Source network load storage regulation resource planning method and system for supply guarantee demand in extreme weather

Abstract

The invention discloses a source network load storage regulation resource planning method and system for an extreme weather guarantee supply demand, and relates to the technical field of power system planning, and the method comprises the steps: constructing a source network load storage collaborative planning model objective function, and carrying out the operation and guarantee supply constraint based on the constructed source network load storage collaborative planning model; performing linearization processing on the guaranteed power supply constraint, and constructing and solving a mixed integer linear programming model based on the constructed target function and the guaranteed power supply constraint condition; and obtaining an industrial park source network load storage planning scheme by using the solved mixed integer linear programming model. According to the method, planning, modeling and solving of the source network load storage resources are realized, the source network load storage resources are scientifically planned and reasonably configured, and the safety and economy of operation of the industrial park power distribution network are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system planning, and in particular to a method and system for planning source-grid-load-storage regulation resources to meet power supply needs in extreme weather. Background Art

[0002] The distribution networks in industrial parks often face great pressure to ensure supply under extreme weather conditions, and the problem of exhausting the regulation capacity of conventional power sources. At present, the main regulation capacity of the distribution networks in industrial parks comes from distributed photovoltaics and industrial loads. The power grid as a whole lacks the means to regulate and trade distributed photovoltaics and industrial loads, and fails to give full play to the active support capabilities of source, grid, load and storage for the power grid. On the other hand, from the perspective of power grids in key areas, users have increasingly higher requirements for power supply, but the current problems such as poor self-healing capabilities of the power grid, insufficient flexible interaction and self-support capabilities of the power grid also affect the high-quality power supply to the load, restricting regional economic development and business environment.

[0003] Therefore, there is an urgent need for a resource planning method for source, grid, load and storage in industrial parks that takes extreme weather into consideration, so as to achieve hierarchical supply guarantee for all links of source, grid, load and storage in industrial parks. Summary of the invention

[0004] In view of the problems existing in the existing source-grid-load-storage regulation resource planning method and system for ensuring supply in extreme weather, the present invention is proposed.

[0005] Therefore, the purpose of the present invention is to provide a source-grid-load-storage regulation resource planning method and system for extreme weather supply guarantee needs. In view of the fact that the overall power grid lacks the means to regulate and trade distributed photovoltaic and industrial loads, and fails to give full play to the active support capabilities of the source-grid-load-storage for the power grid, the present invention adopts a source-grid-load-storage regulation resource planning method and system for extreme weather supply guarantee needs to solve the problem.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In the first aspect, an embodiment of the present invention provides a source-grid-load-storage regulation resource planning method for extreme weather supply guarantee demand, which includes: inputting an extreme weather data model, constructing a source-grid-load-storage collaborative planning model and an objective function, and based on the constructed source-grid-load-storage collaborative planning model; based on the constructed objective function and the conditions of the power supply guarantee constraint, constructing and solving a mixed integer linear programming model;

[0008] The results obtained by solving the mixed integer linear programming model are used to obtain the source-grid-load-storage planning scheme for the industrial park.

[0009] As a preferred solution of the source-grid-load-storage regulation resource planning method based on the extreme weather supply demand described in the present invention, wherein: the objective function of constructing the source-grid-load-storage collaborative planning model includes taking the total cost of the source-grid-load-storage collaborative planning as the target and calculating the investment and construction cost. The specific calculation steps are as follows:

[0010]

[0011]

[0012]

[0013]

[0014]

[0015] in, and are the investment cost of energy storage at node i and the investment cost of a single energy storage unit; N ESS,i The number of energy storage units planned for node i is an integer variable, where: represents the investment cost of shunt capacitors; is the unit investment cost of a single shunt capacitor; N C,i is the number of shunt capacitors at node i, SVC investment cost, where C SVC represents the investment cost of SVC; Q SVC,i is the SVC capacity installed on node i; a, b, c, d are cost coefficients [19,22]; C CL represents the controllable load cost, C grid represents the cost of controllable load per unit of electricity, S CL,i represents the total power consumption of the controllable load of node i; is the investment cost of the on-load tap changer OLTC, represents the investment cost of a single OLTC, N OLTC is the number of OLTCs.

[0016] As a preferred solution of the source-grid-load-storage regulation resource planning method based on extreme weather supply demand described in the present invention, wherein: the operation based on the constructed source-grid-load-storage collaborative planning model includes cost control through operation and maintenance, and the specific calculation formula for cost control through operation and maintenance is:

[0017]

[0018]

[0019]

[0020] in, and They are the total operation and maintenance cost and unit operation and maintenance cost of energy storage; S ESS,i (t) is the apparent power of the energy storage at time t; Δt is 1 hour; T is 8760 hours, where, and are the total operation and maintenance cost and unit operation and maintenance cost of the shunt capacitor respectively; N C,i is the total number of capacitors in parallel.

[0021] As a preferred solution of the source-grid-load-storage regulation resource planning method based on extreme weather supply demand described in the present invention, wherein: the power supply guarantee constraints include branch flow constraints, node power balance constraints, operation constraints, controllable photovoltaic constraints, reactive power compensation equipment constraints, network reconstruction constraints, energy storage constraints and power supply guarantee constraints;

[0022] The specific calculation formula of the branch power flow constraint is:

[0023]

[0024]

[0025] Among them, ρ,k∈{a,b,c} represents the phase, U i , U j represents the node voltage amplitude, and They represent the mutual coupling conductance and susceptance of the ρ phase and the k phase of the three-phase line ij respectively. If ρ = k, then and They represent the ρ-phase conductance and susceptance of the three-phase line ij respectively; represents the phase angle difference between the ρ phase and the k phase at node i; represents the phase angle difference between the ρ phase of node i and the k phase of node j;

[0026] The specific calculation formula of the node power balance constraint is:

[0027]

[0028] in, and denote the ρ-phase active and reactive loads of node i respectively; and Respectively represent the active and reactive output of photovoltaic; and They represent the charging and discharging power of the energy storage at node i respectively; and Respectively represent the reactive compensation power of the shunt capacitor and reactor at node i; Indicates the reactive compensation power of SVC;

[0029] The specific calculation formula of the operation constraint is:

[0030]

[0031] Among them, ΔU is the voltage deviation, U N is the rated voltage.

[0032] As a preferred solution of the source-grid-load-storage regulation resource planning method based on extreme weather supply demand described in the present invention, the specific calculation formula of the controllable photovoltaic constraint is:

[0033]

[0034] Among them, S PV Represents the configuration capacity of distributed photovoltaics; P PV Represents photovoltaic output, Q PV Indicates the reactive power flowing into the system; is the power factor angle;

[0035] The specific calculation formula of the reactive compensation equipment constraint is:

[0036]

[0037]

[0038] in, and They represent the number of parallel capacitors and reactors of phase i at node ρ respectively; and Respectively represent the capacity of a single group of parallel capacitors and reactors to be planned; and They represent the switching states of the shunt capacitor and reactor at the i-node ρ phase at time t, respectively, and are binary variables;

[0039] The specific algorithm is as follows:

[0040]

[0041]

[0042]

[0043] in, and Respectively represent the upper limit of the switching state conversion times of the capacitor and the reactor;

[0044] SVC has the characteristic of continuously adjustable reactive power compensation. The specific calculation formula is:

[0045]

[0046] in, Indicates the capacity of the i-node SVC configuration;

[0047] Reactive power compensation equipment, with the following constraints, the specific algorithm is:

[0048]

[0049]

[0050] Among them, Q res is the reactive power reserve coefficient, The reactive maximum load, the capacitive reactive reserve capacity should be 7% to 8% of the reactive load; 0-1 variable They represent the planned states of capacitor and reactor at phase i respectively.

[0051] As a preferred solution of the source-grid-load-storage regulation resource planning method based on extreme weather supply demand described in the present invention, the network reconstruction constraint includes improvement based on the branch power flow equation through the branch power flow equation, and the specific calculation formula is:

[0052]

[0053]

[0054] Among them, Φ l represents the set of all lines, n b and n s Respectively represent the total number of nodes and root nodes in the power distribution system;

[0055] The specific calculation formula of the energy storage constraint is:

[0056]

[0057] in, Respectively represent the energy storage charging and discharging status. When the energy storage battery is charging is 1, otherwise is 1; represents the planning state of energy storage at node i in phase ρ;

[0058] When the number of charge and discharge state conversions causes loss to the energy storage life, the number of charge and discharge state conversions is limited. The specific calculation formula for the limitation is:

[0059]

[0060]

[0061] SOC min N batt P rated，batt ≤E(t)≤SOC max N batt Prated，batt

[0062]

[0063]

[0064] Among them, E(t), P ch (t), P dis (t), Δt represent the remaining capacity, charging and discharging power and time interval of the energy storage battery at the tth moment, δ, η ch , η dis Respectively represent the hourly self-discharge rate and charge and discharge efficiency of the energy storage battery; N batt Indicates the number of energy storage batteries; S batt，unit It is the capacity of a single energy storage unit; SOC min and SOC max Respectively represent the minimum and maximum values ​​of energy storage and power percentage;

[0065] The specific calculation formula of the power supply guarantee constraint is:

[0066]

[0067] Among them, γ1 and γ2 are the target power abandonment rate and target power shortage rate respectively, and γ3 is the percentage coefficient of the load shedding power in the system at time t to the maximum load value.

[0068] As a preferred solution of the source-grid-load-storage regulation resource planning method based on extreme weather supply demand described in the present invention, wherein: the mixed integer linear programming model solved includes inserting cutting plane constraints on the basis of constraints, tightening linear relaxation constraints, and completing the source-grid-load-storage planning scheme for the industrial park. The specific calculation formula inserted is:

[0069] minc T x

[0070]

[0071] in, And N I ∈N:={1,2,...,n}.

[0072] In the second aspect, an embodiment of the present invention provides a source-grid-load-storage regulation resource planning system for extreme weather supply guarantee needs, which includes: a construction module, which is used to construct the objective function of the source-grid-load-storage collaborative planning model, and perform operation and power supply guarantee constraints based on the constructed source-grid-load-storage collaborative planning model; a processing module, which is used to linearize the power supply guarantee constraints, and construct and solve a mixed integer linear programming model based on the constructed objective function and the conditions of the power supply guarantee constraints; a planning module, which is used to use the solved mixed integer linear programming model to obtain a source-grid-load-storage planning scheme for an industrial park.

[0073] In a third aspect, an embodiment of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the processor executes the computer program, it implements any step of the above-mentioned source-grid-load-storage regulation resource planning method based on extreme weather supply demand.

[0074] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the above-mentioned source-grid-load-storage regulation resource planning method based on extreme weather supply demand is implemented.

[0075] The beneficial effects of the present invention are as follows: the present invention provides a source-grid-load-storage regulation resource planning method that takes into account the supply demand in extreme weather. Under the premise of taking into account the supply demand in extreme weather, the planning modeling and solution of source-grid-load-storage resources are realized, the source-grid-load-storage resources are scientifically planned and reasonably allocated, and the safety and economy of the distribution network operation in the industrial park are effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0077] Figure 1 A specific flow chart of a source-grid-load-storage regulation resource planning method and system for ensuring supply in extreme weather conditions provided by an embodiment of the present invention.

[0078] Figure 2 A topology diagram of a 39-node system of an industrial park distribution network, which is a source-grid-load-storage regulation resource planning method and system for ensuring supply in extreme weather conditions provided by an embodiment of the present invention.

[0079] Figure 3 A typical daily output curve of load nodes of a source-grid-load-storage regulation resource planning method and system for ensuring supply in extreme weather provided by an embodiment of the present invention.

[0080] Figure 4 A typical daily photovoltaic output curve diagram of a source-grid-load-storage regulation resource planning method and system for ensuring supply in extreme weather conditions provided by an embodiment of the present invention.

[0081] Figure 5 A schematic diagram of the A-phase voltage level at each node of the system at 24 hours of a source-grid-load-storage regulation resource planning method and system for extreme weather supply guarantee needs provided by an embodiment of the present invention.

[0082] Figure 6 A schematic diagram of the B-phase voltage level at each node at 24 hours in a system of a source-grid-load-storage regulation resource planning method and system for ensuring supply in extreme weather provided by an embodiment of the present invention.

[0083] Figure 7 A schematic diagram of the C-phase voltage level at each node of the system at 24 hours of a source-grid-load-storage regulation resource planning method and system for extreme weather supply guarantee needs provided by an embodiment of the present invention.

[0084] Figure 8 A schematic diagram of the A-phase voltage level at each node of the system at 24 hours of a source-grid-load-storage regulation resource planning method and system for extreme weather supply guarantee needs provided by an embodiment of the present invention.

[0085] Fig. 9 A schematic diagram of the B-phase voltage level at each node at 24 hours in a system of a source-grid-load-storage regulation resource planning method and system for ensuring supply in extreme weather provided by an embodiment of the present invention.

[0086] Fig.10 A schematic diagram of the C-phase voltage level at each node of the system at 24 hours of a source-grid-load-storage regulation resource planning method and system for ensuring supply in extreme weather provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0087] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0088] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0089] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0090] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0091] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0092] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0093] Example 1

[0094] Reference Figures 1 to 10 , which is the first embodiment of the present invention, and provides a source-grid-load-storage regulation resource planning method for extreme weather supply demand, including:

[0095] S1: Construct the objective function of the source-grid-load-storage collaborative planning model, and perform operation and power supply constraints based on the constructed source-grid-load-storage collaborative planning model.

[0096] Among them, the objective function of constructing the source-grid-load-storage collaborative planning model includes starting from the perspective of the distribution network company, taking the total cost of the source-grid-load-storage collaborative planning as the target and calculating the investment and construction cost under the premise of ensuring the power supply quality of users. The specific calculation steps are as follows:

[0097]

[0098]

[0099]

[0100]

[0101]

[0102] in, and are the investment cost of energy storage at node i and the investment cost of a single energy storage unit; N ESS,i The number of energy storage units planned for node i is an integer variable, where: represents the investment cost of shunt capacitors; is the unit investment cost of a single shunt capacitor; N C,i is the number of shunt capacitors at node i, SVC investment cost, where C SVC represents the investment cost of SVC; Q SVC,i is the SVC capacity installed on node i; a, b, c, d are cost coefficients [19,22]; C CL represents the controllable load cost, C grid represents the cost of controllable load per unit of electricity, S CL,i represents the total power consumption of the controllable load of node i; is the investment cost of the on-load tap changer OLTC, represents the investment cost of a single OLTC, N OLTC is the number of OLTCs.

[0103] S1.1 Based on the constructed source-grid-load-storage collaborative planning model, operation includes cost control through operation and maintenance. The specific calculation formula for cost control through operation and maintenance is:

[0104]

[0105]

[0106]

[0107] in, and They are the total operation and maintenance cost and unit operation and maintenance cost of energy storage; S ESS,i (t) is the apparent power of the energy storage at time t; Δt is 1 hour; T is 8760 hours, where, and are the total operation and maintenance cost and unit operation and maintenance cost of the shunt capacitor respectively; N C,i is the total number of capacitors in parallel.

[0108] Table 1 Energy storage parameters to be planned

[0109] Investment cost per unit capacity 1200 NTD Discharge efficiency 95 Unit capacity operation and maintenance cost 0.02 minimum capacity 10 Charging efficiency 95 Maximum capacity 90

[0110] The unit length impedance of the built lines in Table 1 is 0.45+j0.5Ω / km, the voltage fluctuation rate of each node is set to 0-3%, and the voltage deviation range is -5-7%.

[0111] S2: Linearize the power supply guarantee constraint, and build and solve the mixed integer linear programming model based on the constructed objective function and the conditions of the power supply guarantee constraint.

[0112] Among them, power supply constraints include branch flow constraints, node power balance constraints, operation constraints, controllable photovoltaic constraints, reactive power compensation equipment constraints, network reconstruction constraints, energy storage constraints and power supply constraints;

[0113] The specific calculation formula for branch power flow constraint is:

[0114]

[0115]

[0116] Among them, ρ,k∈{a,b,c} represents the phase, U i , U j represents the node voltage amplitude, and They represent the mutual coupling conductance and susceptance of the ρ phase and the k phase of the three-phase line ij respectively. If ρ = k, then and They represent the ρ-phase conductance and susceptance of the three-phase line ij respectively; represents the phase angle difference between the ρ phase and the k phase at node i; represents the phase angle difference between the ρ phase of node i and the k phase of node j;

[0117] The specific calculation formula of the node power balance constraint is:

[0118]

[0119] in, and denote the ρ-phase active and reactive loads of node i respectively; and Respectively represent the active and reactive output of photovoltaic; and They represent the charging and discharging power of the energy storage at node i respectively; and Respectively represent the reactive compensation power of the shunt capacitor and reactor at node i; Indicates the reactive compensation power of SVC;

[0120] The specific calculation formula for the operation constraint is:

[0121]

[0122] Among them, ΔU is the voltage deviation, U N is the rated voltage.

[0123] S2.1: The specific calculation formula for controllable photovoltaic constraints is:

[0124]

[0125] Among them, S PV Represents the configuration capacity of distributed photovoltaics; P PV Represents photovoltaic output, Q PV Indicates the reactive power flowing into the system; is the power factor angle;

[0126] The specific calculation formula for reactive power compensation equipment constraints is:

[0127]

[0128]

[0129] in, and They represent the number of parallel capacitors and reactors of phase i at node ρ respectively; and Respectively represent the capacity of a single group of parallel capacitors and reactors to be planned; and They represent the switching states of the shunt capacitor and reactor at the i-node ρ phase at time t, respectively, and are binary variables;

[0130] In order to extend the service life of the parallel capacitor / reactor and improve its economic efficiency, the number of switching times is limited, and the absolute value linearization method is used to process it to improve the solution efficiency and put it into operation at the same time. The specific algorithm is as follows:

[0131]

[0132]

[0133]

[0134] in, and Respectively represent the upper limit of the switching state conversion times of the capacitor and the reactor;

[0135] SVC has the characteristic of continuously adjustable reactive power compensation. The specific calculation formula is:

[0136]

[0137] in, Indicates the capacity of the i-node SVC configuration;

[0138] Reactive power compensation equipment can only be switched on after construction, so there are the following constraints. The specific algorithm is:

[0139]

[0140]

[0141] Among them, Q res is the reactive power reserve coefficient, The reactive maximum load, the capacitive reactive reserve capacity should be 7% to 8% of the reactive load; 0-1 variable They represent the planned states of capacitor and reactor at phase i respectively.

[0142] S2.2: The network reconstruction constraint includes improvement based on the branch power flow equation through the branch power flow equation. The specific calculation formula is:

[0143]

[0144] Among them, Φ l represents the set of all lines, n b and n s Respectively represent the total number of nodes and root nodes in the power distribution system;

[0145] The specific calculation formula of energy storage constraint is:

[0146]

[0147] in, Respectively represent the energy storage charging and discharging status. When the energy storage battery is charging is 1, otherwise is 1; represents the planning state of energy storage at node i in phase ρ;

[0148] When the number of charge and discharge state conversions causes loss to the energy storage life, the number of charge and discharge state conversions is limited. The specific calculation formula for the limit is:

[0149]

[0150]

[0151] SOC min N batt P rated，batt ≤E(t)≤SOC max Nbatt P rated，batt

[0152]

[0153]

[0154] Among them, E(t), P ch (t), P dis (t), Δt represent the remaining capacity, charging and discharging power and time interval of the energy storage battery at the tth moment, δ, η ch , η dis Respectively represent the hourly self-discharge rate and charge and discharge efficiency of the energy storage battery; N batt Indicates the number of energy storage batteries; S batt，unit It is the capacity of a single energy storage unit; SOC min and SOC max Respectively represent the minimum and maximum values ​​of energy storage and power percentage;

[0155] The specific calculation formula for power supply guarantee constraint is:

[0156]

[0157] Among them, γ1 and γ2 are the target power abandonment rate and target power shortage rate respectively, and γ3 is the percentage coefficient of the load shedding power in the system at time t to the maximum load value.

[0158] Table 2 Adjustment resource planning results

[0159]

[0160] Based on the parameters in Table 2, the objective function and constraints of the source-grid-load-storage planning model for the industrial park are established. Then, the mixed integer linear programming model is solved by using branch-cut to obtain the resource regulation planning scheme for the industrial park.

[0161] S3: Using the solved mixed integer linear programming model, the source-grid-load-storage planning scheme for the industrial park is obtained.

[0162] Among them, the mixed integer linear programming model solved includes inserting cutting plane constraints on the basis of constraints, tightening linear relaxation constraints, and completing the source-grid-load-storage planning scheme of the industrial park. The specific calculation formula inserted is:

[0163] minc T x

[0164]

[0165] in, And N I ∈N:={1,2,...,n}.

[0166] In a preferred embodiment, a source-grid-load-storage regulation resource planning system for extreme weather supply demand includes a construction module, which constructs an objective function of a source-grid-load-storage collaborative planning model, and performs operation and power supply constraints based on the constructed source-grid-load-storage collaborative planning model; a processing module, which linearizes the power supply constraints, and constructs and solves a mixed integer linear programming model based on the constructed objective function and the conditions of the power supply constraints; and a planning module, which uses the solved mixed integer linear programming model to obtain a source-grid-load-storage planning scheme for an industrial park.

[0167] The above-mentioned unit modules may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above-mentioned modules.

[0168] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0169] In summary, the present invention provides a source-grid-load-storage regulation resource planning method that takes into account the supply demand in extreme weather. Under the premise of taking into account the supply demand in extreme weather, the planning modeling and solution of source-grid-load-storage resources are realized, the source-grid-load-storage resources are scientifically planned and reasonably allocated, and the safety and economy of the distribution network operation in the industrial park are effectively improved.

[0170] Example 2

[0171] Reference Figures 1 to 10 , which is the second embodiment of the present invention, and this embodiment provides a source-grid-load-storage regulation resource planning method for extreme weather supply demand. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0172] The process of solving the above model using branch and cut is as follows: based on the mixed integer linear programming problem constructed in the previous step, determine the optimization direction, in which some variable constraints are integer constraints; relax the integer constraints and transform the mixed integer programming problem into a linear programming problem; solve the LP problem, if the optimal solution satisfies all integer constraints of MILP, then directly find the MILP optimal solution; any feasible solution of the LP problem that satisfies the integer constraints provides the upper bound of the optimal solution; if the upper bound is equal to the lower bound, then the MILP optimal solution is found; cutting plane generation: find a cut that can trim the linear relaxation, if such a cut can be found, return to the second step and solve the linear relaxation model after the cut; if the integer constraint is still not satisfied, there is a situation where the integer variable value is non-integer in the obtained solution, take a variable from the variables that do not satisfy the integer constraint, create two branch nodes n, select a target branch node from the search tree L, relax the node integer problem into a linear programming problem, and use the linear programming solution algorithm to solve the relaxed linear programming problem;

[0173] According to the solution of the linear programming problem, the nodes are pruned. If the relaxed linear programming problem has no solution, the nodes are pruned. If the optimal solution of the relaxed linear programming problem exceeds the upper bound of the current optimal solution, the nodes are pruned. If the optimal solution of the relaxed linear programming problem does not exceed the upper bound of the current optimal solution, and the current solution is a feasible solution to the integer problem, the current upper bound and the current optimal solution are updated. If the node cannot be pruned, further branching is performed, and nodes are created and added to the search tree.

[0174] Table 3 Planning costs and operating indicators

[0175]

[0176] Table 3 verifies the planning effect by comparing the three-phase voltage levels of each node in the system on a typical day before and after planning.

[0177] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A resource planning method for source-grid-load-storage regulation to meet the demand for supply guarantee in extreme weather, characterized by: include, Input the extreme weather data model, build the source-grid-load-storage collaborative planning model and objective function, based on the built source-grid-load-storage collaborative planning model; Based on the constructed objective function and the power supply constraints, a mixed integer linear programming model is constructed and solved; The results obtained by solving the mixed integer linear programming model are used to obtain the source-grid-load-storage planning scheme for the industrial park.

2. The method for planning source-grid-load-storage regulation resources for extreme weather supply demand as claimed in claim 1, characterized in that: The objective function of constructing the source-grid-load-storage collaborative planning model includes taking the total cost of the source-grid-load-storage collaborative planning as the target and calculating the investment and construction cost. The specific calculation steps are as follows: in, and are the investment cost of energy storage at node i and the investment cost of a single energy storage unit; N ESS,i The number of energy storage units planned for node i is an integer variable, where: represents the investment cost of shunt capacitors; is the unit investment cost of a single shunt capacitor; N C,i is the number of shunt capacitors at node i, SVC investment cost, where C SVC represents the investment cost of SVC; Q SVC,i is the SVC capacity installed on node i; a, b, c, d are cost coefficients [19,22]; C CL represents the controllable load cost, C grid represents the cost of controllable load per unit of electricity, S CL,i represents the total power consumption of the controllable load of node i; is the investment cost of the on-load tap changer OLTC, represents the investment cost of a single OLTC, N OLTC is the number of OLTCs.

3. The resource planning method for source-grid-load-storage regulation for extreme weather supply demand as claimed in claim 2, characterized in that: The operation based on the constructed source-grid-load-storage collaborative planning model includes cost control through operation and maintenance. The specific calculation formula for cost control through operation and maintenance is: in, and They are the total operation and maintenance cost and unit operation and maintenance cost of energy storage; S ESS,i (t) is the apparent power of the energy storage at time t; Δt is 1 hour; T is 8760 hours, where, and are the total operation and maintenance cost and unit operation and maintenance cost of the shunt capacitor respectively; N C,i is the total number of capacitors in parallel.

4. The method for planning source-grid-load-storage regulation resources for extreme weather supply demand as claimed in claim 3, characterized in that: The power supply guarantee constraints include branch flow constraints, node power balance constraints, operation constraints, controllable photovoltaic constraints, reactive power compensation equipment constraints, network reconstruction constraints, energy storage constraints and power supply guarantee constraints; The specific calculation formula of the branch power flow constraint is: Among them, ρ,k∈{a,b,c} represents the phase, U i , U j represents the node voltage amplitude, and They represent the mutual coupling conductance and susceptance of the ρ phase and the k phase of the three-phase line ij respectively. If ρ = k, then and They represent the ρ-phase conductance and susceptance of the three-phase line ij respectively; represents the phase angle difference between the ρ phase and the k phase at node i; represents the phase angle difference between the ρ phase of node i and the k phase of node j; The specific calculation formula of the node power balance constraint is: in, and denote the ρ-phase active and reactive loads of node i respectively; and Respectively represent the active and reactive output of photovoltaic; and They represent the charging and discharging power of the energy storage at node i respectively; and Respectively represent the reactive compensation power of the shunt capacitor and reactor at node i; Indicates the reactive compensation power of SVC; The specific calculation formula of the operation constraint is: Among them, ΔU is the voltage deviation, U N is the rated voltage.

5. The method for planning source-grid-load-storage regulation resources for extreme weather supply demand as claimed in claim 4, characterized in that: The specific calculation formula of the controllable photovoltaic constraint is: Among them, S PV Represents the configuration capacity of distributed photovoltaics; P PV Represents photovoltaic output, Q PV Indicates the reactive power flowing into the system; is the power factor angle; The specific calculation formula of the reactive compensation equipment constraint is: in, and They represent the number of parallel capacitors and reactors of phase i at node ρ respectively; and Respectively represent the capacity of a single group of parallel capacitors and reactors to be planned; and They represent the switching states of the shunt capacitor and reactor at the i-node ρ phase at time t, respectively, and are binary variables; The specific algorithm is as follows: in, and Respectively represent the upper limit of the switching state conversion times of the capacitor and the reactor; SVC has the characteristic of continuously adjustable reactive power compensation. The specific calculation formula is: in, Indicates the capacity of the i-node SVC configuration; Reactive power compensation equipment, with the following constraints, the specific algorithm is: Among them, Q res is the reactive power reserve coefficient, The reactive maximum load, the capacitive reactive reserve capacity should be 7% to 8% of the reactive load; 0-1 variable They respectively represent the planned states of the capacitor and the reactor at the i-node ρ phase.

6. The method for planning source-grid-load-storage regulation resources for extreme weather supply demand as claimed in claim 5, characterized in that: The network reconstruction constraint includes improving the branch power flow equation based on the branch power flow equation. The specific calculation formula is: Among them, Φ l Represents the set of all lines, n b and n s Respectively represent the total number of nodes and root nodes in the power distribution system; The specific calculation formula of the energy storage constraint is: in, Respectively represent the energy storage charging and discharging status. When the energy storage battery is charging is 1, otherwise is 1; represents the planning state of energy storage at node i in phase ρ; When the number of charge and discharge state conversions causes loss to the energy storage life, the number of charge and discharge state conversions is limited. The specific calculation formula for the limitation is: SOC min N batt P rated，batt ≤E(t)≤SOC max N batt P rated，batt Among them, E(t), P ch (t), P dis (t), Δt represent the remaining capacity, charging and discharging power and time interval of the energy storage battery at the tth moment, δ, η ch , η dis Respectively represent the hourly self-discharge rate and charge and discharge efficiency of the energy storage battery; N batt Indicates the number of energy storage batteries; S batt，unit It is the capacity of a single energy storage unit; SOC min and SOC max Respectively represent the minimum and maximum values ​​of energy storage and power percentage; The specific calculation formula of the power supply guarantee constraint is: Among them, γ1 and γ2 are the target power abandonment rate and target power shortage rate respectively, and γ3 is the percentage coefficient of the load shedding power in the system at time t to the maximum load value.

7. The method for planning source-grid-load-storage regulation resources for extreme weather supply demand as claimed in claim 6, characterized in that: The mixed integer linear programming model to be solved includes inserting cutting plane constraints on the basis of constraints, tightening linear relaxation constraints, and completing the source-grid-load-storage planning scheme for the industrial park. The specific calculation formula for the insertion is: in, And N I ∈N:={1,2,...,n}.

8. A resource planning system for regulating source, grid, load and storage for supply guarantee in extreme weather, based on the resource planning method for regulating source, grid, load and storage for supply guarantee in extreme weather as claimed in any one of claims 1 to 7, characterized in that: include, A construction module is used to input the extreme weather data model, construct the source-grid-load-storage collaborative planning model and the objective function, based on the constructed source-grid-load-storage collaborative planning model; A processing module, used for constructing and solving a mixed integer linear programming model based on the constructed objective function and the power supply guarantee constraint conditions; The planning module is used to obtain the source-grid-load-storage planning scheme of the industrial park by using the results obtained by solving the mixed integer linear programming model.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the source-grid-load-storage regulation resource planning method for extreme weather supply guarantee needs described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the source-grid-load-storage regulation resource planning method for extreme weather supply guarantee needs as described in any one of claims 1 to 7 are implemented.

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