Power distribution network toughness improving method considering diesel engine electric power measuring system access

Abstract

A power distribution network toughness improving method considering diesel engine electric power measuring system access comprises the steps that after modeling is conducted according to output characteristics of an electric energy feedback part in a diesel engine electric power measuring system, the supporting capacity of the diesel engine electric power measuring system serving as a distributed flexible resource is quantified from the equipment angle; constructing an optimal dispatching model of the diesel engine electric power dynamometer system oriented to the toughness improvement of the power distribution network; and quantifying the influence degree of grid connection of the diesel engine electric power measuring system on the toughness of the power distribution network according to the toughness evaluation index, establishing an optimal dispatching model of the diesel engine electric power measuring system by taking toughness improvement as a target, and solving through a mixed integer programming method to obtain an optimal configuration strategy of the diesel engine electric power measuring system as distributed energy. According to the method, support is provided for the operation of the power distribution network in a disaster scene through the access of the diesel engine electric power measurement system, the load shedding rate is reduced, the overall operation stability degree is improved, and the influence of the method on the post-disaster recovery capability of the power distribution network is evaluated through the toughness evaluation index.

Description

Technical Field

[0001] The present invention relates to a distribution network resilience improvement technology, specifically a distribution network resilience improvement method taking into account the access of a diesel engine electric dynamometer system. Background Art

[0002] The diesel engine dynamometer system is mainly used for performance testing and debugging of diesel engines before leaving the factory. As a load that simulates the actual operation of the diesel engine, the diesel engine electric dynamometer system is the first choice for testing the diesel engine. However, a large amount of electric energy will be wasted during the use of the diesel engine electric dynamometer system. Therefore, the diesel engine electric dynamometer system is used to feedback electric energy as a distributed flexibility resource to provide support for improving the resilience of the distribution network in disaster scenarios. Summary of the invention

[0003] In view of the problem that there are few related applications of the existing diesel engine electric dynamometer system feedback electric energy as a distributed flexibility resource to provide support for the resilience of the distribution network in disaster scenarios, the present invention proposes a distribution network resilience improvement method considering the access of the diesel engine electric dynamometer system. The access of the diesel engine electric dynamometer system is used to provide support for the operation of the distribution network in disaster scenarios, the load shedding rate is reduced and the overall operation stability is improved, and the impact of the above method on the post-disaster recovery capability of the distribution network is evaluated through resilience evaluation indicators.

[0004] The present invention is achieved through the following technical solutions:

[0005] The present invention relates to a method for improving the resilience of a distribution network taking into account the access of a diesel engine electric dynamometer system, comprising:

[0006] Step 1) Modeling is performed according to the output characteristics of the electric energy feedback part in the diesel engine electric dynamometer system;

[0007] Step 2) quantify the supporting capacity of the diesel engine electric dynamometer system as a distributed flexibility resource from the perspective of equipment, and construct and solve the optimal scheduling model of the diesel engine electric dynamometer system for improving the resilience of the distribution network;

[0008] Step 3) Quantify the impact of the diesel engine electric dynamometer system connected to the grid on the resilience of the distribution network based on the resilience assessment index.

[0009] The resilience assessment index is used to evaluate the performance of the distribution network in dealing with extreme disaster events with low probability but high impact, including:

[0010] 1) Quantify the impact of diesel engine power measurement system access on the resilience of the distribution network, i.e., load loss rate Where: Ω L is the distribution network node set, i is the network node number, t is the time period, is the load loss power of node i in time period t, is the total load of node i in time period t;

[0011] The load loss rate reflects the load interruption loss after a distribution network disaster, and is part of the optimization target in the optimization model in which the diesel engine power dynamometer system participates as a distributed flexibility resource in the post-disaster distribution network resilience enhancement scheduling.

[0012] 2) Average power outage duration index for users Where: i is the user number in the distribution network, N LP is the total number of users, U i is the total power outage time of the user in one year, λ i The total number of power outages for the user in one year; this indicator reflects the time when the distribution network load power supply is insufficient during the fault period, that is, the time from the fault occurrence to the line repair.

[0013] 3) The proportion of dispatchable emergency resources, that is,

[0014] 4) Total loss of distribution network load shedding: in: is the unit loss of load shedding in the distribution network, Δp i,t is the load shedding power of the distribution network, and Δt is the load shedding time of the distribution network. This indicator reflects the load shedding loss of the distribution network, which reflects the economic loss caused by the fault to the distribution network, and is equal to the product of the unit load shedding cost and the load shedding amount.

[0015] 5) Expected number of line faults Where: E() is the mathematical expectation, Ω L is the set of distribution network nodes, x ij It is a 0-1 variable, and its value 0 means that the line has no fault, otherwise it means the line is faulty.

[0016] The present invention relates to a system for implementing the above method, comprising: a diesel engine electric dynamometer system processing characteristic modeling unit, a resilience assessment unit and a diesel engine electric dynamometer system optimal configuration strategy calculation unit for resilience improvement, wherein: the diesel engine electric dynamometer system processing characteristic modeling unit performs modeling processing based on the diesel engine electric dynamometer system operation data information to obtain the upper and lower limit results of the diesel engine electric dynamometer system output; the resilience assessment unit performs indicator weight and indicator value calculation processing based on the post-disaster operation information of the distribution network to obtain the overall resilience assessment result; the optimal configuration strategy calculation unit performs optimization solution processing based on the distribution network post-disaster operation resilience assessment result information with the goal of resilience improvement to obtain the optimal configuration strategy result of the diesel engine electric dynamometer system as a distributed energy source. Technical Effects

[0017] The present invention uses the electric energy feedback of the diesel engine electric dynamometer system as a distributed resource to access the distribution network for distribution network resilience support in disaster scenarios. Compared with the prior art, the present invention can derive the optimal configuration strategy of the diesel engine electric dynamometer system as a distributed energy source, effectively improving the resilience of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of the present invention;

[0019] Figure 2 It is a schematic diagram of the energy management system;

[0020] Figure 3 The structural diagram of the diesel engine electric dynamometer system connected to the power grid;

[0021] Figure 4 This is a schematic diagram of the improved IEEE33 node distribution network;

[0022] Figure 5 Schematic diagram of load shedding power for each node during the entire 24h scheduling period. DETAILED DESCRIPTION like Figure 1 As shown, this implementation involves a method for improving the resilience of a distribution network considering the access of a diesel engine electric dynamometer system, comprising the following steps:

[0023] Step 1: Construct an output characteristic model of the electric energy feedback system based on the diesel engine electric dynamometer system.

[0024] The diesel engine electric dynamometer system is in a power generation state when testing the diesel engine. At this time, the diesel engine electric dynamometer system converts the mechanical energy generated by the diesel engine into electrical energy, and converts it into electrical energy with the same frequency and phase as the power grid through processes such as rectification and inversion to achieve electrical energy feedback.

[0025] The diesel engine electric dynamometer system is rigidly coupled to the diesel engine, and the output shafts of the two are connected through an intermediate connector. The diesel engine electric dynamometer system is driven by the diesel engine, and the mechanical energy of the diesel engine is transmitted to the diesel engine electric dynamometer system through rigid coupling. It is in a power generation mode, and its output electric energy is transmitted to the distribution network after being processed by the feedback system, providing power support for the distribution network.

[0026] The characteristic curve mode means that when the diesel engine electric dynamometer system is in the power generation state, it can reverse the drag operation of the diesel engine and control the drag power according to the set propulsion characteristic curve. The drag power is in a cubic relationship with the speed of the prototype.

[0027] like Figure 2As shown, the diesel engine electric dynamometer system is further connected to an energy management system, which includes: a main control system and two controllers, wherein: the main control system outputs control instructions to the first and second controllers respectively, the first controller controls the torque of the diesel engine electric dynamometer system, and the second controller controls the speed of the diesel engine, and the torque and speed data are transmitted back to the main control through sensors and communication systems as a control basis for the main control system, thereby forming an information feedback loop.

[0028] like Figure 3 As shown, the electric energy feedback system contains at least one diesel engine electric dynamometer system and is equipped with an inverter control device. These control devices process the output electric energy of each diesel engine electric dynamometer system and output it to the plug-in bus.

[0029] The output characteristic model of the diesel engine electric dynamometer system includes power constraints: in: is the output power of the diesel engine electric dynamometer system at node i at time t, It is a 0-1 variable, indicating whether the diesel engine electric dynamometer system is called. It is the maximum output power of the diesel engine electric dynamometer system.

[0030] Step 2: Construct and solve the optimal dispatch model of the diesel engine electric dynamometer system for improving the resilience of the distribution network, including:

[0031] Step 2.1, establish the objective function: the distribution network reduces load loss and improves the resilience of the distribution network by optimizing the configuration of the electric energy fed back by the diesel engine electric dynamometer system. Therefore, the optimization goal is to minimize the load loss of the distribution network and the call cost of the diesel engine electric dynamometer system electric energy feedback system in multiple periods after the disaster. Specifically: Where: C cut Represents the unit power loss cost when load shedding occurs; x i,t is a 0-1 variable, indicating whether load shedding occurs at node i at time t. i,t = 0, there is no load loss at node i at time t. i,t =1, it means that the node i occurs and the load at time t, and the node load has loss cost; is the load shedding power; α i is the load weight of node i; r t is the load rate at time t; C m The cost of using the electric energy fed back to the diesel engine electric dynamometer system; is the output power of the diesel engine electric dynamometer system at node i at time t, It is a 0-1 variable, indicating whether the diesel engine electric dynamometer system is called.

[0032] Step 2.2: Establish node power balance constraints: Where: P mi,t is the active power flowing from node m to node i at time t, φ(i) is the set of all parent nodes of node i in the distribution network, is the DG output in node i at time t, P in,t The ratio is the active power flowing from node i to node n at time t, is the set of all child nodes of distribution network node i. The formula contains nonlinear terms between 0-1 decision variables and continuous decision variables, so the big M method is used to transform it into: Among them: L1, L2 and L3 are continuous variables, ξ i (i=1,2,3) instead of 0-1 decision variables and x i,t , and P i For estimation and M is an arbitrarily large positive number.

[0033] Step 2.3: Establish distributed generator output constraints: in: and are the minimum and maximum output of DG at node i, R i,up and R i,down is the DG ramp up and down rate at node i. This equation is the power constraint and ramp constraint of the DG device.

[0034] Step 2.4: Establish load switching frequency constraints: Where: X max The maximum number of load switching times for a single bus node.

[0035] Step 2.5: Establish voltage constraints, including: Among them: U i,t is the voltage value of node i during period t; U i,max and U i,min They are the maximum and minimum voltages of the nodes during normal operation, respectively.

[0036] Step 2.6, the above model is a mixed integer programming model, and the decision variable is the output power of the diesel engine electric dynamometer system. The model is solved to obtain the optimal scheduling strategy of the diesel engine electric dynamometer system for improving the resilience of the distribution network.

[0037] Step 3: Evaluate the post-disaster recovery capability of the strategy obtained from the optimal dispatching model of the diesel engine electric dynamometer system for improving the resilience of the distribution network in step 2 according to the resilience evaluation index, including:

[0038] Step 3.1: Calculate the objective weight of each indicator according to the anti-entropy weight method (ANP), specifically:

[0039] When the number of macro factors is m, the network indicator set under the i-th factor is y i1 ,y i2 ,…y in , n is the number of micro-indicators under this factor. For the i-th macro-factor, take the j-th network indicator as the criterion, and get the comparison of the influence of the other m-1 network indicators in turn, and get the sorting sequence vector, and then get the judgment matrix under the i-th macro-factor. Similarly, get the judgment matrix of the influence of the i-th macro-factor on other macro-factors, and thus construct the super-matrix under each criterion Where: d i and They are the anti-entropy value and objective weight of the network indicator respectively; a ij Network indicator values, Where: k is the dimension of the normalized feature vector; ω si is the determined subjective weight value. Combined with the calculated weight relationship coefficient, the final combined weight is calculated:

[0040] Step 3.2: Calculate the comprehensive evaluation result of distribution network resilience by multiplying the index value and the index weight obtained in step 3.1 and the selected resilience index, so as to evaluate the impact of the diesel engine electric dynamometer system connected to the grid on the resilience of the distribution network.

[0041] like Figure 4 As shown in the figure, after specific actual experiments, the maximum output of the diesel engine electric dynamometer system electric energy feedback system is set to 500kW, the call cost is 900 yuan / kW, the load shedding cost is 90 yuan / kW, the maximum number of diesel engine electric dynamometer system connections allowed is 5, commercial area (nodes 1-10), industrial area (nodes 11-20) and residential area (nodes 21-33), the corresponding load weights are 1.2, 2.0 and 0.9 respectively. In order to study the impact of the diesel engine electric dynamometer system connected to the distribution network in the form of distributed flexibility resources on its resilience, two scenarios are set. Scenario 1) represents the situation including the access of the diesel engine electric dynamometer system, and solves its optimal dispatching strategy with the goal of improving the resilience of the distribution network. Scenario 2) represents the situation without the access of the diesel engine electric dynamometer system and only including the DG grid connection, which is used for comparative analysis.

[0042] From the perspective of the impact of the diesel engine power measurement system access on the improvement of the distribution network resilience, the load loss rates of scenario 1) and scenario 2) calculated by the above method are 0.2761 and 0.3522 respectively. It can be seen that the access of the diesel engine power measurement system can improve the resilience index selected by the present invention, and the load loss rate is reduced by 21.6%. The load shedding power of each node in the entire 24h scheduling period is as follows: Figure 5 As shown in the figure, it is intuitively demonstrated that the access to the diesel power dynamometer system can reduce the load shedding power. From the perspective of the post-disaster operation economy of the distribution network, the access to the diesel power dynamometer system can reduce the load shedding cost. Even if the call-up cost is incurred to call up the diesel power dynamometer system output, the total post-disaster operation cost is reduced from 147,216 yuan to 87,516 yuan, a reduction of 40.55%.

[0043] The above-mentioned specific implementation can be partially adjusted in different ways by those skilled in the art without departing from the principle and purpose of the present invention. The protection scope of the present invention shall be based on the claims and shall not be limited by the above-mentioned specific implementation. Each implementation scheme within its scope shall be subject to the constraints of the present invention.

Claims

1. A method for improving the resilience of a distribution network considering the access of a diesel engine electric dynamometer system, characterized in that: After modeling the output characteristics of the electric energy feedback part in the diesel engine electric dynamometer system, the supporting capacity of the diesel engine electric dynamometer system as a distributed flexibility resource is quantified from the equipment perspective, and an optimal scheduling model of the diesel engine electric dynamometer system for improving the resilience of the distribution network is constructed; then, the impact of the grid connection of the diesel engine electric dynamometer system on the resilience of the distribution network is quantified according to the resilience evaluation index, and with the goal of improving resilience, an optimal scheduling model of the diesel engine electric dynamometer system is established, and solved by the mixed integer programming method, the optimal configuration strategy of the diesel engine electric dynamometer system as a distributed energy source is obtained.

2. The method for improving the resilience of a distribution network considering the access of a diesel engine electric dynamometer system according to claim 1 is characterized in that: The resilience assessment index is used to evaluate the performance of the distribution network in dealing with extreme disaster events with low probability but high impact, including: 1) Quantify the impact of diesel engine power measurement system access on the resilience of the distribution network, i.e., load loss rate Where: Ω L is the distribution network node set, i is the network node number, t is the time period, is the load loss power of node i in time period t, is the total load of node i in time period t; the load loss rate reflects the load interruption loss after the distribution network disaster, and is part of the optimization target in the optimization model of diesel engine power measurement system as a distributed flexibility resource participating in the post-disaster distribution network resilience improvement scheduling; 2) Average power outage duration index for users Where: i is the user number in the distribution network, N LP is the total number of users, U i is the total power outage time of the user in one year, λ i The total number of power outages for the user in a year. This indicator reflects the time when the distribution network load power supply is insufficient during the fault period, that is, the time from the fault occurrence to the line repair. 3) The proportion of dispatchable emergency resources, i.e. 4) Total loss of distribution network load shedding: in: is the unit loss of load shedding in the distribution network, Δp i,t is the load shedding power of the distribution network, and Δt is the load shedding time of the distribution network; this indicator reflects the load shedding loss of the distribution network, which reflects the economic loss caused by the fault to the distribution network, and is equal to the product of the unit load shedding cost and the load shedding amount; 5) Expected number of line faults Where: E() is the mathematical expectation, Ω L is the set of distribution network nodes, x ij It is a 0-1 variable, and its value 0 means that the line has no fault, otherwise it means the line is faulty.

3. The method for improving the resilience of a distribution network considering the access of a diesel engine electric dynamometer system according to claim 1 or 2, characterized in that: The diesel engine electric dynamometer system is in a power generation state when testing the diesel engine. At this time, the diesel engine electric dynamometer system converts the mechanical energy generated by the diesel engine into electrical energy, and converts it into electrical energy with the same frequency and phase as the power grid through processes such as rectification and inversion, so as to realize the feedback of electrical energy; The diesel engine electric dynamometer system is rigidly coupled to the diesel engine, and the output shafts of the two are connected through an intermediate connecting piece; the diesel engine electric dynamometer system is driven by the diesel engine, and the mechanical energy of the diesel engine is transmitted to the diesel engine electric dynamometer system through the rigid coupling, and is in a power generation mode, and its output electric energy is transmitted to the distribution network after being processed by the feedback system, so as to provide power support for the distribution network; when the diesel engine electric dynamometer system is in a power generation state, the diesel engine is reversely dragged, and the dragging power can be controlled according to the set propulsion characteristic curve, that is, it is in a characteristic curve mode, and the dragging power is in a cubic relationship with the speed of the principle prototype.

4. The method for improving the resilience of a distribution network considering the access of a diesel engine electric dynamometer system according to claim 3 is characterized in that: The diesel engine electric dynamometer system is further connected to an energy management system, which includes: a main control system and two controllers, wherein: the main control system outputs control instructions to the first and second controllers respectively, the first controller controls the torque of the diesel engine electric dynamometer system, and the second controller controls the speed of the diesel engine. The torque and speed data are transmitted back to the main control through sensors and communication systems as the control basis of the main control system, thereby forming an information feedback loop.

5. The method for improving the resilience of a distribution network considering the access of a diesel engine electric dynamometer system according to any one of claims 1 to 4, characterized in that: include: Step 1: construct an output characteristic model of the electric energy feedback system according to the diesel engine electric dynamometer system; The electric energy feedback system includes at least one diesel engine electric dynamometer system and an inverter control device, and these control devices process the output electric energy of each diesel engine electric dynamometer system and output it to the plug-in busbar; The output characteristic model of the diesel engine electric dynamometer system includes power constraints: in: is the output power of the diesel engine electric dynamometer system at node i at time t, It is a 0-1 variable, indicating whether the diesel engine electric dynamometer system is called. The maximum output power of the diesel engine electric dynamometer system; Step 2: Construct and solve the optimal dispatch model of the diesel engine electric dynamometer system for improving the resilience of the distribution network, including: Step 2.1, establish the objective function: the distribution network reduces load loss and improves the resilience of the distribution network by optimizing the configuration of the electric energy fed back by the diesel engine electric dynamometer system. Therefore, the optimization goal is to minimize the load loss of the distribution network and the call cost of the diesel engine electric dynamometer system electric energy feedback system in multiple periods after the disaster. Specifically: Where: C cut Represents the unit power loss cost when load shedding occurs; x i,t is a 0-1 variable, indicating whether load shedding occurs at node i at time t. i,t = 0, there is no load loss at node i at time t. i,t =1, it means that the node i occurs and the load at time t, and the node load has loss cost; is the load shedding power; α i is the load weight of node i; r t is the load rate at time t; C m The cost of using the electric energy fed back to the diesel engine electric dynamometer system; is the output power of the diesel engine electric dynamometer system at node i at time t, It is a 0-1 variable, indicating whether the diesel engine electric dynamometer system is called; Step 2.2: Establish node power balance constraints: Where: P mi,t is the active power flowing from node m to node i at time t, v(i) is the set of all parent nodes of node i in the distribution network, is the DG output in node i at time t, P in,t The ratio is the active power flowing from node i to node n at time t, is the set of all child nodes of distribution network node i; the formula contains nonlinear terms between 0-1 decision variables and continuous decision variables, so the big M method is used to transform it into: Among them: L1, L2 and L3 are continuous variables, ξ i (i=1,2,3) instead of 0-1 decision variables and x i,t , and P i For estimation and M is an arbitrarily large positive number; Step 2.3: Establish distributed generator output constraints: in: and are the minimum and maximum output of DG at node i, R i,up and R i,down is the DG ramp up and down rate at node i; this equation is the power constraint and ramp constraint of the DG device; Step 2.4: Establish load switching frequency constraints: Where: X max The maximum switching times of load on a single bus node; Step 2.5: Establish voltage constraints, including: Among them: U i,t is the voltage value of node i during period t; U i,max and U i,min are the maximum and minimum voltage values ​​of the nodes during normal operation respectively; Step 2.6, the above model is a mixed integer programming model, the decision variable is the output power of the diesel engine electric dynamometer system, and the model is solved to obtain the optimal dispatching strategy of the diesel engine electric dynamometer system for improving the resilience of the distribution network; Step 3: Evaluate the post-disaster recovery capability of the strategy obtained from the optimal dispatching model of the diesel engine electric dynamometer system for improving the resilience of the distribution network in step 2 according to the resilience evaluation index, including: Step 3.1, calculate the objective weight of each indicator according to the anti-entropy weight method; Step 3.2: Calculate the comprehensive evaluation result of distribution network resilience by multiplying the index value and the index weight obtained in step 3.1 and the selected resilience index, so as to evaluate the impact of the diesel engine electric dynamometer system connected to the grid on the resilience of the distribution network.

6. The method for improving the resilience of a distribution network considering the access of a diesel engine electric dynamometer system according to claim 5 is characterized in that: The anti-entropy weight method is as follows: when the number of macro factors is m, the network indicator set under the i-th factor is y i1 ,y i2 ,…y in , n is the number of micro-indicators under this factor; for the i-th macro-factor, take the j-th network indicator as the criterion, get the comparison of the influence of the other m-1 network indicators in turn, get the sorting sequence vector, and then get the judgment matrix under the i-th macro-factor; similarly, get the judgment matrix of the influence of the i-th macro-factor on other macro-factors, and thus construct the super-matrix under each criterion Where: d i and They are the anti-entropy value and objective weight of the network indicator respectively; a ij Network indicator values, Where: k is the dimension of the normalized feature vector; ω si is the determined subjective weight value; combined with the calculated weight relationship coefficient, the final combined weight is calculated:

7. A distribution network resilience improvement system considering the access of a diesel engine electric dynamometer system to implement any of the methods described in claims 1-6, characterized in that: include: A diesel engine electric dynamometer system processing characteristic modeling unit, a resilience assessment unit, and a diesel engine electric dynamometer system optimal configuration strategy calculation unit for resilience improvement, wherein: the diesel engine electric dynamometer system processing characteristic modeling unit performs modeling processing based on the diesel engine electric dynamometer system operation data information to obtain the upper and lower limit results of the diesel engine electric dynamometer system output; the resilience assessment unit performs indicator weight and indicator value calculation processing based on the post-disaster operation information of the distribution network to obtain the overall resilience assessment result; the optimal configuration strategy calculation unit performs optimization solution processing based on the distribution network post-disaster operation resilience assessment result information with the goal of improving resilience, and obtains the optimal configuration strategy result of the diesel engine electric dynamometer system as a distributed energy source.

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