CN107528314A - The power network robust planing method of safety check is considered under a kind of uncertain environment - Google Patents
The power network robust planing method of safety check is considered under a kind of uncertain environment Download PDFInfo
- Publication number
- CN107528314A CN107528314A CN201710695389.XA CN201710695389A CN107528314A CN 107528314 A CN107528314 A CN 107528314A CN 201710695389 A CN201710695389 A CN 201710695389A CN 107528314 A CN107528314 A CN 107528314A
- Authority
- CN
- China
- Prior art keywords
- formula
- line
- planning
- power grid
- power
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- 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
-
- 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]
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Medicines Containing Antibodies Or Antigens For Use As Internal Diagnostic Agents (AREA)
Abstract
The invention discloses the power network robust planing method that safety check is considered under a kind of uncertain environment.First, electric network information is inputted, establishes under uncertain environment and considers the power network robust plan model of safety check；Secondly, using Benders decomposition methods, power network robust plan model is decomposed into planning primal problem and runs the solution of subproblem；Then, planning primal problem is solved, obtains power network robust programme；Operation solved under normal condition is asked and the operation subproblem under the state of emergency；Finally, the feasibility of verification operation subproblem, obtains final power network robust programme.The present invention compensate for various defects existing for prior art, " N K " safety checks situations and the uncertainty of workload demand and renewable energy power generation, all possible realization of uncertain variables for being adapted in normal condition and in emergency circumstances being defined by uncertainty are considered simultaneously.
Description
Technical Field
The invention belongs to the technical field of power transmission network planning, and particularly relates to a power grid robust planning method considering safety verification in an uncertain environment.
Background
With the annual increase in load demand and power generation, transmission line networks need to be enlarged and strengthened to meet the increasing demand of transmission capacity, ensuring safe operation of the system. Grid robust planning (TEP) is a problem of determining when and where to reinforce an existing line or to establish a new line to provide sufficient transmission capacity and to meet relative reliability standards.
The ability of a power system to withstand accidents is a very important aspect of the reliability of a power system. According to the grid planning Standard (TPL-004-0 [1 ]), as defined by North Electric Reliability Corporation (NERC), if only one element fails ("N-1" emergency), the system should not have a load shedding amount. In the case of K simultaneous failures ("N-K" emergency), the load shedding amount should not be greater than a specified level. These requirements may also be formalized as the "N-K- ε" criterion, where ε represents a vector of load shedding amounts at emergency level K as part of the total load demand.
Although the current research on TEP is numerous, most studies overlook the importance of security verification. Some documents consider the TEP problem of security verification, but they all have a great limitation: all emergencies are explicitly modeled in formulas, and thus a large amount of computational effort is required to check each emergency event in an enumerated manner. To reduce the amount of computation, some documents propose optimized methods to screen out a small fraction of the most severe emergencies and then to check the feasibility of the grid planning in selected emergencies. Recently, some documents propose more advanced methods to determine the worst emergency, model the problem of determining the worst emergency as a Mixed Integer Linear Programming (MILP) problem by a technique of primal-dual algorithm (primal-dual method), and apply Benders' decomposition (BD) to reduce the computational complexity, however, none of these documents consider the load demand and the uncertainty of renewable energy generation, i.e., the TEP problem of safety check is studied in a deterministic manner. However, as the penetration of RES power generation increases rapidly, the proportion of RES power generation to the total power generation increases, and the intermittency of RES power generation causes uncertainty in power generation, which not only has a significant impact on system operation, but also affects the planning strategy of TEP. Much of the literature is devoted to studying TEP problems that take into account the uncertainty of the load demand or the uncertainty of the RES generation or both, and different methods have been proposed to achieve optimal extension planning for various uncertainty factors. Some documents apply scenario-based stochastic planning to calculate expected operating costs under different implementations of load demand and RES power generation, the accuracy of which depends on the number of scenarios, but as the number of scenarios increases, the amount of required calculations also increases rapidly. Some documents employ robust optimization methods (RO), which, in contrast to stochastic programming, attempt to obtain an optimal solution with knowledge of only the range of uncertainty, and not the exact probability distribution of the stochastic variables. Stochastic planning may minimize the total expected cost for all possible scenarios, while RO may minimize the worst-case cost for all possible implementations within a given uncertainty range. However, the relevant literature does not take into account the "N-K" security check condition, and some literature only checks the "N-1" security check condition in two given scenarios: minimum/maximum wind power generation and maximum load demand.
Disclosure of Invention
In order to solve the technical problems in the background art, the invention aims to provide a power grid robust planning method considering safety check in an uncertain environment, make up for various defects in the prior art, and consider the 'N-K' safety check condition and load demand as well as the uncertainty of renewable energy power generation.
In order to achieve the technical purpose, the technical scheme of the invention is as follows:
a power grid robust planning method considering security verification in an uncertain environment comprises the following steps:
(1) Inputting power grid information including power transmission network frames, candidate routes, generators, loads and related parameters of renewable energy, and establishing a power grid robust planning model considering safety verification in an uncertain environment;
(2) Decomposing the power grid robust planning model into a main planning problem and a sub-operation problem by adopting a Benders decomposition method;
(3) Solving a planning main problem to obtain a power grid robust planning scheme; solving the operation subproblem in the normal state and the operation subproblem in the emergency state;
(4) And verifying the feasibility of the operation subproblems, if the feasibility is not feasible, adding the cut sets generated by the operation subproblems into the solution of the planning main problem as constraint conditions, and if the feasibility is feasible, obtaining a final power grid robust planning scheme.
Further, in the step (1), establishing a power grid robust planning model considering safety verification under an uncertain environment considers the uncertainty of load demand and renewable energy power generation:
u∈U＝[U min ,U max ] (4)
in the formula (1), the reaction mixture is,which represents the desired load at the bus bar i,and withRespectively the lower limit and the upper limit of the load of the bus i, and B is the number of the buses; in the formula (2), the reaction mixture is,representing the desired generated power in the renewable energy power generating unit w,and withRespectively representing the lower limit and the upper limit of the generated power in a renewable energy power generation unit W, wherein W is the number of the renewable energy power generation units; in the formula (3), u represents a vector of an uncertain variable, and if there is no load on a certain bus i, the corresponding bus i is subjected toIs not included in u; in the formula (4), U represents all possibilities of all uncertain variables, U min And U max Respectively, the lower limit and the upper limit of the uncertain variable.
Further, in step (1), the robust planning model of the power grid considering the safety check in the uncertain environment is as follows:
s.t.
the equation (5) is an objective function of the robust power grid planning model, and equations (6) to (18) are constraint conditions of the robust power grid planning model; in the formula (5), C e Denotes the investment cost, x, of the line e e The variable is 0-1, when a line e is built, the variable is 1, when the line e is not built, the variable is 0, E is a transmission line set, x is the built state of the line, f is the line power, p is the power sent by a generator, q is the load shedding amount of a certain bus, and theta is the phase angle of the line; in the formula (6), the reaction mixture is,representing the power generated by the generator g in an emergency state s,representing the power transmitted by line e in state s,representing the power emitted by the renewable energy source in an emergency state s,indicating the load of the bus i lost in an emergency state s, G i Set of generating cells representing bus i, E ·i Line set representing bus i as line end, E i· Line set W representing bus i as line start i Set of renewable energy generating units, u, represented on bus i (D,i) Indicates if line i is loaded, u (D,i) As elements in a vector uIf line i is not loaded, then u (D,i) Is 0; in the formula (7), B e Is the susceptance of the line e,the phase angle at the beginning of the line e in the emergency state s,is the phase angle of the end of the line e in the emergency state s, M e Is a constant integer value of the line e,is a variable of 0 to 1, is 1 when the line e is in a fault state in the emergency state s, and is 0 otherwise; in the formula (9), the reaction mixture is,represents the maximum transmission capacity of line e in emergency state s; in the formula (10), the reaction mixture is,is the maximum capacity of the generator g; in the formula (11), σ is the minimum utilization level of the renewable energy power generation, u (W,w) Representing the w-th renewable energy generating unit, S, in vector u 0 Indicating that 0 faults occurred; in the formula (12), S \ S 0 Indicates that the other failures except for 0 failures occurred, and in equation (14), ε <s> Indicating the proportion of load, subscript, that can be cut off in a given emergency state s<s&The number of the equipment faults is shown; in formula (15), E 0 Indicating an already existing set of lines; in the formula (16), E \ E 0 Indicates removal of E 0 An outer set of transmission lines; in the formula (17), the compound represented by the formula (I),<u>, representing the size of the vector u,in the formula (18), Γ is an uncertainty, and its value varies from 0 to 1.
Further, in step (2), the planning master question is as follows:
s.t.
formula (15), (16)
And (3) obtaining a power grid robust planning scheme by performing iterative solution on the formula (21) by taking the formula (21) as an objective function of a planning main problem and taking the formulas (15) and (16) as constraint conditions.
Further, in the step (2), the operation subproblems comprise an operation subproblem in a normal state and an operation subproblem in an emergency state;
the running sub-problem in the normal state is as follows:
s.t.
formulas (6) - (10), formulas (12), (13)
Equation (22) is the objective function of the running subproblem in the normal state, which means that in the normal state, S ∈ S 0 All over th Solving planning main problem by secondary iteration to obtain power grid robust planning schemeMaximum load shedding amount ofIs a target; formulae (6) to (10), formula (12),(13) The expressions (23), (24) and (25) are constraint conditions, and in the expression (22),representing the wind curtailment and light curtailment of the renewable energy unit w;
the operational sub-problems in emergency are as follows:
s.t.
equation (22) is the objective function of the running subproblem in the normal state, which means that in the normal state, S ∈ S k ，S k Indicates the occurrence of k faults, in ll th Secondary iteration solution planning main problem to obtain power grid robust planning schemeMaximum load shedding amount ofIs a target; equations (27) to (37) are constraints; in equation (27), k represents the number of failures.
Further, in step (4), ifThe operation sub-problem under the normal state is considered to be infeasible, and the cut set of the operation sub-problem needs to be added into the planning main problem as a constraint condition; if it isThe operation sub-problem in the emergency state is considered to be not feasible, and the cut set of the operation sub-problem needs to be added into the planning main problem as a constraint condition.
Adopt the beneficial effect that above-mentioned technical scheme brought:
the invention is based on establishing load demand and renewable energyAnd the uncertainty of the source power generation and the source power generation is considered, and the uncertainty of variables in the uncertainty is limited by defining uncertainty. Decomposing a power grid robust planning method problem considering safety verification under an uncertain environment into a planning main problem and an operation subproblem by adopting a Benders decomposition method to simplify the solution of the problem, wherein the planning main problem takes a basic constraint condition and a feasibility cut set obtained by solving the subproblem as constraint conditions to solve the first ll th Secondary power grid robust planning schemeThe operation subproblems are divided into solving of the maximum load shedding amount under the normal condition and the maximum load shedding amount under the condition of N-K safety check, the solving is converted into solving of a mixed integer programming problem by adopting a double-layer theory so as to reduce the calculated amount, and if the ll th problem is solved th Secondary power grid robust planning schemeIf the feasibility requirement is not met, corresponding constraint conditions are generated and added to the next solution of the main problem, so that the finally obtained power grid robust planning scheme can adapt to all possible implementations of uncertain variables defined by uncertainty in normal state and emergency.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The technical scheme of the invention is explained in detail in the following with the accompanying drawings.
FIG. 1 is a flow chart of the method of the present invention. Firstly, when iterative computation is started, a numerical value of uncertainty gamma is set, then a planning main problem is solved by using an initial constraint condition to obtain a power grid robust planning scheme, then operation sub-problems under a normal condition and an N-K safety check condition are solved to obtain a feasibility cut-set, then the constraint condition of the main problem is updated to solve the planning main problem for the next time until the power grid robust planning scheme meets the feasibility requirements of the two operation sub-problems, and the final power grid robust planning scheme under the set uncertainty gamma and the N-K safety check condition is obtained. The method comprises the following specific steps.
Step 1, inputting information of a power transmission network, including information of a power generation unit, a load unit, a transmission line and the like, and establishing a power network robust planning model considering safety verification in an uncertain environment;
step 2, decomposing the power grid robust planning considering safety check under the uncertain environment into a main planning problem and a solution of an operation sub-problem by adopting a Benders decomposition method;
step 3, solving a planning main problem to obtain a power grid robust planning scheme, and solving a sub-problem of maximum load shedding and wind and light power abandonment of renewable energy under a normal condition and a sub-problem of maximum load shedding amount operation under an N-K safety check condition;
and 4, subtracting the feasibility cut set as a constraint condition by solving the operation sub-problem, adding the constraint condition to the solution of the planning main problem, and obtaining a final power grid robust planning scheme when the feasibility of the sub-problem meets the condition.
In the step 1, the uncertainty of the load demand and the renewable energy power generation is considered by a power grid robust planning model considering the safety verification under the uncertain environment as shown in formulas (1) to (4):
(3)u∈U＝[U min ,U max ] (4)
in formula (1)Which represents the desired load at the bus bar i,andthe lower limit and the upper limit of the load of the bus i are respectively; in formula (2)Representing the desired generated power in the renewable energy power generating unit w,andrespectively represent the lower limit and the upper limit of the generated power in the renewable energy power generation unit w; the load demand and the renewable energy power generation change in the uncertain set thereof are expressed by the formulas (1) and (2); u in equation (3) represents a vector of uncertain variables, and if there is no load on a certain bus i, the corresponding elementIs not included in u; u in formula (4) represents all possibilities for all uncertain variables, U min And U max Lower and upper limits for the uncertain variable, respectively.
A power grid robust planning model considering safety verification in an uncertain environment is described as shown in formulas (5) to (16):
s.t.
c in the formula (5) e Represents the investment cost of line e; x is the number of e Is a variable of 0 to 1, is 1 when the line e is built, and is 0 when the line e is not built; e is a transmission line set; x is the commissioning state of the line; f is line power and p is power generationThe power developed by the machine; q is a certain bus load shedding amount; theta is the phase angle of the line; in formula (6)Represents the power generated by the generator g in the emergency state s;represents the power transmitted by line e in state s;represents the power generated by the renewable energy source in an emergency state s;a load representing the loss of bus i in emergency state s; g i A set of power generation cells representing a bus i; e · i Representing a bus i as a line set of line ends; e i A line set representing the bus i as the line start; w is a group of i Representing a renewable energy power generation unit set at a bus i; u. of (D,i) Indicates if line i is loaded, u (D,i) As elements in a vector uIf line i is unloaded, then u (D,i) Is 0; in formula (7) B e Is the susceptance of line e;the phase angle at the beginning of the line e in the emergency state s,the phase angle of the tail end of the line e in the emergency state s; m is a group of e A large integer value of constant;is a variable of 0 to 1, is 1 when the line e is in a fault state in the emergency state s, and is 0 otherwise; in formula (9)Represents the maximum transmission capacity of line e in emergency state s; in formula (10)Is the maximum capacity of the generator g; σ in the formula (11) is a minimum utilization level at which power can be generated in renewable energy; u. of (W,w) Representing the w-th renewable energy power generation unit in vector u; ε in formula (14) <s> Indicating at a given level of urgency<S> lower load proportion, epsilon <s> S in (1) represents a set of emergency states resulting from k or fewer faults occurring in all existing lines, S = S 0 ∪S 1 ∪S 2 …∪S k (ii) a For a given operating state s of the vehicle,<s> represents the number of the equipment faults, namely the emergency level. E in the formula (15) 0 Indicating an already existing set of lines.
All quantities relating to the dc power flow in equations (5) - (16) are parameterized by u in equation (4), indicating that the above variables are affected by u in every possible case of u.
In the model, the equation (5) is an objective function and represents that the minimum line investment cost is taken as the target; the expression (6) represents the emergency state (including the normal state S ∈ S) 0 ) And each uncertain parameter U belongs to the power balance constraint of each line under the possible realization of U; the expressions (7) and (8) represent kirchhoff voltage law linearized by the large M method; the equation (9) is the interval limit constraint of the branch power flow; the equation (10) is the interval limit value constraint of the output of the generator; the formula (11) is a constraint for ensuring that the power generation level of the renewable energy source is greater than a specified value in a normal state; equation (12) is to give priority to the emergency operation of the system in consideration of the emergency state without limiting the renewable energy power generation level; equation (13) is that the load shedding amount of each line cannot exceed the load demand of the line; equation (14) ensures that the total load shedding amount in each emergency state s does not exceed a specified value, i.e., the total load demand to specified ratio ε <s> The product of (a); formula (15) represents an already existing line; equation (16) shows that when a candidate route is selected for deployment, it is followedThe installation state is still the state for several years.
Equations (17) and (18) define the range of variation of the uncertain variable u, i.e. the uncertainty Γ, and define the upper and lower limits to which its parameters must reach not exceed Γ · < u >.
WhereinAndas shown in formula (19) and formula (20), respectively:
the uncertainty Γ in equation (18) is a variable between 0 and 1, and the choice of its value directly affects the conservatism of the robust planning scheme, when Γ =0, z =0,meaning that there is no uncertainty, when Γ =1, all parameters in u may reach either the upper or lower bound, where the resulting robust planning scheme is most conservative.
In summary, the objective function of the power grid robust planning model considering the safety verification in the uncertain environment is equation (5), and the constraint conditions are equations (6) - (20).
In step 2, a Bender is adoptedsolving the power grid robust planning problem considering the safety check under the uncertain environment by the s decomposition method, wherein the main problem is about solving ll th Secondary iteration power grid robust planning schemeAs shown in formula (21):
equation (21) needs to satisfy the constraints of equations (15) - (16) and the feasibility cut set generated by the subproblem, and ll =1 at the first iteration, there is no feasibility cut set.
The operation sub-problem (SP _ N) in the normal state can be described as shown in equations (22) to (25):
s.t. formulae (6) - (10), (12) - (13)
The expression (22) is an objective function, and indicates that (S ∈ S) is normal 0 ) Ll obtained with a given solution to the planning master problem th Extended planning scheme for sub-iterationsMaximum load shedding amount ofIs the target.
Writing equations (22) - (25) into a compact matrix format, as shown in equations (26) - (29):
wherein d, G, H, T, Q and R are in the form of matrix, representing the matrix formed by the corresponding constraints.λ and η represent the dual coefficients for solving the corresponding constraints.
Y in equation (26) is a vector of continuous variables, which are function constraints of the uncertain variable u; (27) Corresponding to equations (6), (10), (12), (13), (23), constraint (28) corresponding to equations (7) - (9), constraint (29) corresponding to equations (24) - (25), I u Is a matrix, where the coefficient corresponding to the variable for which y is equal to u is 1 and the remaining coefficients are 0.
Based on strong dual theory, equations (26) - (29) can be written as shown in equations (30) - (32):
the equations (30) to (32) are then written in the form of mixed integer linear programming as shown in equations (33) to (42):
in formula (34), M is a larger positive integer, and formulas (34) - (37) are represented by the large M method with the variable β of 0-1 + And beta - A related constraint; adding six auxiliary variables (. Eta.) + ,η - ,η' + ,η' - ,β + ,β - ) To solve for all possible maximum goals in u.
In the emergency state, for a given emergency level k and ll obtained by solving the planning main problem th Secondary iteration power grid robust planning schemeThe operation sub-problem (SP _ C) in the emergency state can be described as shown in equations (45) to (56):
wherein alpha is i ， β e ， δ e ，γ i ，ψ w ，υ D,i And upsilon W,w Are dual coefficients of corresponding constraints.
Will be formulae (45) - (56)) The conversion of the described two-layer problem into a mixed integer linear programming problem results in bilinear termsAndto be provided withFor example, a McCormick linearization method is adopted to linearize bilinear terms as shown in formulas (57) to (60):
in the formulaIs thatThe lower limit of (c). By equations (58) - (60), bilinear termsCan useInstead, the same method is used to define (π) 1 ,π 3 ,π 3 ,π 4 ) Let us orderApplying dual theory and linearization methods, equations (45) - (56) can be transformed into mixed integer linear programming problems such as equations (61) - (68):
other constraints on bivariates are as in equations (69) to (71):
adding six auxiliary variables (. Eta.) + ,η - ,η' + ,η' - ,β + ,β - ) Converting equations (61) - (71) to mixed integer programming problems are as in equations (72) - (75):
s.t. formulae (34) - (40), (62) - (64), (67) - (69)
β +l ∈{0,1},β -l ∈{0,1} (75)
In step 3, an uncertainty gamma is set, and then a planning main problem (21) is solved according to planning problem constraints (15) and (16) to obtain ll th Secondary iteration power grid robust planning schemeSolving the sub-problem equations (33) - (42) of maximum load shedding and wind and light power abandoning operation of renewable energy under normal conditions to obtain the maximum load shedding amount under normal conditionsAnd the corresponding situation u when the load shedding amount reaches the maximum value and the wind and light abandoning power of the renewable energy source is abandoned * As shown in formula (43):
in step 4, if the maximum load shedding amount is reachedGreater than 0, then the feasibility cut set shown in equation (44) will be added as a constraint to the planning main problem:
solving the sub-problem expressions (72) - (75) of the maximum load shedding operation under the condition of the safety check of N-K to obtain the emergencyMaximum load shedding amount under condition that total number of faults is kA corresponding situation can be obtained from equation (43), ifIs greater thanThen the feasibility cut-sets of equation (76) will be added as constraints to the planning main problem:
and when the maximum load shedding amount of the operation subproblem under the normal condition and the operation subproblem under the emergency condition meets the condition, obtaining a final power grid robust planning scheme.
The embodiments are only for illustrating the technical idea of the present invention, and the technical idea of the present invention is not limited thereto, and any modifications made on the basis of the technical scheme according to the technical idea of the present invention fall within the scope of the present invention.
Claims (6)
1. A power grid robust planning method considering security verification in an uncertain environment is characterized by comprising the following steps:
(1) Inputting power grid information including power transmission network frames, candidate routes, generators, loads and related parameters of renewable energy, and establishing a power grid robust planning model considering safety verification in an uncertain environment;
(2) Decomposing the power grid robust planning model into a main planning problem and a sub-operation problem by adopting a Benders decomposition method;
(3) Solving a planning main problem to obtain a power grid robust planning scheme; solving the operation subproblem in the normal state and the operation subproblem in the emergency state;
(4) And verifying the feasibility of the operation subproblems, if the feasibility is not feasible, adding the cut sets generated by the operation subproblems into the solution of the planning main problem as constraint conditions, and if the feasibility is feasible, obtaining a final power grid robust planning scheme.
2. The power grid robust planning method considering safety verification under the uncertain environment according to claim 1, characterized in that: in the step (1), a power grid robust planning model considering safety verification under an uncertain environment is established, and the uncertainty of load demand and renewable energy power generation is considered:
u∈U＝[U min ,U max ] (4)
in the formula (1), the reaction mixture is,which represents the desired load at the bus bar i,andrespectively the lower limit and the upper limit of the load of the bus i, and B is the number of the buses; in the formula (2), the reaction mixture is,representing the desired generated power in the renewable energy power generating unit w,andrespectively representing the lower limit and the upper limit of the generated power in a renewable energy power generation unit W, wherein W is the number of the renewable energy power generation units; in the formula (3), u represents a vector of an uncertain variable, and if there is no load on a certain bus i, the corresponding bus i is subjected toIs not included in u; in formula (4), U represents all possibilities of all uncertain variables, U min And U max Respectively, the lower limit and the upper limit of the uncertain variable.
3. The power grid robust planning method considering safety verification under the uncertain environment according to claim 2, characterized in that: in step (1), the power grid robust planning model considering the safety check in the uncertain environment is as follows:
s.t.
the equation (5) is an objective function of the robust power grid planning model, and equations (6) to (18) are constraint conditions of the robust power grid planning model; in the formula (5), C e Denotes the investment cost, x, of the line e e The variable is 0-1, when a line e is built, the variable is 1, when the line e is not built, the variable is 0, E is a transmission line set, x is the built state of the line, f is the line power, p is the power sent by a generator, q is the load shedding amount of a certain bus, and theta is the phase angle of the line; in the formula (6), the reaction mixture is,representing the power generated by the generator g in the emergency state s,representing the power transmitted by line e in state s,representing the power emitted by the renewable energy source in the emergency state s,load, G, representing loss of bus i in emergency state s i Set of generating cells, E, representing bus i i RepresentBus i as a line set at the end of the line, E i Line set W representing bus i as the starting end of the line i Set of renewable energy generating units, u, represented on bus i (D,i) Indicates if line i is loaded, u (D,i) As elements in a vector uIf line i is not loaded, then u (D,i) Is 0; in the formula (7), B e Is the susceptance of the line e,the phase angle at the beginning of the line e in the emergency state s,is the phase angle of the end of the line e in the emergency state s, M e Is a constant integer value of the line e,is a variable of 0 to 1, is 1 when the line e is in a fault state in the emergency state s, and is 0 otherwise; in the formula (9), the reaction mixture is,represents the maximum transmission capacity of line e in emergency state s; in the formula (10), the compound represented by the formula (10),is the maximum capacity of the generator g; in the formula (11), σ is the minimum utilization level at which power generation by renewable energy can be performed, and u (W,w) Representing the w-th renewable energy generating unit, S, in vector u 0 Indicating that 0 faults occurred; in the formula (12), S \ S0 represents the case where other failures except for the 0-failure-occurring failure are eliminated, and in the formula (14), ε <s> Indicating the proportion of load, subscript, that can be cut off in a given emergency state s<s&The number of the equipment faults is shown; in the formula (15), E 0 Indicating an already existing set of lines; in the formula (16), E \ E 0 Indicates removal of E 0 An outer set of transmission lines; in the formula (17), the compound represented by the formula (I),<u>, representing the size of the vector u,in the formula (18), Γ represents an uncertainty, and its value varies from 0 to 1.
4. The power grid robust planning method considering safety verification under the uncertain environment according to claim 3, characterized in that: in step (2), the planning main problem is as follows:
s.t.
formula (15), (16)
And (3) obtaining a power grid robust planning scheme by performing iterative solution on the formula (21) by taking the formula (21) as an objective function of a planning main problem and taking the formulas (15) and (16) as constraint conditions.
5. The power grid robust planning method considering safety verification in the uncertain environment as claimed in claim 4, wherein: in the step (2), the operation subproblems comprise an operation subproblem in a normal state and an operation subproblem in an emergency state;
the running sub-problem in the normal state is as follows:
s.t.
formulas (6) - (10), formulas (12), (13)
Equation (22) is the objective function of the running subproblem in the normal state, and indicates that S ∈ S in the normal state 0 All over th Secondary iteration solution planning main problem to obtain power grid robust planning schemeMaximum load shedding amount ofIs a target; formulas (6) to (10), formulas (12), (13), (23), (24), and (25) are constraints, and in formula (22),representing the wind curtailment amount of the renewable energy unit w;
the operational sub-problems in emergency are as follows:
s.t.
equation (22) is the objective function of the running subproblem in the normal state, which means that in the normal state, S ∈ S k ，S k Indicates the occurrence of k faults, in ll th Secondary iteration solution planning main problem to obtain power grid robust planning schemeMaximum load shedding amount ofIs a target; equations (27) to (37) are constraints; in equation (27), k represents the number of failures.
6. The power grid robust planning method considering safety verification under the uncertain environment according to claim 5, characterized in that: in step (4), ifConsidering that the operation sub-problem in the normal state is not feasible, and adding the cut set of the operation sub-problem as a constraint condition into the planning main problem; if it isThe operation sub-problem in the emergency state is considered to be infeasible, and the cut set of the operation sub-problem needs to be added into the planning main problem as a constraint condition.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710695389.XA CN107528314B (en) | 2017-08-15 | 2017-08-15 | The power grid robust planing method of safety check is considered under a kind of uncertain environment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710695389.XA CN107528314B (en) | 2017-08-15 | 2017-08-15 | The power grid robust planing method of safety check is considered under a kind of uncertain environment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107528314A true CN107528314A (en) | 2017-12-29 |
| CN107528314B CN107528314B (en) | 2019-11-05 |
Family
ID=60681112
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710695389.XA Active CN107528314B (en) | 2017-08-15 | 2017-08-15 | The power grid robust planing method of safety check is considered under a kind of uncertain environment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107528314B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108304665A (en) * | 2018-02-07 | 2018-07-20 | 中国人民解放军海军工程大学 | A kind of spare parts demand amount computational methods of more complete equipments |
| CN109858774A (en) * | 2019-01-09 | 2019-06-07 | 燕山大学 | Improve the source net lotus planing method of security of system and harmony |
| CN109932901A (en) * | 2019-01-22 | 2019-06-25 | 国网山西省电力公司电力科学研究院 | A kind of two stages robust Unit Combination method counted and failure constrains |
| CN111786384A (en) * | 2020-07-10 | 2020-10-16 | 中国船舶工业集团公司第七0八研究所 | Robust optimized operation method for elastically-guided power distribution network subjected to external interference |
| CN116415708A (en) * | 2022-12-30 | 2023-07-11 | 三峡大学 | Power grid robust planning method considering confidence level |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105528674A (en) * | 2015-12-04 | 2016-04-27 | 中国电力科学研究院 | Grid planning method based on stochastic dual dynamic theory |
-
2017
- 2017-08-15 CN CN201710695389.XA patent/CN107528314B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105528674A (en) * | 2015-12-04 | 2016-04-27 | 中国电力科学研究院 | Grid planning method based on stochastic dual dynamic theory |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108304665A (en) * | 2018-02-07 | 2018-07-20 | 中国人民解放军海军工程大学 | A kind of spare parts demand amount computational methods of more complete equipments |
| CN108304665B (en) * | 2018-02-07 | 2021-08-31 | 中国人民解放军海军工程大学 | Method for calculating spare part demand of multiple sets of equipment |
| CN109858774A (en) * | 2019-01-09 | 2019-06-07 | 燕山大学 | Improve the source net lotus planing method of security of system and harmony |
| CN109858774B (en) * | 2019-01-09 | 2020-10-27 | 燕山大学 | Source network load planning method for improving system safety and coordination |
| CN109932901A (en) * | 2019-01-22 | 2019-06-25 | 国网山西省电力公司电力科学研究院 | A kind of two stages robust Unit Combination method counted and failure constrains |
| CN111786384A (en) * | 2020-07-10 | 2020-10-16 | 中国船舶工业集团公司第七0八研究所 | Robust optimized operation method for elastically-guided power distribution network subjected to external interference |
| CN111786384B (en) * | 2020-07-10 | 2022-03-04 | 中国船舶工业集团公司第七0八研究所 | Robust optimized operation method for elastically-guided power distribution network subjected to external interference |
| CN116415708A (en) * | 2022-12-30 | 2023-07-11 | 三峡大学 | Power grid robust planning method considering confidence level |
| CN116415708B (en) * | 2022-12-30 | 2024-03-29 | 三峡大学 | Power grid robust planning method considering confidence level |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107528314B (en) | 2019-11-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107528314A (en) | The power network robust planing method of safety check is considered under a kind of uncertain environment | |
| Zhao et al. | A model predictive control based generator start-up optimization strategy for restoration with microgrids as black-start resources | |
| Moradi-Sepahvand et al. | Hybrid AC/DC transmission expansion planning considering HVAC to HVDC conversion under renewable penetration | |
| Wiget et al. | Probabilistic security constrained optimal power flow for a mixed HVAC and HVDC grid with stochastic infeed | |
| CN109038660A (en) | A kind of wind-electricity integration System Reactive Power planing method considering quiet Enhancement of Transient Voltage Stability | |
| CN112260271B (en) | Method and device for generating power distribution network fault recovery strategy | |
| CN109598377B (en) | AC/DC hybrid power distribution network robust planning method based on fault constraint | |
| Nikoobakht et al. | Towards robust OPF solution strategy for the future AC/DC grids: case of VSC‐HVDC‐connected offshore wind farms | |
| CN112217196A (en) | Long-term coordination extension planning method for gas-electricity combined system considering N-1 safety criterion and probability reliability index | |
| CN103632207B (en) | A kind of power generating facilities and power grids comprehensive optimization method | |
| CN106980918A (en) | A kind of generating and transmitting system reliability evaluation system | |
| Home-Ortiz et al. | PV hosting capacity assessment in distribution systems considering resilience enhancement | |
| CN113452025B (en) | Model-data hybrid driven power grid expected fault assessment method and system | |
| CN107301479B (en) | Natural disaster risk-based multi-scene planning method for power transmission system | |
| Beddard et al. | Availability analysis of VSC-HVDC schemes for offshore windfarms | |
| CN112436542A (en) | Steady-state safety emergency control online pre-decision method considering stability control strategy | |
| Huang et al. | Robust $ Nk $ Security-constrained Optimal Power Flow Incorporating Preventive and Corrective Generation Dispatch to Improve Power System Reliability | |
| KR20200017248A (en) | Explosion-proof system of elevator door landing interlock | |
| Fu et al. | A tractable failure probability prediction model for predictive maintenance scheduling of large-scale modular-multilevel-converters | |
| CN111709706B (en) | Automatic generation method of new equipment starting scheme based on self-adaptive pattern recognition | |
| Siddique et al. | Control strategy for a smart grid-hybrid controller for renewable energy using artificial neuro and fuzzy intelligent system | |
| CN108808670B (en) | Partition scheme optimization method and device for power system recovery after blackout | |
| Shi et al. | A control strategy for improving power system resilience in Nk contingency | |
| CN114330884B (en) | Multi-time scale coordinated AC/DC power grid dynamic safety early warning method and system | |
| Sun et al. | Two-Stage Robust Voltage Control Strategy for Seaport Microgrids with Health-Aware All-Electric Ships |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |