Electric power system economic dispatching method and device considering N-k complex disconnection fault

Abstract

The invention discloses a power system economic dispatching method and device considering an N-k complex disconnection fault. The method comprises the following steps: acquiring basic data information of a power system by setting a data center; according to the basic data information and a power system security domain model, analyzing and constructing a mapping relation between node injection uncertainty and a security boundary to obtain an N-k complex fault constraint model; the N-k complex fault constraint model is solved through a Cornish-Fisher series method, and a linear opportunity constraint expression is obtained; constructing a security constraint economic dispatching model based on linear opportunity constraint; and under the condition that the security constraint condition is met, solving the security constraint economic dispatching model by setting a solving strategy to obtain an optimal dispatching scheme. According to the method, the inoperative constraints can be found in advance for the economic dispatching model containing a large number of redundant constraints, and the inoperative constraints are eliminated, so that the solving efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of economic dispatch of power systems, and particularly to a method and device for economic dispatch of power systems considering N-k complex disconnection faults. Background Art

[0002] The security-constrained economic dispatch (SCED) of power systems is an important link for solving power market clearing. However, with the advancement of China's power market reform, it is difficult to solve the SCED model considering a large number of constraints. Especially after considering fault scenarios such as N-1, the number of security constraints increases exponentially. The increased complexity of the model will further lead to a decrease in the efficiency of market clearing. It is more difficult to consider complex constraints such as N-k and transient stability, which is not conducive to the rapid development of the power market.

[0003] Currently, the industrial community uses a post-verification method to check whether the dispatch method can pass the constraint verification. Or according to expert experience, pre-screen the possible constraint sets for power market clearing, which has certain deviations. In addition, the large-scale access of new energy to the power grid also leads to the existence of uncertainties in the dispatch plan.

[0004] Therefore, how to construct linear constraints that can be used for optimization and improve the optimization and solution rate of security-constrained economic dispatch is a key problem that needs to be solved urgently. Summary of the Invention

[0005] To this end, the present invention provides a method and device for economic dispatch of power systems considering N-k complex disconnection faults, which linearize the N-k complex disconnection fault constraints by using the Cornish-Fisher series method based on semi-invariants, and construct a linear chance-constrained expression; at the same time, by setting different confidence levels for faults with different occurrence probabilities, a security-constrained economic dispatch model is constructed to dynamically identify the active constraints and realize the adaptive solution process of economic dispatch that satisfies the N-k complex constraints.

[0006] To achieve the above object, the present invention provides the following technical solution: A method for economic dispatch of power systems considering N-k complex disconnection faults, including:

[0007] Obtain the basic data information of the power system through a set data center;

[0008] According to the basic data information and the power system security domain model, analyze and construct the mapping relationship between the node injection uncertainty and the safety boundary to obtain an N-k complex fault constraint model;

[0009] Solve the N-k complex fault constraint model by the Cornish-Fisher series method to obtain a linear chance-constrained expression;

[0010] Based on the linear chance constraint, construct a security-constrained economic dispatch model;

[0011] Under the condition of meeting the security constraints, solve the security-constrained economic dispatch model by setting a solution strategy to obtain an optimal dispatch plan.

[0012] As a preferred solution of an economic dispatch method for a power system considering N-k complex line-break faults, the expression of the power system security region model is:

[0013]

[0014] In the formula, Ω SS is the set of the comprehensive security region; Ω T is the set of THSR; Ω V is the set of SVSR; g and f are algebraic equations about I, V, and θ; x is the decision space; C I and C V are hypercuboids composed of branch power constraints and node voltage constraints respectively; are the active power constraint and reactive power constraint of the control variable respectively; P i and Q i are the active power injection and reactive power injection of node i respectively; and are the upper and lower limits of the active power injection respectively; and are the upper and lower limits of the reactive power injection respectively.

[0015] As a preferred solution of an economic dispatch method for a power system considering N-k complex line-break faults, the linear chance-constrained expression is:

[0016]

[0017]

[0018] In the formula, are the coefficients of the hyperplane expression respectively; Pr(·) is the probability of constraint compliance; and are the confidence levels for the upper and lower limits of the branch power and the upper and lower limits of the node voltage to hold in the N-k case respectively.

[0019] As a preferred solution of an economic dispatch method for a power system considering N-k complex line-break faults, the expression of the security-constrained economic dispatch model is:

[0020]

[0021] Wherein, I B 、I G and I L are the sets of nodes, generator sets and branches respectively; I R is the set of new energy nodes; PG i and QG i are the active and reactive power outputs of the generator at node i respectively; PD i and QD i are the active and reactive powers of the load at node i respectively; F is the objective function value to be solved; V k is the voltage of node k; PG i are the upper and lower limits of the active power output of the generator respectively; QG i are the upper and lower limits of the reactive power output of the generator respectively; P i 、 ΔP i are the actual output, predicted output and power adjustment amount of the generator at node i respectively; Q i 、 ΔQ i are the reactive power output, predicted reactive power output and reactive power adjustment amount of the generator at node i respectively; ρ i is the power generation unit price; l is the branch; j is the node; are the introduced slack variables respectively; N b is the number of nodes.

[0022] As an optimal scheme of an economic dispatch method for a power system considering N-k complex line-break faults, during the process of solving the security-constrained economic dispatch model by the set solution strategy, a set confidence level is set for the faults with set occurrence probabilities, and the problem scale is reduced through the active constraint identification technology, reducing the conservatism of the optimization result.

[0023] The present invention also provides an economic dispatch device for a power system considering N-k complex line-break faults. Based on the above economic dispatch method for a power system considering N-k complex line-break faults, it includes:

[0024] A basic data information acquisition module, configured to acquire the basic data information of the power system through a set data center;

[0025] An N-k complex fault constraint model construction module, configured to analyze and construct the mapping relationship between the node injection uncertainty and the safety boundary according to the basic data information and the power system safety domain model, to obtain an N-k complex fault constraint model;

[0026] The N-k complex fault constraint model solving module is used to solve the N-k complex fault constraint model by the Cornish-Fisher series method to obtain a linear chance constraint expression;

[0027] The security-constrained economic dispatch model construction module is used to construct a security-constrained economic dispatch model based on the linear chance constraint;

[0028] The optimal dispatch plan obtaining module is used to solve the security-constrained economic dispatch model by setting a solution strategy under the condition of meeting the security constraints to obtain an optimal dispatch plan.

[0029] As an optimal solution of a power system economic dispatch device considering N-k complex line-breaking faults, in the N-k complex fault constraint model construction module, the expression of the power system security domain model is:

[0030]

[0031] In the formula, Ω SS is the set of comprehensive security domains; Ω T is the set of THSR; Ω V is the set of SVSR; g and f are algebraic equations about I, V, and θ respectively; x is the decision space; C I and C V are hypercuboids composed of branch power flow constraints and node voltage constraints respectively; are the active power constraint and reactive power constraint of the control variable respectively; P i and Q i are the active power injection and reactive power injection of node i respectively; and are the upper and lower limits of active power injection respectively; and are the upper and lower limits of reactive power injection respectively.

[0032] As an optimal solution of a power system economic dispatch device considering N-k complex line-breaking faults, in the N-k complex fault constraint model solving module, the linear chance constraint expression is:

[0033]

[0034] In the formula, are the coefficients of the hyperplane expression respectively; Pr(·) is the probability of constraint compliance; and are the confidence levels for the upper and lower limits of branch power and the upper and lower limits of node voltage to hold in the N-k case respectively.

[0035] As an optimal solution for a power system economic dispatch device considering N-k complex line outage faults, in the safety-constrained economic dispatch model construction module, the expression of the safety-constrained economic dispatch model is as follows:

[0036]

[0037] In the formula, I B 、I G and I L are the sets of nodes, generator sets, and branches respectively; I R is the set of new energy nodes; PG i and QG i are the active and reactive power output powers of the generator at node i respectively; PD i and QD i are the active and reactive powers of the load at node i respectively; F is the objective function value to be solved; V k is the voltage at node k; PG i are the upper and lower limits of the active power output of the generator respectively; QG i are the upper and lower limits of the reactive power output of the generator respectively; P i 、 ΔP i are the actual output power, predicted output power, and power adjustment amount of the generator at node i respectively; Q i 、 ΔQ i are the reactive power output, predicted reactive power output, and reactive power adjustment amount of the generator at node i respectively; ρ i is the unit price of power generation; l is a branch; j is a node; are the introduced slack variables respectively; N b is the number of nodes.

[0038] As an optimal solution for a power system economic dispatch device considering N-k complex line outage faults, in the optimal dispatch plan acquisition module, during the process of solving the safety-constrained economic dispatch model by the set solution strategy, a set confidence level is set for the faults with a set occurrence probability, and the problem scale is reduced through the active constraint identification technology to reduce the conservatism of the optimization result.

[0039] The present invention has the following advantages: The present invention obtains the basic data information of the power system through the set data center; according to the basic data information and the power system security domain model, the mapping relationship between the node injection uncertainty and the security boundary is analyzed and constructed to obtain the N-k complex fault constraint model; the N-k complex fault constraint model is solved by the Cornish-Fisher series method to obtain a linear chance constraint expression; based on the linear chance constraint, a security-constrained economic dispatch model is constructed; under the condition of satisfying the security constraints, the security-constrained economic dispatch model is solved by setting a solution strategy to obtain an optimal dispatch plan. The present invention focuses on the research of an economic dispatch method for a power system considering N-k complex open-circuit faults. It first proposes a method for constructing a security domain with N-k complex constraints, which can make full use of the advantages of linear constraints in the security domain to solve the optimization problem under the condition of satisfying a certain probability level. At the same time, for the economic dispatch model with a large number of redundant constraints, ineffective constraints are discovered in advance and removed to improve the solution efficiency. Description of the Drawings

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only exemplary, and for those of ordinary skill in the art, other implementation drawings can be obtained by extending according to the provided drawings without creative efforts.

[0041] The structures, ratios, sizes, etc. shown in this specification are only used to cooperate with the content disclosed in the specification for those who are familiar with this technology to understand and read, and are not used to limit the limiting conditions under which the present invention can be implemented. Therefore, they do not have a substantial technical meaning. Any modification of the structure, change of the proportional relationship, or adjustment of the size, without affecting the effects that the present invention can produce and the purposes that can be achieved, should still fall within the scope covered by the technical content disclosed in the present invention.

[0042] Figure 1 It is a schematic flow chart of an economic dispatch method for a power system considering N-k complex open-circuit faults provided in Embodiment 1 of the present invention;

[0043] Figure 2 It is a schematic flow chart of identifying effective constraints in an economic dispatch method for a power system considering N-k complex open-circuit faults provided in Embodiment 1 of the present invention; among them, 1, 2, 3, 4, 5 are redundant constraint boundaries; 6, 7, 8, 9, 10, 11, 12, 13 are effective constraint boundaries;

[0044] Figure 3Schematic diagram of the probability density curves of the voltages / powers of some nodes / branches in a possible embodiment provided in Embodiment 1 of the present invention;

[0045] Figure 4 Schematic diagram of the 24-hour predicted values of new energy and load in a possible embodiment provided in Embodiment 1 of the present invention;

[0046] Figure 5 Schematic diagram of the power fluctuation of branch 33-49 in a possible embodiment provided in Embodiment 1 of the present invention;

[0047] Figure 6 Schematic diagram of the architecture of a power system economic dispatch device considering N-k complex line-break faults provided in Embodiment 2 of the present invention. Detailed implementation manners

[0048] The following specific embodiments illustrate the implementation manners of the present invention. Those skilled in the art can easily understand the other advantages and effects of the present invention from the content disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0049] Embodiment 1

[0050] See Figure 1 , Embodiment 1 of the present invention provides a power system economic dispatch method considering N-k complex line-break faults, including the following steps:

[0051] S1. Obtain the basic data information of the power system through a set data center;

[0052] S2. According to the basic data information and the power system security domain model, analyze and construct the mapping relationship between node injection uncertainty and the safety boundary to obtain an N-k complex fault constraint model;

[0053] S3. Solve the N-k complex fault constraint model by the Cornish-Fisher series method to obtain a linear chance constraint expression;

[0054] S4. Based on the linear chance constraint, construct a security-constrained economic dispatch model;

[0055] S5. Under the condition of meeting the security constraint conditions, solve the security-constrained economic dispatch model through a set solution strategy to obtain an optimal dispatch plan.

[0056] In this embodiment, in step S1, the basic data information of the power system is obtained through a set data center;

[0057] Among them, the basic data information includes: the topological structure of the power system, branch data, fault sets, and fault occurrence probabilities, etc.

[0058] In this embodiment, in step S2, according to the basic data information and the power system security region model, the mapping relationship between the node injection uncertainty and the security boundary is analyzed and constructed to obtain the N-k complex fault constraint model;

[0059] Among them, the power system security region is divided into a thermal security region (THSR) and a steady-state voltage security region (SVSR). Then, the expressions of THSR and SVSR are defined on the decision space x as follows:

[0060]

[0061] Among them, C I and C V are respectively hypercuboids composed of branch power flow constraints and node voltage constraints.

[0062]

[0063] Similarly, the constraints on the active power and reactive power of the control variables can be expressed as:

[0064]

[0065] In summary, as shown in formulas (1)-(6), the final form of PSSR is given, that is, the intersection of all constraints:

[0066]

[0067] In the formula, Ω SS is the set of the comprehensive security region; Ω T is the set of THSR; Ω V is the set of SVSR; g and f are algebraic equations about I, V, and θ; x is the decision space; I i is the current of branch i; and are respectively the upper and lower limits of the branch current; V i is the voltage of node i; and are respectively the upper and lower limits of the node voltage; are respectively the active power constraint and reactive power constraint of the control variable; P i and Q iThe active power injection and reactive power injection of node i, respectively; and are the upper and lower limits of active power injection, respectively; and are the upper and lower limits of reactive power injection, respectively.

[0068] In this embodiment, in step S3, the Cornish-Fisher series method is used to solve the N-k complex fault constraint model to obtain a linear chance constraint expression;

[0069] Specifically, based on the linear analytical form of the security region, the N-0 security constraint and the chance constraint forms of the N-1 bundle and the security constraint are constructed as follows:

[0070]

[0071] l ∈ I L (12)

[0072] Where and are the coefficients of the hyperplane expression, as shown in formulas (8)-(12), which is the chance constraint expression of the N-0 security constraint; Pr(r( represents the probability of constraint compliance; and are the confidence levels for the upper and lower limits of branch power and the upper and lower limits of node voltage constraints to hold in the N-0 case, respectively.

[0073]

[0074] In the formula, are the coefficients of the hyperplane expression, respectively; Pr(r( is the probability of constraint compliance; and are the confidence levels for the upper and lower limits of branch power and the upper and lower limits of node voltage constraints to hold in the N-k case, respectively.

[0075] In this embodiment, taking formula (8) as an example, the linearization of the chance constraint economic dispatch model constructed based on PSSR is derived as follows:

[0076] Let Similarly for reactive power, that is Then the transformation of formula (8) can be obtained as shown in formula (17):

[0077]

[0078] Obviously, given the characteristic that the security region is independent of the operating state of the power system, that is, the coefficients of the security region in the nodal injection space have been calculated and saved offline. At the same time, the predicted values of the active and reactive powers of the nodal injection are also fixed, that is, the first half of Equation (17) should be a constant value.

[0079]

[0080] In the formula, is the introduced auxiliary variable. For a given topology and day-ahead prediction scheduling scheme, this term is fixed. Substituting Equation (18) into Equation (17) gives Equation (19):

[0081]

[0082] After further arrangement, we can get:

[0083]

[0084] As shown above, define a new function as shown in Equation (21):

[0085]

[0086] In the formula, represents the probability distribution function with respect to the x variable, satisfying

[0087] is monotonically increasing with respect to x. Based on the definition of Equation (21), Equation (21) can be modified into the form shown in Equation (22):

[0088]

[0089] After the inverse transformation of the function, Equation (22) can be transformed into the form of Equation (23):

[0090]

[0091] In the formula, G -1 is 's inverse function.

[0092] Let Here, can be solved by the Cornish-Fisher series method based on semi-invariants, which is much more efficient than the traditional convolution algorithm. The specific derivation process is as follows:

[0093]

[0094] In the formula, is the probability density function of the standard normal distribution; is the σ-th semi-invariant of a random variable.

[0095] After transformation and derivation of Equation (23), the chance-constrained expression for the upper limit of the branch power flow in the case of N - 0 is constructed as shown in Equation (25):

[0096]

[0097] After further arrangement, Equation (26) can be obtained:

[0098]

[0099] In this embodiment, in step S4, a security-constrained economic dispatch model is constructed based on linear chance constraints;

[0100] Specifically, for the security-constrained economic dispatch model, aiming to solve the optimal dispatch plan on the premise that the security constraints are satisfied, the traditional modeling forms are shown in Equations (27)-(32).

[0101]

[0102]

[0103] Among them, I B , I G and I L are the sets of nodes, generators, and branches respectively; PG i and QG i are the active and reactive power outputs of the generator at node i respectively; PD i and QD i are the active and reactive powers of the load at node i respectively; F is the objective function value to be solved; V i is the voltage at node i; PG i , QG i , V i , and PF k are the upper and lower limits of the active power output, reactive power output, node voltage, and branch active power of the generator respectively.

[0104] In the chance-constrained optimal power flow model, first, the uncertainty modeling of new energy / load at node i is given, and the forms are shown in Formulas (33) and (34).

[0105]

[0106] In the formula, R i , ΔR iThe actual output, predicted output, and prediction deviation of new energy at node i, respectively; I R is the set of new energy nodes.

[0107]

[0108] In the formula, L i , ΔL i The actual power, predicted power, and prediction deviation of the load at node i, respectively; I L is the set of load nodes.

[0109] In this embodiment, a single - period chance - constrained model is given. Assuming that the scheduling window of the optimal power flow is 30 min (it can also be 1 h, 15 min, 5 min, etc.). Then the primary constraint to be satisfied within this period is the power balance constraint, that is, on the basis of the original scheduling scheme, the output of adjustable units can cover the power deviation caused by the uncertainty of new energy / load. Therefore, the total unbalanced power Λ within this period can be modeled as formula (35):

[0110]

[0111] Considering that Automatic Generation Control (AGC) can spontaneously distribute unbalanced power to controllable units and respond quickly within tens of seconds to several minutes to meet the system's demand for unbalanced power. Therefore, for the unbalanced power caused by uncertainty, the reserve capacity allocation model of generators can be constructed as shown in formula (36):

[0112]

[0113] In the formula, P i , ΔP i The actual output, predicted output, and power adjustment amount of the generator at node i, respectively; μ i is the allocation factor of the AGC unit, ensuring that the adjustable output of a single generator set is not greater than the total unbalanced power.

[0114] Therefore, with the goal of minimizing the adjustment cost, the chance - constrained optimization model is sorted out as shown in formula (37):

[0115]

[0116] In the formula, Q i , ΔQ i The reactive power output, predicted reactive power output, and reactive power adjustment amount of the generator at node i, respectively; ρ i$p$ is the power generation unit price; $l$ is the branch; $j$ is the node; are the introduced slack variables respectively; $N$ b is the number of nodes.

[0117] In this embodiment, since the security region is linearly expressed, when the confidence interval is determined, the obtained and are also both fixed values. In theory, a sufficient number of boundary constraints can be transformed into an opportunity-constrained linearization model and added to formula (37) for solution.

[0118] Even as described above, in theory, all security region boundaries in the cases of N-0 to N-k can be derived. In practical applications, especially for power grids at the provincial level and above, it is very difficult to take into account all security region constraints completely. Therefore, except for fully considering the security region boundaries of N-0 and N-1, the security boundaries above the k-th order depend on the expert experience of dispatchers to decide whether to add them. As shown in the derivation process, every time a security constraint is added (or the grid structure changes), it is necessary to solve the corresponding opportunity-constrained linear expression and re-solve the optimization model.

[0119] Due to the relaxation effect of the opportunity constraint, each security boundary is expanded by the actual range. Therefore, there will be a large number of constraint failures, that is, a large number of active constraints are removed from the comprehensive security region. By sorting and appropriately, some redundant constraints can be removed to enhance the solution efficiency of the optimization problem.

[0120] In this embodiment, in step S5, under the condition of satisfying the security constraints, the security-constrained economic dispatch model is solved by setting a solution strategy to obtain an optimal dispatch plan.

[0121] Specifically, the security-constrained economic dispatch model is solved by setting a solution strategy to find the optimal dispatch plan on the premise that the security constraints are satisfied.

[0122] In this embodiment, as Figure 2 shown, by setting different confidence levels for faults with different occurrence probabilities and using the active constraint identification technology to reduce the problem scale and reduce the conservativeness of the optimization result.

[0123] In a possible embodiment, a specific verification example is provided as follows:

[0124] To avoid the optimization results from being overly conservative, the confidence levels for five scenarios of N-4, N-3, N-2, N-1, and N-0 are set to different values, namely 0.90, 0.90, 0.90, 0.95, and 0.95, which reduces the impact of the security constraints corresponding to severe faults on the optimization results. To reflect the constraint violation situation after optimization, that is, the over-limit situation of branch power flow / node voltage, the Monte Carlo simulation method is used to generate 10,000 samples for verification. As Figure 3 shown, it is the probability density curve of voltage / power for some nodes / branches. Figure 3 lists some over-limit scenarios (other scenarios also meet the qualification rate requirements). Through statistics, it can be found that due to the relatively low confidence levels set for the N-4, N-3, and N-2 scenarios themselves, there will be situations where the over-limit probability is greater than 5%, which are all reasonable results.

[0125] Combined with the 24-hour prediction, as Figure 4 shown, the optimization solution is carried out for the entire period. Then, based on the Monte Carlo simulation samples, the fluctuation range of branch power is characterized, as Figure 5 shown. The results show that none of them exceed the limit value (1078 MW) of this line, meeting the system security requirements at the cost of sacrificing a certain amount of economy. Referring to formula (26), the upper and lower bounds of the fluctuation range in the figure correspond to the boundaries after the chance constraint is linearized.

[0126] In summary, the present invention obtains the basic data information of the power system by setting the data center; according to the basic data information and the power system security domain model, analyzes and constructs the mapping relationship between the node injection uncertainty and the security boundary to obtain the N-k complex fault constraint model; solves the N-k complex fault constraint model by the Cornish-Fisher series method to obtain a linear chance constraint expression; constructs a security-constrained economic dispatch model based on the linear chance constraint; and under the condition of meeting the security constraints, solves the security-constrained economic dispatch model by setting a solution strategy to obtain an optimal dispatch plan. The present invention conducts research on the economic dispatch method of the power system considering N-k complex disconnection faults. It first proposes a method for constructing the security domain of N-k complex constraints, which can make full use of the advantages of the linear constraints of the security domain to solve the optimization problem under the condition of meeting a certain probability level. At the same time, for the economic dispatch model with a large number of redundant constraints, it can discover the ineffective constraints in advance and eliminate them to improve the solution efficiency.

[0127] It should be noted that the method of the embodiments of the present disclosure can be executed by a single device, such as a computer or a server. The method of this embodiment can also be applied to a distributed scenario and completed by multiple devices cooperating with each other. In this case of a distributed scenario, one of the multiple devices can only execute one or more steps of the method of the embodiments of the present disclosure, and these multiple devices will interact with each other to complete the described method.

[0128] It should be noted that some embodiments of the present disclosure have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the above embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0129] Embodiment 2

[0130] See Figure 6 , Embodiment 2 of the present invention also provides a power system economic dispatch device considering N-k complex disconnection faults, including:

[0131] A basic data information acquisition module 001, configured to acquire the basic data information of the power system through a set data center;

[0132] An N-k complex fault constraint model construction module 002, configured to analyze and construct the mapping relationship between node injection uncertainty and the safety boundary according to the basic data information and the power system safety domain model, and obtain an N-k complex fault constraint model;

[0133] An N-k complex fault constraint model solving module 003, configured to solve the N-k complex fault constraint model by the Cornish-Fisher series method to obtain a linear chance constraint expression;

[0134] A security constraint economic dispatch model construction module 004, configured to construct a security constraint economic dispatch model based on the linear chance constraint;

[0135] An optimal dispatch plan acquisition module 005, configured to solve the security constraint economic dispatch model through a set solution strategy under the condition of meeting the security constraints to obtain an optimal dispatch plan.

[0136] In this embodiment, in the N-k complex fault constraint model construction module 002, the expression of the power system safety domain model is:

[0137]

[0138] wherein, Ω SS is the set of comprehensive security domains; Ω T is the set of THSR; Ω V is the set of SVSR; g and f are algebraic equations with respect to I, V, and θ respectively; x is the decision space; C I and C V are hypercuboids formed by branch power flow constraints and node voltage constraints respectively; are the active power constraint and reactive power constraint of the control variable respectively; P i and Q i are the active power injection and reactive power injection of node i respectively; and are the upper and lower limits of active power injection respectively; and are the upper and lower limits of reactive power injection respectively.

[0139] In this embodiment, in the N-k complex fault constraint model solving module 003, the linear chance constraint expression is:

[0140]

[0141] wherein, are the coefficients of the hyperplane expression respectively; Pr(·) is the probability of constraint compliance; and are the confidence levels for the upper and lower limits of branch power and the upper and lower limits of node voltage to hold under the N-k condition respectively.

[0142] In this embodiment, in the security-constrained economic dispatch model construction module 004, the expression of the security-constrained economic dispatch model is:

[0143]

[0144] wherein, I B , I G and I L are the sets of nodes, generator sets, and branches respectively; I R is the set of new energy nodes; PG i and QG i are the active and reactive output powers of the generator at node i respectively; PD i and QD i are the active and reactive powers of the load at node i respectively; F is the objective function value to be solved; V k is the voltage of node k; PG i are the upper and lower limits of the active power output of the generator respectively; QG i are the upper and lower limits of the reactive power output of the generator; P i , ΔP i are the actual output, predicted output and power adjustment amount of the generator at node i respectively; Q i , ΔQ i are the reactive power output, predicted reactive power output and reactive power adjustment amount of the generator at node i respectively; ρ i is the power generation unit price; l is a branch; j is a node; are the introduced slack variables respectively; N b is the number of nodes.

[0145] In this embodiment, in the optimal scheduling scheme acquisition module 005, during the process of solving the security-constrained economic dispatch model by using the set solution strategy, a set confidence level is set for the faults with a set occurrence probability, and the problem scale is reduced by using the active constraint identification technology, so as to reduce the conservatism of the optimization result.

[0146] It should be noted that the information interaction, execution process, etc. among the above-mentioned system modules, due to being based on the same concept as the method embodiment in Embodiment 1 of the present application, bring the same technical effects as the method embodiment of the present application. For specific content, reference can be made to the description in the method embodiment shown above in the present application, and details will not be repeated here.

[0147] Embodiment 3

[0148] Embodiment 3 of the present invention provides a non-transitory computer-readable storage medium, in which a program code of an economic dispatch method for a power system considering N-k complex line-break faults is stored, and the program code includes instructions for executing an economic dispatch method for a power system considering N-k complex line-break faults in Embodiment 1 or any possible implementation manner thereof.

[0149] The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center integrating one or more available media. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (SSD)), etc.

[0150] Embodiment 4

[0151] Embodiment 4 of the present invention provides an electronic device, including: a memory and a processor;

[0152] The processor and the memory complete communication with each other through a bus; the memory stores program instructions executable by the processor, and the processor can execute an economic dispatch method for a power system considering N-k complex disconnection faults according to Embodiment 1 or any possible implementation manner thereof by invoking the program instructions.

[0153] Specifically, the processor can be implemented by hardware or software. When implemented by hardware, the processor can be a logic circuit, an integrated circuit, etc.; when implemented by software, the processor can be a general-purpose processor, which is implemented by reading software code stored in the memory. The memory can be integrated in the processor or can exist independently outside the processor.

[0154] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions according to the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable systems. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.).

[0155] Obviously, those skilled in the art should understand that the above-mentioned modules or steps of the present invention can be implemented by a general-purpose computing system. They can be concentrated on a single computing system or distributed on a network composed of multiple computing systems. Optionally, they can be implemented by program code executable by the computing system, so that they can be stored in the storage system and executed by the computing system. And in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules respectively, or multiple modules or steps among them can be made into a single integrated circuit module to implement. Thus, the present invention is not limited to any specific combination of hardware and software.

[0156] Although the present invention has been described in detail above with general descriptions and specific embodiments, on the basis of the present invention, some modifications or improvements can be made, which are obvious to those skilled in the art. Therefore, these modifications or improvements made without departing from the spirit of the present invention all fall within the scope of protection required by the present invention.

Claims

1. A method for economic dispatch of power system considering Nk complex disconnection fault, characterized in that: include: Obtain basic data information of the power system by setting up a data center; According to the basic data information and the power system security domain model, the mapping relationship between the node injection uncertainty and the safety boundary is analyzed and constructed to obtain the Nk complex fault constraint model; The Nk complex fault constraint model is solved by the Cornish-Fisher series method to obtain a linear chance constraint expression; Based on linear opportunity constraints, a safety-constrained economic dispatch model is constructed; Under the condition of satisfying the safety constraint, the safety constraint economic dispatch model is solved by setting a solution strategy to obtain the optimal dispatch solution.

2. The method for economic dispatch of a power system considering Nk complex disconnection faults according to claim 1, characterized in that: The expression of the power system security domain model is: In the formula, Ω SS is the set of comprehensive security domains; Ω T is the set of THSR; Ω V is the set of SVSRs; g and f are algebraic equations about I, V and θ respectively; x is the decision space; C I and C V They are super cuboids composed of branch power flow constraints and node voltage constraints respectively; are the active power constraint and reactive power constraint of the control variable respectively; P i and Q i are the active power injection and reactive power injection of node i respectively; and They are respectively the upper and lower limits of active power injection; and They are the upper and lower limits of reactive power injection respectively.

3. The method for economic dispatch of a power system considering Nk complex disconnection faults according to claim 2, characterized in that: The linear chance constraint expression is: In the formula, are the coefficients of the hyperplane expression respectively; Pr(r(is the probability of constraint compliance; and They are the confidence levels for the establishment of the upper and lower limits of branch power and the upper and lower limits of node voltage under the condition of Nk.

4. The method for economic dispatch of a power system considering Nk complex disconnection faults according to claim 3 is characterized in that: The expression of the safety-constrained economic dispatch model is: In the formula, I B ,I G and I L are the collections of nodes, generator sets and branches respectively; I R is the collection of new energy nodes; PG i and QG i are the active and reactive output power of the generator at node i; PD i and QD i are the active and reactive power of the load at node i respectively; F is the objective function value to be solved; V k is the voltage of node k; PG i They are the upper and lower limits of the active output of the generator respectively; QG i are the upper and lower limits of the reactive power output of the generator respectively; P i , ΔP i are the actual output, predicted output and power adjustment of the generator at node i; Q i , ΔQ i are the reactive power output, predicted reactive power output and reactive power adjustment of the generator at node i respectively; ρ i is the power generation unit price; l is the branch; j is the node; are the introduced slack variables; N b is the number of nodes.

5. The method for economic dispatch of a power system considering Nk complex disconnection faults according to claim 4, characterized in that: In the process of solving the safety-constrained economic dispatch model by using the set solution strategy, a set confidence level is set for the fault with a set probability of occurrence, and the problem scale is reduced by using the active constraint identification technology to reduce the conservatism of the optimization result.

6. An economic dispatch device for a power system considering Nk complex disconnection faults, adopting an economic dispatch method for a power system considering Nk complex disconnection faults as described in any one of claims 1 to 5, characterized in that: include: A basic data information acquisition module is used to acquire basic data information of the power system by setting a data center; An Nk complex fault constraint model construction module is used to parse and construct the mapping relationship between node injection uncertainty and safety boundary according to the basic data information and the power system safety domain model to obtain the Nk complex fault constraint model; An Nk complex fault constraint model solving module, used for solving the Nk complex fault constraint model by using the Cornish-Fisher series method to obtain a linear chance constraint expression; Safety-constrained economic dispatch model building module, used to build a safety-constrained economic dispatch model based on linear opportunity constraints; The optimal scheduling solution acquisition module is used to solve the safety constraint economic scheduling model by setting a solution strategy under the condition of satisfying the safety constraint to obtain the optimal scheduling solution.

7. The economic dispatching device for a power system considering Nk complex disconnection faults according to claim 6, characterized in that: In the Nk complex fault constraint model construction module, the expression of the power system security domain model is: In the formula, Ω SS is the set of comprehensive security domains; Ω T is the set of THSR; Ω V is the set of SVSRs; g and f are algebraic equations about I, V and θ respectively; x is the decision space; C I and C V They are super cuboids composed of branch power flow constraints and node voltage constraints respectively; are the active power constraint and reactive power constraint of the control variable respectively; P i and Q i are the active power injection and reactive power injection of node i respectively; and They are respectively the upper and lower limits of active power injection; and They are the upper and lower limits of reactive power injection respectively.

8. The power system economic dispatching device considering Nk complex disconnection fault according to claim 7 is characterized in that: In the Nk complex fault constraint model solving module, the linear chance constraint expression is: In the formula, are the coefficients of the hyperplane expression respectively; Pr(·) is the probability of constraint compliance; and They are the confidence levels for the establishment of the upper and lower limits of branch power and the upper and lower limits of node voltage under the condition of Nk.

9. The economic dispatching device for a power system considering Nk complex disconnection faults according to claim 8, characterized in that: In the safety-constrained economic dispatch model construction module, the expression of the safety-constrained economic dispatch model is: In the formula, I B ,I G and I L are the collections of nodes, generator sets and branches respectively; I R is the collection of new energy nodes; PG i and QG i are the active and reactive output power of the generator at node i; PD i and QD i are the active and reactive power of the load at node i respectively; F is the objective function value to be solved; V k is the voltage of node k; PG i They are the upper and lower limits of the active output of the generator respectively; QG i are the upper and lower limits of the reactive power output of the generator respectively; P i , ΔP i are the actual output, predicted output and power adjustment of the generator at node i; Q i , ΔQ i are the reactive power output, predicted reactive power output and reactive power adjustment of the generator at node i respectively; ρ i is the power generation unit price; l is the branch; j is the node; are the introduced slack variables; N b is the number of nodes.

10. The economic dispatching device for a power system considering Nk complex disconnection faults according to claim 9, characterized in that: In the optimal scheduling solution acquisition module, in the process of solving the safety-constrained economic scheduling model through the set solution strategy, a set confidence level is set for the fault with a set probability of occurrence, and the problem scale is reduced through the effective constraint identification technology to reduce the conservatism of the optimization result.

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