i≤1，α
i1 means that load i is completely interrupted;
a penalty fee for interrupting the unit power load;
the maximum duration of the load interruption in the scheduling period;
for the number of times the interruptible load i is actually invoked,
for maximum number of load interruptions allowed in a scheduling period, u
i,tIndicating an interruptible load state, u
i,t1 represents an interrupt;
(3b) translatable load modeling
The time-of-day power rate-responsive translatable load is
The translation amount constraint is:
an equivalent scheduling cost of
In the formula:
the predicted t-period load for the day-ahead schedule,
respectively load transferred into the t time period and load transferred out of the t time period; p
y,j(t-1) power after the load capable of rotating horizontally responds in the t-1 time period;
maximum allowable power variation for the load; p
y0(t) is the initial power usage of the load during the time period t;C
y0(t) is the original electricity price at time t; c
y(t) is the time-of-use electricity price at time t, P
y,j(t) is the actual power of the translatable load j at time t, and Δ t is the sampling time.
4. The wind power system rotating standby optimal configuration method considering demand response of claim 1, wherein the step 3: the method comprises the following steps of determining the optimized rotating reserve capacity by analyzing the initial rotating reserve capacity and the reduced rotating reserve capacity, and specifically comprises the following steps:
the minimum total generating cost C of the system is solved according to the system generating cost, the positive and negative rotation standby cost of the generating side, the wind abandoning cost and the response cost of the demand side
minAnd establishing an objective function, wherein the objective function is as follows:
in the formula: f (t) is the total economic cost of the thermal power generating unit at the moment t, P
G,i(t) is the output of the generator i at time t, P
G,j(t) is the output of generator j at time t, a
i，b
i，c
iIs the unit output coal consumption coefficient of the thermal power generating unit, F
wcPenalizing cost for wind abandon, C
wcPrice penalized for wind abandonment, F
SRFor spinning reserve costs α
i,uAnd α
i,dRespectively are up-down rotating standby prices,
and
R i,trespectively up-down rotating reserve capacity; f
loadIn order to meet the demand response cost,
to represent the compensation charge given to the user i by the power system after the interruptible load has participated in the scheduling, S
jRepresenting a translatable load equivalent scheduling cost;
in order to obtain the optimal optimization effect of the objective function, the objective function is constrained, and the constraint conditions are as follows: according to active power balance constraints; according to power plant output constraints; according to a transmission power constraint of the transmission line; according to the climbing rate constraint of the conventional unit; according to positive and negative rotation standby constraints.
5. The wind power system rotating standby optimal configuration method considering demand response of claim 1, wherein the step 4: solving the optimized spinning reserve demand by adopting a Matlab tool box YALMIP programming solving method to obtain the optimal configuration of the spinning reserve demand, which specifically comprises the following steps:
(5a) inputting wind power output and output prediction data of each time period of 24 hours in the future of the load;
(5b) setting parameters of a conventional unit, parameters of a demand response model and constraint conditions;
(5c) solving the unit combination by using a GUROBI solver to determine the output plan and the rotary standby capacity of each unit;
(5d) adjusting the predicted value of each time interval of the translatable load according to the time-of-use electricity price, and repeating the step (5 c);
(5e) and (5) adjusting the interruptible load electricity utilization condition according to the set wind power and load fluctuation case, and repeating the step (5 c).
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