CN113270903B - Load recovery double-layer optimization method considering time-varying step length - Google Patents

Load recovery double-layer optimization method considering time-varying step length Download PDF

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CN113270903B
CN113270903B CN202110710597.9A CN202110710597A CN113270903B CN 113270903 B CN113270903 B CN 113270903B CN 202110710597 A CN202110710597 A CN 202110710597A CN 113270903 B CN113270903 B CN 113270903B
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load
node
formula
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recovery
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CN113270903A (en
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孙磊
杨智超
李明明
丁明
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Hefei University of Technology
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/48—Controlling the sharing of the in-phase component
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
    • H02J3/144—Demand-response operation of the power transmission or distribution network
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/50—Controlling the sharing of the out-of-phase component
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/222—Demand response systems, e.g. load shedding, peak shaving

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Abstract

The invention discloses a load recovery double-layer optimization method considering time-varying step length, which comprises the following steps: considering direct current power flow constraint, cold load characteristic constraint and the like, establishing a load recovery upper-layer optimization model by taking the maximum weighted load recovery quantity as an optimization target; because the upper layer model does not consider network loss and reactive power output, and the direct current power flow calculation has errors, the alternating current power flow constraint, the node voltage safety constraint and the like are considered, and the load recovery lower layer optimization model is established by taking the shortest current time step load recovery step length as an optimization target; modeling is carried out on AMPL optimization software, solvers CPLEX and SNOPT are called to carry out iterative solution, and the optimal load recovery scheme under the current time-step shortest load recovery step length is obtained. The method can effectively obtain the optimal load recovery scheme and the shortest load recovery duration time in different power system running states, thereby improving the speed of actual power system load recovery and shortening the power failure time of the power system.

Description

Load recovery double-layer optimization method considering time-varying step length
Technical Field
The invention relates to the field of power system recovery, in particular to a double-layer optimization method under consideration of grid-load cooperative recovery optimization in load recovery.
Background
Load recovery is a multi-time-step process, most researches adopt fixed time to model the load recovery process, and the main defect is that the uncertainty of parameters can influence the optimization result of the fixed time and even lead to the reformulation of a recovery scheme. In the initial stage of load recovery, although the main grid frame of the power system is recovered, a part of lines are not recovered, and a load recovery scheme which is made by ignoring the unrecovered lines may fail in the implementation process, so that the recovery time is prolonged, and even a power failure is caused again. In addition, the cold load effect during the load recovery process may increase the risk of safe and stable operation of the power system. Therefore, how to comprehensively solve the single-time-step load recovery optimization problem and the cold load modeling problem in the network-load cooperative recovery optimization process needs to be further explored.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides a load recovery double-layer optimization method considering time-varying step length, so that the influence of cold load characteristics in the recovery process can be considered, and the optimal load recovery scheme under the shortest load recovery duration is obtained aiming at different running states in the recovery process of the power system, so that the load recovery speed of the actual power system is increased, and the power failure time of the power system is shortened.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
the invention relates to a load recovery double-layer optimization method considering time-varying step length, which is characterized by being applied to a load recovery stage of a power system, wherein the power system comprises a wind storage combined system, load nodes considering cold load characteristics, unit nodes and power transmission lines among the nodes, a linearized cold load characteristic curve is established according to the load capacity of each load node, and the load recovery double-layer optimization method is carried out according to the following steps:
step one, establishing a load recovery upper layer optimization model based on direct current power flow:
step 1.1, defining an objective function for maximizing the weighted load quantity under the kth time step by using an equation (1):
Figure GDA0003778670340000011
in formula (1): omega B Is a set of all nodes in the power system;
Figure GDA0003778670340000012
a set of load points to be recovered on the ith load node at the kth time step; w is a i,h The weight of the h load point on the ith load node is obtained;
Figure GDA0003778670340000013
the active load demand of the h load point on the ith load node is obtained; c. C i,h,k The cold load coefficient of the h load point on the ith load node at the kth time step; z is a radical of formula i,h,k Is the recovery state of the h load point on the ith load node at the k time step, if z is i,h,k When z is 1, the h-th load point is recovered i,h,k 0; indicating that the h load point is not restored;
step 1.2, establishing direct current power flow constraint by using the formula (2) -formula (7):
Figure GDA0003778670340000021
Figure GDA0003778670340000022
Figure GDA0003778670340000023
Figure GDA0003778670340000024
Figure GDA0003778670340000025
Figure GDA0003778670340000026
formula (2) to formula (7):
Figure GDA00037786703400000224
the maximum power angle difference of the power transmission line between the ith node and the jth node is represented; s ij,k The recovery state of the power transmission line between the ith node and the jth node at the kth time step is shown, if s ij,k 1, denotes the kth time stepRecovering the power transmission line between the lower ith node and the jth node if s ij,k When the transmission line is not recovered, the transmission line between the ith node and the jth node is not recovered; delta i,k The phase angle of the ith node in the kth time step; x is the number of ij Representing the reactance of the transmission line between the ith node and the jth node;
Figure GDA0003778670340000027
the active power transmitted on the transmission line between the ith node and the jth node at the kth time step;
Figure GDA0003778670340000028
the set of the transmission lines to be recovered at the kth time step;
Figure GDA0003778670340000029
the set of the recovered transmission lines at the k-1 time step;
Figure GDA00037786703400000210
the maximum active power which can be transmitted on the power transmission line between the ith node and the jth node is obtained;
Figure GDA00037786703400000211
active power output scheduled by the wind storage combined system on the ith node at the kth time step;
Figure GDA00037786703400000212
the active power output by the ith unit node at the kth time step; omega L Representing a set of transmission lines;
Figure GDA00037786703400000213
the active load demand on the ith load node at the kth time step;
Figure GDA00037786703400000214
is the maximum phase angle at the ith node;
step 1.3, establishing a cold load constraint by using an equation (8) to an equation (14):
Figure GDA00037786703400000215
Figure GDA00037786703400000216
Figure GDA00037786703400000217
Figure GDA00037786703400000218
Figure GDA00037786703400000219
Figure GDA00037786703400000220
Figure GDA00037786703400000221
formula (8) -formula (14):
Figure GDA00037786703400000222
considering the active load demand after the cold load characteristic for the h load point on the ith load node at the kth time step;
Figure GDA00037786703400000223
the maximum active load after the cold load characteristic is considered for the h load point on the ith load node; lambda [ alpha ] i,h,α The slope of a linear cold load characteristic curve of an h load point on an ith load node in an alpha section; zeta i,h,α,k Is an auxiliary variable and represents the recovery time of the h load point on the i load node at the k time step in the interval
Figure GDA0003778670340000031
The length of time of the inner;
Figure GDA0003778670340000032
an alpha segment point of the linearized cooling load characteristic curve representing the h load point on the i load node;
Figure GDA0003778670340000033
an α -1 th segment point of the linearized cooling load characteristic curve representing an h-th load point at the i-th load node;
Figure GDA0003778670340000034
representing the set of restored load points at time step k-1; t is t i,h,k-1 The time that the h load point on the ith load node is recovered at the k-1 time step is represented; Δ t k,sc Representing the load recovery duration of the load recovery upper-layer optimization model at the kth time step; n represents the number of segmentation points of the linearized cold load characteristic curve; v. of i,h,α,k The recovery time length of the h load point on the i load node at the k time step is represented by a Boolean variable, and whether the recovery time length is in the alpha section of the linear cooling load characteristic curve or not is represented;
step 1.4, establishing unit output constraint by using the formula (15) to the formula (17):
Figure GDA0003778670340000035
Figure GDA0003778670340000036
Figure GDA0003778670340000037
formula (15) to formula (17):
Figure GDA0003778670340000038
to representThe maximum active power allowed to be output by the g-th unit node at the k-th time step;
Figure GDA0003778670340000039
the active power output by the g unit node at the k-1 time step; r is g The grade climbing rate of the g-th unit node is obtained;
Figure GDA00037786703400000310
the maximum active power allowed to be output for the g-th unit node; omega G The method comprises the steps of (1) collecting unit nodes;
Figure GDA00037786703400000311
representing the minimum active power allowed to be output by the g-th unit node at the k-th time step;
Figure GDA00037786703400000312
the minimum active power allowed to be output for the g-th unit node;
Figure GDA00037786703400000313
the active power actually output by the g-th unit node at the k-th time step;
step 1.5, establishing an optimal load input amount constraint by using an equation (18):
Figure GDA00037786703400000314
in formula (18):
Figure GDA00037786703400000315
the maximum load input allowed by the power system at the kth time step;
step 1.6, establishing unit standby constraint by using the formula (19) to the formula (20):
Figure GDA00037786703400000316
Figure GDA00037786703400000317
formula (19) to formula (20):
Figure GDA00037786703400000318
the reserve capacity of the g unit node at the k time step; rho g Representing the ratio of the reserve capacity of the g-th unit node in the total active output of the unit node;
step 1.7, establishing recovery state constraint by using the formula (21) to the formula (24):
Figure GDA00037786703400000319
Figure GDA00037786703400000320
Figure GDA0003778670340000041
Figure GDA0003778670340000042
formula (20) to formula (24): y is i,k Indicating the recovery state of the ith node at the kth time step if y i,k 1 means that the ith node has recovered, if y i,k 0, which means that the ith node is not recovered; ε is a constant;
Figure GDA0003778670340000043
the maximum load point number on the ith node is obtained;
step 1.8, establishing wind-storage combined system dispatching output constraint by using a formula (25):
Figure GDA0003778670340000044
in formula (25):
Figure GDA0003778670340000045
the minimum active power output of the wind storage combined system accessed by the ith node at the kth time step;
Figure GDA0003778670340000046
the dispatching output of the wind storage combined system accessed by the ith node at the kth time step is obtained;
Figure GDA0003778670340000047
the maximum active power output of the wind storage combined system accessed by the ith node at the kth time step; omega B,W The method comprises the steps of collecting nodes of an accessed wind storage combined system;
step 1.9, the objective function shown in the formula (1) and the constraint conditions shown in the formulas (2) to (25) jointly form the load recovery upper-layer optimization model;
step two, establishing a load recovery lower-layer optimization model based on alternating current power flow:
step 2.1, defining an objective function that minimizes the load recovery duration of the kth time step using equation (26):
min△t k,xc (26)
in formula (26): Δ t k,xc Load recovery duration for the load recovery underlying optimization model;
step 2.2, establishing an alternating current power flow constraint by using the formula (27) to the formula (28):
Figure GDA0003778670340000048
Figure GDA0003778670340000049
formula (27) to formula (28): u shape i,k The voltage value of the ith node at the kth time step is shown;
Figure GDA00037786703400000410
restoring the power transmission line set restored by the upper-layer optimization model for the load at the kth time step; g ij The conductance value of the power transmission line between the ith node and the jth node is obtained; b is ij The susceptance value of the power transmission line between the ith node and the jth node is obtained;
Figure GDA00037786703400000411
the reactive power output of the ith unit node at the kth time step;
Figure GDA00037786703400000412
the reactive load demand on the ith load node at the kth time step;
and 2.3, jointly forming a load constraint considering the cold load characteristic in the load recovery lower-layer optimization model by using the formula (8), the formula (10) -the formula (13) and the formula (29) -the formula (31):
Figure GDA00037786703400000413
Figure GDA00037786703400000414
Figure GDA00037786703400000415
formula (29) -formula (31):
Figure GDA0003778670340000051
restoring the node set restored by the upper-layer optimization model for the load at the kth time step;
Figure GDA0003778670340000052
a set of load points on the ith load node;
step 2.4, establishing a unit output constraint by using the formula (32) -the formula (36):
Figure GDA0003778670340000053
Figure GDA0003778670340000054
Figure GDA0003778670340000055
Figure GDA0003778670340000056
Figure GDA0003778670340000057
formula (32) -formula (36):
Figure GDA0003778670340000058
representing the minimum reactive power allowed to be output by the g unit node;
Figure GDA0003778670340000059
the real output reactive power of the g-th unit node in the k-th time step;
Figure GDA00037786703400000510
representing the maximum reactive power allowed to be output by the g-th unit node;
step 2.5, establishing node voltage constraint by using the formula (37):
Figure GDA00037786703400000511
and 2.6, establishing a current step size correlation constraint by using an equation (38):
-△t min ≤△t k,xc -△t k,sc ≤△t min (38)
in formula (38): Δ t min Is a loadRecovering the minimum difference of the recovery duration between the upper-layer optimization model and the lower-layer optimization model for load recovery;
step 2.7, the objective function shown in the formula (26) and the formula (8), the formula (10) -the formula (13), the formula (19), the formula (20), the formula (25) and the formula (27) -the formula (38) jointly form the load recovery lower layer optimization model;
step three, solving a load recovery double-layer optimization model considering time-varying step length:
step 3.1, inputting initial data of the power system in the load recovery stage, wherein the initial data comprises the following steps: the output of the unit node, the load quantity of the recovered/unrecovered load point and the initial running state of the power system; and initializing k to 1;
step 3.2, solving a load recovery double-layer optimization model considering the step length of the time-varying step under the kth time step;
step 3.2.1, solving the load recovery upper layer optimization model by utilizing a solver CPLEX to obtain an optimal load recovery result at the kth time step, wherein the method comprises the following steps: the load point is recovered, and the transmission line is recovered;
step 3.2.2, transmitting the optimal load recovery scheme to the load recovery lower-layer optimization model, and solving the load recovery lower-layer optimization model by using a non-linear solver SNOPT to obtain the shortest load recovery duration and the optimal unit output at the kth time step;
step 3.2.3, judging whether the load recovery double-layer optimization model at the kth time step meets the iteration termination condition, if so, executing the step 3.3, otherwise, after transmitting the optimal load recovery duration at the kth time step to the load recovery upper-layer optimization model, returning to the step 3.2.1; wherein the iteration termination condition is | Δ t k,sc -Δt k,xc |≤Δt min And the load recovery amount under the current time step is not changed any more;
step 3.3, outputting the optimal load recovery scheme of the kth time step, comprising: recovering the load point, the power transmission line, the duration and the output of the optimal unit;
and 3.4, judging whether all load points of the power system are recovered at the kth time step, if so, outputting an optimal load recovery scheme from the 1 st time step to the kth time step, otherwise, updating the running state of the power system, and returning to the step 3.2 after k +1 is assigned with k.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention considers the optimal load recovery schemes under different running states in the recovery process of the power system, provides a load recovery optimization model based on single time step, solves the problem that the power failure time of the power system is prolonged by adopting fixed time step length in the formulation process of the load recovery scheme of the power system, and improves the recovery speed of the power system.
2. The invention provides a load recovery double-layer optimization framework, which effectively reduces the calculated amount, avoids the multi-objective optimization problem, reduces the difficulty of making a load recovery scheme of an electric power system and provides a new research idea for the load recovery problem of the electric power system.
3. The invention provides the linear constraint of the cold load characteristics, is suitable for a load recovery optimization method considering time-varying step length, solves the problem that the cold load constraint considering the time-varying characteristics is difficult to apply to the time-varying step optimization problem, and improves the accuracy of the actual load recovery scheme of the power system.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a flow chart of the method of the present invention.
Detailed Description
In this embodiment, as shown in fig. 1, a load recovery double-layer optimization method considering a time-varying step length is applied to a load recovery stage of an electric power system, where the electric power system includes a wind power storage combined system, load nodes considering a cold load characteristic, a unit node, and an electric transmission line between the nodes, and a linearized cold load characteristic curve is established according to a load amount of each load node, and the method includes the main steps of: considering direct current power flow constraint, cold load characteristic constraint and the like, establishing a load recovery upper-layer optimization model by taking the maximum weighted load recovery quantity as an optimization target; because the upper layer model does not consider network loss and reactive power output and the direct current power flow calculation has errors, the alternating current power flow constraint, the node voltage safety constraint and the like are considered, and the load recovery lower layer optimization model is established by taking the current time step shortest load recovery step length as an optimization target; modeling is carried out on AMPL optimization software, solvers CPLEX, SNOPT/MINOS are called to carry out iterative solution, and the optimal load recovery scheme under the current time-step shortest load recovery step length is obtained. Specifically, the method comprises the following steps:
step one, establishing a load recovery upper-layer optimization model based on direct current power flow:
step 1.1, an objective function for maximizing the weighted load amount at the kth time step is defined by using a formula (39):
Figure GDA0003778670340000071
in formula (41): omega B Is a set of all nodes in the power system;
Figure GDA0003778670340000072
a set of load points to be recovered on the ith load node at the kth time step; w is a i,h The weight of the h load point on the ith load node is obtained;
Figure GDA0003778670340000073
the active load demand of the h load point on the ith load node is obtained; c. C i,h,k The cold load coefficient of the h load point on the ith load node at the kth time step; z is a radical of formula i,h,k The recovery state of the h load point on the ith load node at the k time step, if z i,h,k 1, denotes the h-th load point recovery, if z i,h,k 0; indicating that the h load point is not restored;
step 1.2, establishing direct current power flow constraint by using the formula (2) -formula (7):
Figure GDA0003778670340000074
Figure GDA0003778670340000075
Figure GDA0003778670340000076
Figure GDA0003778670340000077
Figure GDA0003778670340000078
Figure GDA0003778670340000079
the formula (2) and the formula (3) respectively represent direct current flow expressions of the kth time step to-be-recovered power transmission line and the kth-1 time step recovered power transmission line; the formula (4) and the formula (5) respectively represent the maximum/minimum power flow constraint of the power transmission line to be recovered at the kth time step and the recovered power transmission line at the kth-1 time step; equation (6) represents the nodal balance equation; equation (7) represents the maximum/minimum phase angle constraint for the node;
formula (2) to formula (7):
Figure GDA00037786703400000719
the maximum power angle difference of the power transmission line between the ith node and the jth node is represented; s ij,k The recovery state of the power transmission line between the ith node and the jth node at the kth time step is shown, if s ij,k 1, the power transmission line between the ith node and the jth node is recovered at the kth time step, if s ij,k When the transmission line is not recovered, the transmission line between the ith node and the jth node is not recovered; delta i,k The phase angle of the ith node in the kth time step; x is a radical of a fluorine atom ij Representing the reactance of the transmission line between the ith node and the jth node；
Figure GDA00037786703400000710
The active power transmitted on the transmission line between the ith node and the jth node at the kth time step;
Figure GDA00037786703400000711
the set of the transmission lines to be recovered at the kth time step;
Figure GDA00037786703400000712
the set of the recovered transmission lines at the k-1 time step;
Figure GDA00037786703400000713
the maximum active power which can be transmitted on the power transmission line between the ith node and the jth node is obtained;
Figure GDA00037786703400000714
active power output scheduled by the wind storage combined system on the ith node at the kth time step;
Figure GDA00037786703400000715
the active power output by the ith unit node at the kth time step; omega L Representing a set of transmission lines;
Figure GDA00037786703400000716
the active load demand on the ith load node at the kth time step;
Figure GDA00037786703400000717
is the maximum phase angle at the ith node;
step 1.3, establishing a cold load constraint by using an equation (8) to an equation (14):
Figure GDA00037786703400000718
Figure GDA0003778670340000081
Figure GDA0003778670340000082
Figure GDA0003778670340000083
Figure GDA0003778670340000084
Figure GDA0003778670340000085
Figure GDA0003778670340000086
equation (8) represents that the active load demand considering the cold load characteristic is equal to the maximum active load capacity minus the load decay amount; the formula (9) shows that the sum of the recovered time of the load point h on the kth-1 time step node i and the load recovery time of the kth time step is equal to the load recovery ending time of the kth time step, and the value is the sum of the auxiliary variables; equation (10) to equation (13) indicate that the recovery time of the load point h on the node i is within a certain period of the cold load curve; equation (14) represents that the active load demand of the kth time step node i is equal to the amount of the recovered load point of the kth time step-1 plus the active load demand of the kth time step optimized recovery multiplied by the cold load coefficient;
formula (8) -formula (14):
Figure GDA0003778670340000087
considering the active load demand after the cold load characteristic for the h load point on the ith load node at the kth time step;
Figure GDA0003778670340000088
considering the cold load for the h load point on the i load nodeMaximum active load after the characteristic; lambda [ alpha ] i,h,α The slope of a linear cold load characteristic curve of an h load point on an ith load node in an alpha section; zeta i,h,α,k Is an auxiliary variable and represents the recovery time of the h load point on the i load node at the k time step in the interval
Figure GDA0003778670340000089
The length of time of the inner;
Figure GDA00037786703400000810
an alpha segment point of the linearized cooling load characteristic curve representing the h load point on the i load node;
Figure GDA00037786703400000811
an α -1 th segment point of the linearized cooling load characteristic curve representing an h-th load point at the i-th load node;
Figure GDA00037786703400000812
representing the set of restored load points at the k-1 time step; t is t i,h,k -1 represents the time that the h load point on the i load node has been restored at the k-1 time step; Δ t k,sc Representing the load recovery duration of the load recovery upper-layer optimization model at the kth time step; n represents the number of segmentation points of the linearized cold load characteristic curve; v. of i,h,α,k The recovery time length of the h load point on the i load node at the k time step is represented by a Boolean variable, and whether the recovery time length is in the alpha section of the linear cooling load characteristic curve or not is represented;
step 1.4, establishing unit output constraint by using the formula (15) to the formula (17):
Figure GDA00037786703400000813
Figure GDA00037786703400000814
Figure GDA00037786703400000815
the formula (15) and the formula (16) are used for calculating the maximum/minimum active output of the kth time-stepping unit g; the formula (17) is used for restricting the active output of the kth time step unit g within the range of the maximum/minimum threshold value of the k time step unit g;
formula (15) to formula (17):
Figure GDA0003778670340000091
representing the maximum active power allowed to be output by the g-th unit node at the k-th time step;
Figure GDA0003778670340000092
the active power output by the g unit node at the k-1 time step; r is g The grade climbing rate of the g unit node is obtained;
Figure GDA0003778670340000093
the maximum active power allowed to be output for the g-th unit node; omega G The method comprises the steps of (1) collecting unit nodes;
Figure GDA0003778670340000094
representing the minimum active power allowed to be output by the g-th unit node at the k-th time step;
Figure GDA0003778670340000095
the minimum active power allowed to be output for the g-th unit node;
Figure GDA0003778670340000096
the active power actually output by the g-th unit node at the k-th time step;
step 1.5, establishing an optimal load input amount constraint by using an equation (18):
Figure GDA0003778670340000097
in formula (18):
Figure GDA0003778670340000098
the maximum load input allowed by the power system at the kth time step; the expression (18) shows that the sum of the recovered load quantities of the kth time step does not exceed the maximum load input quantity allowed by the system, and is used for limiting the stability of the frequency in the recovery process;
step 1.6, establishing unit standby constraint by using the formula (19) to the formula (20):
Figure GDA0003778670340000099
Figure GDA00037786703400000910
formula (19) shows that the sum of the active output and the reserve capacity of the kth time-step unit g does not exceed the maximum active output of the current time-step unit; the formula (20) is used for restricting the reserve capacity of the kth time step unit g;
formula (19) -formula (20):
Figure GDA00037786703400000911
the reserve capacity of the g unit node at the k time step; rho g Representing the ratio of the reserve capacity of the g-th unit node in the total active output of the unit node;
step 1.7, establishing recovery state constraint by using the formula (21) to the formula (22):
Figure GDA00037786703400000912
Figure GDA00037786703400000913
Figure GDA00037786703400000914
Figure GDA00037786703400000915
formula (20) -formula (23) indicate that the necessary condition for recovering the node i in the kth time step is that at least one power transmission line connected with the node i is recovered or at least one load point on the node i is recovered; equation (24) represents recovering only one transmission line per time step;
formula (21) to formula (24): y is i,k Indicating the recovery state of the ith node at the kth time step if y i,k 1, indicates that the ith node has recovered, if y i,k 0, which means that the ith node is not recovered; ε is a constant;
Figure GDA00037786703400000916
the maximum load point number on the ith node is obtained;
step 1.8, establishing wind storage combined system dispatching output constraint by using a formula (25):
Figure GDA00037786703400000917
in formula (25):
Figure GDA00037786703400000918
the minimum active power output of the wind storage combined system accessed by the ith node at the kth time step;
Figure GDA00037786703400000919
the dispatching output of the wind storage combined system accessed by the ith node at the kth time step is obtained;
Figure GDA0003778670340000101
the maximum active power output of the wind storage combined system accessed by the ith node at the kth time step; omega B,W The method comprises the steps of collecting nodes of an accessed wind storage combined system;
step 1.9, a target function shown in a formula (1) and constraint conditions shown in formulas (2) and (25) jointly form the load recovery upper-layer optimization model, and the optimal load recovery scheme under the current step length can be obtained by solving with a fixed time step length;
step two, establishing a load recovery lower-layer optimization model based on the alternating current power flow:
step 2.1, defining an objective function that minimizes the load recovery duration of the kth time step using equation (26):
min△t k,xc (66)
in formula (26): Δ t k,xc Load recovery duration for the load recovery underlying optimization model;
step 2.2, establishing an alternating current power flow constraint by using the formula (27) to the formula (28):
Figure GDA0003778670340000102
Figure GDA0003778670340000103
expressions (27) and (28) represent alternating current power flow expressions of a kth time step node i, wherein the expression (27) considers the scheduling output of the kth time step wind storage combined system;
formula (27) to formula (28): u shape i,k The voltage value of the ith node at the kth time step is shown;
Figure GDA0003778670340000104
restoring the power transmission line set restored by the upper-layer optimization model for the load at the kth time step; g ij The conductance value of the power transmission line between the ith node and the jth node is obtained; b is ij The susceptance value of the power transmission line between the ith node and the jth node is obtained;
Figure GDA0003778670340000105
the reactive power output of the ith unit node at the kth time step;
Figure GDA0003778670340000106
the reactive load demand on the ith load node at the kth time step;
and 2.3, jointly forming a load constraint considering the cold load characteristic in the load recovery lower-layer optimization model by using the formula (8), the formula (10) -the formula (13) and the formula (29) -the formula (31):
Figure GDA0003778670340000107
Figure GDA0003778670340000108
Figure GDA0003778670340000109
equation (29) shows that the load amount recovered by the load point h at the kth time step node i is equal to the maximum active load amount thereof due to the cold load characteristic; the formula (30) has the same meaning as the formula (9) except that the load recovery duration in the formula (30) is a variable; equation (31) represents that the active load demand of the node i is equal to the active load demand of all load points on the node i;
formula (29) -formula (31):
Figure GDA00037786703400001010
restoring the node set restored by the upper-layer optimization model for the load at the kth time step;
Figure GDA00037786703400001011
a set of load points on the ith load node;
step 2.4, establishing a unit output constraint by using the formula (32) -formula (36):
Figure GDA0003778670340000111
Figure GDA0003778670340000112
Figure GDA0003778670340000113
Figure GDA0003778670340000114
Figure GDA0003778670340000115
since the unit output and the load recovery duration in the load recovery underlying model are both variable, it is necessary to perform linearization processing on equations (15) and (16). The equations (32) and (33) are used for constraining the minimum active output of the kth time step unit g; equations (34) and (35) are used for constraining the maximum active output of the kth time step unit g; equation (36) is used to constrain the reactive power output of the kth time step group g within its maximum/minimum threshold range;
formula (32) -formula (36):
Figure GDA0003778670340000116
the minimum reactive power which is allowed to be output by the g-th unit node is represented;
Figure GDA0003778670340000117
the real output reactive power of the g-th unit node in the k-th time step;
Figure GDA0003778670340000118
representing the maximum reactive power allowed to be output by the g-th unit node;
step 2.5, establishing node voltage constraint by using an equation (37):
Figure GDA0003778670340000119
equation (37) indicates that if node i recovers at the kth time step, the voltage should be within its threshold range, otherwise the voltage at node i is 0; step 2.6, establishing the current step size related constraint by using the formula (38):
-△t min ≤△t k,xc -△t k,sc ≤△t min (78)
in formula (38): Δ t min The minimum difference of the recovery duration between the load recovery upper-layer optimization model and the load recovery lower-layer optimization model is obtained; the formula (38) is used for restricting the step length of the upper/lower layer model load recovery time step not to exceed the acceptable range;
step 2.7, the load recovery lower-layer optimization model is formed by the objective function shown in the formula (26) and the formula (8), the formula (10) -the formula (13), the formula (19), the formula (20), the formula (25) and the formula (27) -the formula (38), and the optimal load recovery duration under the current load recovery scheme is solved and obtained on the basis of the optimal load recovery scheme solved by the load recovery upper-layer optimization model;
step three, solving the load recovery double-layer optimization model considering the time-varying step length, wherein the solving process is shown as the figure 2:
step 3.1, inputting initial data of the power system in the load recovery stage, wherein the initial data comprises the following steps: the output of the unit node, the load quantity of the recovered/unrecovered load point and the initial running state of the power system; and initializing k to 1;
step 3.2, solving a load recovery double-layer optimization model considering the step length of the time-varying step under the kth time step;
step 3.2.1, solving the load recovery upper layer optimization model by utilizing a solver CPLEX to obtain an optimal load recovery result at the kth time step, wherein the method comprises the following steps: the load point is recovered, and the transmission line is recovered;
step 3.2.2, transmitting the optimal load recovery scheme to the load recovery lower-layer optimization model, and solving the load recovery lower-layer optimization model by using a nonlinear solver SNOPT to obtain the shortest load recovery duration and the output of the optimal unit at the kth time step;
step 3.2.3, judging whether the load recovery double-layer optimization model at the kth time step meets the iteration termination condition, if so, executing the step 3.3, otherwise, after transmitting the optimal load recovery duration at the kth time step to the load recovery upper-layer optimization model, returning to the step 3.2.1; wherein the iteration termination stripThe component is | Δ t k,sc -Δt k,xc |≤Δt min And the load recovery amount under the current time step is not changed any more;
step 3.3, outputting the optimal load recovery scheme of the kth time step, comprising: recovering the load point, the power transmission line, the duration and the output of the optimal unit;
and 3.4, judging whether all load points of the power system are recovered at the kth time step, if so, outputting an optimal load recovery scheme from the 1 st time step to the kth time step, otherwise, updating the running state of the power system, and returning to the step 3.2 after k +1 is assigned with k.

Claims (1)

1. A load recovery double-layer optimization method considering time-varying step length is characterized by being applied to a load recovery stage of a power system, wherein the power system comprises a wind storage combined system, load nodes considering cold load characteristics, unit nodes and power transmission lines among the nodes, a linear cold load characteristic curve is established according to the load capacity of each load node, and the load recovery double-layer optimization method is carried out according to the following steps:
step one, establishing a load recovery upper-layer optimization model based on direct current power flow:
step 1.1, defining an objective function for maximizing the weighted load quantity under the kth time step by using an equation (1):
Figure FDA0003778670330000011
in formula (1): omega B Is a set of all nodes in the power system; Ω D, C i, k is the set of load points to be recovered on the ith load node at the kth time step; w is a i,h The weight of the h load point on the ith load node is obtained; pd i, h is the active load demand of the h load point on the i load node; c. C i,h,k The cold load coefficient of the h load point on the ith load node at the kth time step; z is a radical of i,h,k Is the recovery state of the h load point on the ith load node at the k time step, if z is i,h,k 1 denotes the firsth load points are recovered, if z i,h,k 0; indicating that the h-th load point is not recovered;
step 1.2, establishing direct current power flow constraint by using the formula (2) to the formula (7):
Figure FDA0003778670330000012
Figure FDA0003778670330000013
Figure FDA0003778670330000014
Figure FDA0003778670330000015
Figure FDA0003778670330000016
Figure FDA0003778670330000017
formula (2) to formula (7): θ max ij represents the maximum power angle difference of the power transmission line between the ith node and the jth node; s ij,k The recovery state of the power transmission line between the ith node and the jth node at the kth time step is shown, if s ij,k 1, the power transmission line between the ith node and the jth node is recovered at the kth time step, if s ij,k When the transmission line is not recovered, the transmission line between the ith node and the jth node is not recovered; delta i,k The phase angle of the ith node in the kth time step is obtained; x is the number of ij Representing the reactance of the transmission line between the ith node and the jth node; PL ij, k is the power transmission line between the ith node and the jth node at the kth time stepThe active power of the transmission; Ω L, C k is a set of transmission lines to be restored at the kth time step; omega L, R k-1 is the set of recovered transmission lines at the k-1 time step; PL, max ij is the maximum active power which can be transmitted on the power transmission line between the ith node and the jth node; PWESi, k is the active power output scheduled by the wind storage combined system on the ith node at the kth time step; PG i, k is the active power output by the ith unit node at the kth time step; omega L Representing a set of transmission lines; PD i, k is the active load demand on the ith load node at the kth time step; δ max i is the maximum phase angle at the ith node;
step 1.3, establishing a cold load constraint by using an equation (8) to an equation (14):
Figure FDA0003778670330000021
Figure FDA0003778670330000022
Figure FDA0003778670330000023
Figure FDA0003778670330000024
Figure FDA0003778670330000025
Figure FDA0003778670330000026
Figure FDA0003778670330000027
formula (9) to formula (15): pd i, h and k are active load requirements of the ith load point on the ith load node in the kth time step after the cold load characteristics are considered; pmax i, h is the maximum active load of the ith load point on the ith load node after the cold load characteristic is considered; lambda [ alpha ] i,h,α The slope of a linear cold load characteristic curve of an h load point on an ith load node in an alpha section; zeta i,h,α,k Is an auxiliary variable and indicates that the recovery time of the h load point on the i load node at the k time step is in the interval [ tadd i, h, a-tadd i, h, a-1]The length of time of the inner; tadd i, h, a represents the alpha segment point of the linearized cooling load characteristic curve of the h load point on the i load node; tadd i, h, a-1 represents the alpha-1 segment point of the linearized cold load characteristic curve of the h load point on the i load node; Ω D, R i, k-1 represents the set of restored load points at time step k-1; t is t i,h,k-1 The time that the h load point on the ith load node is recovered at the k-1 time step is represented; Δ t k,sc Representing the load recovery duration of the load recovery upper-layer optimization model at the kth time step; n represents the number of segmentation points of the linearized cold load characteristic curve; v. of i,h,α,k The recovery time length of the h load point on the i load node at the k time step is represented by a Boolean variable, and whether the recovery time length is in the alpha section of the linear cooling load characteristic curve or not is represented;
step 1.4, establishing unit output constraint by using the formula (15) to the formula (17):
Figure FDA0003778670330000028
Figure FDA0003778670330000029
Figure FDA00037786703300000210
formula (16) to formula (18): PG (PG)Mg, k represents the maximum active power allowed to be output by the g unit node at the k time step; PG g, k-1 is the active power output by the g unit node at the k-1 time step; r is g The grade climbing rate of the g-th unit node is obtained; PG, max g is the maximum active power allowed to be output by the g-th unit node; omega G The method comprises the steps of (1) collecting unit nodes; PG, m g, k represents the minimum active power allowed to be output by the g-th unit node at the k-th time step; PG, min g is the minimum active power allowed to be output by the g-th unit node; PG g, k is the active power actually output by the g unit node at the k time step;
step 1.5, establishing an optimal load input amount constraint by using an equation (18):
Figure FDA0003778670330000031
in formula (19): Δ Pmax k is the maximum load input allowed by the power system at the kth time step;
step 1.6, establishing unit standby constraint by using the formula (19) to the formula (20):
Figure FDA0003778670330000032
Figure FDA0003778670330000033
formula (20) to formula (21): PR g, k is the spare capacity of the g unit node at the k time step; rho g Representing the ratio of the reserve capacity of the g-th unit node in the total active output of the unit node;
step 1.7, establishing recovery state constraint by using the formula (21) to the formula (24):
Figure FDA0003778670330000034
Figure FDA0003778670330000035
Figure FDA0003778670330000036
Figure FDA0003778670330000037
formula (22) to formula (25): y is i,k Indicating the recovery state of the ith node at the kth time step if y i,k 1, indicates that the ith node has recovered, if y i,k 0, which means that the ith node is not recovered; ε is a constant; nmax i is the maximum load point number on the ith node;
step 1.8, establishing wind storage combined system dispatching output constraint by using a formula (25):
Figure FDA0003778670330000038
in formula (26): PWES, min i, k is the minimum active power output of the wind storage combined system accessed by the ith node at the kth time step; PWESi, k is the dispatching output of the wind power storage combined system accessed by the ith node at the kth time step; PWES, max i, k is the maximum active power output of the wind storage combined system accessed by the ith node at the kth time step; omega B,W The method comprises the steps of collecting nodes of an accessed wind storage combined system;
step 1.9, the objective function shown in the formula (1) and the constraint conditions shown in the formulas (2) to (26) jointly form the load recovery upper-layer optimization model;
step two, establishing a load recovery lower-layer optimization model based on the alternating current power flow:
step 2.1, defining an objective function that minimizes the load recovery duration of the kth time step using equation (26):
min△t k,xc (26) in formula (27): Δ t k,xc Load recovery duration for the load recovery underlying optimization model;
step 2.2, establishing an alternating current power flow constraint by using the formula (27) to the formula (28):
Figure FDA0003778670330000041
Figure FDA0003778670330000042
formula (28) to formula (29): u shape i,k The voltage value of the ith node at the kth time step is shown; omega L, SC k is the set of power transmission lines recovered by the load recovery upper-layer optimization model at the kth time step; g ij The conductance value of the power transmission line between the ith node and the jth node is obtained; b ij The susceptance value of the power transmission line between the ith node and the jth node is obtained; QG i, k is reactive power output on the ith unit node at the kth time step; QDs i, k are reactive load requirements on the ith load node in the kth time step;
and 2.3, jointly forming a load constraint considering the cold load characteristic in the load recovery lower-layer optimization model by using the formula (9), the formula (11) -the formula (14) and the formula (29) -the formula (31):
Figure FDA0003778670330000043
Figure FDA0003778670330000044
Figure FDA0003778670330000045
formula (30) to formula (32): omega B, SC k is a node set recovered by the load recovery upper-layer optimization model at the kth time step; Ω D i is the set of load points on the ith load node;
step 2.4, establishing a unit output constraint by using the formula (32) -the formula (36):
Figure FDA0003778670330000046
Figure FDA0003778670330000047
Figure FDA0003778670330000048
Figure FDA0003778670330000049
Figure FDA00037786703300000410
formula (33) -formula (37): QG, min g represents the minimum reactive power allowed to be output by the g-th unit node; QG g, k is the reactive power actually output by the g unit node at the k time step; QG, max g represents the maximum reactive power allowed to be output by the g-th unit node;
step 2.5, establishing node voltage constraint by using the formula (37):
Figure FDA00037786703300000411
and 2.6, establishing a current step size correlation constraint by using an equation (38):
-△t min ≤△t k,xc -△t k,sc ≤△t min (38)
in formula (39): Δ t min Optimizing models for upper layers of load recoveryThe minimum difference of the recovery duration time with the lower-layer optimization model of load recovery;
step 2.7, the objective function shown in the formula (27) and the formula (9), the formula (11) -the formula (14), the formula (20), the formula (21), the formula (26) and the formula (28) -the formula (39) jointly form the load recovery lower layer optimization model;
step three, solving a load recovery double-layer optimization model considering the time-varying step length:
step 3.1, inputting initial data of the power system in the load recovery stage, wherein the initial data comprises the following steps: the output of the unit node, the load quantity of the recovered/unrecovered load point and the initial running state of the power system; and initializing k-1;
step 3.2, solving a load recovery double-layer optimization model considering the step length of the time-varying step under the kth time step;
step 3.2.1, solving the load recovery upper layer optimization model by utilizing a solver CPLEX to obtain an optimal load recovery result at the kth time step, wherein the method comprises the following steps: the load point is recovered, and the transmission line is recovered;
step 3.2.2, transmitting the optimal load recovery scheme to the load recovery lower-layer optimization model, and solving the load recovery lower-layer optimization model by using a nonlinear solver SNOPT to obtain the shortest load recovery duration and the output of the optimal unit at the kth time step;
step 3.2.3, judging whether the load recovery double-layer optimization model at the kth time step meets the iteration termination condition, if so, executing the step 3.3, otherwise, after transmitting the optimal load recovery duration at the kth time step to the load recovery upper-layer optimization model, returning to the step 3.2.1; wherein the iteration termination condition is | Δ t k,sc -Δt k,xc |≤Δt min And the load recovery amount under the current time step is not changed any more;
step 3.3, outputting the optimal load recovery scheme of the kth time step, comprising: recovering the load point, the power transmission line, the duration and the output of the optimal unit;
and 3.4, judging whether all load points of the power system are recovered at the kth time step, if so, outputting an optimal load recovery scheme from the 1 st time step to the kth time step, otherwise, updating the running state of the power system, and returning to the step 3.2 after k +1 is assigned with k.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108493930A (en) * 2018-03-30 2018-09-04 国网江苏省电力有限公司 The load restoration two-phase optimization method of meter and wind power integration
AU2020100983A4 (en) * 2019-11-14 2020-07-16 Shandong University Multi-energy complementary system two-stage optimization scheduling method and system considering source-storage-load cooperation
CN112054520A (en) * 2020-09-08 2020-12-08 国网上海市电力公司电力科学研究院 Urban power grid load recovery method considering cold load starting characteristic

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108493930A (en) * 2018-03-30 2018-09-04 国网江苏省电力有限公司 The load restoration two-phase optimization method of meter and wind power integration
AU2020100983A4 (en) * 2019-11-14 2020-07-16 Shandong University Multi-energy complementary system two-stage optimization scheduling method and system considering source-storage-load cooperation
CN112054520A (en) * 2020-09-08 2020-12-08 国网上海市电力公司电力科学研究院 Urban power grid load recovery method considering cold load starting characteristic

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
计及风电条件风险价值的负荷恢复双层优化;赵瑾等;《中国电机工程学报》;20170920(第18期);第5275-5285+5526页 *

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