Hierarchical optimization configuration method and terminal for distribution network considering micro-grid cluster access

Abstract

The application discloses a power distribution network hierarchical optimization configuration method and terminal considering micro-grid cluster access, which is different from traditional alternating current micro-grid cluster, generates a micro-grid cluster layer optimization configuration model according to a micro-grid cluster layer optimization configuration objective function and a micro-grid cluster layer operation constraint condition, and generates a power distribution network layer optimization configuration model according to a power distribution network layer optimization configuration objective function and a power distribution network layer operation constraint, the cluster contains alternating current sub-micro-grids and direct current sub-micro-grids, and the influence of power interaction on the power distribution network safety operation at a micro-grid cluster common grid connection point is considered, so that the planning decision scheme has higher safety compared with micro-grid cluster independent planning, the input of a converter for power distribution network configuration is effectively reduced, and therefore the safety and economy of the power distribution network are effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of optimal configuration of power distribution network, and particularly relates to a layered optimal configuration method of power distribution network considering micro-grid cluster access and a terminal. BACKGROUND

[0002] The micro-grid can be divided into DC micro-grid, AC micro-grid and AC / DC hybrid micro-grid according to the power transmission mode. At present, due to the AC radial characteristics of the power distribution network, the AC micro-grid is mostly used in practice. However, there are more and more new elements of negative factors, such as electric vehicles, LED lamps and DC loads such as DC motors, and a large amount of inverter cost needs to be invested in the original AC micro-grid structure. Therefore, it is necessary to carry out new research on the expansion planning scheme of the power distribution network.

[0003] On the other hand, with the continuous progress of energy transformation and energy field technology, the penetration rate of distributed power sources such as roof photovoltaic, energy storage and wind turbine in the power distribution network is getting higher and higher, and the volatility and uncertainty of the distributed power sources bring challenges to the safe operation of the power distribution network. SUMMARY

[0004] The technical problem to be solved by the present application is to provide a layered optimal configuration method of power distribution network considering micro-grid cluster access and a terminal, which can effectively improve the safety and economy of the power distribution network.

[0005] In order to solve the above technical problems, the technical scheme adopted by the present application is as follows:

[0006] A layered optimal configuration method of power distribution network considering micro-grid cluster access, comprising the steps of:

[0007] using a power flow calculation method based on the forward-backward substitution method to perform power flow calculation on the micro-grid cluster to obtain power flow calculation results;

[0008] establishing a micro-grid cluster layer optimal configuration objective function to minimize the sum of the construction cost of photovoltaic, wind turbine, energy storage, DC feeder and AC feeder of each sub-micro-grid, and establishing a micro-grid cluster layer operation constraint condition corresponding to the micro-grid cluster layer optimal configuration objective function, wherein the micro-grid cluster layer operation constraint condition includes AC sub-micro-grid power balance constraint, DC sub-micro-grid power balance constraint, distributed power output constraint and energy storage operation constraint;

[0009] establishing a power distribution network layer optimal configuration objective function to minimize the sum of the annual line planning scheme and the installed capacity cost of the distributed power source, and establishing a power distribution network layer operation constraint corresponding to the power distribution network layer optimal configuration objective function based on the power flow calculation results, wherein the power distribution network layer operation constraint includes node power balance constraint, node voltage safety constraint and line carrying capacity constraint;

[0010] After the micro-grid group layer optimization configuration model is generated according to the micro-grid group layer optimization configuration objective function and the micro-grid group layer operation constraint condition, a power distribution network layer optimization configuration model is generated according to the power distribution network layer optimization configuration objective function and the power distribution network layer operation constraint;

[0011] The micro-grid group layer optimization configuration model and the power distribution network layer optimization configuration model are solved in layers by using an alternating direction multiplier method, so as to obtain a planning decision scheme.

[0012] In order to solve the above technical problems, the present application adopts another technical solution:

[0013] A power distribution network layer optimization configuration terminal considering micro-grid group access comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, and the processor realizes the following steps when executing the computer program:

[0014] A power flow calculation method based on a forward-backward substitution method is used to perform power flow calculation on the micro-grid group, so as to obtain a power flow calculation result;

[0015] A micro-grid group layer optimization configuration objective function is established by minimizing the sum of the construction costs of photovoltaic power, wind driven generators, energy storage, direct current feeders and alternating current feeders of each sub-micro-grid, and a micro-grid group layer operation constraint condition corresponding to the micro-grid group layer optimization configuration objective function is established, wherein the micro-grid group layer operation constraint condition comprises alternating current sub-micro-grid power balance constraint, direct current sub-micro-grid power balance constraint, distributed power output constraint and energy storage operation constraint;

[0016] A power distribution network layer optimization configuration objective function is established by minimizing the sum of the annual line planning scheme and the installed cost of distributed power, and a power distribution network layer operation constraint corresponding to the power distribution network layer optimization configuration objective function is established based on the power flow calculation result, wherein the power distribution network layer operation constraint comprises node power balance constraint, node voltage safety constraint and line load flow constraint;

[0017] After the micro-grid group layer optimization configuration model is generated according to the micro-grid group layer optimization configuration objective function and the micro-grid group layer operation constraint condition, a power distribution network layer optimization configuration model is generated according to the power distribution network layer optimization configuration objective function and the power distribution network layer operation constraint;

[0018] The micro-grid group layer optimization configuration model and the power distribution network layer optimization configuration model are solved in layers by using an alternating direction multiplier method, so as to obtain a planning decision scheme.

[0019] The application has the beneficial effects that, different from the traditional AC micro-grid cluster, the micro-grid cluster layer optimization configuration target function and the micro-grid cluster layer operation constraint condition are used to generate the micro-grid cluster layer optimization configuration model, the distribution network layer optimization configuration target function and the distribution network layer operation constraint are used to generate the distribution network layer optimization configuration model, the cluster contains AC sub-micro-grid and DC sub-micro-grid, and the influence of power interaction on the distribution network safe operation at the micro-grid cluster public grid connection point is considered, so that the planning decision scheme has higher safety compared with the micro-grid cluster independent planning, and the input of the converter for the distribution network configuration is effectively reduced, thereby effectively improving the safety and economy of the distribution network. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 A step flow chart of a distribution network layered optimization configuration method considering micro-grid cluster access for an embodiment of the application;

[0021] Figure 2 A structure schematic diagram of a distribution network layered optimization configuration terminal considering micro-grid cluster access for an embodiment of the application;

[0022] Figure 3 An AC / DC converter structure schematic diagram in the distribution network layered optimization configuration method considering micro-grid cluster access for an embodiment of the application;

[0023] Figure 4 A solving flow chart in the distribution network layered optimization configuration method considering micro-grid cluster access for an embodiment of the application. DETAILED DESCRIPTION

[0024] To make the technical content, the achieved purposes and effects of the application clear, the following will be described in detail in combination with the embodiments and the drawings.

[0025] Please refer to Figure 1 A distribution network layered optimization configuration method considering micro-grid cluster access, comprising the following steps:

[0026] A power flow calculation method based on the forward-backward substitution method is used to perform power flow calculation on the micro-grid cluster, and the power flow calculation result is obtained;

[0027] A micro-grid cluster layer optimization configuration target function is established by minimizing the sum of the construction cost of the photovoltaic, wind turbine, energy storage, DC feeder and AC feeder of each sub-micro-grid, and a micro-grid cluster layer operation constraint condition corresponding to the micro-grid cluster layer optimization configuration target function is established, the micro-grid cluster layer operation constraint condition includes AC sub-micro-grid power balance constraint, DC sub-micro-grid power balance constraint, distributed power output constraint and energy storage operation constraint;

[0028] The distribution network layer optimization configuration objective function is established by minimizing the sum of annual line planning schemes and installation costs of distributed power supplies, and the distribution network layer operation constraint corresponding to the distribution network layer optimization configuration objective function is established based on the power flow calculation result, and the distribution network layer operation constraint includes a node power balance constraint, a node voltage safety constraint and a line load flow constraint;

[0029] After the micro-grid group layer optimization configuration model is generated according to the micro-grid group layer optimization configuration objective function and the micro-grid group layer operation constraint condition, a distribution network layer optimization configuration model is generated according to the distribution network layer optimization configuration objective function and the distribution network layer operation constraint;

[0030] The micro-grid group layer optimization configuration model and the distribution network layer optimization configuration model are solved by using an alternating direction multiplier method, and a planning decision scheme is obtained.

[0031] As can be seen from the above description, the beneficial effects of the present application are that, unlike the traditional alternating current micro-grid group, the micro-grid group layer optimization configuration model is generated according to the micro-grid group layer optimization configuration objective function and the micro-grid group layer operation constraint condition, and the distribution network layer optimization configuration model is generated according to the distribution network layer optimization configuration objective function and the distribution network layer operation constraint, the cluster contains alternating current sub-micro grids and direct current sub-micro grids, and the influence of power interaction on the distribution network safety operation at the micro-grid group public grid connection point is considered, so that the planning decision scheme has higher safety compared with the micro-grid group independent planning, and the investment of the converter for the distribution network configuration is effectively reduced, thereby effectively improving the safety and economy of the distribution network.

[0032] Further, the micro-grid group layer optimization configuration objective function is established by minimizing the sum of installation and construction costs of the photovoltaic, wind turbine, energy storage, direct current feeder and alternating current feeder of each sub-micro grid, and includes:

[0033]

[0034] In the formula, F m represents the sum of installation and construction costs of the photovoltaic, wind turbine, energy storage, direct current feeder and alternating current feeder of each sub-micro grid, M represents the number of alternating current sub-micro grids and direct current sub-micro grids in the micro-grid group layer, C pv represents the unit installation and construction cost of the photovoltaic, P pv,m represents the photovoltaic capacity installed by the sub-micro grid, C wind represents the unit installation and construction cost of the wind turbine, P wind,m represents the wind turbine capacity installed by the sub-micro grid, C Bat represents the unit installation and construction cost of the energy storage, P Bat,m represents the energy storage capacity installed by the sub-micro grid, N ac represents the number of alternating current sub-micro grids, C linc-acunit construction cost of AC feeder, feeder length of AC sub-microgrid construction, N dc number of DC sub-microgrid, C line-dc feeder length of DC feeder, feeder length of DC sub-microgrid construction.

[0035] From the above description, it can be known that the microgrid aims to realize self-sufficiency of loads in the jurisdiction area by means of distributed power supply, but the wind and light output has uncertainty, and the configuration of energy storage can effectively alleviate the influence of wind and light output uncertainty on the safe operation of the microgrid, so the microgrid group layer optimization configuration objective function is established by minimizing the sum of construction costs of photovoltaic, wind turbine, energy storage, DC feeder and AC feeder of each sub-microgrid.

[0036] Further, the AC sub-microgrid power balance constraint is:

[0037]

[0038] In the formula, P AC-wind indicates the wind turbine output of the AC sub-microgrid, P AC-pv indicates the photovoltaic output of the AC sub-microgrid, P AC-bat indicates the total net discharge power of the energy storage of the AC sub-microgrid, indicates the power delivered by the power distribution network to the AC sub-microgrid group, P AC-load indicates the load of the AC sub-microgrid;

[0039] The DC sub-microgrid power balance constraint is:

[0040]

[0041] In the formula, P DC-wind indicates the wind turbine output of the DC sub-microgrid, P DC-pv indicates the photovoltaic output of the DC sub-microgrid, P DC-bat indicates the total net discharge power of the energy storage of the DC sub-microgrid, P grid-MGDC indicates the power delivered by the power distribution network to the DC sub-microgrid group, P DC-load indicates the load of the DC sub-microgrid;

[0042] The distributed power output constraint is:

[0043]

[0044] In the formula, P pv indicates the photovoltaic output, P pv,max indicates the upper limit of the photovoltaic output, P wind indicates the wind turbine output, P wind,maxrepresents the upper limit of the fan output;

[0045] The energy storage operation constraint is:

[0046]

[0047] In the formula, SOC min represents the lower limit value of the state of charge of the energy storage device, SOC t represents the state of charge of the energy storage device at time t, SOC max represents the upper limit value of the state of charge of the energy storage device, Pc(t) represents the charging power of the energy storage device, P c,max represents the upper limit of the charging power of the energy storage device, Pd(t) represents the discharging power of the energy storage device, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC Δt represents the state of charge of the energy storage device after a charging and discharging time interval, η c represents the charging efficiency of the energy storage device, η d represents the discharging efficiency of the energy storage device, and Δt represents the time interval taken by the planning period.

[0048] As can be seen from the above description, the most basic condition for the microgrid layer operation is to meet the power balance constraint, that is, the power supplied by the distributed power supply and the upper layer distribution network realizes the self-sufficiency of the load in the jurisdictional area. Then, in order to make the microgrid run in a safe range, the node voltage needs to be within the safe upper and lower limits. Secondly, the output of the distributed power supply during operation cannot exceed the upper and lower limits, and the energy storage operation cannot be charging and discharging at the same time. Therefore, the AC sub-microgrid power balance constraint, the DC sub-microgrid power balance constraint, the distributed power supply output constraint and the energy storage operation constraint are established to ensure the safe operation of the microgrid layer.

[0049] Further, the establishment of the distribution network layer optimization configuration objective function by minimizing the sum of the annual line planning scheme and the installed cost of the distributed power supply includes:

[0050]

[0051] In the formula, F D represents the sum of the annual line planning scheme and the installed cost of the distributed power supply, c ij represents the expansion cost of the line, δ ij represents the planning variable, c d represents the investment cost of the distributed power supply d, x d represents the planning capacity of the distributed power supply d, and ω(DG) represents the set of distributed power supplies.

[0052] From the above description, the power distribution network needs to deliver certain electric power to each micro-grid, and the existing line current carrying capacity constraints cannot guarantee that the power delivery demand can be met, so the line needs to be planned, and the distributed power supply is installed at the appropriate location to reduce the power supply pressure of the substation, to minimize the sum of the annual line planning scheme and the installation cost of the distributed power supply to establish the power distribution network layer optimization configuration objective function.

[0053] Further, the node power balance constraint is:

[0054]

[0055] In the formula, Ω(:,m) represents the power line with m as the terminal point, P lm,t represents the active power on the line lm, I lm,t represents the line lm current, R lm represents the resistance of the line lm, represents the active output power of the substation of node m, Ω(m,:) represents the power line with m as the starting point, P mk,t represents the active power on the line mk, represents the active load, represents the electric power provided by the power distribution network at node m to the sub-micro-grid, Q lm,t represents the reactive power on the line lm, X lm represents the reactance of the line lm, represents the reactive output power of the substation of node m, Q mk,t represents the reactive power on the line mk, represents the reactive load;

[0056] The node voltage safety constraint is:

[0057]

[0058] In the formula, represents the upper limit of the voltage, U m,t represents the voltage amplitude of node m at time t, represents the lower limit of the voltage;

[0059] The line current carrying capacity constraint is:

[0060]

[0061] In the formula, represents the upper limit of the line current carrying capacity.

[0062] From the above description, the node power balance constraint, the node voltage safety constraint and the line load flow constraint are established to ensure that the total inflow power of the node is equal to the total outflow power of the node, the node voltage amplitude is within the safe voltage upper and lower limits, and the current of the line does not exceed the maximum allowable current of the line, thereby ensuring the safety of the operation of the power distribution network.

[0063] Further, the micro-grid group layer optimization configuration model and the power distribution network layer optimization configuration model are solved by using the alternating direction multiplier method, and a planning decision scheme is obtained.

[0064] A power distribution network layer and a micro-grid group layer coupling constraint are established.

[0065] A penalty term is added to the micro-grid group layer optimization configuration objective function of the micro-grid group layer optimization configuration model to obtain a modified micro-grid group layer optimization configuration model.

[0066] The penalty term is added to the power distribution network layer optimization configuration objective function of the power distribution network layer optimization configuration model to obtain a modified power distribution network layer optimization configuration model.

[0067] Under the power distribution network layer and micro-grid group layer coupling constraint, the modified micro-grid group layer optimization configuration model and the modified power distribution network layer optimization configuration model are solved by using the alternating direction multiplier method to obtain a planning decision scheme.

[0068] From the above description, since the main body of the power distribution network considering the access of the micro-grid is numerous, the calculation amount of the traditional centralized solving method is huge, and all parameters need to be shared by each main body. In order to protect the privacy of each main body, the alternating direction multiplier method is used to realize the hierarchical solving of the power distribution network layer and the micro-grid group layer, reduce the size of parallel solving of each sub-problem, and effectively improve the solving efficiency.

[0069] Further, the power distribution network layer and micro-grid group layer coupling constraint is:

[0070]

[0071] In the formula, P (MG, m) represents the power delivered by the power distribution network to the AC sub-micro-grid group, P (MG, m) represents the power delivered by the power distribution network to the DC sub-micro-grid group, P (MG, m) represents the power provided by the power distribution network at node m to the sub-micro-grid, P (MG, m) represents the power provided by the power distribution network at node n to the sub-micro-grid, ω (MG AC ) represents the power distribution network node accessed by the AC sub-micro-grid, ω (MG DC ) represents the power distribution network node accessed by the DC sub-micro-grid.

[0072] From the above description, it can be seen that the establishment of the coupling constraint of the power distribution network layer and the micro-grid group layer can ensure that after the original problem is decomposed into two sub-problems, although they are solved independently, the consistency constraint of the coupling variable is still obeyed, and the quality of the obtained solution is ensured.

[0073] Further, the adding of the penalty term to the power distribution network layer optimization configuration objective function of the power distribution network layer optimization configuration model to obtain a modified micro-grid group layer optimization configuration model comprises:

[0074]

[0075] In the formula, C m represents the micro-grid group layer optimization configuration objective function under the distributed solving framework, F m represents the sum of the installation costs of the photovoltaic, wind turbine, energy storage, DC feeder and AC feeder of each sub-micro-grid, λ represents the Lagrange multiplier, represents the auxiliary variable determined by the coupling variable of the power distribution network and the AC sub-micro-grid in the u-th iteration, and ρ represents the penalty factor, represents the auxiliary variable determined by the coupling variable of the power distribution network and the DC sub-micro-grid in the u-th iteration.

[0076] From the above description, it can be seen that the adding of the penalty term to the power distribution network layer optimization configuration objective function of the power distribution network layer optimization configuration model ensures that in one iteration process, the sub-problems will tend to the coupling variable when solving their own variables, so that the overall value of the penalty term tends to zero, and when the optimal solution is obtained, F m will be approximately equal to C m .

[0077] Further, the adding of the penalty term to the power distribution network layer optimization configuration objective function of the power distribution network layer optimization configuration model to obtain a modified power distribution network layer optimization configuration model comprises:

[0078]

[0079] In the formula, C d represents the power distribution network layer optimization configuration objective function under the distributed solving framework, F D represents the sum of the annual line planning scheme and the installation cost of the distributed power supply, represents the power provided by the power distribution network to the sub-micro-grid at node m in the u-th iteration, represents the power provided by the power distribution network to the sub-micro-grid at node n in the u-th iteration.

[0080] From the above description, it can be seen that the adding of the penalty term to the power distribution network layer optimization configuration objective function of the power distribution network layer optimization configuration model ensures that in one iteration process, the sub-problems will tend to the coupling variable when solving their own variables, so that the overall value of the penalty term tends to zero, and when the optimal solution is obtained, F

[0081] Please refer to Figure 2 Another embodiment of the present invention provides a distribution network hierarchical optimization configuration terminal considering microgrid cluster access, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements each step in the above-described distribution network hierarchical optimization configuration method considering microgrid cluster access.

[0082] The hierarchical optimization configuration method and terminal for distribution networks considering microgrid cluster access described above in this invention are applicable to distribution networks with microgrid cluster access. The following detailed embodiments illustrate this:

[0083] Please refer to Figure 1 , Figure 3 and Figure 4 Embodiment 1 of the present invention is as follows:

[0084] A hierarchical optimization configuration method for distribution networks considering microgrid cluster access includes the following steps:

[0085] S1. Power flow calculation is performed on the microgrid cluster using a forward-backward substitution method, and the power flow calculation results are obtained, specifically including S11-S15:

[0086] The distribution network includes AC / DC converters to enable energy exchange between the AC bus and the DC sub-microgrid, such as... Figure 3 As shown, I dc U dc These represent the current and voltage on the DC side, respectively. include Let A, B, and C represent the phase voltages on the AC side, respectively. P, Q, and I represent the active power, reactive power, and AC current injected into the DC sub-microgrid by the converter, respectively. R and X represent the impedance values ​​of the AC side lines, respectively. j is a basic symbol describing line parameters, and R+jX is a complex number.

[0087] S11. Initialize the iteration count n = 1, initialize the voltage of each power node to the rated voltage, and initialize the identifier a representing AC convergence. AC and the identifier a representing DC convergence DC All are 0.

[0088] S12. Based on the AC load value at the end of the distribution network, the current value on each branch of the AC sub-microgrid is obtained by extrapolation. Then, the voltage of each power node in the AC sub-microgrid is calculated based on the current value on each branch and the rated voltage. The iteration count is incremented by one. Specifically:

[0089] Y ac,i U ac,i (k)=I ac,i (k);

[0090] U ac,0 (k) = U0;

[0091] In the formula, Y ac,i U represents the admittance value of line i in the AC sub-microgrid. ac,i (k) represents the voltage value of node i in the AC sub-microgrid during the k-th iteration, I ac,i (k) represents the current in line i of the AC sub-microgrid in the k-th iteration, U ac,0 (k) represents the voltage value of the root node in the k-th iteration, and U0 represents the rated voltage. Where Y ac,i U0 is a constant input value, and the rest are variables to be solved.

[0092] S13. If the absolute value of the difference between the voltage of each power node in the AC sub-microgrid calculated in this iteration and the voltage of each power node in the AC sub-microgrid calculated in the previous iteration is less than the preset convergence criterion value, then the identifier a representing AC convergence will be set to... AC Update to 1 and execute S14; otherwise, return to execute S12.

[0093] S14. Calculate the power flow of the DC sub-microgrid based on the voltage of each node, specifically as follows:

[0094] G dc,i U dc,i (k+1)=I dc,i (k+1);

[0095]

[0096] In the formula, G dc,i U represents the admittance value of line i in a DC sub-microgrid. dc,i (k+1) represents the voltage value of node i in the (k+1)th iteration of the DC sub-microgrid, I dc.i (k+1) represents the current of line i in the (k+1)th iteration of the DC sub-microgrid, U ac,j This represents the voltage value at node j in the AC sub-microgrid.

[0097] S15. If the absolute value of the difference between the voltage of each power node in the DC sub-microgrid calculated in this iteration and the voltage of each power node in the DC sub-microgrid calculated in the previous iteration is less than the preset convergence criterion value, then the identifier a representing DC convergence will be set to... DC Update to 1 and stop iterating; otherwise, continue to the next iteration.

[0098] S2, establish a micro-grid group layer optimal configuration objective function aiming at minimizing the sum of the construction and installation costs of the photovoltaic, wind turbine, energy storage, DC feeder and AC feeder of each sub-micro-grid, and establish a micro-grid group layer operation constraint condition corresponding to the micro-grid group layer optimal configuration objective function, the micro-grid group layer operation constraint condition including an AC sub-micro-grid power balance constraint, a DC sub-micro-grid power balance constraint, a distributed power output constraint and an energy storage operation constraint.

[0099] The micro-grid aims to achieve self-sufficiency of the load in the jurisdiction area by means of the distributed power supply, but the wind and light output is uncertain, and the configuration of the energy storage can effectively alleviate the impact of the wind and light output uncertainty on the operation safety of the micro-grid. Therefore, the micro-grid group layer optimal configuration objective function is:

[0100]

[0101] In the formula, F m represents the sum of the construction and installation costs of the photovoltaic, wind turbine, energy storage, DC feeder and AC feeder of each sub-micro-grid, M represents the number of the DC sub-micro-grid and the AC sub-micro-grid in the micro-grid group layer, C pv represents the unit construction and installation cost of the photovoltaic, P pv,m represents the photovoltaic capacity constructed by the sub-micro-grid, C wind represents the unit construction and installation cost of the wind turbine, P wind,m represents the wind turbine capacity constructed by the sub-micro-grid, C Bat represents the unit construction and installation cost of the energy storage, P Bat,m represents the energy storage capacity constructed by the sub-micro-grid, N ac represents the number of the AC sub-micro-grid, C linc-ac represents the unit construction and installation cost of the AC feeder, represents the feeder length constructed by the AC sub-micro-grid, N dc represents the number of the DC sub-micro-grid, C line-dc represents the feeder length of the DC feeder, represents the feeder length constructed by the DC sub-micro-grid.

[0102] The AC sub-micro-grid power balance constraint is:

[0103]

[0104] In the formula, P AC-wind represents the wind turbine output of the AC sub-micro-grid, P AC-pv represents the photovoltaic output of the AC sub-micro-grid, P AC-bat represents the net discharging total power of the energy storage of the AC sub-micro-grid, represents the electric power transmitted by the power distribution network to the AC sub-micro-grid group, P AC-loadPd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC

[0105] The DC sub-microgrid power balance constraint is:

[0106]

[0107] Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC DC-wind Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC DC-pv Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC DC-bat Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC grid-MGDC Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC DC-load Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC

[0108] The distributed power output constraint is:

[0109]

[0110] Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC pv Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC pv,max Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC wind Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC wind,max Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC pv,max Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC wind,max Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC

[0111] The energy storage operation constraint is:

[0112]

[0113] Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC min Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC t Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC max Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC c,max Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC Δt Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC c Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC d Pd(t) represents the discharging power of the energy storage device at time t, Pd,max represents the upper limit of the discharging power of the energy storage device, SOC

[0114] S3, establishing a distribution network layer optimization configuration objective function to minimize the sum of annual line planning scheme and distributed power installation cost, and establishing a distribution network layer operation constraint corresponding to the distribution network layer optimization configuration objective function based on the power flow calculation result, the distribution network layer operation constraint including node power balance constraint, node voltage safety constraint and line load flow constraint.

[0115] Wherein, the distribution network needs to deliver certain electric power to each micro-grid, and the load flow constraint of the existing line cannot guarantee that the power transmission demand can be met, so the line needs to be planned, and the distributed power needs to be installed at appropriate positions to reduce the power supply pressure of the transformer substation. Therefore, the distribution network layer optimization configuration objective function is:

[0116]

[0117] In the formula, F D represents the sum of annual line planning scheme and distributed power installation cost, c ij represents the expansion cost of the line, δ ij represents the planning variable, c d represents the investment cost of the distributed power d, x d represents the planning capacity of the distributed power d, ω(DG) represents the distributed power set.

[0118] The node power balance constraint is:

[0119]

[0120] In the formula, Ω(:,m) represents the power line with m as the terminal, P lm,t represents the active power on the line lm, I lm,t represents the line lm current, R lm represents the resistance of the line lm, represents the active output power of the transformer substation of node m, Ω(m,:) represents the power line with m as the starting point, P mk,t represents the active power on the line mk, represents the active load, represents the electric power provided by the distribution network at node m to the sub-micro-grid, Q lm,t represents the reactive power on the line lm, X lm represents the reactance of the line lm, represents the reactive output power of the transformer substation of node m, Q mk,t represents the reactive power on the line mk, represents the reactive load;

[0121] The node voltage safety constraint is:

[0122]

[0123] wherein, denotes the upper limit of the voltage, U m,t denotes the voltage amplitude of node m at time t, calculated by S1, denotes the lower limit of the voltage;

[0124] The line current carrying capacity constraint is:

[0125]

[0126] wherein, denotes the upper limit of the line current carrying capacity.

[0127] S4, after the micro-grid group layer optimization configuration target function and the micro-grid group layer operation constraint condition are used to generate a micro-grid group layer optimization configuration model, a distribution network layer optimization configuration model is generated according to the distribution network layer optimization configuration target function and the distribution network layer operation constraint.

[0128] S5, the micro-grid group layer optimization configuration model and the distribution network layer optimization configuration model are solved by using an alternating direction multiplier method, to obtain a planning decision scheme. Considering that the distribution network main body is numerous after the micro-grid is accessed, the calculation amount of the traditional centralized solving method is huge, and all parameters need to be shared by each main body. The alternating direction multiplier method can protect the privacy of each main body, and reduce the size when each sub-problem is solved in parallel, thereby effectively improving the solving efficiency, as shown in the following formula: Figure 4 Specifically, S51-S54 are included:

[0129] S51, a distribution network layer and a micro-grid group layer coupling constraint are established, specifically:

[0130]

[0131] wherein, denotes the electric power delivered by the distribution network to the AC sub-micro-grid group, denotes the electric power delivered by the distribution network to the DC sub-micro-grid group, denotes the electric power provided by the distribution network at node m to the sub-micro-grid, denotes the electric power provided by the distribution network at node n to the sub-micro-grid, ω(MG AC denotes the distribution network node accessed by the AC sub-micro-grid, ω(MG DC denotes the distribution network node accessed by the DC sub-micro-grid.

[0132] S52, a penalty term is added to the micro-grid group layer optimization configuration target function of the micro-grid group layer optimization configuration model, to obtain a modified micro-grid group layer optimization configuration model, specifically:

[0133]

[0134] wherein C m denotes the microgrid group layer optimization configuration objective function under the distributed solving framework, F m denotes the sum of the construction and installation costs of the photovoltaic, wind turbine, energy storage, DC feeder and AC feeder of each sub-microgrid, and λ denotes the Lagrange multiplier, denotes the auxiliary variable determined by the coupling variable of the power distribution network and the AC sub-microgrid in the u-th iteration, and ρ denotes the penalty factor, denotes the auxiliary variable determined by the coupling variable of the power distribution network and the DC sub-microgrid in the u-th iteration.

[0135] S53, adding the penalty term to the power distribution network layer optimization configuration objective function of the power distribution network layer optimization configuration model to obtain a modified power distribution network layer optimization configuration model, specifically:

[0136]

[0137] wherein C d denotes the power distribution network layer optimization configuration objective function under the distributed solving framework, F D denotes the sum of the annual line planning scheme and the installation cost of the distributed power supply, denotes the power provided by the power distribution network to the sub-microgrid at node m in the u-th iteration, denotes the power provided by the power distribution network to the sub-microgrid at node n in the u-th iteration.

[0138] wherein the power distribution network and the microgrid are coupled through the auxiliary variable to decouple the coupling variable, the value of each iteration is affected by the value of the coupling variable in the previous iteration result of each subsystem, and the auxiliary variable is updated in the following manner:

[0139]

[0140] wherein, denotes the power transmitted by the power distribution network to the AC sub-microgrid group in the u-1-th iteration, denotes the power provided by the power distribution network to the sub-microgrid at node m in the u-1-th iteration, denotes the power transmitted by the power distribution network to the DC sub-microgrid group in the u-1-th iteration, denotes the power provided by the power distribution network to the sub-microgrid at node n in the u-1-th iteration.

[0141] S54, under the coupling constraint of the power distribution network layer and the microgrid group layer, the modified microgrid group layer optimization configuration model and the modified power distribution network layer optimization configuration model are solved by using the alternating direction multiplier method to obtain a planning decision scheme.

[0142] Wherein, in the solving process, whether the current converges is judged by the original residual and the dual residual, when the original residual and the dual residual are both less than a given threshold, the solving converges, and the iteration ends, specifically:

[0143]

[0144] In the formula, σ AC Indicates the first original residual, σ DC Indicates the second original residual, σ D Indicates the dual residual, Indicates the auxiliary variable determined by the coupling variable of the power distribution network and the alternating current sub-microgrid in the u-1th iteration, Indicates the auxiliary variable determined by the coupling variable of the power distribution network and the direct current sub-microgrid in the u-1th iteration, ε P Indicates the original residual limit value, ε D Indicates the dual residual limit value. The first original residual and the second original residual realize the coupling variable close enough between the connected subsystems.

[0145] Please refer to Figure 2 Embodiment two of the present application is:

[0146] A power distribution network hierarchical optimization configuration terminal considering microgrid cluster access, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements each step in the power distribution network hierarchical optimization configuration method considering microgrid cluster access in embodiment one when executing the computer program.

[0147] In summary, the power distribution network hierarchical optimization configuration method and terminal considering microgrid cluster access provided by the present application are different from the traditional alternating current microgrid cluster, generate a microgrid cluster layer optimization configuration model according to the microgrid cluster layer optimization configuration objective function and the microgrid cluster layer operation constraint condition, and generate a power distribution network layer optimization configuration model according to the power distribution network layer optimization configuration objective function and the power distribution network layer operation constraint, the cluster contains alternating current sub-microgrids and direct current sub-microgrids, and the influence of power interaction on the microgrid cluster public grid connection point on the safe operation of the power distribution network is considered, so that the planning decision scheme has higher safety compared with the microgrid cluster independent planning, and the input of the converter for the power distribution network configuration is effectively reduced, thereby effectively improving the safety and economy of the power distribution network. In addition, since the main body of the power distribution network considering microgrid access is numerous, the traditional centralized solving method has a large amount of calculation, and all parameters need to be shared by each main body. In order to protect the privacy of each main body, the hierarchical solving of the power distribution network layer and the microgrid cluster layer is realized based on the alternating direction multiplier method, the size of each sub-problem parallel solving is reduced, and the solving efficiency is effectively improved.

[0148] The above merely illustrates the embodiments of the present application, and is not intended to limit the patent scope of the present application. Any equivalent transformation or direct or indirect application in the related technical field based on the content of the present application specification and drawings is also included in the patent protection scope of the present application.

Claims

1.A hierarchical optimization configuration method for a power distribution network considering micro-grid cluster access, characterized in that, The method comprises the steps of: performing power flow calculation on the micro-grid cluster by using a power flow calculation method based on a forward-backward substitution method to obtain power flow calculation results; establishing a micro-grid cluster layer optimal configuration objective function by minimizing the sum of the construction and installation costs of photovoltaic power, wind power generators, energy storage, DC feeder lines and AC feeder lines of each sub-micro-grid, and establishing micro-grid cluster layer operation constraints corresponding to the micro-grid cluster layer optimal configuration objective function, wherein the micro-grid cluster layer operation constraints comprise AC sub-micro-grid power balance constraints, DC sub-micro-grid power balance constraints, distributed power output constraints and energy storage operation constraints; establishing a distribution network layer optimal configuration objective function by minimizing the sum of annual line planning schemes and distributed power installation costs, and establishing distribution network layer operation constraints corresponding to the distribution network layer optimal configuration objective function based on the power flow calculation results, wherein the distribution network layer operation constraints comprise node power balance constraints, node voltage safety constraints and line load flow constraints; generating a micro-grid cluster layer optimal configuration model according to the micro-grid cluster layer optimal configuration objective function and the micro-grid cluster layer operation constraints, and generating a distribution network layer optimal configuration model according to the distribution network layer optimal configuration objective function and the distribution network layer operation constraints; solving the micro-grid cluster layer optimal configuration model and the distribution network layer optimal configuration model by using an alternating direction multiplier method to obtain a planning decision scheme; the micro-grid cluster layer optimal configuration objective function is established by minimizing the sum of the construction and installation costs of photovoltaic power, wind power generators, energy storage, DC feeder lines and AC feeder lines of each sub-micro-grid; ； In the formula, represents the sum of the construction cost of the photovoltaic, wind turbine, energy storage, DC feeder and AC feeder of each sub-microgrid, and M represents the number of DC sub-microgrids and AC sub-microgrids in the microgrid group layer, represents the unit construction cost of the photovoltaic, represents the photovoltaic capacity constructed by the sub-microgrid, represents the unit construction cost of the wind turbine, represents the wind turbine capacity constructed by the sub-microgrid, represents the unit construction cost of the energy storage, represents the energy storage capacity constructed by the sub-microgrid, N ac represents the number of AC sub-microgrids, represents the unit construction cost of the AC feeder, represents the feeder length constructed by the AC sub-microgrid, N dc represents the number of DC sub-microgrids, represents the feeder length of the DC feeder, represents the feeder length constructed by the DC sub-microgrid; the AC sub-micro-grid power balance constraints are as follows: ； wherein, Pwind,ac represents the wind power output of the AC sub-microgrid, Ppv,ac represents the photovoltaic power output of the AC sub-microgrid, Pstorage,ac represents the total net discharging power of the energy storage of the AC sub-microgrid, Pgrid,ac represents the power delivered by the distribution grid to the AC sub-microgrid group, Pload,ac represents the load of the AC sub-microgrid; the DC sub-micro-grid power balance constraints are as follows: ； wherein, Pwind,dc represents the wind power output of the DC sub-microgrid, Ppv,dc represents the photovoltaic power output of the DC sub-microgrid, Pstorage,dc represents the total net discharging power of the energy storage of the DC sub-microgrid, Pgrid,dc represents the power delivered by the distribution grid to the DC sub-microgrid group, Pload,dc represents the load of the DC sub-microgrid; the distributed power output constraints are as follows: ； wherein denotes the photovoltaic output, denotes the upper limit of the photovoltaic output, denotes the wind turbine output, denotes the upper limit of the wind turbine output; the energy storage operation constraints are as follows: ； wherein represents a lower limit value of the state of charge of the energy storage device, represents the state of charge of the energy storage device at time t, represents an upper limit value of the state of charge of the energy storage device, represents the charging power of the energy storage device, represents an upper limit of the charging power of the energy storage device, represents the discharging power of the energy storage device, represents an upper limit of the discharging power of the energy storage device, represents the state of charge of the energy storage device after one charging and discharging time interval, represents the charging efficiency of the energy storage device, represents the discharging efficiency of the energy storage device, represents the time interval taken by the planning period; the distribution network layer optimal configuration objective function is established by minimizing the sum of annual line planning schemes and distributed power installation costs; ； wherein, represents the sum of the annual line planning scheme and the installed cost of distributed power, represents the expansion cost of the line, represents the planning variable, represents the investment cost of the distributed power d, represents the planning capacity of the distributed power d, represents the distributed power set. 2.The power grid hierarchical optimization configuration method considering micro-grid cluster access according to claim 1, wherein, the node power balance constraints are as follows: ； ； wherein denotes the power line ending in m, denotes the active power on line lm, denotes the line lm current, denotes the resistance of line lm, denotes the active output power of the substation at node m, denotes the power line starting in m, denotes the active power on line mk, denotes the active load, denotes the electric power provided by the distribution grid at node m to the sub-microgrid, denotes the reactive power on line lm, denotes the reactance of line lm, denotes the reactive output power of the substation at node m, denotes the reactive power on line mk, denotes the reactive load; the node voltage safety constraints are as follows: ； wherein represents an upper limit of the voltage, represents the voltage amplitude of the node m at time t, represents a lower limit of the voltage; the line load flow constraints are as follows: ； In the formula, represents the upper limit of the line current-carrying capacity. 3.The power grid hierarchical optimization configuration method considering micro-grid cluster access according to claim 1, wherein, the micro-grid cluster layer optimal configuration model and the distribution network layer optimal configuration model are solved by using the alternating direction multiplier method to obtain a planning decision scheme, which comprises: establishing distribution network layer and micro-grid cluster layer coupling constraints; adding a penalty term to the micro-grid cluster layer optimal configuration objective function of the micro-grid cluster layer optimal configuration model to obtain a modified micro-grid cluster layer optimal configuration model; adding the penalty term to the distribution network layer optimal configuration objective function of the distribution network layer optimal configuration model to obtain a modified distribution network layer optimal configuration model; solving the modified micro-grid cluster layer optimal configuration model and the modified distribution network layer optimal configuration model by using the alternating direction multiplier method under the distribution network layer and micro-grid cluster layer coupling constraints to obtain a planning decision scheme. 4.The power grid hierarchical optimization configuration method considering micro-grid cluster access according to claim 3, wherein, the distribution network layer and micro-grid cluster layer coupling constraints are as follows: ； ； wherein Pm,grid→m represents the power delivered by the distribution grid to the AC sub-microgrid group, Pm,grid→m represents the power delivered by the distribution grid to the DC sub-microgrid group, Pm,grid→m represents the power delivered by the distribution grid to the sub-microgrid at node m, Pm,grid→m represents the power delivered by the distribution grid to the sub-microgrid at node n, Pm,grid→m represents the power delivered by the distribution grid to the sub-microgrid at node m, Pm,grid→m represents the power delivered by the distribution grid to the sub-microgrid at node n, 5. The power distribution network hierarchical optimization configuration method considering microgrid cluster access according to claim 4, characterized in that, the penalty term is added to the distribution network layer optimal configuration objective function of the distribution network layer optimal configuration model to obtain a modified micro-grid cluster layer optimal configuration model, which comprises: ； In the formula, represents the micro-grid group layer optimization configuration objective function under the distributed solution framework, represents the sum of the construction and installation costs of the photovoltaic, wind turbine, energy storage, DC feeder and AC feeder of each sub-micro-grid, represents the Lagrange multiplier, represents the auxiliary variable determined by the u-th iteration of the distribution network and the AC sub-micro-grid coupling variable, represents the penalty factor, represents the auxiliary variable determined by the u-th iteration of the distribution network and the DC sub-micro-grid coupling variable. 6.The power grid hierarchical optimization configuration method considering micro-grid cluster access according to claim 5, wherein, The penalty term is added to the power distribution network layer optimization configuration model to obtain a modified power distribution network layer optimization configuration model. ； In the formula, represents the distribution network layer optimization configuration objective function under the distributed solution framework, represents the sum of the annual line planning scheme and the installed cost of the distributed power supply, represents the power provided by the distribution network to the sub-microgrid at node m in the u-th iteration, represents the power provided by the distribution network to the sub-microgrid at node n in the u-th iteration. 7.A power distribution network hierarchical optimization configuration terminal considering micro-grid cluster access, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that, The processor implements each step of the power distribution network layered optimization configuration method considering micro-grid cluster access in any one of claims 1 to 6 when executing the computer program.

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