Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides an economic dispatching method of an electric power system based on opportunity constraint. The invention provides an effective solving method for sequentially determining the electricity abandonment amount of the renewable energy source and the output of the traditional generator, considers the fluctuation of the renewable energy source in the power system, ensures the safety of the power system, is suitable for being applied to the economic dispatching scene of the power system with high permeability of the renewable energy source, and has high application value.
The invention provides an opportunity constraint-based power system economic dispatching method which is characterized by firstly establishing an opportunity constraint-based power system economic dispatching model composed of an objective function and constraint conditions, then converting the model, writing opportunity constraints in the model into a quantile form, introducing relaxation variables, establishing a relaxed opportunity constraint-based power system economic dispatching model, and solving to obtain values of the relaxation variables; and obtaining a constraint condition that an economic dispatching model of the power system based on opportunity constraint has a feasible solution by using the values of the relaxation variables, then sequentially establishing a renewable energy power curtailment dispatching model and a generator output optimization model and respectively solving the models to obtain the power curtailment of each renewable energy source and the active power of each generator in each time period, thereby obtaining a final dispatching result. The method comprises the following steps:
1) Establishing an opportunity constraint-based economic dispatching model of the power system, wherein the model consists of an objective function and constraint conditions; the method comprises the following specific steps:
1-1) determining an objective function of an economic dispatching model of the power system, wherein the expression is as follows:
wherein T is the number of time segments of the optimization cycle, N
G In order to access the set of nodes of the generator,
for the active power of the ith generator during time period t,
for the generating cost of the ith generator in the time period t, N
R In order to access the set of nodes of the renewable energy source,
the active power output upper limit for the jth renewable energy source,
a power abandon penalty cost for the jth renewable energy source in the time period t;
wherein the content of the first and second substances,
wherein A is gi ,B gi ,C gi Generating cost coefficient of the ith generator;
wherein, K
j Penalty cost coefficient for jth renewable energy source, C
j Is the maximum capacity of the jth renewable energy source,
a probability density function of available capacity for the jth renewable energy source over time period t;
1-2) determining the constraint conditions of the economic dispatching model of the power system, comprising the following steps:
1-2-1) generator power constraint:
wherein, the first and the second end of the pipe are connected with each other,
upper and lower power limits, rup, of the ith generator, respectively
i ,Rdown
i The power limit of the ith generator is limited by upward climbing power and downward climbing power;
1-2-2) renewable energy power constraints:
wherein the content of the first and second substances,
the power is scheduled for the jth renewable energy source for time period t,
the predicted power for the jth renewable energy source over time period t,
the actual power for the jth renewable energy source during time period t,
available power for the jth renewable energy source for time period t;
1-2-3) power balance constraints:
wherein the content of the first and second substances,
for node k load demand over time period t, N
D A node set for accessing a load;
1-2-4) affine control and backup constraints:
wherein the content of the first and second substances,
actual power, beta, for the ith generator under consideration of affine control
i Affine control participation factor, alpha, for the i-th generator
UR ,α
DR Respectively the maximum allowable probability of the shortage of the up-regulation equipment and the maximum allowable probability of the shortage of the down-regulation equipment;
1-2-5) line transmission capacity constraints:
wherein N is
W Is a collection of lines, and is,
power transfer factors, P, of the line L with respect to the nodes i, j, k, respectively
L For the maximum transmission capacity of the line L,
respectively the maximum allowable probability of forward out-of-limit and the maximum allowable probability of reverse out-of-limit of the transmission capacity of the line L;
2) Converting the model established in the step 1), establishing a relaxed opportunity constraint-based power system economic dispatching model and solving the model; the method comprises the following specific steps:
2-1) by substitution in formula (10)
Opportunities of model in step 1)The constraints (11) - (14) are written in the form of quantiles as follows:
wherein Q (xi | p) is the p quantile of the random variable xi,
to account for the equivalent power transfer factor of line L with respect to node j under affine control, M
L Correction coefficients for affine control to the branch L power transfer factors;
let the joint distribution of renewable energy power over time period t be as follows:
wherein the content of the first and second substances,
a random variation of the available power composition for each renewable energy source over time t,
random variables composed of power output of each renewable energy source in a time period t;
2-2) use with
In alternative quantiles (15) - (18)
And introducing relaxation variables with constraints (16) and transmission power constraints (17) - (18) in the down-regulation to obtain equations (23) - (26);
wherein, drs
t Slack variables in the constraints are backed up for a period of t,
the slack variable in the forward constraint and the slack variable in the reverse constraint of the line transmission capacity in the t period are respectively;
2-3) establishing a relaxed opportunity constraint economic dispatching model and solving;
wherein the model objective function is formula (27), the constraint conditions include formulas (4) to (7), formula (9), formulas (23) to (26), and formula (28), and the expression is as follows:
s.t. formulae (4) - (7), (9), (23) - (26) and (28)
Wherein the content of the first and second substances,
wherein, in the process,
respectively adjusting the standby weight coefficient and the cross section risk weight coefficient in the t time period;
solving the model to obtain
The optimal solution of (2);
3) Determining the electric quantity discarded by each renewable energy source and the active power of each generator to obtain a scheduling result of the power system; the method comprises the following specific steps:
3-1) utilizing the solving result of the model in the step 2-3) and relaxing the variable
Obtaining the constraint condition that the power system economic dispatching model based on the opportunity constraint, which is established in the step 1), has a feasible solution:
if the slack variable drs t After the renewable energy is abandoned, if the model in the step 1) has a feasible solution, the inequality constraint shown in the following formula is satisfied:
if the relaxation variable is changed
If not zero, the quantile in equation (17) satisfies the inequality constraint shown in equation (30) below:
if the relaxation variable is changed
If not, the quantile in equation (18) satisfies the inequality constraint shown in equation (31) below:
the constraints (29) to (31) are written as shown in the following formula:
wherein Ω is a subscript set of renewable energy sources participating in electricity abandonment, c j ,c k Is a constant coefficient;
3-2) establishing a renewable energy power abandoning amount scheduling model and solving;
the objective function of the renewable energy power curtailment scheduling model is shown as the following formula:
the first and second derivatives of equation (33) are respectively as follows:
the curtailment penalty in equation (33) is approximated by a linear inequality as shown in equation (36):
obtaining the electric quantity abandoned by each renewable energy source in each time period t through solving the formula (36)
Then, based on the probability distribution of the available power of the renewable energy source obtained by the probability prediction and quantiles in the electric quantity abandoning calculation formulas (15) to (18) obtained by solving the formula (36), the constraint formulas (15) to (18) become deterministic linear constraints;
3-3) establishing a generator output optimization model and solving by using the result of the step 3-2) to obtain the active power of each generator in each period
Wherein, the objective function of the optimization model is formula (37), and the constraint conditions include: formulae (4) to (7), formula (9), formulae (15) to (18), and formula (38), the expressions are as follows:
s.t. formulae (4) - (7), (9), (15) - (18) and (38)
3-4) the electric energy abandon amount of each renewable energy source obtained in the step 3-2) in each time interval and the active power of each generator obtained in the step 3-3) in each time interval are the dispatching results of the power system.
The invention provides an opportunity constraint-based economic dispatching method for an electric power system, which has the advantages that:
(1) The power system economic dispatching method based on opportunity constraint provided by the invention optimizes the output of the conventional generator and the renewable energy power-abandoning strategy at the same time so as to reduce the total operation cost to the maximum extent and limit the operation risk.
(2) The invention provides an effective solving method for sequentially determining the electricity abandonment amount of renewable energy sources and the output of a traditional generator, establishes an easily-solved optimization model for each step, and is suitable for being applied to an economic dispatching scene of a power system with high renewable energy permeability.
Detailed Description
The invention provides an opportunity constraint-based power system economic dispatching method which comprises the steps of firstly establishing an opportunity constraint-based power system economic dispatching model consisting of an objective function and constraint conditions, then converting the model, writing opportunity constraints in the model into quantiles and introducing relaxation variables, establishing a relaxed opportunity constraint-based power system economic dispatching model, and solving to obtain values of the relaxation variables; and obtaining a constraint condition that an economic dispatching model of the power system based on opportunity constraint has a feasible solution by using the values of the relaxation variables, then sequentially establishing a renewable energy power curtailment dispatching model and a generator output optimization model and respectively solving the models to obtain the power curtailment of each renewable energy source and the active power of each generator in each time period, thereby obtaining a final dispatching result. The method comprises the following steps:
1) Establishing an opportunity constraint-based economic dispatching model of the power system, wherein the model consists of an objective function and constraint conditions; the method comprises the following specific steps:
1-1) determining a target function of an economic dispatching model of the power system;
the objective of economic dispatch of the power system is to minimize the total cost, which includes the cost of generating power and the penalty cost of renewable energy power abandonment, and the objective function is shown as the following formula:
wherein T is the number of time segments of the optimization cycle, N
G In order to access the set of nodes of the generator,
for the active power of the ith generator during time period t,
for the generating cost of the ith generator in the time period t, N
R In order to access the set of nodes of the renewable energy source,
the active power output upper limit of the jth renewable energy source,
and charging the j-th renewable energy source by the electricity abandoning penalty cost in the time period t.
Wherein the power generation cost can be represented by a quadratic function of the following formula:
wherein, A gi ,B gi ,C gi The power generation cost coefficient of the ith generator.
The penalty charge for electricity abandonment of renewable energy sources is shown as follows:
wherein, K
j Penalty cost coefficient for jth renewable energy source, C
j Is the maximum capacity of the jth renewable energy source,
for the jth renewable energy source during time period tAvailable capacity probability density function.
1-2) determining constraint conditions of an economic dispatching model of the power system, wherein the constraint conditions comprise:
1-2-1) generator power constraint:
wherein, the first and the second end of the pipe are connected with each other,
upper and lower power limits, rup, of the ith generator, respectively
i ,Rdown
i The power limit for ascending and the power limit for descending grade of the ith generator are respectively.
1-2-2) renewable energy power constraints:
wherein the content of the first and second substances,
the power is scheduled for the jth renewable energy source for time period t,
the predicted power for the jth renewable energy source over time period t,
the actual power for the jth renewable energy source during time period t,
available power for the jth renewable energy source for time period t.
1-2-3) power balance constraints:
wherein, the first and the second end of the pipe are connected with each other,
for node k load demand over time period t, N
D Is the set of nodes accessing the load.
1-2-4) affine control and backup constraints:
wherein, the first and the second end of the pipe are connected with each other,
actual power, beta, for the ith generator under consideration of affine control
i Affine control participation factor, alpha, for the i-th generator
UR ,α
DR The maximum allowable probability of under-provisioning and the maximum allowable probability of under-provisioning are respectively up-provisioning and down-provisioning.
1-2-5) line transmission capacity constraints:
wherein N is
W Is a collection of lines, and is,
the power transfer factors of the line L with respect to the nodes i, j, k,
for the maximum transmission capacity of the line L,
respectively, a maximum allowed probability of the transmission capacity of the line L being out of limit in the forward direction and a maximum allowed probability of the transmission capacity being out of limit in the reverse direction.
2) Detecting infeasible constraints and renewable energy power consumption, converting the model established in the step 1), establishing a relaxed power system economic dispatching model based on opportunity constraints, and solving; the method comprises the following specific steps:
2-1) by substitution in formula (10)
The opportunity constraints (11) - (14) are written in the form of quantiles as follows:
wherein Q (xi | p) is the p quantile of the random variable xi,
to account for the equivalent power transfer factor of line L relative to node j in affine control, M
L And controlling a correction coefficient of the power transfer factor of the branch L for affine control.
Assuming that the joint distribution of renewable energy power over time period t is known, as follows:
wherein the content of the first and second substances,
a random variation of the available power composition for each renewable energy source over time t,
random variables composed of power output of each renewable energy source in a time period t;
actual renewable energy power in traditional opportunistic constrained economic dispatch without considering renewable energy power curtailment
Equal to available renewable energy power
However, the calculation of the number of bits in equations (16) - (18) is based on the assumption that there is no electricity curtailment for renewable energy sources, which may result in conventional generator power
There is no feasible solution.
2-2) renewable energy power can be curtailed by reducing the quantiles to the right of the intermediate equations (16) - (18), thereby reducing the risk of down-regulation of backup shortages and transmission blockages. By using
In alternative quantiles (15) - (18)
And introducing relaxation variables in the down-regulation by the constraint (16) and the transmission power constraints (17) to (18), the following formulas (23) to (26) can be obtained:
wherein, drs
t Slack variables in the standby constraints are adjusted for a period of time t,
the slack variable in the forward constraint and the slack variable in the reverse constraint of the line transmission capacity in the t period are respectively;
2-3) establishing a relaxed power system economic dispatching model based on opportunity constraint and solving;
wherein the model objective function is equation (27), and the objective of equation (27) is to minimize the weighted sum of the relaxation variables to solve the generator active power
There is no feasible solution case. In the process of calculating the linear combination
After quantiles of (a), the following relaxed opportunity constraint-based power system economic dispatch model can be solved directly with linear programming.
s.t. formulae (4) - (7), (9), (23) - (26) and (28)
Wherein the content of the first and second substances,
wherein the content of the first and second substances,
respectively as the weight coefficient of standby and the weight coefficient of section risk under t time interval.
Solving the model to obtain
The optimal solution of (2);
3) Determining the electric quantity discarded by each renewable energy source and the active power of each generator to obtain a scheduling result of the power system; the method comprises the following specific steps:
3-1) after solving the power system economic dispatching model based on the opportunity constraint after the relaxation in the step 2-3), obtaining the economic dispatching model through relaxation variables
Obtaining the constraint conditions of feasible solutions of the power system economic dispatching model based on the opportunity constraint established in the step 1):
if the slack variable drs in the backup constraint is adjusted downward t After the renewable energy is abandoned, in order to make the model of step 1) feasible, the inequality constraint shown in the following formula must be satisfied:
if the relaxation variable
If the value is not zero, the quantile in the transmission capacity constraint equation (17) satisfies an inequality constraint represented by the following equation (30):
if the relaxation variable is changed
If the value is not zero, the quantile in the transmission capacity constraint equation (18) satisfies an inequality constraint shown in the following equation (31):
the constraints (29) - (31) can be written as shown in the following formula:
wherein, omega is a subscript set of renewable energy sources participating in electricity abandonment, c j ,c k Is a constant coefficient.
3-2) establishing a renewable energy power abandoning amount scheduling model and solving;
the objective function of renewable energy power curtailment scheduling is to minimize the overall power curtailment penalty cost as shown in the following formula:
the quantile in equation (32) and the objective function in equation (33) are with respect to the upper limit of renewable energy power
The linear approximation of equations (32) and (33) can be used to obtain a solvable renewable energy power curtailment scheduling model, whose first and second derivatives of objective function equation (33) are respectively as follows:
since the second derivative of the objective function (33) is greater than or equal to zero, the power dump penalty is related to the upper power limit of the renewable energy source
A convex function of (a). The curtailment penalty in equation (33) is approximated by a linear inequality shown in equation (36) below, according to the nature of the convex function:
by passingThe solution formula (36) can obtain the electricity abandon quantity of each renewable energy source in each time period
Then, based on the probability distribution of the renewable energy available power obtained by the probability prediction and the quantiles in the electricity curtailment calculation equations (15) to (18) obtained by solving the equation (36), the constraints (15) to (18) become deterministic linear constraints.
3-3) obtaining the active power of each generator in each time period by solving a generator output optimization model shown as the following step by using the result of the step 3-2)
Thereby obtaining the dispatching output of the generator.
The objective function of the optimization model is equation (37), and equation (38) is used to limit the scheduled output of the renewable energy source to be lower than the upper power limit in the constraint condition.
s.t. formulae (4) - (7), (9), (15) - (18) and (38)
3-4) the electric energy abandon quantity of each renewable energy source obtained in the step 3-2) in each time interval and the active power of each generator obtained in the step 3-3) in each time interval are the power system dispatching results.