Evaluation and verification method for grid-connected autonomous peak regulation of newly-added planning unit of electric power system

Abstract

The invention discloses an evaluation and verification method for grid-connected autonomous peak regulation of a newly-added planning unit of a power system. The method comprises the following steps: acquiring system data of the power system; according to the system data, constructing a daily optimization scheduling model containing the thermal power generating unit paid peak regulation compensation cost; based on the new energy power generation annual typical output curve and the load annual typical power curve, solving and obtaining an annual operation simulation result according to the daily optimization scheduling model; obtaining annual peak regulation data according to the annual operation simulation result; and an autonomous peak regulation principle of the newly-added planning main body is established based on the annual peak regulation data: the newly-added planning unit of the electric power system completes planning based on the autonomous peak regulation principle, an annual power curve and an annual output curve of the newly-added planning unit are acquired, and an annual peak regulation evaluation and verification model is constructed to realize evaluation and verification of grid-connected autonomous peak regulation of the newly-added planning unit of the electric power system. The method solves the problems that at present, a paid peak regulation part is mainly considered when a peak regulation model is established from a thermal power generating unit level, the peak regulation demand evaluated from a net power fluctuation level actually comprises the paid peak regulation part and the free peak regulation part, but the paid peak regulation part and the free peak regulation part cannot be distinguished, it cannot be ensured that a newly-added planning unit does not increase the peak regulation burden of the system, and the peak regulation efficiency is low. And absorption of original new energy power generation is influenced.

Description

Technical Field

[0001] The present invention relates to the field of power system operation technology for power system expansion planning, and in particular to an evaluation and verification method for grid-connected autonomous peak regulation of a newly added planning unit of a power system. Background Art

[0002] As the proportion of renewable energy generation in the power system increases, its access brings an increasing operational burden to the power system. Therefore, the planning stage needs to solve the problem of flexible resource allocation such as frequency regulation and peak regulation. In order to add new planning units without increasing the peak regulation burden of the system, a development model of self-load configuration of renewable energy has emerged. Self-load means that during the construction and operation of new energy projects, medium- and long-term contracts are signed with large electricity users to ensure the reliable consumption of renewable energy generation and to explore flexible adjustment resources on the load side as much as possible.

[0003] Renewable energy generation has the characteristics of uncertainty, volatility and intermittency, and the impact of its output uncertainty needs to be considered in the planning stage. With the increasing number of renewable energy sources in the power system, it is difficult to fully absorb renewable energy generation. It will be more practical to explore new energy planning methods that meet a certain absorption rate. In order to reduce the operating burden of renewable energy planning on the power grid, many studies have been conducted on the joint planning of renewable energy generation and various flexible resources such as energy storage and thermal power units.

[0004] In the existing planning methods, new flexible resources are used together with the original flexible resources of the system to deal with the fluctuation and absorption of new energy, resulting in the new renewable energy power generation occupying the original flexible resources of the system. The lack of peak-shaving resources is one of the main reasons for the current abandonment of new energy in my country. The peak-shaving demand of the power system can be quantitatively evaluated from two aspects. First, the peak-shaving demand of the system is evaluated according to the fluctuation of net load. Second, the paid peak-shaving demand of the system is evaluated by using the accumulated deep peak-shaving amount of thermal power units. In summary, the establishment of the peak-shaving model at the level of thermal power units mainly considers the paid peak-shaving part. The peak-shaving demand evaluated at the level of net power fluctuation actually includes paid peak-shaving and unpaid peak-shaving, but it is impossible to distinguish between paid and unpaid peak-shaving parts.

[0005] Therefore, it is urgent to propose an evaluation and verification method that can comprehensively consider the paid peak-shaving and unpaid peak-shaving of thermal power, and ensure that the newly added planning units do not increase the system peak-shaving burden and do not affect the absorption of the original new energy power generation. Summary of the invention

[0006] The present invention provides an evaluation and verification method for grid-connected autonomous peak-shaving of a newly added planning unit in an electric power system to overcome the above-mentioned technical problems.

[0007] In order to achieve the above object, the technical solution of the present invention is:

[0008] An evaluation and verification method for grid-connected autonomous peak load regulation of a newly added planning unit in a power system comprises the following steps:

[0009] S1: Obtain system data of the power system;

[0010] The system data at least includes system topology parameters, power supply parameters, annual typical output curve of new energy power generation and annual typical power curve of load;

[0011] S2: Construct a daily optimal dispatching model including paid peak load compensation costs of thermal power units based on system data;

[0012] The daily optimization scheduling model includes a daily optimization scheduling objective function and scheduling constraints;

[0013] S3: Based on the annual typical output curve of renewable energy power generation and the annual typical power curve of load, solve and obtain the annual operation simulation results according to the daily optimization dispatch model;

[0014] The annual operation simulation results at least include the annual peak load period, annual valley load period and wind curtailment period of the power system;

[0015] And obtain annual peak load regulation data based on annual operation simulation results;

[0016] The annual peak load regulation data includes paid peak load regulation, free peak load regulation and wind power consumption;

[0017] S4: Establish the autonomous peak-shaving principle for newly added planning units based on annual peak-shaving data:

[0018] During the paid peak load period, new planning units are not allowed to supply power to the power system; during the unpaid peak load period, new planning units are allowed to supply power to the power system, and the new planning units do not increase the annual total unpaid peak load demand of the power system; during the wind abandonment period, the power supply of new planning units to the power system is limited;

[0019] S5: The newly added planning unit of the power system completes the planning based on the principle of autonomous peak regulation and obtains its annual power curve and annual output curve;

[0020] S6: Based on the daily optimization dispatch model, the annual daily optimization operation simulation is carried out according to the annual power curve and the annual output curve to obtain new annual peak-shaving data, and the evaluation and verification of the autonomous peak-shaving of the newly planned units connected to the grid of the power system is realized according to the constructed annual peak-shaving evaluation and verification model.

[0021] Furthermore, the expression of the daily optimization scheduling objective function of the daily optimization scheduling model including the paid peak load compensation fee of thermal power units constructed in S2 is:

[0022]

[0023] Where: They represent the output of thermal power units, the startup state variables of the units, and the paid peak-shaving capacity of the thermal power units at the hth gear respectively; Represents the fuel cost of thermal power units; It represents the paid peak load compensation cost of thermal power units. It indicates the cost of starting up a thermal power unit once; Indicates the unit startup status variable; and represents the paid peak-shaving capacity and compensation price of the hth gear of the thermal power unit; t represents the time period index; T represents the total number of time periods for daily scheduling; h represents the paid peak-shaving level index; H represents the total number of paid peak-shaving levels; α i , β i , γ i Both represent the quadratic function coefficients of the power generation cost of thermal power units.

[0024] Furthermore, the dispatch constraint conditions of the daily optimal dispatch model including the paid peak load compensation cost of thermal power units constructed in S2 are:

[0025] Including power system power balance constraints, power system upward and downward rotation reserve constraints, thermal power unit paid peak load capacity constraints, thermal power unit reserve capacity constraints, thermal power unit output constraints and thermal power unit minimum start and stop time constraints;

[0026] The power balance constraint of the power system is

[0027]

[0028] Where: L t represents the sum of the load powers of all nodes in the power system; M represents the number of nodes in the power system; L m,t represents the load power of the mth node; n g Indicates the number of thermal power units in the power system; Indicates the output of thermal power units; Indicates the dispatch output of the original renewable energy power generation;

[0029] The upward and downward spinning reserve constraints of the power system are

[0030]

[0031] Where: and Respectively represent the upward and downward reserve capacity of thermal power units; and They represent the upward and downward reserve requirements of the power system respectively;

[0032] The paid peak load capacity constraint of the thermal power unit is:

[0033]

[0034] Where: Indicates the output of thermal power units; Indicates the starting point of paid peak load regulation capacity of thermal power units; Indicates the starting point of the h-th level paid peak load regulation of thermal power units;

[0035] The reserve capacity constraint of the thermal power unit is

[0036]

[0037] Where: and Indicates the maximum upward and downward reserve capacity of thermal power units; and Indicates the maximum and minimum technical output of thermal power units;

[0038] The output constraint of the thermal power unit is

[0039]

[0040] Where: Indicates the operating state variable of the thermal power unit;

[0041] The minimum start and stop time constraint of the thermal power unit is:

[0042]

[0043] Where: and Indicates the start and stop state variables of the thermal power unit; U i With D i Indicates the minimum start and stop time of thermal power units.

[0044] Furthermore, the S3 specifically includes the following steps:

[0045] S31: Divide the annual load of the power system and the output curve of new energy sources into daily data sets according to date;

[0046] S32: Based on the CPLEX optimization solver, the annual load and renewable energy output curves of the power system in the daily data set are simulated according to the daily optimization scheduling model and the daily operation simulation classification results are output;

[0047] The daily operation simulation classification results include the peak load period, valley load period and wind abandonment period within each day;

[0048] And the valley load period is the paid peak load compensation fee of thermal power units after the optimization scheduling simulation is carried out. The time period with non-zero value;

[0049] The peak load period is a period during which the upward spinning reserve constraint of the power system is a tight constraint;

[0050] S33: splicing the daily operation simulation classification results respectively according to the preset time sequence to obtain the annual operation simulation results;

[0051] The annual operation simulation results include the annual peak load period, annual valley load period and wind curtailment period of the power system;

[0052] S34: Obtain annual peak load regulation data according to annual operation simulation results;

[0053] The annual peak load regulation data includes paid peak load regulation, free peak load regulation and wind power consumption;

[0054] The paid peak load-shaving amount is the paid peak load-shaving compensation fee in the same-day optimization dispatch model The sum of the optimization results; the free peak regulation amount is the sum of the output regulation amounts of thermal power units caused by the net load fluctuation of the power system.

[0055] Furthermore, the newly added planning unit in S4 does not increase the annual total free peak load demand constraint of the power system, including the power consumption constraint during the peak load period of the power system and the power transmission constraint during the valley load period, which is expressed as

[0056]

[0057] Where: T P represents the set of peak load periods of the power system when the total output of thermal power units reaches the upper limit after considering auxiliary service capacity such as reserve; T V represents the set of valley load periods of the power system; P s1,t P represents the power purchased from the grid by the newly added wind-fire-load-storage bundling unit; s2,t Indicates the power delivered by the bundling unit to the grid.

[0058] Furthermore, the autonomous peak-shaving principle of the newly added planning entity is established in S4, which also includes the transmission capacity constraint constructed based on the DC power flow model and the power balance constraint of the power system after the newly added planning unit is connected to the grid;

[0059] The transmission capacity constraint is

[0060] P l =M PTDF ×P

[0061]

[0062] MPTDF =B l AB -1

[0063] Where: P l represents the power flow of the newly added planning unit branch l in the power system; P represents the node injection power vector of the power system, P m,t represents the element of the power system corresponding to node m, that is, the difference between the power output of the power source connected to node m and the load power, and represents the power of the generator at node m; represents the new energy output of node m; P represents the power flow transmission limit of the newly added planning unit branch l in the power system; PTDF represents the power transfer matrix; A represents the association matrix of the network topology of the power system; B represents the branch admittance matrix of the power system ignoring the branch conductance;

[0064] The power balance constraint of the power system after the newly added planning unit is connected to the grid is:

[0065]

[0066] Furthermore, the annual peak load evaluation and verification model constructed in S6 is expressed as

[0067]

[0068] Where: and It represents the output of thermal power units before and after the newly added planning unit of the power system is connected to the grid; n g Indicates the number of thermal power units in the power system; T N It represents the time period set of the power system except the peak load period and the valley load period, that is, the normal period set; Indicates the annual consumption of existing new energy; Indicates the dispatching output of existing renewable energy power generation.

[0069] Beneficial effect: The present invention provides an evaluation and verification method for the autonomous peak-shaving of the grid-connected newly planned units in an electric power system. By comprehensively considering the paid peak-shaving and unpaid peak-shaving of thermal power, an autonomous peak-shaving principle of the newly added planning subject is established to realize the planning of the grid-connected newly planned units in the electric power system, and obtain its annual power curve and annual output curve; based on the daily optimization scheduling model, an annual daily optimization operation simulation is performed according to the annual power curve and the annual output curve to obtain new annual peak-shaving data, and an evaluation and verification of the autonomous peak-shaving of the grid-connected newly planned units in the electric power system is realized according to the constructed annual peak-shaving evaluation and verification model, which effectively ensures that when the newly added planning units in the electric power system are connected to the grid, the peak-shaving burden of the power grid system is not increased, and the absorption of the original new energy power generation is not affected, thereby realizing the joint planning of new energy power generation and various flexible resources such as energy storage and thermal power units. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0071] Figure 1 A flow chart of an evaluation and verification method for grid-connected autonomous peak load regulation of a newly added planning unit in a power system of the present invention;

[0072] Figure 2 The load curve and wind power curve diagram in this embodiment;

[0073] Figure 3 The upward and downward climbing curves of the system before and after the Internet access are newly added in this embodiment;

[0074] Figure 4 The first-level paid peak-shaving demand curve of the power system before and after the planning unit is added in this embodiment;

[0075] Figure 5 The curve diagram of the secondary paid peak load demand of the power system before and after the planning unit is added in this embodiment;

[0076] Figure 6 This is a core flow chart of the evaluation and verification method for the grid-connected autonomous peak load regulation of a newly added planning unit in the power system in this embodiment. DETAILED DESCRIPTION

[0077] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0078] This embodiment provides a method for evaluating and verifying the grid-connected autonomous peak load regulation of a newly added planning unit in a power system, such as Figure 1 As shown, the following steps are included:

[0079] S1: Obtain system data of the power system;

[0080] The system data at least includes system topology parameters, power supply parameters, annual typical output curve of new energy power generation and annual typical power curve of load;

[0081] Specifically, the system topology parameters include grid node numbers and types, branch connection relationships, transmission line parameters, and branch power constraints;

[0082] The power supply parameters include rated power, minimum start and stop time, operating cost and ramp rate;

[0083] S2: Construct a daily optimal dispatching model including paid peak load compensation costs of thermal power units based on system data;

[0084] The daily optimization scheduling model includes a daily optimization scheduling objective function and scheduling constraints;

[0085] The expression of the daily optimization scheduling objective function of the daily optimization scheduling model constructed with paid peak load compensation for thermal power units is:

[0086]

[0087] Where: They represent the output of thermal power units, the startup state variables of the units, and the paid peak-shaving capacity of the thermal power units at the hth gear respectively; Represents the fuel cost of thermal power units; It represents the paid peak load compensation cost of thermal power units. It indicates the cost of starting up a thermal power unit once; Indicates the unit startup status variable; and It represents the paid peak load regulation capacity and compensation price of the thermal power unit at level h;

[0088] t represents the time period index; T represents the total number of time periods for daily scheduling; h represents the paid peak load level index; H represents the total paid peak load level; αi , β i , γ i Both represent the quadratic function coefficients of the power generation cost of thermal power units;

[0089] The dispatching constraints of the daily optimal dispatching model including the paid peak-shaving compensation costs of thermal power units are constructed, including power system power balance constraints, power system upward and downward rotation reserve constraints, paid peak-shaving capacity constraints of thermal power units, reserve capacity constraints of thermal power units, output constraints of thermal power units, and minimum start-stop time constraints of thermal power units;

[0090] The power balance constraint of the power system is

[0091]

[0092] Where: L t represents the sum of the load powers of all nodes in the power system; M represents the number of nodes in the power system; L m,t represents the load power of the mth node; n g Indicates the number of thermal power units in the power system; Indicates the output of thermal power units; Indicates the dispatch output of the original renewable energy power generation;

[0093] The upward and downward spinning reserve constraints of the power system are

[0094]

[0095] Where: and Respectively represent the upward and downward reserve capacity of thermal power units; and Respectively represent the upward and downward reserve requirements of the power system; and It is a tightly constrained period, i.e., the peak load period;

[0096] The paid peak load capacity constraint of the thermal power unit is:

[0097]

[0098] Where: Indicates the output of thermal power units; Indicates the starting point of paid peak load regulation capacity of thermal power units; Indicates the starting point of the h-th level paid peak load regulation of thermal power units;

[0099] The reserve capacity constraint of the thermal power unit is

[0100]

[0101] Where: and Indicates the maximum upward and downward reserve capacity of thermal power units; and Indicates the maximum and minimum technical output of thermal power units;

[0102] The output constraint of the thermal power unit is

[0103]

[0104] Where: Indicates the operating state variable of the thermal power unit;

[0105] The minimum start and stop time constraint of the thermal power unit is:

[0106]

[0107] Where: and Indicates the start and stop state variables of the thermal power unit; U i With D i Indicates the minimum start and stop time of thermal power units;

[0108] S3: Based on the annual typical output curve of renewable energy power generation and the annual typical power curve of load, solve and obtain the annual operation simulation results according to the daily optimization scheduling model, such as Figure 6 As shown;

[0109] The annual operation simulation results at least include the annual peak load period, annual valley load period and wind curtailment period of the power system;

[0110] And obtain annual peak load regulation data based on annual operation simulation results;

[0111] The annual peak load regulation data includes paid peak load regulation, free peak load regulation and wind power consumption;

[0112] The specific steps include:

[0113] S31: Divide the annual load of the power system and the output curve of new energy sources into daily data sets according to date;

[0114] S32: Based on the CPLEX optimization solver, the annual load and renewable energy output curves of the power system in the daily data set are simulated according to the daily optimization scheduling model and the daily operation simulation classification results are output;

[0115] The daily operation simulation classification results include the peak load period, valley load period and wind abandonment period within each day;

[0116] And the valley load period is the paid peak load compensation fee of thermal power units after the optimization scheduling simulation is carried out. The time period with non-zero value;

[0117] The peak load period is a period during which the upward spinning reserve constraint of the power system is a tight constraint;

[0118] S33: splicing the daily operation simulation classification results respectively according to the preset time sequence to obtain the annual operation simulation results;

[0119] The annual operation simulation results include the annual peak load period, annual valley load period and wind curtailment period of the power system;

[0120] S34: Obtain annual peak load regulation data according to annual operation simulation results;

[0121] The annual peak load regulation data includes paid peak load regulation, free peak load regulation and wind power consumption;

[0122] The paid peak load-shaving amount is the paid peak load-shaving compensation fee in the same-day optimization dispatch model The sum of the optimization results of; the free peak load regulation is the sum of the output regulation of thermal power units caused by the net load fluctuation of the power system;

[0123] In this embodiment, a comprehensive analysis of the data throughout the year is conducted to verify whether the proposed method is universal throughout the year and to ensure that the conclusion is not affected by the bias of short-term samples. The data throughout the year may show changes in load patterns in different time periods (such as seasonal differences, differences between working days and holidays) to improve the applicability of the results.

[0124] S4: Establish the autonomous peak-shaving principle for new planning entities based on annual peak-shaving data:

[0125] During the paid peak load period, new planning units are not allowed to supply power to the power system; during the unpaid peak load period, new planning units are allowed to supply power to the power system, and the new planning units do not increase the annual total unpaid peak load demand of the power system; during the wind abandonment period, the power supply of new planning units to the power system is limited;

[0126] Specifically, in order to prevent the newly added planning units from increasing the system's paid peak-shaving burden, the power consumption and transmission power of the newly added planning units during the system's peak and valley load periods must meet the following two constraints, namely, the newly added planning units do not increase the annual total unpaid peak-shaving demand for the power system, including the power consumption constraint during the peak load period and the transmission power constraint during the valley load period, and the expression is:

[0127]

[0128] Where: T P represents the set of peak load periods of the power system when the total output of thermal power units reaches the upper limit after considering auxiliary service capacity such as reserve; T Vrepresents the set of valley load periods (deep peak regulation of thermal power units) of the power system; P s1,t P represents the power purchased from the grid by the newly added wind-fire-load-storage bundling unit; s2,t Indicates the power delivered by the bundling unit to the grid;

[0129] Specifically, the autonomous peak-shaving principle of the newly added planning subject (newly added planning unit) is established in S4, which also includes the transmission capacity constraint constructed based on the DC power flow model and the power balance constraint of the power system after the newly added planning unit is connected to the grid, and the newly added planning unit is the newly added "wind-fire-load-storage bundling unit";

[0130] In this embodiment, the impact of the newly added planning unit on the original new energy consumption after grid connection is reflected in two aspects, namely, the occupation of system peak-shaving resources and the original new energy transmission channel. In order not to affect the consumption of the original new energy in the system, the transmission capacity constraint must also be considered in the proposed model of the autonomous peak-shaving principle. That is, based on the DC power flow model, the matrix form of the transmission capacity constraint is expressed as

[0131] P l =M PTDF ×P

[0132]

[0133] M PTDF =B l AB -1

[0134] Where: P l represents the power flow of the newly added planning unit branch l in the power system; P represents the node injection power vector of the power system, P m,t represents the element of the power system corresponding to node m, that is, the difference between the power output of the power source connected to node m and the load power, and represents the power of the generator at node m; represents the new energy output of node m; P represents the power flow transmission limit of the newly added planning unit branch l in the power system; PTDF represents the power transfer matrix; A represents the association matrix of the network topology of the power system; B represents the branch admittance matrix of the power system ignoring the branch conductance;

[0135] The power balance constraint of the power system after the newly added planning unit is connected to the grid is:

[0136]

[0137] S5: The newly added planning unit of the power system completes the planning based on the principle of autonomous peak regulation and obtains its annual power curve and annual output curve;

[0138] S6: Based on the daily optimization dispatch model, the annual daily optimization operation simulation is carried out according to the annual power curve and the annual output curve to obtain new annual peak-shaving data, and the evaluation and verification of the autonomous peak-shaving of the newly planned units connected to the grid of the power system is realized according to the constructed annual peak-shaving evaluation and verification model.

[0139] Specifically, this embodiment aims at the problem of new energy power abandonment caused by insufficient peak-shaving resources, comprehensively considers the paid peak-shaving and unpaid peak-shaving of thermal power, proposes the concept and operation principle of autonomous peak-shaving as the grid-connected marginal conditions of the newly added planning unit, and constructs an annual demand assessment model for paid peak-shaving and unpaid peak-shaving of the power system, that is, the constructed annual peak-shaving assessment verification model, which is expressed as

[0140]

[0141] Where: and It represents the output of thermal power units before and after the newly added planning unit of the power system is connected to the grid; n g Indicates the number of thermal power units in the power system; T N It represents the time period set of the power system except the peak load period and the valley load period, that is, the normal period set; Indicates the annual consumption of existing new energy; Indicates the dispatch output of the original renewable energy power generation. In this embodiment, free peak regulation refers to the process of changing the output of the generator set to adapt to the change of power load. In this embodiment, the change in the output of the thermal power unit outside the paid peak regulation period is defined as the free peak regulation demand of the system. Therefore, the constraint that the newly added planning unit does not increase the free peak regulation demand can be expressed as not increasing the total output regulation of the system thermal power units after the newly added planning unit is connected, and the system wind abandonment situation can also be obtained through annual operation simulation.

[0142] The specific implementation cases of this embodiment are as follows:

[0143] Based on the IEEE 118-node system, a case analysis was carried out. The case includes 66 thermal power units, 7 hydropower units, and 3 wind farms connected to nodes 36, 69, and 77 respectively. The power system load and wind power curves are shown in Figure 2. Figure 2 And by conducting annual operation simulation of the power system, the original paid peak-shaving period of the system is obtained.

[0144] The evaluation indicators of the autonomous peak-shaving principle proposed in this embodiment include: system paid peak-shaving amount, unpaid peak-shaving amount (i.e., power ramping amount of thermal power units) and wind curtailment amount. For this purpose, the evaluation obtained various autonomous peak-shaving evaluation indicators before and after the new wind-fire-load-storage planning unit was connected to the system under the 10% wind curtailment scenario, as shown in Table 1;

[0145] Table 1. Peak and valley times

[0146]

[0147]

[0148] After the verification converges, the three indicators corresponding to the planning scheme of this embodiment are within the standard, that is, the autonomous peak-shaving requirements are met. Since the termination condition of the evaluation test is that all indicators are within the standard, when the worst indicator is close to the limit boundary, the evaluation test is stopped. In the example, when the autonomous peak-shaving requirements are met and converged, the abandoned wind volume is closest to the limit indicator (reduced by 0.02%), and the other two indicators are slightly better than before planning, as shown in Table 2;

[0149] Table 2. Autonomous peak load verification results

[0150]

[0151] like Figure 3 It is the upward and downward climbing conditions of the thermal power units before and after the newly added planning units are connected to the grid within a certain period of time (one week). Figures 4 to 5 The first-level and second-level paid peak-shaving demands of the system before and after the newly added planning unit is connected to the grid are shown. Since the net power of the newly added bundled unit is allowed to be connected to the grid during the non-paid peak-shaving period, the system's up / down climbing power changes slightly, but the annual total index does not increase. Since the online power of the newly added bundled unit changes the load curve of the original system, the first-level paid peak-shaving capacity of the system also decreases slightly. In general, the access of the newly added bundled unit will affect the system peak-shaving demand at different times, but it can ensure that the peak-shaving demand does not increase throughout the year, that is, it meets the autonomous peak-shaving requirements. That is, the new paid peak-shaving capacity, unpaid peak-shaving demand, and wind power consumption obtained through planning are compared with the existing old paid peak-shaving capacity, unpaid peak-shaving demand, and wind power consumption, thereby illustrating the effectiveness of the method of this embodiment. Figure 4 It shows that the power system mainly has the first-level paid peak-shaving demand, and the peak-shaving demand before and after planning has not changed in most periods. Figure 5It can be seen that: only some periods of time have deep (secondary) peak-shaving needs, because the minimum output of the thermal power units in the IEEE 118 node system is relatively small, and the starting point of paid peak-shaving is relatively low. This embodiment comprehensively considers the paid peak-shaving and unpaid peak-shaving of thermal power, and establishes the autonomous peak-shaving principle of the newly added planning subject to realize the planning of the grid connection of the newly added planning unit of the power system, and obtain its annual power curve and annual output curve; based on the daily optimization scheduling model, the annual daily optimization operation simulation is carried out according to the annual power curve and the annual output curve to obtain new annual peak-shaving data, and the evaluation and verification of the autonomous peak-shaving of the grid connection of the newly added planning unit of the power system is realized according to the constructed annual peak-shaving evaluation and verification model, which effectively ensures that when the newly added planning unit of the power system is connected to the grid, it does not increase the peak-shaving burden of the power grid system, and does not affect the absorption of the original new energy power generation, thereby realizing the joint planning of new energy power generation and various flexible resources such as energy storage and thermal power units.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating and verifying the grid-connected autonomous peak load regulation of a newly added planning unit in a power system, characterized in that: The specific steps include: S1: Obtain system data of the power system; The system data at least includes system topology parameters, power supply parameters, annual typical output curve of new energy power generation and annual typical power curve of load; S2: Construct a daily optimal dispatching model including paid peak load compensation costs of thermal power units based on system data; The daily optimization scheduling model includes a daily optimization scheduling objective function and scheduling constraints; S3: Based on the annual typical output curve of renewable energy power generation and the annual typical power curve of load, solve and obtain the annual operation simulation results according to the daily optimization dispatch model; The annual operation simulation results at least include the annual peak load period, annual valley load period and wind curtailment period of the power system; And obtain annual peak load regulation data based on annual operation simulation results; The annual peak load regulation data includes paid peak load regulation, free peak load regulation and wind power consumption; S4: Establish the autonomous peak-shaving principle for newly added planning units based on annual peak-shaving data: During the paid peak load period, new planning units are not allowed to supply power to the power system; during the unpaid peak load period, new planning units are allowed to supply power to the power system, and the new planning units do not increase the annual total unpaid peak load demand of the power system; during the wind abandonment period, the power supply of new planning units to the power system is limited; S5: enables the newly added planning unit of the power system to complete the planning based on the principle of autonomous peak regulation, and obtain its annual power curve and annual output curve; S6: Based on the daily optimization dispatch model, the annual daily optimization operation simulation is carried out according to the annual power curve and the annual output curve to obtain new annual peak-shaving data, and the evaluation and verification of the autonomous peak-shaving of the newly planned units connected to the grid of the power system is realized according to the constructed annual peak-shaving evaluation and verification model.

2. The evaluation and verification method for grid-connected autonomous peak load regulation of a newly added planning unit in a power system according to claim 1, characterized in that: The expression of the daily optimization scheduling objective function of the daily optimization scheduling model including the paid peak load compensation fee of thermal power units constructed in S2 is: Where: They represent the output of thermal power units, the startup state variables of the units, and the paid peak-shaving capacity of the thermal power units at the hth gear respectively; It represents the fuel cost of thermal power units; It represents the paid peak load compensation cost of thermal power units. It indicates the cost of starting up a thermal power unit once; Indicates the unit startup status variable; and It represents the paid peak load regulation capacity and compensation price of the thermal power unit at level h; t represents the time period index; T represents the total number of time periods for daily scheduling; h represents the paid peak load level index; H represents the total paid peak load level; α i , β i , γ i Both represent the quadratic function coefficients of the power generation cost of thermal power units.

3. The evaluation and verification method for grid-connected autonomous peak load regulation of a newly added planning unit in a power system according to claim 2, characterized in that: The dispatch constraints of the daily optimal dispatch model including the paid peak load compensation costs of thermal power units constructed in S2, Including power system power balance constraints, power system upward and downward rotation reserve constraints, thermal power unit paid peak load capacity constraints, thermal power unit reserve capacity constraints, thermal power unit output constraints and thermal power unit minimum start and stop time constraints; The power balance constraint of the power system is Where: L t represents the sum of the load powers of all nodes in the power system; M represents the number of nodes in the power system; L m,t represents the load power of the mth node; n g Indicates the number of thermal power units in the power system; Indicates the output of thermal power units; Indicates the dispatch output of the original renewable energy power generation; The upward and downward spinning reserve constraints of the power system are Where: and Respectively represent the upward and downward reserve capacity of thermal power units; and They represent the upward and downward reserve requirements of the power system respectively; The paid peak load capacity constraint of the thermal power unit is: Where: Indicates the output of thermal power units; Indicates the starting point of paid peak load regulation capacity of thermal power units; Indicates the starting point of the h-th level paid peak load regulation of thermal power units; The reserve capacity constraint of the thermal power unit is Where: and Indicates the maximum upward and downward reserve capacity of thermal power units; and Indicates the maximum and minimum technical output of thermal power units; The output constraint of the thermal power unit is Where: Indicates the operating state variable of the thermal power unit; The minimum start and stop time constraint of the thermal power unit is: Where: and Indicates the start and stop state variables of the thermal power unit; U i With D i Indicates the minimum start and stop time of thermal power units.

4. The evaluation and verification method for grid-connected autonomous peak load regulation of a newly added planning unit in a power system according to claim 3, characterized in that: The S3 specifically includes the following steps: S31: Divide the annual load of the power system and the output curve of new energy sources into daily data sets according to date; S32: Based on the CPLEX optimization solver, the annual load and renewable energy output curves of the power system in the daily data set are simulated according to the daily optimization scheduling model and the daily operation simulation classification results are output; The daily operation simulation classification results include the peak load period, valley load period and wind abandonment period within each day; And the valley load period is the paid peak load compensation fee of thermal power units after the optimization scheduling simulation is carried out. The time period with non-zero value; The peak load period is a period during which the upward spinning reserve constraint of the power system is a tight constraint; S33: splicing the daily operation simulation classification results respectively according to the preset time sequence to obtain the annual operation simulation results; The annual operation simulation results include the annual peak load period, annual valley load period and wind curtailment period of the power system; S34: Obtain annual peak load regulation data according to annual operation simulation results; The annual peak load regulation data includes paid peak load regulation, free peak load regulation and wind power consumption; The paid peak load-shaving amount is the paid peak load-shaving compensation fee in the same-day optimization dispatch model The sum of the optimization results; the free peak regulation amount is the sum of the output regulation amounts of thermal power units caused by the net load fluctuation of the power system.

5. The evaluation and verification method for grid-connected autonomous peak load regulation of a newly added planning unit in a power system according to claim 4, characterized in that: The newly added planning unit in S4 does not increase the annual total free peak load demand constraint of the power system, including the power consumption constraint during the peak load period of the power system and the power transmission constraint during the valley load period. Its expression is: Where: T P represents the set of peak load periods of the power system when the total output of thermal power units reaches the upper limit after considering auxiliary service capacity such as reserve; T V represents the set of valley load periods of the power system; P s1,t P represents the power purchased from the grid by the newly added wind-fire-load-storage bundling unit; s2,t Indicates the power delivered by the bundling unit to the grid.

6. The evaluation and verification method for grid-connected autonomous peak load regulation of a newly added planning unit in a power system according to claim 4, characterized in that: The autonomous peak-shaving principle of the newly added planning entities is established in S4, which also includes the transmission capacity constraints based on the DC power flow model and the power balance constraints of the power system after the newly added planning units are connected to the grid; The transmission capacity constraint is P l =M PTDF ×P M PTDF =B l AB -1 Where: P l represents the power flow of the newly added planning unit branch l in the power system; P represents the node injection power vector of the power system, P m,t represents the element of the power system corresponding to node m, that is, the difference between the power output of the power source connected to node m and the load power, and represents the power of the generator at node m; represents the new energy output of node m; P represents the power flow transmission limit of the newly added planning unit branch l in the power system; TDF represents the power transfer matrix; A represents the association matrix of the network topology of the power system; B represents the branch admittance matrix of the power system ignoring the branch conductance; The power balance constraint of the power system after the newly added planning unit is connected to the grid is:

7. The evaluation and verification method for grid-connected autonomous peak load regulation of a newly added planning unit in a power system according to claim 4, characterized in that: The annual peak load assessment verification model constructed in S6 is expressed as Where: and It represents the output of thermal power units before and after the newly added planning unit of the power system is connected to the grid; n g Indicates the number of thermal power units in the power system; T N It represents the time period set of the power system except the peak load period and the valley load period, that is, the normal period set; Indicates the annual consumption of existing new energy sources; Indicates the dispatching output of existing renewable energy power generation.

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