Distributed photovoltaic access power distribution network operation risk assessment method, medium and equipment

Abstract

The invention discloses a distributed photovoltaic access power distribution network operation risk assessment method, a medium and equipment. The method comprises the following steps: constructing power distribution network risk assessment double-layer indexes; establishing a day-ahead optimal scheduling objective function of the power distribution network, and solving the day-ahead optimal scheduling objective function of the power distribution network based on the first constraint condition to obtain day-ahead operation power of the energy storage equipment; establishing a power distribution network operation risk assessment objective function, and solving the power distribution network operation risk assessment objective function based on a second constraint condition to obtain an energy storage equipment power adjustment amount, a load shedding power adjustment amount, a light abandoning power adjustment amount and a worst photovoltaic uncertainty output scene; and determining a scheduling risk index value, determining an operation risk index value according to the worst photovoltaic uncertainty output scene data, and performing scheduling regulation and control according to the scheduling risk index value when the operation risk index value reaches a set threshold value. According to the method, the operation risk of the large-scale distributed photovoltaic access power distribution network can be evaluated, and scheduling regulation and control can be carried out based on the evaluation result.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid risk assessment, and in particular to a method, medium and equipment for assessing the operational risk of distributed photovoltaic access to a distribution network. Background Art

[0002] With the continuous maturity of distributed power technology and the reduction of costs, its installed capacity has expanded rapidly, especially in the fields of photovoltaic and wind power. Due to the large-scale, multi-point decentralized access characteristics, intermittent and random nature of distributed power, the access of distributed power will change the power flow distribution of the power grid, resulting in frequent fluctuations in the voltage and frequency of the local power grid, and prone to voltage and frequency over-limit problems, which will in turn affect the power supply quality of the power grid, and may also cause damage to the equipment in the power grid, reduce the reliability of the power grid, and easily cause power grid failures or power outages. Therefore, the access of distributed power greatly increases the complexity and difficulty of control of the power grid, and brings challenges to the safe production and stable operation of the power grid. Therefore, it is imperative to evaluate the impact of large-scale distributed photovoltaic access on the operation risk of the distribution network. Summary of the invention

[0003] The present invention aims to solve at least one of the technical problems in the related art to a certain extent. To this end, the first object of the present invention is to provide a method for assessing the operating risk of distributed photovoltaic access to a distribution network, which can perform a robustness assessment on the operating risk of a large-scale distributed photovoltaic access to a distribution network, and can perform corresponding scheduling and regulation based on the assessment results.

[0004] A second object of the present invention is to provide a computer-readable storage medium.

[0005] A third object of the present invention is to provide an electronic device.

[0006] To achieve the above object, the present invention is implemented through the following technical solutions:

[0007] A method for assessing the operation risk of distributed photovoltaic access to a distribution network, comprising:

[0008] Constructing a double-layer indicator for distribution network risk assessment, wherein the double-layer indicator for distribution network risk assessment includes an operation risk indicator and a dispatching risk indicator;

[0009] Establishing a distribution network day-ahead optimization dispatching objective function and establishing a first constraint condition, solving the distribution network day-ahead optimization dispatching objective function based on the first constraint condition to obtain the day-ahead operating power of the energy storage device;

[0010] Establishing a distribution network operation risk assessment objective function and a second constraint condition, solving the distribution network operation risk assessment objective function based on the second constraint condition to obtain the energy storage device power adjustment, load shedding power adjustment, abandoned light power adjustment and the worst photovoltaic uncertainty output scenario;

[0011] The day-ahead load shedding power and the day-ahead abandoned light power are obtained, and a dispatching risk index value is determined according to the day-ahead operating power of the energy storage device, the power adjustment amount of the energy storage device, the day-ahead load shedding power, the day-ahead abandoned light power, the load shedding power adjustment amount, and the abandoned light power adjustment amount; the operation risk index value is determined according to the worst photovoltaic uncertainty output scenario data; and when the operation risk index value reaches a set threshold, the dispatching and control are performed with the dispatching risk index value.

[0012] Preferably, the operation risk indicators include a voltage over-limit indicator, a line power over-limit indicator and a power factor over-limit indicator.

[0013] Preferably, the dispatch risk indicators include an energy storage equipment daily operating power indicator, a load shedding indicator, and a solar abandonment indicator.

[0014] Preferably, the distribution network day-ahead optimal dispatch objective function is established, including:

[0015] The power distribution cost of the distribution network, the operating cost of the energy storage equipment, the cost of abandoned light and the line loss cost are obtained, and the day-ahead optimization scheduling objective function of the distribution network is established based on the power distribution cost of the distribution network, the operating cost of the energy storage equipment, the cost of abandoned light and the line loss cost.

[0016] Preferably, the first constraint condition includes an operation index constraint condition, an active power constraint condition, a reactive power constraint condition, a distributed photovoltaic node voltage drop constraint condition and a power balance constraint condition.

[0017] Preferably, the distribution network operation risk assessment objective function is established, including:

[0018] The load shedding cost, the abandonment cost, and the probability of the photovoltaic uncertain output scenario of the photovoltaic uncertain output scenario are obtained, and the distribution network operation risk assessment objective function is established according to the load shedding cost, the abandonment cost, and the probability of the photovoltaic uncertain output scenario of the photovoltaic uncertain output scenario.

[0019] Preferably, the second constraint condition is a probability distribution constraint condition of discrete scenarios of photovoltaic uncertain output.

[0020] Preferably, the daily operating power index of the energy storage equipment is determined according to the day-ahead operating power of the energy storage equipment and the power adjustment amount of the energy storage equipment; the daily load shedding power is determined according to the day-ahead load shedding power and the load shedding power adjustment amount, the daily abandoned light power is determined according to the day-ahead abandoned light power and the abandoned light power adjustment amount, and the load shedding index and the abandoned light index are respectively determined according to the day-ahead load shedding power and the day-abandoned light power.

[0021] To achieve the above-mentioned purpose, the second aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the above-mentioned distributed photovoltaic access distribution network operation risk assessment method is implemented.

[0022] To achieve the above-mentioned purpose, the third aspect of the present invention provides an electronic device, 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, the above-mentioned distributed photovoltaic access to the distribution network operation risk assessment method is implemented.

[0023] The present invention has at least the following technical effects:

[0024] The present invention proposes a method for risk assessment of distributed photovoltaic access distribution network operation for a distribution network system with large-scale distributed photovoltaic access. The method constructs a double-layer index for distribution network risk assessment, establishes a distribution network day-ahead optimization dispatching objective function, a distribution network operation risk assessment objective function and corresponding constraints, wherein the constraint of the distribution network operation risk assessment objective function is a probability distribution constraint of discrete scenarios of photovoltaic uncertainty output. The distribution network operation risk assessment objective function is solved based on the constraint and risk assessment is performed according to the decision results of the solution, which can make the risk assessment more robust. In addition, the present invention can also use the dispatching risk index in the double-layer index for dispatching and regulation based on the risk assessment result, which can reduce the operation risk of the distribution network.

[0025] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 The present invention is a flowchart of a method for assessing the operation risks of distributed photovoltaic access to a distribution network according to an embodiment of the present invention.

[0027] Figure 2 This is a node power distribution network topology diagram of an embodiment of the present invention.

[0028] Figure 3 Schematic diagram of a typical distributed photovoltaic output scenario according to an embodiment of the present invention.

[0029] Figure 4 Schematic diagram of the energy storage day-ahead output plan according to an embodiment of the present invention.

[0030] Figure 5 Schematic diagram of photovoltaic reduction amount in the day-ahead scheduling plan according to an embodiment of the present invention.

[0031] Figure 6(a)-6(c) Schematic diagram of the operational risk indicator evaluation results of each scheme in an embodiment of the present invention.

[0032] Figure 7 Schematic diagram of scheduling risk indicator evaluation for each solution in an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The present embodiment is described in detail below, and examples of the embodiment are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0034] The following describes the distributed photovoltaic access distribution network operation risk assessment method, medium and device of this embodiment with reference to the accompanying drawings.

[0035] Figure 1 Flow chart of the method for risk assessment of distributed photovoltaic access to distribution network operation according to an embodiment of the present invention. Figure 1 As shown, the method includes:

[0036] Step S1: construct a two-layer indicator for distribution network risk assessment, which includes an operation risk indicator and a dispatching risk indicator.

[0037] In this embodiment, the operation risk indicators include a voltage over-limit indicator, a line power over-limit indicator, and a power factor over-limit indicator.

[0038] The maximum allowable risk is scaled so that each indicator becomes a standardized result distributed in the interval [0,1], and the larger the value of the operation risk indicator, the greater the risk. When the operation risk indicator is 1, corresponding control measures need to be taken.

[0039] The voltage over-limit indicator is expressed as follows:

[0040]

[0041] Among them, r V represents the voltage over-limit index, i represents the i-th photovoltaic uncertainty output scenario, s represents the number of photovoltaic uncertainty output scenarios, π i represents the probability of occurrence of the i-th photovoltaic uncertainty output scenario, j represents the j-th distributed photovoltaic node, and j nrepresents the total number of distributed photovoltaic nodes, max represents the maximum value function, represents the voltage of node j at time t under photovoltaic uncertainty output scenario i, , V Represent the upper and lower limits of the node voltage respectively.

[0042] The line power over-limit indicator is expressed as follows:

[0043]

[0044] Among them, r P Indicates the line power limit indicator, L indicates the Lth line, L n Indicates the total number of lines, P L，max Indicates the upper limit of active power of line L. It represents the active power of line L at time t under the PV uncertain output scenario i.

[0045] The power factor over-limit index is expressed as follows:

[0046]

[0047] Among them, r Z Indicates the power factor over-limit indicator. It represents the power factor deviation at time t under the photovoltaic uncertainty output scenario i, Indicates the maximum power factor deviation that can be accepted during normal system operation.

[0048] Dispatching risk indicators include the daily operating power index, load shedding index and solar abandonment index of energy storage equipment.

[0049] When any of the operating risk indicators reaches its respective risk threshold, it is necessary to first use active and reactive reserve to make adjustments. When the reserve capacity of the energy storage equipment is insufficient, it is necessary to take load shedding and light abandonment measures to meet the safety requirements of the distribution network operation. For example, the voltage over-limit indicator threshold is set to 10%, the line power over-limit indicator threshold is set to 85%, and the power factor over-limit indicator threshold is set to 9%. When any of the operating risk indicators reaches its respective risk threshold, it can be regulated based on the daily operating power of the energy storage equipment. When the reserve capacity of the energy storage equipment is insufficient, the load shedding power and the light abandonment power can be dispatched and regulated during the day, and the dispatch risk indicator is met when the load shedding indicator and the light abandonment indicator are met.

[0050] The load shedding index is expressed as follows:

[0051]

[0052] Among them, r c Indicates the load shedding index, It represents the load shedding power at time t in the day under the photovoltaic uncertainty output scenario i.

[0053] The abandoned light index is expressed as follows:

[0054]

[0055] Among them, r ab Indicates the light abandonment indicator. It represents the abandoned light power at time t in the day under the photovoltaic output uncertainty scenario i.

[0056] Step S2: Establish a distribution network day-ahead optimization dispatching objective function and establish a first constraint condition, and solve the distribution network day-ahead optimization dispatching objective function based on the first constraint condition to obtain the day-ahead operating power of the energy storage device.

[0057] In this embodiment, establishing a distribution network day-ahead optimization dispatch objective function includes: obtaining the distribution network distribution cost, the energy storage equipment operation cost, the abandoned light cost and the line loss cost, and establishing the distribution network day-ahead optimization dispatch objective function based on the distribution network distribution cost, the energy storage equipment operation cost, the abandoned light cost and the line loss cost. The first constraint condition includes an operation index constraint condition, an active power constraint condition, a reactive power constraint condition, a distributed photovoltaic node voltage drop constraint condition and a power balance constraint condition.

[0058] Specifically, based on the distributed photovoltaic forecast data in the day-ahead stage, a distribution network day-ahead optimization dispatching model with the minimum total operation cost of the distribution network can be constructed. The day-ahead optimization dispatching model of the distribution network takes into account the power supply side, the grid side, the load side and the flexibility resources, and also takes into account the risk constraints of the distribution network operation. The total operation cost of the day-ahead optimization dispatching of the distribution network includes the distribution cost of the upper distribution network, the operation cost of the energy storage equipment, the cost of abandoned light and the line loss cost. The distribution network flow model adopts the DistFlow flow model. The distribution network day-ahead optimization dispatching objective function can be expressed as:

[0059] min C PG +C ES +C ab +C loss (6)

[0060]

[0061] Among them, C PG , C ES , C ab and C loss They represent the distribution network distribution cost, energy storage equipment operation cost, abandoned light cost and line loss cost respectively, T is the dispatching period, and They represent the power distribution of the distribution network, the day-ahead operating power of the energy storage equipment, the day-ahead abandoned optical power and the line loss power respectively. and They represent the unit costs of distribution network distribution power, day-ahead operating power of energy storage equipment, day-ahead abandoned optical power and line loss power respectively.

[0062] The first constraint is expressed as follows:

[0063] r V ,r P ,r Z ≤1(11)

[0064]

[0065] Among them, P hj (t), Q hj (t) represent the active power and reactive power flowing from distributed photovoltaic node h to distributed photovoltaic node j, respectively, P jk (t), Q jk (t) represent the active power and reactive power flowing from distributed photovoltaic node j to distributed photovoltaic node k, respectively. k is the downstream node connected to j, K is the set of downstream nodes connected to j, P j (t), Q j (t) represent the active power and reactive power of distributed photovoltaic node j, which are obtained through the distributed photovoltaic prediction data in the day-ahead stage, r hj 、x hj They represent the resistance and reactance of the hj line, I hj '(t) represents the square of the current in the hj line, V j '(t), V h '(t) represents the square of the voltage of distributed photovoltaic nodes j and h. Wherein, equations (11)-(15) are the operating index constraint conditions, active power constraint conditions, reactive power constraint conditions, distributed photovoltaic node voltage drop constraint conditions and power balance constraint conditions.

[0066] It should be noted that the first constraint condition also includes the energy storage device operation constraint condition. The energy storage device operation constraint condition is expressed as follows:

[0067]

[0068] in, They represent the energy storage capacity at time t and time t+1 respectively, Respectively represent the energy storage charging and discharging power, η cha , η dis Respectively represent the energy storage charging and discharging efficiency coefficient, υ ES Represents the self-loss coefficient of energy storage equipment, Indicates the maximum charging and discharging power of energy storage.

[0069] In this embodiment, the day-ahead optimization dispatch objective function of the distribution network can be solved based on the first constraint condition to obtain the day-ahead operating power of the energy storage device, that is, , and get the abandoned optical power

[0070] Step S3: Establish a distribution network operation risk assessment objective function and establish a second constraint condition. Based on the second constraint condition, solve the distribution network operation risk assessment objective function to obtain the energy storage equipment power adjustment, load shedding power adjustment, abandoned light power adjustment and the worst photovoltaic uncertainty output scenario.

[0071] In this embodiment, a distribution network operation risk assessment objective function is established, including: obtaining the load shedding cost, the abandonment cost, and the probability of occurrence of photovoltaic uncertainty output scenarios in photovoltaic uncertainty output scenarios, and establishing a distribution network operation risk assessment objective function based on the load shedding cost, the abandonment cost, and the probability of occurrence of photovoltaic uncertainty output scenarios in photovoltaic uncertainty output scenarios.

[0072] Among them, the second constraint condition is the probability distribution constraint condition of discrete scenarios of photovoltaic uncertain output.

[0073] Specifically, based on the above-mentioned distribution network day-ahead optimization dispatch model and the day-ahead distributed photovoltaic output forecast results, the distribution network day-ahead optimization dispatch strategy can be formulated. The risk of the actual operation of the distribution network during the day is related to the uncertainty of distributed photovoltaic output. Historical data contains important distributed photovoltaic output information. Based on the data-driven method, a probability distribution fuzzy set can be constructed to evaluate the risk of distribution network operation during the day under the worst photovoltaic uncertainty output scenario.

[0074] The objective function of distribution network operation risk assessment is expressed as follows:

[0075]

[0076] Among them, min is the minimum function, X is the decision variable, including the power adjustment of energy storage equipment, load shedding power adjustment and abandoned light power adjustment in each period, p i represents the probability distribution prediction value of the PV uncertainty output scenario i, φ represents the probability scenario fuzzy set, They represent the load shedding cost and the solar curtailment cost of the photovoltaic output uncertainty scenario i. i Under all probability scenario fuzzy sets, the worst photovoltaic uncertainty output scenario set can be found. The decision variable X is expressed as follows:

[0077]

[0078] in, They respectively represent the power adjustment of energy storage equipment, load shedding power adjustment and abandoned light power adjustment.

[0079] Formula (18) contains the photovoltaic uncertainty output scenario, and it is impossible to obtain a more accurate scenario distribution probability based on historical data. In order to characterize the robustness characteristics of the scenario, a confidence interval based on the 1-norm and the ∞-norm is established to constrain the fluctuation range of the probability constraint of the photovoltaic uncertainty output discrete scenario, where the probability distribution constraint condition of the photovoltaic uncertainty output discrete scenario is expressed as follows:

[0080]

[0081] p(||p i -p*|| ∞ ≤θ ∞ )≥1-2N exp(-2Mθ ∞ ) (twenty one)

[0082] Where: p(·) is the probability distribution function of the PV output uncertainty scenario, p* is the actual value of the probability distribution of the PV output uncertainty scenario, θ1, θ ∞ They represent the deviation allowable values ​​of 1-norm and ∞-norm respectively, N is the number of discrete scenarios, and M is the number of sample scenarios. ∞ They are respectively expressed as follows:

[0083]

[0084] Among them, α1, α ∞ are the confidence levels of the 1-norm and the ∞-norm respectively.

[0085] The confidence set P of the probability distribution can be expressed as:

[0086]

[0087] Among them, p i * Actual value of probability distribution of PV uncertainty output scenario i.

[0088] In this embodiment, the distribution network operation risk assessment objective function is solved based on the second constraint condition to obtain the power adjustment of the energy storage device, the load shedding power adjustment, and the abandoned light power adjustment, that is, and the worst photovoltaic output uncertainty scenario.

[0089] Step S4: Obtain the load shedding power and the abandoned light power on the previous day, determine the dispatching risk index value according to the previous day operating power of the energy storage device, the power adjustment amount of the energy storage device, the load shedding power on the previous day, the abandoned light power on the previous day, the load shedding power adjustment amount and the abandoned light power adjustment amount, determine the operation risk index value according to the worst photovoltaic uncertainty output scenario data, and when the operation risk index value reaches the set threshold, perform dispatching and control based on the dispatching risk index value.

[0090] Specifically, the day-ahead load shedding power can be obtained in advance, and the day-ahead curtailed optical power and the day-ahead operating power of the energy storage device can be solved by the day-ahead optimization dispatching model of the distribution network. The power adjustment amount of the energy storage device, the load shedding power adjustment amount and the curtailed optical power adjustment amount can be solved by the distribution network operation risk assessment model. Therefore, the day-ahead operating power of the energy storage device can be obtained by the day-ahead operating power of the energy storage device and the power adjustment amount of the energy storage device. The day-ahead load shedding power is determined according to the day-ahead load shedding power and the load shedding power adjustment amount, and the day-ahead optical power is determined according to the day-ahead curtailed optical power and the curtailed optical power adjustment amount. Then, the day-ahead load shedding power and the day-ahead optical power are substituted into formulas (4) and (5) to obtain the dispatching risk indicators, namely the load shedding index and the curtailed optical index. Among them, after obtaining the worst photovoltaic uncertainty output scenario, the voltage over-limit index value, line power over-limit index value and power factor over-limit index value can be calculated based on the data in the worst photovoltaic uncertainty output scenario, such as the parameters in formulas (1)-(3). When any of these operation risk index values ​​reaches the corresponding threshold, regulation is performed based on the daily operating power of the energy storage device. When the backup capacity of the energy storage device is insufficient, the daily load shedding power and the daily abandoned light power can be dispatched and regulated, and satisfying the load shedding index and the abandoned light index means satisfying the dispatch risk index requirements.

[0091] In this embodiment, the daily operating power, daily load shedding power and daily abandoned optical power of the energy storage device are respectively expressed as follows:

[0092]

[0093] in, Indicates the daily operating power of the energy storage device. Indicates the load shedding power on the previous day.

[0094] Take the 33-node distribution network system as an example for analysis. Figure 2 As shown in Figure 1, the distribution network system is connected to 10 distributed photovoltaic power generation systems, each with an installed capacity of 1000kW. Three energy storage devices are configured at nodes 4, 12, and 33, respectively. Based on the data-driven approach, the distributed photovoltaic scenarios are reduced to obtain typical photovoltaic scenarios and probability values ​​as shown in Figure 1. Figure 3 As shown, the probability value corresponding to each scene can be obtained by reducing the algorithm based on the data-driven approach.

[0095] Four energy storage equipment configuration capacity comparison schemes are set up:

[0096] Solution 1: The energy storage device configuration capacity of each node is 0;

[0097] Solution 2: The energy storage equipment configuration capacity of each node is 500kW, and the maximum charging and discharging power is 100kW;

[0098] Solution 3: The energy storage equipment configuration capacity of each node is 5000kW, and the maximum charging and discharging power is 1000kW;

[0099] The energy storage equipment output plan is as follows: Figure 4 As shown in the figure, it can be seen that energy storage equipment can play an important role in regulating the operation of distribution networks, storing electricity during the peak photovoltaic period at noon, and releasing electricity during peak load periods, smoothing the peak and valley fluctuations in electricity demand and supply, and promoting the consumption of new energy. Figure 4 It can also be seen that Case 2 has a smaller storage configuration capacity than Scheme 3, and its output in the day-ahead dispatch plan is also smaller, and its ability to balance the source and load of the distribution network system is also smaller. Figure 5 The photovoltaic capacity cut in each scheme at each time period is shown. It can be found that schemes 1 and 2 cannot fully absorb photovoltaic power during the peak photovoltaic period, and photovoltaic power needs to be cut to meet the safety constraints of distribution network operation. However, scheme 3, with large-capacity energy storage equipment, can fully adjust the source-load balance and achieve a high proportion of distributed photovoltaic power consumption.

[0100] The operational risk assessment index results of each scheme are as follows: Figure 6(a)-6(c) As shown in Figure 1, by comparing the operational risk assessment indicators of the three cases, it can be seen that without configuring energy storage equipment, Solution 1 in 6(a) has poor ability to cope with the uncertainty of distributed photovoltaics and has a larger operational risk indicator. Figure 7 As shown in the figure, in order to ensure the safe and stable operation of the distribution network, there is a large risk of curtailment and load shedding during the day. However, for Schemes 2 and 3, due to the flexible adjustment of energy storage equipment, the uncertainty of distributed photovoltaics during the day can be effectively dealt with, so the scheduling risk is 0.

[0101] Furthermore, the present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the above-mentioned distributed photovoltaic access to a distribution network operation risk assessment method can be implemented.

[0102] Furthermore, the present invention also provides an electronic device, 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, the above-mentioned distributed photovoltaic access to the distribution network operation risk assessment method can be implemented.

[0103] In summary, the present invention proposes a method for risk assessment of distributed photovoltaic access distribution network operation for a distribution network system with large-scale distributed photovoltaic access. The method constructs a two-layer index for distribution network risk assessment, establishes a distribution network day-ahead optimization scheduling objective function, a distribution network operation risk assessment objective function and corresponding constraints, wherein the constraint of the distribution network operation risk assessment objective function is a probability distribution constraint of discrete scenarios of photovoltaic uncertainty output. The distribution network operation risk assessment objective function is solved based on the constraint and risk assessment is performed according to the decision results of the solution, which can make the risk assessment more robust. In addition, the present invention can also use the scheduling risk indicator in the two-layer index to perform scheduling and regulation based on the risk assessment result, which can reduce the operation risk of the distribution network.

[0104] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0105] Although the content of the present invention has been described in detail through the above preferred embodiments, it should be appreciated that the above description should not be considered as a limitation of the present invention. After reading the above content, it will be apparent to those skilled in the art that various modifications and substitutions of the present invention will occur. Therefore, the protection scope of the present invention should be limited by the appended claims.

Claims

1. A method for risk assessment of distributed photovoltaic access to distribution network operation. It is characterized in that include: Constructing a double-layer indicator for distribution network risk assessment, wherein the double-layer indicator for distribution network risk assessment includes an operation risk indicator and a dispatching risk indicator; Establishing a distribution network day-ahead optimization dispatching objective function and establishing a first constraint condition, solving the distribution network day-ahead optimization dispatching objective function based on the first constraint condition to obtain the day-ahead operating power of the energy storage device; Establishing a distribution network operation risk assessment objective function and a second constraint condition, solving the distribution network operation risk assessment objective function based on the second constraint condition to obtain the energy storage device power adjustment, load shedding power adjustment, abandoned light power adjustment and the worst photovoltaic uncertainty output scenario; The day-ahead load shedding power and the day-ahead abandoned light power are obtained, and a dispatching risk index value is determined according to the day-ahead operating power of the energy storage device, the power adjustment amount of the energy storage device, the day-ahead load shedding power, the day-ahead abandoned light power, the load shedding power adjustment amount, and the abandoned light power adjustment amount; the operation risk index value is determined according to the worst photovoltaic uncertainty output scenario data; and when the operation risk index value reaches a set threshold, the dispatching and control are performed with the dispatching risk index value.

2. The method for assessing the operation risk of distributed photovoltaic access to a distribution network as claimed in claim 1, It is characterized in that The operation risk indicators include voltage over-limit indicator, line power over-limit indicator and power factor over-limit indicator.

3. The method for assessing the operation risk of distributed photovoltaic access to a distribution network as claimed in claim 1, It is characterized in that The dispatch risk indicators include the daily operating power index, load shedding index and curtailment index of the energy storage equipment.

4. The method for risk assessment of distributed photovoltaic access to distribution network operation as claimed in claim 1, It is characterized in that Establish the distribution network day-ahead optimal dispatch objective function, including: The power distribution cost of the distribution network, the operating cost of the energy storage equipment, the cost of abandoned light and the line loss cost are obtained, and the day-ahead optimization scheduling objective function of the distribution network is established based on the power distribution cost of the distribution network, the operating cost of the energy storage equipment, the cost of abandoned light and the line loss cost.

5. The method for assessing the operation risk of distributed photovoltaic access to a distribution network as claimed in claim 1, It is characterized in that The first constraint condition includes an operation index constraint condition, an active power constraint condition, a reactive power constraint condition, a distributed photovoltaic node voltage drop constraint condition and a power balance constraint condition.

6. The method for assessing the operation risk of distributed photovoltaic access to a distribution network as claimed in claim 1, It is characterized in that Establish the distribution network operation risk assessment objective function, including: The load shedding cost, the abandonment cost, and the probability of the photovoltaic uncertain output scenario of the photovoltaic uncertain output scenario are obtained, and the distribution network operation risk assessment objective function is established according to the load shedding cost, the abandonment cost, and the probability of the photovoltaic uncertain output scenario of the photovoltaic uncertain output scenario.

7. The method for assessing the operation risk of distributed photovoltaic access to a distribution network as claimed in claim 1, It is characterized in that The second constraint condition is a probability distribution constraint condition for discrete scenarios of photovoltaic uncertain output.

8. The method for assessing the operation risk of distributed photovoltaic access to a distribution network as claimed in claim 3, It is characterized in that The daily operating power index of the energy storage equipment is determined according to the day-ahead operating power of the energy storage equipment and the power adjustment amount of the energy storage equipment; the daily load shedding power is determined according to the day-ahead load shedding power and the load shedding power adjustment amount; the daily abandoned light power is determined according to the day-ahead abandoned light power and the abandoned light power adjustment amount; and the load shedding index and the abandoned light index are respectively determined according to the day-ahead load shedding power and the day-abandoned light power.

9. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, the method for assessing the operation risk of a distributed photovoltaic access distribution network as described in any one of claims 1 to 8 is implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the computer program, the method for assessing the operation risk of a distributed photovoltaic access to a distribution network as described in any one of claims 1 to 8 is implemented.

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