A method and system for evaluating the new energy carrying capacity of a power system

Abstract

The present invention provides a method and system for evaluating the carrying capacity of new energy in an electric power system, including: obtaining the influencing factors, equipment data and operation data related to each node of the new energy unit of the electric power system within the evaluation time; based on the equipment data and operation data related to each node and the predetermined new energy carrying capacity evaluation model, the control variable method is used to perform flow calculations on the influencing factors related to each node, and the sensitivity of the influencing factors to the absorption amount when the active power is adjusted to the maximum value is determined; at least one influencing factor corresponding to the sensitivity is selected from large to small to evaluate the carrying capacity of new energy in the electric power system; the present invention uses the new energy carrying capacity evaluation model to evaluate the problem of insufficient absorption capacity of new energy. At the same time, the present invention also finds the influencing factors of the carrying capacity of new energy in the electric power system, providing guidance for the planning and operation of new energy and future electric power systems.

Description

Technical Field

[0001] The present invention belongs to the technical field of planning of power systems containing new energy, and in particular, relates to a method and system for evaluating the new energy carrying capacity of a power system. Background Art

[0002] The basic task of transmission network planning is to determine the location, capacity, time and other factors of new lines based on the existing grid structure for a given load level and power generation resources in the future planning year, so as to meet the future load demand of the power grid and the safety and reliability requirements of the system.

[0003] With the global attention to environmental issues and the demand for sustainable development, achieving energy structure transformation through the replacement of traditional fossil energy with renewable energy has become an important development goal of all countries, and the penetration rate of renewable energy in the power system has also increased rapidly. From 2009 to 2018, China's total installed capacity of renewable energy increased from 17.6GW to 358.9GW, and by the end of 2018, the proportion of renewable energy installed capacity reached 18.9%. In 2008, the proportion of renewable energy installed capacity in Europe and the United States was 3.7% and 2.25% respectively, and in 2017, the ratio increased to 13.5% and 8.47% respectively. At the same time, the impact of renewable energy generation on the power system has gradually been taken seriously, but areas with a high penetration rate of renewable energy have insufficient power system capacity to absorb renewable energy. Summary of the invention

[0004] In order to overcome the above-mentioned deficiencies of the prior art, the present invention proposes a method for evaluating the new energy carrying capacity of a power system, comprising:

[0005] Obtain the influencing factors, equipment data and operation data related to each node of the power system's new energy units within the evaluation period;

[0006] Based on the equipment data and operation data related to each node and the predetermined new energy carrying capacity assessment model, the control variable method is used to perform power flow calculations on the influencing factors related to each node to determine the sensitivity of the influencing factors to the absorption capacity when the active power is adjusted to the maximum value;

[0007] Select at least one influencing factor corresponding to the sensitivity from large to small to evaluate the new energy carrying capacity of the power system;

[0008] Among them, the new energy carrying capacity assessment model is constructed with the goal of maximizing the absorption of active output of various influencing factors of the new energy unit within the assessment time.

[0009] Preferably, the control variable method is used to perform power flow calculation on the influencing factors related to each node to determine the sensitivity of the influencing factors to the absorption amount when the active power is adjusted to a maximum value, including:

[0010] According to the influencing factors related to each node, the power flow calculation is performed with the actual value of the current influencing factor and the maximum value of other influencing factors to obtain the absorption capacity of the current influencing factor;

[0011] When the actual value is greater than the absorption amount, the sensitivity is determined by the ratio of the actual value of the current influencing factor to the absorption amount;

[0012] When the actual value is less than the absorption capacity, the coefficient of the influencing factor is actually set at a certain step size, the actual value of the current influencing factor is increased based on the set coefficient, and the flow calculation is performed based on the increased actual value of the current influencing factor until the absorption capacity is less than the limit absorption capacity or the coefficient is unreasonable, and the current coefficient is determined to be the sensitivity.

[0013] Preferably, the establishment of the new energy carrying capacity assessment model includes:

[0014] The objective function of the new energy carrying capacity assessment is to maximize the active power output of each influencing factor of the new energy unit within the assessment time, and the constraints of the transmission network flow constraint, transmission line transmission capacity constraint, node voltage amplitude constraint, conventional generator unit output constraint, conventional generator unit ramp rate constraint, renewable energy output constraint and tie line power constraint are the constraints of the new energy carrying capacity assessment.

[0015] Linearizing the constraint conditions of the new energy carrying capacity assessment to obtain linearized constraint conditions;

[0016] Based on the linearized constraints and the objective function of the new energy carrying capacity assessment, a new energy carrying capacity assessment model is established.

[0017] Preferably, the calculation formula of the objective function of the new energy carrying capacity assessment is as follows:

[0018]

[0019] In the formula, F obj The maximum active power consumption of new energy units within the evaluation period is Ψ RE is the set of renewable energy access units, T is the total operation period, It is the active power output of the new energy unit node i at time t.

[0020] Preferably, the calculation formula of the power transmission network flow constraint is as follows:

[0021]

[0022] Where P i,t Q is the active power injected by the new energy unit node i at time t; i,t V is the reactive power injected by the node i of the new energy unit at time t; i,t is the voltage amplitude of the node i of the new energy unit at time t; V j,t is the voltage amplitude of the node j of the new energy unit at time t; θ ij,t G is the voltage phase difference at both ends of the new energy unit line ij at time t; ij is the real part of row i and column j in the node admittance matrix of the new energy unit, B ij is the imaginary part of row i and column j in the node admittance matrix of the new energy unit; B i Represents the set of end nodes of all branches connected to node i by all new energy units;

[0023] The calculation formula of the transmission line transmission capacity constraint is as follows:

[0024]

[0025] In the formula, S ij is the equivalent transmission capacity of branch ij; branch is the collection of transmission lines; P ij,t The active power injected into both ends of the new energy units i and j at time t; Q ij,t is the reactive power injected at both ends of the renewable energy units i and j at time t; T is the total time, and t is any time.

[0026] Preferably, the linearization of the constraint conditions of the new energy carrying capacity assessment to obtain the linearized constraint conditions includes:

[0027] The power flow constraint of the power transmission network and the transmission capacity constraint of the power transmission line are linearized to obtain linearized power flow constraint of the power transmission network and transmission capacity constraint of the power transmission line.

[0028] Preferably, the calculation formula of the linearized power transmission network flow constraint is as follows:

[0029]

[0030] Where P i ' ,t is the active injection power of the linearized new energy unit node i at time t; Q i ' ,t is the reactive injection power of the linearized new energy unit node i at time t; represents the square of the voltage amplitude of node i at time t; represents the square of the voltage amplitude of node j at time t; θ ij,tB is the voltage phase difference at both ends of the new energy unit line ij at time t; i represents the set of terminal nodes of all branches connected to node i by all new energy units; g ii is the real part of row i and column i in the node matrix; b ii is the imaginary part of row i and column i in the node matrix; g ij is the real part of row i and column j in the node matrix; b ij is the imaginary part of the i-th row and j-th column in the node matrix.

[0031] Preferably, the calculation formula of the linearized transmission line transmission capacity constraint is as follows:

[0032]

[0033] In the formula, S ij is the equivalent transmission capacity of branch ij, P ij,t The active power injected into both ends of the new energy units i and j at time t; Q ij,t P is the reactive power injected at both ends of the new energy units i and j at time t; ij Inject active power into the two ends of the new energy units i and j; Q ij Inject reactive power into the two ends of the new energy units i and j.

[0034] Preferably, the influencing factors related to each node of the new energy generating unit of the power system include: the installed capacity of renewable energy, the maximum external power transmission, the voltage amplitude and the climbing ability of the conventional unit.

[0035] Based on the same inventive concept, the present invention also provides a power system new energy carrying capacity assessment system, including: an acquisition module, a calculation module and a determination module;

[0036] The acquisition module is used to acquire influencing factors, equipment data and operation data related to each node of the new energy unit of the power system within the evaluation time;

[0037] The calculation module is used to perform power flow calculations on the influencing factors related to each node using the control variable method based on the equipment data and operation data related to each node and a predetermined new energy carrying capacity assessment model, and determine the sensitivity of the influencing factors to the absorption amount when the active power is adjusted to a maximum value;

[0038] The determination module is used to select at least one influencing factor corresponding to the sensitivity from large to small to evaluate the new energy carrying capacity of the power system;

[0039] Among them, the new energy carrying capacity assessment model is constructed with the goal of maximizing the absorption of active output of each influencing factor within the assessment time.

[0040] Compared with the closest prior art, the present invention has the following beneficial effects:

[0041] The present invention realizes a method and system for evaluating the renewable energy carrying capacity of an electric power system, comprising: obtaining influencing factors, equipment data and operation data related to each node of a renewable energy unit of an electric power system within an evaluation time; based on the equipment data and operation data related to each node and a predetermined renewable energy carrying capacity evaluation model, respectively using a control variable method to perform flow calculations on the influencing factors related to each node, and determining the sensitivity of the influencing factors to the absorption amount when the active power is adjusted to a maximum value; selecting at least one influencing factor corresponding to a sensitivity from large to small to evaluate the renewable energy carrying capacity of the electric power system; wherein the renewable energy carrying capacity evaluation model is constructed with the goal of maximizing the absorption amount of the active output of each influencing factor of the renewable energy unit within the evaluation time; the present invention improves the accuracy of the renewable energy carrying capacity evaluation, and at the same time, the present invention can also find the influencing factors of the renewable energy carrying capacity of the electric power system, and provide guidance for the planning and operation of renewable energy and future electric power systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A schematic diagram of a flow chart of a method for evaluating the new energy carrying capacity of a power system provided by the present invention;

[0043] Figure 2 It is a schematic diagram of a flow chart of the new energy carrying capacity of the power system in an embodiment of the present invention;

[0044] FIG3( a ) is a schematic diagram showing a voltage distribution comparison of an IEEE 14-node system in an embodiment of the present invention;

[0045] FIG3( b ) is a schematic diagram of phase angle comparison of an IEEE 14-node system in an embodiment of the present invention;

[0046] FIG3( c ) is a schematic diagram showing a comparison of branch active power of an IEEE 14-node system in an embodiment of the present invention;

[0047] FIG3( d ) is a schematic diagram of branch reactive power comparison of an IEEE 14-bus system in an embodiment of the present invention;

[0048] FIG4( a ) is a schematic diagram showing a comparison of voltage distribution of an IEEE 39-bus system in an embodiment of the present invention;

[0049] FIG4( b ) is a schematic diagram of phase angle comparison of an IEEE 39-node system in an embodiment of the present invention;

[0050] FIG4( c ) is a schematic diagram of comparing branch active power of an IEEE 39-node system in an embodiment of the present invention;

[0051] FIG4(d) is a schematic diagram of branch reactive power comparison of the IEEE 39-bus system in an embodiment of the present invention;

[0052] FIG5( a ) is a schematic diagram of PV absorption and power cut-off in the load-bearing capacity analysis according to an embodiment of the present invention;

[0053] FIG5( b ) is a schematic diagram of WP absorption and machine cutting in the bearing capacity analysis according to an embodiment of the present invention;

[0054] FIG5( c ) is a schematic diagram of the output of a conventional unit in the load capacity analysis according to an embodiment of the present invention;

[0055] FIG5(d) is a schematic diagram of the transmission power of the tie line in the carrying capacity analysis in an embodiment of the present invention;

[0056] Figure 6 Schematic diagram of node voltage distribution in an embodiment of the present invention;

[0057] FIG. 7( a ) is a schematic diagram of sensitivity analysis of installed capacity of new energy sources in an embodiment of the present invention;

[0058] FIG7( b ) is a schematic diagram of maximum external power sensitivity analysis in an embodiment of the present invention;

[0059] FIG7( c ) is a schematic diagram of a voltage amplitude upper limit sensitivity analysis in an embodiment of the present invention;

[0060] FIG7( d ) is a schematic diagram of a sensitivity analysis of a conventional unit ramp rate in an embodiment of the present invention;

[0061] Figure 8 A schematic diagram of the structure of a power system new energy carrying capacity assessment system provided by the present invention. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0063] Embodiment 1:

[0064] The application principle of the present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0065] like Figure 1 As shown, the method of the embodiment of the present invention includes:

[0066] Step 1: Obtain the influencing factors, equipment data and operation data related to each node of the new energy units in the power system within the evaluation period;

[0067] Step 2: Based on the equipment data and operation data related to each node and the predetermined new energy carrying capacity assessment model, the control variable method is used to perform power flow calculations on the influencing factors related to each node to determine the sensitivity of the influencing factors to the absorption capacity when the active power is adjusted to the maximum value;

[0068] Step 3: Select at least one influencing factor corresponding to the sensitivity from large to small to evaluate the new energy carrying capacity of the power system;

[0069] Among them, the new energy carrying capacity assessment model is constructed with the goal of maximizing the absorption of active output of various influencing factors of the new energy unit within the assessment time.

[0070] In this embodiment, before executing the method for evaluating the new energy carrying capacity of the power system, it is necessary to pre-build a new energy carrying capacity evaluation model, and then evaluate the new energy carrying capacity of the power system based on the new energy carrying capacity evaluation model. The overall process of building a new energy carrying capacity evaluation model and evaluating the new energy carrying capacity of the power system is as follows: Figure 2 As shown, including the following:

[0071] The process of constructing a new energy carrying capacity assessment model includes: taking the maximum active power consumption as the goal, establishing a new energy carrying capacity assessment model considering the power flow of the transmission network with power flow constraints of the transmission network, transmission line transmission capacity constraints, node voltage amplitude constraints, conventional generator output constraints, conventional generator ramp rate constraints, renewable energy output constraints and tie line power constraints as constraints, linearizing the new energy carrying capacity assessment model, and establishing a new energy carrying capacity assessment model based on linear optimal power flow (i.e., new energy carrying capacity assessment model);

[0072] A new energy carrying capacity assessment model based on mathematical programming is established, and the optimization goal is to maximize the active output of renewable energy units within the assessment time, including the following calculation formula:

[0073]

[0074] Among them, RE is the set of renewable energy access units, T is the total operation period, is the active power output of the renewable energy unit at node i at time t.

[0075] The constraints are transmission network flow constraints, transmission line transmission capacity constraints, node voltage amplitude constraints, conventional generator set output constraints, conventional generator set ramp rate constraints, renewable energy output constraints and interconnection line power constraints.

[0076] Transmission network flow constraints:

[0077]

[0078] Where: P i,t and Q i,t are the active and reactive injected power of node i at time t respectively; V i,t is the voltage amplitude of node i at time t; θ ij,t G is the voltage phase difference at both ends of line ij at time t; ij and B ij are the real and imaginary parts of the node admittance matrix in row i and column j, respectively. i represents the set of end nodes of all branches connected to node i. The expression of injected power is:

[0079]

[0080] In the formula, and are respectively the active and reactive outputs of the conventional generator set at node i at time t; and are the active and reactive outputs of the renewable energy unit at node i at time t; and are respectively the active and reactive outputs of the tie line of node i at time t; and are the active and reactive loads of node i at time t respectively.

[0081] Transmission line transmission capacity constraints:

[0082]

[0083] Where: S ij is the equivalent transmission capacity of branch ij, Ψ branch A collection of transmission lines.

[0084] Node voltage amplitude constraint:

[0085]

[0086] Where: V min and V max are the upper and lower limits of the voltage amplitude of node i, bus is the set of all nodes.

[0087] Output constraints of conventional generator sets:

[0088]

[0089] Where: P i G,max is the upper limit of active output of conventional units at node i, Q i G,minand Q i G,max They are respectively the lower and upper limits of reactive power output of conventional units at node i.

[0090] Conventional generator set ramp rate constraints:

[0091]

[0092] Where: P i G,C It is the upper limit of the ramp rate of the conventional unit at node i.

[0093] Renewable energy output constraints:

[0094]

[0095] Where: is the upper limit of active output of the new energy unit at node i at time t.

[0096] Tie line power constraints:

[0097]

[0098] Where: and are the upper and lower limits of the active power interaction of the tie line of node i, and They are respectively the upper and lower limits of reactive power interaction of the tie line at node i.

[0099] Then the new energy carrying capacity assessment model considering the power transmission network flow is linearized.

[0100] Linearize the power flow constraint and replace it with:

[0101]

[0102] Among them, P i ' ,t is the active injection power of the linearized new energy unit node i at time t; Q i ' ,t is the reactive power injected by the linearized renewable energy unit node i at time t; represents the square of the voltage amplitude of node i at time t; represents the square of the voltage amplitude of node j at time t; θ ij,t B is the voltage phase difference at both ends of the new energy unit line ij at time t; i represents the set of terminal nodes of all branches connected to node i by all new energy units; g ii is the real part of row i and column i in the node matrix; b iiis the imaginary part of row i and column i in the node matrix; g ij is the real part of row i and column j in the node matrix; b ij is the imaginary part of the i-th row and j-th column in the node matrix.

[0103] The circular constraint linearization method is used to relax the transmission capacity constraint of the transmission line to realize the linearization of the transmission capacity constraint of the transmission line. The transmission capacity constraint of the transmission line after linearization is:

[0104]

[0105] Where: S ij is the equivalent transmission capacity of branch ij, P ij,t The active power injected into both ends of the new energy units i and j at time t; Q ij,t P is the reactive power injected at both ends of the new energy units i and j at time t; ij Inject active power into the two ends of the new energy units i and j; Q ij Inject reactive power into the two ends of new energy units i and j.

[0106] Step 2 specifically includes: based on the new energy carrying capacity assessment model, the control variable method (only one factor is a variable, and other factors take the maximum value) is used to calculate the absorption capacity; each factor (installed capacity of renewable energy, maximum external power transmission, voltage amplitude, climbing ability of conventional units, etc.) will calculate the absorption capacity according to the actual value, and then use each calculated absorption capacity to compare with the actual value, including: when the actual value is greater than the absorption capacity, the sensitivity is determined by the ratio of the actual value to the absorption capacity;

[0107] When the actual value is less than the absorption capacity, the coefficient of the currently adjusted factor is adjusted, and the calculation is performed again according to the adjusted actual value until it is less than the limit absorption capacity or the coefficient is unreasonable, and the current coefficient is determined as the sensitivity.

[0108] Step 3 specifically includes: when there is an over-configuration of new energy capacity, after determining the ranking based on the sensitivity of each factor, the factors corresponding to the first few (or 1) with the largest ranking are selected as the main factors limiting the new energy carrying capacity, and when the system has an objective voltage regulation capability, the new energy carrying capacity is improved.

[0109] Embodiment 2:

[0110] First, the proposed power flow linearization model of the transmission network is verified. The verification method is to compare the power flow results obtained by the exact power flow algorithm and the linear power flow algorithm in standard examples of different scales. The IEEE 14 and 39 node standard test examples are selected for verification, and the results of some state quantities are displayed. The solution results of the IEEE 14 node are shown in Figure 3(a), Figure 3(b), Figure 3(c) and Figure 3(d), including Figure 3(a) voltage distribution comparison, Figure 3(b) phase angle comparison, Figure 3(c) branch active power comparison and Figure 3(d) branch reactive power comparison. The solution results of the IEEE 39 node are shown in Figure 4(a), Figure 4(b), Figure 4(c) and Figure 4(d), including Figure 4(a) voltage distribution comparison, Figure 4(b) phase angle comparison, Figure 4(c) branch active power comparison and Figure 4(d) branch reactive power comparison. It can be seen that the linear model proposed in the present invention has high calculation accuracy, especially in terms of line active power involving factors such as grid peak-shaving capacity, interconnection line power and conventional unit output. It has very high accuracy and can be used to model the transmission network for evaluating the carrying capacity of new energy, thereby verifying the accuracy of the transmission network linear programming model proposed in the present invention.

[0111] The improved IEEE 30-node test system is selected as an example for analysis, and the basic parameter settings are shown in Table 1.

[0112] Table 1 Parameter settings

[0113]

[0114]

[0115] Among them, node 7 is connected to a photovoltaic power source with a rated capacity of 200MW, and node 11 is connected to a photovoltaic power source with a rated capacity of 300MW; node 19 is connected to a wind power source with a rated capacity of 300MW, and node 29 is connected to a wind power source with a rated capacity of 200MW.

[0116] Under the parameter settings shown in the table above, the load-bearing capacity assessment model is solved. The results show that the total PV consumption is 2188.80MW·h, and the power cut is 486.47MW·h; the total WP consumption is 1681.85MW·h, and the power cut is 1615.57MWh. Among them, the consumption of PV and WP, ​​the output of conventional units, and the power transmission of the interconnection line are shown in Figure 5(a), Figure 5(b), Figure 5(c), and Figure 5(d), respectively. And the node voltage distribution of the system is shown in Figure 6 shown.

[0117] Combination Figure 6As can be seen from Figure 5(a), Figure 5(b), Figure 5(c) and Figure 5(d), under the current parameter settings, there is a certain amount of power outage when photovoltaic and wind power are generated. During most of the time periods when power outages occur, the transmission power of the interconnection line reaches the maximum value, and the voltage of some nodes also reaches the maximum value. The results show that the transmission lines have reached the capacity boundary. Therefore, it can be preliminarily judged that the transmission power and node voltage constraints may constitute the key factors limiting the carrying capacity of renewable energy.

[0118] Next, we will analyze the renewable energy carrying capacity of the transmission network. First, we will conduct a sensitivity analysis on the installed capacity of renewable energy. Based on the settings in Table 1, we will conduct a sensitivity analysis on the four parameters of renewable energy installed capacity factor, maximum external power, voltage amplitude upper limit, and conventional unit ramp rate. We will use the control variable method and verify only one variable at a time. The analysis results are as follows: Figure 7(a)-Figure 7(d) shown.

[0119] Figure 7(a) shows the consumption of renewable energy installed capacity after multiplying the coefficient r, and analyzes the impact of different values ​​of r on the total consumption and the amount of power cuts. It can be seen that when r>0.6, the amount of power cuts begins to increase significantly. When the current parameters and installed location are determined, r within 0.6 is more economical.

[0120] Secondly, a sensitivity analysis is conducted on the maximum value of the external transmission power. Based on the settings listed in Table 1, only the maximum value of the external transmission power is modified, and the results are shown in Figure 7(b). It can be seen that when the maximum value of the external transmission power is less than 300MW, the total consumption of new energy is approximately linearly related to the external transmission power, and when the external transmission power exceeds 300MW, its growth contributes no longer significantly to the consumption of new energy output. When the external transmission power limit is not considered (that is, the upper limit of the external transmission power is a sufficiently large positive number), the maximum power consumption is 4217.59MW·h, and the consumption rate is 70.61%.

[0121] Figure 7(c) shows the verification results of the total amount of new energy consumption when the voltage amplitude upper limit constraint changes. It can be seen that with the gradual relaxation of the voltage amplitude constraint, the total amount of new energy consumption continues to increase, and its upward trend continues until the voltage amplitude upper limit reaches about 1.15. When the voltage amplitude upper limit constraint is not set, the maximum amount of electricity consumed is 4902.52MW·h, and the consumption rate is 82.08%. Obviously, the voltage amplitude upper limit cannot be set to a value as high as 1.15, but this result reflects the effect on the total amount of consumption when the system has sufficient voltage regulation capability. From the perspective of the maximum consumption rate without considering the voltage amplitude constraint, the voltage constraint plays a more obvious role in limiting the carrying capacity of new energy than the transmission power constraint.

[0122] Figure 7(d) shows the impact of the change in the ramping capacity of conventional units on the total power consumption. It should be noted that this constraint includes the change rate constraint of the interconnection line power. It can be seen that the ramping rate constraint will only affect the new energy consumption when the upper limit is lower than 30MW / h, and the impact is not significant. This is mainly because the present invention takes into account both wind power and photovoltaic power, and wind power and photovoltaic power have complementary properties in terms of timing output, so the requirements for the system peak load regulation capacity are not harsh.

[0123] Based on the above analysis, it can be seen that in the calculation example given in the present invention, the configuration of new energy capacity is excessive, and the external power constraint and voltage amplitude constraint are the main factors limiting the carrying capacity of new energy. When the system has objective voltage regulation capabilities, the carrying capacity of new energy will be continuously and objectively improved.

[0124] The above embodiment is only verified for the IEEE 14 and 39 node standard test examples. When the example of the present invention is used to calculate the specific data of other nodes, the main factors limiting the new energy carrying capacity are determined according to the value of the coefficient (such as coefficient r) set at a certain step size in the installed capacity of renewable energy, the maximum external power, the voltage amplitude and the climbing ability of conventional units.

[0125] Embodiment 3:

[0126] Based on the same inventive concept, the present invention also provides a system for evaluating the new energy carrying capacity of an electric power system. Since the principles of these devices for solving technical problems are similar to a method for evaluating the new energy carrying capacity of an electric power system, the repeated parts will not be repeated.

[0127] The system, such as Figure 8 As shown, including:

[0128] Acquisition module, calculation module and determination module;

[0129] The acquisition module is used to acquire influencing factors, equipment data and operation data related to each node of the new energy unit of the power system within the evaluation time;

[0130] The calculation module is used to perform power flow calculations on the influencing factors related to each node using the control variable method based on the equipment data and operation data related to each node and a predetermined new energy carrying capacity assessment model, and determine the sensitivity of the influencing factors to the absorption amount when the active power is adjusted to a maximum value;

[0131] The determination module is used to select at least one influencing factor corresponding to the sensitivity from large to small to evaluate the new energy carrying capacity of the power system;

[0132] Among them, the new energy carrying capacity assessment model is constructed with the goal of maximizing the absorption of active output of each influencing factor within the assessment time.

[0133] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0134] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0135] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0136] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0137] 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 its protection scope. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that after reading the present invention, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the invention, but these changes, modifications or equivalent substitutions are all within the protection scope of the pending claims of the invention.

Claims

1. A method for evaluating the new energy carrying capacity of a power system. It is characterized in that include: Obtain the influencing factors, equipment data and operation data related to each node of the power system's new energy units within the evaluation period; Based on the equipment data and operation data related to each node and the predetermined new energy carrying capacity assessment model, the control variable method is used to perform power flow calculations on the influencing factors related to each node to determine the sensitivity of the influencing factors to the absorption capacity when the active power is adjusted to the maximum value; Select at least one influencing factor corresponding to the sensitivity from large to small to evaluate the new energy carrying capacity of the power system; The new energy carrying capacity assessment model is constructed with the goal of maximizing the active output of each influencing factor of the new energy unit within the assessment time; The control variable method is used to calculate the power flow for the influencing factors related to each node, and the sensitivity of the influencing factors to the absorption amount when the active power is adjusted to the maximum value is determined, including: According to the influencing factors related to each node, the power flow calculation is performed with the actual value of the current influencing factor and the maximum value of other influencing factors to obtain the absorption capacity of the current influencing factor; When the actual value is greater than the absorption amount, the sensitivity is determined by the ratio of the actual value of the current influencing factor to the absorption amount; When the actual value is less than the absorption capacity, the coefficient of the influencing factor is actually set at a certain step size, the actual value of the current influencing factor is increased based on the set coefficient, and the flow calculation is performed based on the increased actual value of the current influencing factor until the absorption capacity is less than the limit absorption capacity or the coefficient is unreasonable, and the current coefficient is determined to be the sensitivity.

2. The method according to claim 1, It is characterized in that The establishment of the new energy carrying capacity assessment model includes: The objective function of the new energy carrying capacity assessment is to maximize the active power output of each influencing factor of the new energy unit within the assessment time, and the constraints of the transmission network flow constraint, transmission line transmission capacity constraint, node voltage amplitude constraint, conventional generator unit output constraint, conventional generator unit ramp rate constraint, renewable energy output constraint and tie line power constraint are the constraints of the new energy carrying capacity assessment. Linearizing the constraint conditions of the new energy carrying capacity assessment to obtain linearized constraint conditions; Based on the linearized constraints and the objective function of the new energy carrying capacity assessment, a new energy carrying capacity assessment model is established.

3. The method according to claim 2, It is characterized in that The calculation formula of the objective function of the new energy carrying capacity assessment is as follows: In the formula, F obj The maximum active power consumption of the new energy unit within the evaluation period is Ψ RE is the set of renewable energy access units, T is the total operation period, is the active power output of the new energy unit node i at time t.

4. The method according to claim 2, It is characterized in that The calculation formula of the transmission network power flow constraint is as follows: Where P i,t Q is the active power injected by the new energy unit node i at time t; i,t V is the reactive power injected by the node i of the new energy unit at time t; i,t is the voltage amplitude of the node i of the new energy unit at time t; V j,t is the voltage amplitude of the node j of the new energy unit at time t; θ ij,t is the voltage phase difference at both ends of the new energy unit line ij at time t; G ij is the real part of row i and column j in the node admittance matrix of the new energy unit, B ij is the imaginary part of row i and column j in the node admittance matrix of the new energy unit; B i Represents the set of end nodes of all branches connected to node i by all new energy units; The calculation formula of the transmission line transmission capacity constraint is as follows: In the formula, S ij is the equivalent transmission capacity of branch ij; branch is the collection of transmission lines; P ij,t The active power injected into both ends of the new energy units i and j at time t; Q ij,t is the reactive power injected at both ends of the renewable energy units i and j at time t; T is the total time, and t is any time.

5. The method according to claim 2, It is characterized in that The linearization of the constraint conditions of the new energy carrying capacity assessment to obtain linearized constraint conditions includes: The power flow constraint of the power transmission network and the transmission capacity constraint of the power transmission line are linearized to obtain linearized power flow constraint of the power transmission network and transmission capacity constraint of the power transmission line.

6. The method according to claim 5, It is characterized in that The linearized power transmission network flow constraint is calculated as follows: Where P' i,t is the active injection power of the linearized new energy unit node i at time t; Q' i,t is the reactive injection power of the linearized new energy unit node i at time t; represents the square of the voltage amplitude of node i at time t; represents the square of the voltage amplitude of node j at time t; θ ij,t is the voltage phase difference at both ends of the new energy unit line ij at time t; B i represents the set of terminal nodes of all branches connected to node i by all new energy units; g ii is the real part of row i and column i in the node matrix; b ii is the imaginary part of row i and column i in the node matrix; g ij is the real part of row i and column j in the node matrix; b ij is the imaginary part of the i-th row and j-th column in the node matrix.

7. The method according to claim 5, It is characterized in that The calculation formula of the linearized transmission line transmission capacity constraint is as follows: In the formula, S ij is the equivalent transmission capacity of branch ij, P ij,t The active power injected into both ends of the new energy units i and j at time t; Q ij,t P is the reactive power injected at both ends of the new energy units i and j at time t; ij Inject active power into the two ends of the new energy units i and j; Q ij Inject reactive power into the two ends of the new energy units i and j.

8. The method according to claim 1, It is characterized in that The influencing factors related to each node of the new energy units in the power system include: the installed capacity of renewable energy, the maximum external power transmission, the voltage amplitude and the climbing ability of conventional units.

9. A power system new energy carrying capacity assessment system, It is characterized in that include: Acquisition module, calculation module and determination module; The acquisition module is used to acquire influencing factors, equipment data and operation data related to each node of the new energy unit of the power system within the evaluation time; The calculation module is used to perform power flow calculations on the influencing factors related to each node using the control variable method based on the equipment data and operation data related to each node and a predetermined new energy carrying capacity assessment model, and determine the sensitivity of the influencing factors to the absorption amount when the active power is adjusted to a maximum value; The determination module is used to select at least one influencing factor corresponding to the sensitivity from large to small to evaluate the new energy carrying capacity of the power system; The new energy carrying capacity assessment model is constructed with the goal of maximizing the active power consumption of each influencing factor within the assessment time. The calculation module uses the control variable method to perform power flow calculation on the influencing factors related to each node, and determines the sensitivity of the influencing factors to the absorption amount when the active power is adjusted to the maximum value, including: According to the influencing factors related to each node, the power flow calculation is performed with the actual value of the current influencing factor and the maximum value of other influencing factors to obtain the absorption capacity of the current influencing factor; When the actual value is greater than the absorption amount, the sensitivity is determined by the ratio of the actual value of the current influencing factor to the absorption amount; When the actual value is less than the absorption capacity, the coefficient of the influencing factor is actually set at a certain step size, the actual value of the current influencing factor is increased based on the set coefficient, and the flow calculation is performed based on the increased actual value of the current influencing factor until the absorption capacity is less than the limit absorption capacity or the coefficient is unreasonable, and the current coefficient is determined to be the sensitivity.

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