Electrochemical energy storage low-voltage distribution network voltage treatment method based on heuristic algorithm

Abstract

The invention provides an electrochemical energy storage low-voltage distribution network voltage treatment method based on a heuristic algorithm, and relates to the technical field of power grid dispatching, and the method comprises the steps: 1, carrying out the prediction of a transformer area load; 2, making a first time scale scheduling plan of energy storage equipment, and planning energy storage active power; 3, high-frequency power flow checking is carried out, and a checking result is obtained; step 4, checking whether the node voltage has a voltage out-of-limit risk or not; if the out-of-limit risk exists, executing the step 5; if the out-of-limit risk does not exist, executing the step 6; 5, starting a high-frequency energy storage scheduling plan correction algorithm to obtain a second time scale scheduling plan; step 6, generating a scheduling instruction of this time, and executing an energy storage operation; 7, judging whether the current scheduling period is still in the current scheduling period or not; if the current scheduling period is in the current scheduling period, executing the step 3; if the current scheduling period is not in the current scheduling period, executing the step 1; the problem of out-of-limit of a low-voltage power grid is solved by using electrochemical energy storage equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid dispatching, and in particular to a voltage management method for an electrochemical energy storage low-voltage distribution network based on a heuristic algorithm. Background Art

[0002] With the development of new rural areas and rural urbanization, the development of power grids is gradually extending from main grid management to user management. However, the development of rural distribution networks is affected by multiple factors such as geographical environment, economic conditions, and load distribution, and has certain difficulties and complexities. Compared with urban areas, rural distribution networks are relatively weak, with longer power supply radius, insufficient voltage control means and measures, and the problem of low voltage is particularly prominent, which seriously affects the safety and economic benefits of distribution networks. The key technologies for rural power grid voltage management include reactive power compensation, voltage regulator use, distributed generation, smart distribution network application, line transformation, energy storage system deployment, and advanced control strategies. These technologies work together to stabilize voltage and improve the operating efficiency and power supply quality of rural power grids by improving power factor, reducing line losses, optimizing supply and demand balance, and achieving rapid response.

[0003] However, due to the imperfection of rural power grids, voltage over-limit problems often occur. Voltage over-limit problems refer to the voltage fluctuation of the power grid exceeding the prescribed range, causing damage to household appliances and unstable electricity use in agricultural production. Especially in the vast rural areas, the stability and quality of electricity used for production and life are directly related to the efficiency of agricultural production and the quality of farmers' lives. With the development of my country's rural economy and the advancement of agricultural modernization, the demand for rural electricity is growing, and the problem of power supply is becoming increasingly prominent. Especially during the peak period of agricultural production and the peak period of rural residents' lives, the insufficient power supply capacity and large voltage fluctuations of rural low-voltage power grids have had a serious impact on rural production and life. The existing voltage management methods mainly optimize the line power supply radius, reduce line losses, reasonably set reactive power compensation devices, improve the regulation and control capabilities of distribution networks, reasonably set transformer taps, and flexibly adjust the output voltage according to load changes. The shortcomings of voltage management in rural low-voltage distribution networks mainly include: the management effect of adjusting transformer taps is limited and cannot fully meet the voltage demand; the cost of reactive power compensation devices and intelligent control systems is high and requires regular maintenance; optimizing line layout may require a large initial investment; distributed power generation requires corresponding technical and economic support; load management may affect users' electricity usage habits. In general, these methods, while improving voltage quality, also bring additional economic and technical challenges. Although measures such as optimizing the line power supply radius and setting reactive power compensation devices can improve the regulation capability of the distribution network, the effect of reactive power compensation to improve the voltage at the end of the distribution network line is very limited, and requires a lot of manpower and financial investment, and is difficult to implement. Although the reasonable setting of transformer taps can flexibly adjust the output voltage according to load changes, it is necessary to establish a sound distribution network operation and maintenance mechanism, and professional personnel are required to regularly inspect and adjust, which is complicated to operate. The existing technology also only uses voltage regulating devices to adjust voltage deviations.

[0004] To this end, the present invention provides an electrochemical energy storage low-voltage distribution network voltage management method based on a heuristic algorithm, which aims to utilize the characteristics of energy storage devices that can be dynamically adjusted according to load demand, quickly respond to voltage fluctuations, alleviate the pressure on existing power grid facilities, and reduce the demand for capacity expansion of transformers and lines to solve the problem of over-limit of rural low-voltage power grids controlled by electrochemical energy storage, so as to promote the sustainable and healthy development of the rural economy. Summary of the invention

[0005] The purpose of the present invention is to provide a voltage management method for an electrochemical energy storage low-voltage distribution network based on a heuristic algorithm to solve the voltage over-limit problem of a rural low-voltage power grid, comprising: step 1, predicting the load of the substation to obtain a prediction result; step 2, formulating a first time scale scheduling plan for the energy storage device according to the prediction result, and planning the energy storage active power at each time point within the first time scale; step 3, performing a high-frequency flow verification according to the energy storage active power to obtain a verification result; step 4, based on the verification result, checking whether the node voltage has a risk of voltage over-limit; if there is a risk of voltage over-limit If there is no risk of exceeding the limit, execute step 5; if there is no risk of exceeding the limit, execute step 6; in step 5, start the high-frequency energy storage scheduling plan correction algorithm to obtain the second time scale scheduling plan; in step 6, generate the current scheduling instruction according to the first time scale scheduling plan or the second time scale scheduling plan, and send it to each energy storage device to perform energy storage operation; in step 7, determine whether it is still in the current scheduling cycle; if it is in the current scheduling cycle, execute step 3; check the next time point; if it is not in the current scheduling cycle, execute step 1 to perform energy storage scheduling for the next scheduling cycle.

[0006] Furthermore, the objective function of the first time scale scheduling plan is:

[0007] f peakshaving =F p1 +F p2 +F p3 +F p4 ;

[0008]

[0009] F p3 =ρ3SoC DV ;

[0010]

[0011] Where: F peakshaving is the objective function of the first time scale scheduling plan; min is minimization; F p1 is the first scheduling objective function; F p2 is the second scheduling objective function; F p3 is the third scheduling objective function; F p4 is the fourth scheduling objective function; ρ1 is the weight coefficient of the first scheduling objective function; and They are the maximum power and minimum power of the grid connection point during the dispatch period respectively; is the capacity of the transformer in the substation; ρ2 is the weight coefficient of the second dispatch objective function; ρ3 is the weight coefficient of the third dispatch objective function; SoC DVis the absolute value of the difference between the actual state of charge at the end of the scheduling period and the preset target state of charge; ρ4 is the weight coefficient of the fourth scheduling objective function; is the absolute value of the active power difference between adjacent time periods within the scheduling cycle; t represents the time variable;

[0012] The constraints of the first time scale scheduling plan are:

[0013]

[0014] SoC min ≤SoC t ≤SoC max ;

[0015]

[0016] Where: is the active power of the low voltage grid connection point at time t; SoC t Real-time state of charge for electrochemical energy storage; SoC min SoC is the preset minimum state of charge. max The preset maximum state of charge; Real-time charging of active power for electrochemical energy storage; It is an indicator of the charging status of the energy storage system; The minimum charging power allowed by the hardware device; The maximum charging power allowed by the hardware device; Real-time discharge of active power for electrochemical energy storage; It is an indicator of the discharge status of the energy storage system.

[0017] Furthermore, the maximum and minimum power of the grid-connected point during the dispatch period and The calculation formula is:

[0018]

[0019] The absolute value of the difference between the actual state of charge and the preset target state of charge at the end of the scheduling period SoC DV The calculation formula is:

[0020] SoC DV =|SoC tend -SoC target |;

[0021] The absolute value of the active power difference between adjacent time periods within the dispatch cycle The calculation formula is:

[0022]

[0023] Electrochemical energy storage real-time state of charge SoC t The calculation formula is:

[0024]

[0025] In the formula: max means taking the maximum value; min means taking the minimum value; is the grid connection point power at time point t, t represents the time variable, and its value is 1-T, T is the total number of time points in the scheduling cycle; SoC tend The actual state of charge at the end of the scheduling cycle; SoC target is a preset target state of charge; is the active power of the low voltage grid connection point at time t-1; SoC t-1 The real-time charge state of the electrochemical energy storage at time t-1; and are the charging efficiency and discharging efficiency of energy storage respectively; is the rated battery capacity of energy storage; Δt is the scheduling time step of real-time correction.

[0026] Furthermore, the calculation formula of the energy storage active power is:

[0027]

[0028] Where: is the active power of the low voltage grid connection point at time t; It is the real-time active power of the energy storage system; Provide real-time power output for distributed power sources in the area; It is the real-time power demand of the load in the substation.

[0029] Furthermore, the real-time active power of the energy storage system The calculation formula is:

[0030]

[0031] Where: Real-time charging of active power for electrochemical energy storage; Real-time discharge of active power for electrochemical energy storage.

[0032] Furthermore, the objective function of the high-frequency energy storage scheduling plan correction algorithm is:

[0033] MinF voltage =F v1，1 +F v1，2 +F v2 +F v3 +F v4 ;

[0034]

[0035] Where: Min is minimization; F voltage is the objective function of the high-frequency energy storage scheduling correction algorithm; F v1，1 is the first correction function; F v1，2 is the first and second correction function; F v2 is the second correction function; F v3 is the third correction function; F v4 is the fourth correction function; M is a very large number; The apparent power of electrochemical energy storage operation; Power installation for PCS; It is the reference coefficient for dimensionless processing of the over-limit level; Power factor for electrochemical energy storage operation; is the lower limit of energy storage power factor; The reference coefficient for de-dimensionalizing the power factor over-limit level; SoC D SoC is the charge state of energy storage after scheduling; min SoC is the preset minimum state of charge. max The preset maximum state of charge; The reference coefficient for de-dimensionalizing the energy storage state of charge over-limit level; That is, the voltage over-limit cost of node phase n under this power flow distribution; n represents the node variable; N bus Indicates the total number of nodes in the entire area; phase indicates the phase; The penalty cost for the deviation between energy storage dispatch and target power; is the regulated energy storage active power; is the target power of energy storage; Reference coefficient for de-dimensionalization of active deviation; is the regulated energy storage reactive power; is the target reactive power of energy storage; It is the reference coefficient for dimensionless processing of reactive power deviation.

[0036] Furthermore, the apparent power of electrochemical energy storage operation The calculation formula is:

[0037]

[0038] Power Factor of Electrochemical Energy Storage Operation The calculation formula is:

[0039]

[0040] State of charge SoC of energy storage after dispatch D The calculation formula is:

[0041]

[0042] Under this power flow distribution, the voltage over-limit cost of node n phase is The calculation formula is:

[0043]

[0044] Where: SoC R The real-time charge state of the energy storage; and They are respectively the charging active power of the energy storage and the discharging active power of the energy storage; and are the charging efficiency and discharging efficiency of energy storage respectively; is the rated battery capacity of the energy storage; Δt is the scheduling time step of real-time correction; The voltage rise exceeds the limit level; Unit cost of voltage rise exceeding the limit; The voltage drop exceeds the limit level; Unit cost of voltage drop exceeding limit; V n，phase Under this power flow distribution, the phase voltage of node n is V upd and V lowb are the upper and lower voltage thresholds respectively; It is the reference coefficient for de-dimensionalizing the voltage over-limit level.

[0045] Furthermore, before scheduling, it also includes:

[0046] Collect and analyze data from the station area;

[0047] Model the substation and perform power flow calculations.

[0048] Furthermore, the first time scale is minute level; the second time scale is real time.

[0049] Furthermore, a heuristic algorithm is used to solve the scheduling plan.

[0050] The technical solution of the embodiment of the present invention has at least the following advantages and beneficial effects:

[0051] The voltage management method of the electrochemical energy storage low-voltage distribution network based on the heuristic algorithm provided by the present invention can quickly respond to load changes, effectively alleviate the voltage over-limit phenomenon by dynamically adjusting the output of the energy storage device, and reduce the impact of voltage fluctuations on users. In addition, the application of energy storage equipment can also smooth the power fluctuations of the power grid, thereby reducing the pressure on the power grid facilities and improving the stability and reliability of the overall power grid.

[0052] The present invention comprehensively considers multiple factors such as load distribution, geographical location and power demand in the rural power grid area. The energy storage equipment with appropriate capacity is installed at the best location in the area to ensure its maximum operating efficiency and benefits. This targeted layout not only improves the responsiveness of the energy storage system, but also optimizes the power quality and utilization efficiency of power grid resources.

[0053] This invention will provide technical support for the transformation and upgrading of rural low-voltage power grids, help improve the quality of rural power supply, and lay the foundation for achieving the goal of building a new power system. At the same time, the project results are of great significance for promoting rural energy development. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 An exemplary flow chart of the method for voltage management of low-voltage distribution network using electrochemical energy storage based on a heuristic algorithm provided by the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0056] The voltage management method of the electrochemical energy storage low-voltage distribution network based on the heuristic algorithm provided by the present invention includes the following contents:

[0057] Collect and analyze regional data.

[0058] For the line analysis of the low-voltage distribution network area (transformer and its connected downstream power users), there are N nodes in total, and the voltage value of each node and the active power and reactive power of the line are collected respectively. N represents the total number of collection nodes in the area.

[0059] Model the substation and perform power flow calculations.

[0060] The power flow calculation is mainly carried out using open source software, and the specific means of implementing the power flow calculation are not specified. When calculating the power flow in this patent, it is assumed that all nodes in the low-voltage substation have the conditions for electrical data collection and the electrical topology parameter data of the substation is complete, and the power flow calculation is realized through full topology modeling.

[0061] During voltage dispatch, the energy storage plan is processed into the power flow distribution data according to the grid-connected phase and grid-connected nodes of the actual energy storage in the scenario, and then the voltage value of each node is obtained as the output through the power flow distribution calculation.

[0062] The input equipment configuration parameters, operating parameters and target power are used as boundaries. A dispatching point is set every 15 minutes for the collected 24-hour data. For each energy storage dispatching moment, the active power of the original feeder in the remaining time of the next day is processed by the smoothed power consumption curve function to obtain the energy storage dispatching plan for the next moment (first time scale dispatching plan), and the energy storage dispatching power at the current moment is taken to enter the voltage dispatching entry function, thereby determining the final energy storage dispatching power at that moment (second time scale dispatching plan) to meet the voltage within a reasonable range.

[0063] Through the following algorithm modules, it is possible to form the following algorithm based on the given energy storage capacity, grid-connected nodes, substation topology and necessary flow information: Figure 1 The standard process of the voltage management method for low-voltage distribution network with electrochemical energy storage based on heuristic algorithm is shown.

[0064] After the algorithm starts executing, it will call the algorithm module cyclically with the preset minute-level energy storage plan generation step size and high-frequency energy storage scheduling correction step size, such as Figure 1 As shown, the process is described as follows:

[0065] Step 1: Predict the load of the substation and obtain the prediction result. For example, the load of the substation can be predicted based on various artificial intelligence load prediction algorithms to obtain the power load prediction value of each node.

[0066] Step 2: formulate a first time scale scheduling plan for the energy storage device according to the prediction results, and plan the energy storage active power at each time point within the first time scale to achieve energy storage scheduling with the goal of peak shaving and valley filling. The first time scale is minute level, and the first time scale scheduling plan may refer to a minute level energy storage active power plan.

[0067] By using energy storage to smooth out the peak and valley of power supply in the substation, the peak load level of power consumption can be reduced, thereby reducing the network loss and voltage drop in the corresponding period. Therefore, the present invention designs a substation-level peak-shaving and valley-shaving energy storage scheduling algorithm based on substation load prediction and mixed integer programming algorithm, and plans the energy storage active power output with a time step of minutes, wherein the objective function of the first time scale scheduling plan (substation-level peak-shaving and valley-shaving energy storage scheduling algorithm) is:

[0068] min F peakshaving =F p1 +F p2 +F p3 +F p4 ;

[0069]

[0070] F p3 =ρ3SoCDV ;

[0071]

[0072] Where: F peakshaving is the objective function of the first time scale scheduling plan; min is minimization; F p1 is the first dispatch objective function, which aims to minimize the difference between the maximum power and the minimum power of the grid connection point in the dispatch period; F p2 is the second dispatch objective function, which aims to minimize the peak load of the grid connection point in the dispatch period; F p3 is the third dispatch objective function, which is used to set the target requirement for the state of charge at the end of the dispatch period in energy storage dispatch; F p4 is the fourth scheduling objective function, which aims to further smooth the power curve based on the above objectives; ρ1 is the weight coefficient of the first scheduling objective function; and They are the maximum power and minimum power of the grid connection point during the dispatch period respectively; is the capacity of the transformer in the substation; ρ2 is the weight coefficient of the second dispatch objective function; ρ3 is the weight coefficient of the third dispatch objective function; SoC DV is the absolute value of the difference between the actual state of charge at the end of the scheduling period and the preset target state of charge; ρ4 is the weight coefficient of the fourth scheduling objective function; is the absolute value of the active power difference between adjacent time periods within the dispatching cycle; t represents the time variable;

[0073] During the dispatching process, the power of the low-voltage grid connection point should be limited by considering the capacity of the transformer in the grid to avoid over-limit operation of the transformer. Therefore, the restriction conditions of the first time scale dispatching plan are:

[0074]

[0075] SoC min ≤SoC t ≤SoC max ;

[0076]

[0077] Where: is the active power of the low voltage grid connection point at time t; SoC t Real-time state of charge for electrochemical energy storage; SoC min SoC is the preset minimum state of charge. max The preset maximum state of charge; Real-time charging of active power for electrochemical energy storage; It is the charging status indicator of the energy storage system (1 is charging status, 0 is non-charging status). Should not be lower than the minimum charging power allowed by the hardware device It should also not be higher than the maximum charging power allowed by the hardware device. The minimum charging power allowed by the hardware device; The maximum charging power allowed by the hardware device; Real-time discharge of active power for electrochemical energy storage; It is the discharge state indicator of the energy storage system (1 is the discharge state, 0 is the non-discharge state). For the discharge power of electrochemical energy storage, during the dispatch process, Should not be lower than the minimum discharge power allowed by the hardware device It should also not be higher than the maximum discharge power allowed by the hardware device. The above formula can accurately evaluate the regulation ability of electrochemical energy storage by requiring the real-time state of charge of electrochemical energy storage at time t, ensuring that the real-time state of charge SoC of electrochemical energy storage is t Will not fall below the preset minimum state of charge SoC min , and will not exceed the preset maximum state of charge standard SoC max The above formula limits the energy storage system charging state indication And energy storage system discharge status indicator The sum of is less than or equal to 1, so that during the operation of electrochemical energy storage, the energy storage device is ensured not to be in the charging state and the discharging state at the same time.

[0078] The calculation formula of the energy storage active power is:

[0079]

[0080] Where: is the active power of the low voltage grid connection point at time t; is the real-time active power of the energy storage system, using the load type sign specification (i.e., positive for charging and negative for discharging); Provide real-time power output for distributed power sources in the area; It is the real-time power demand of the load in the substation.

[0081] Among them, the maximum power and minimum power of the grid connection point during the dispatch period and The calculation formula is:

[0082]

[0083]

[0084] The absolute value of the difference between the actual state of charge and the preset target state of charge at the end of the scheduling period SoC DV The calculation formula is:

[0085] SoC DV =|SoC teng -SoC target |;

[0086] The absolute value of the active power difference between adjacent time periods within the dispatch cycle The calculation formula is:

[0087]

[0088] Electrochemical energy storage real-time state of charge SoC t The calculation formula is:

[0089]

[0090] In the formula: max means taking the maximum value; min means taking the minimum value; is the grid connection point power at time point t, t represents the time variable, and its value is 1-T, T is the total number of time points in the scheduling cycle; SoC tend The actual state of charge at the end of the scheduling cycle; SoC target is a preset target state of charge; is the active power of the low voltage grid connection point at time t-1; SoC t-1 The real-time charge state of the electrochemical energy storage at time t-1; and are the charging efficiency and discharging efficiency of energy storage respectively; is the rated battery capacity of energy storage; Δt is the scheduling time step of real-time correction.

[0091] Real-time active power of energy storage system The calculation formula is:

[0092]

[0093] Where: Real-time charging of active power for electrochemical energy storage; Real-time discharge of active power for electrochemical energy storage.

[0094] Step 3: Perform high-frequency power flow verification according to the energy storage active power to obtain verification results to ensure the feasibility and accuracy of the first time scale scheduling plan. The verification result may refer to the result of whether the scheduling plan can be successfully executed. The verification result at least includes whether there is a short-term voltage limit violation or line overload problem.

[0095] Step 4: based on the verification result, check whether the node voltage has a risk of voltage over-limit; if there is a risk of over-limit, execute step 5; if there is no risk of over-limit, execute step 6. The node voltage may refer to the voltage at a node in the substation, for example, the voltage of an electricity user.

[0096] Step 5: Start the high-frequency energy storage scheduling plan correction algorithm to obtain a second time scale scheduling plan. The second time scale refers to a time scale shorter than the first time scale. For example, the first time scale is at the minute level and the second time scale is at the second level. In the present application, the second time scale may be real time.

[0097] In the energy storage power output of the smooth power consumption curve, although the energy storage active power dispatch plan can play the role of peak shaving and valley filling and alleviate the voltage deviation problem in the substation to a certain extent, the corresponding plan preparation does not combine the actual power flow distribution in the substation to analyze the voltage level. At the same time, the load fluctuates frequently and the power flow distribution changes rapidly in the operation of the power system. The risk of voltage exceeding the limit in the low-voltage substation cannot be completely eliminated by relying solely on minute-level energy storage active power dispatch. In addition, affected by the characteristics of rural power equipment and the current status of rural low-voltage power grid construction, there is often an unreasonable configuration of reactive compensation. The impact of reactive power output on the substation voltage cannot be ignored in energy storage dispatch.

[0098] Based on the active power target of the pre-station-level peak-shaving and valley-smoothing energy storage scheduling algorithm, the active and reactive outputs of energy storage are coordinated to further optimize the efficiency of energy storage in regulating the voltage of low-voltage stations. Taking the active power and reactive power output of energy storage as decision variables, a high-frequency energy storage scheduling plan correction algorithm is constructed. The objective function of the high-frequency energy storage scheduling plan correction algorithm is:

[0099] MinF voltage =F v1，1 +F v1，2 +F v2 +F v3 +F v4 ;

[0100] Where: Min is minimization; F voltage is the objective function of the high-frequency energy storage scheduling correction algorithm; F v1，1 is the first correction function; F v1，2 is the first and second correction function; F v2 is the second correction function; F v3 is the third correction function; F v4 is the fourth correction function.

[0101] The first correction function F v1，1The purpose is to include the rated capacity of the electrochemical energy storage PCS into the optimization constraints. When the feasible solution leads to the risk of over-limit of the electrochemical energy storage PCS capacity, the objective function will reflect the extremely high cost, thereby excluding the solution from the optimal solution range. The calculation formula of the first correction function is:

[0102]

[0103] Where: M is a very large number, and a very large penalty is imposed on capacity exceeding the limit; The apparent power of electrochemical energy storage operation; Power installation for PCS; The reference coefficient for de-dimensionalizing the over-limit level; It is the real-time active power of the energy storage system; is the regulated energy storage reactive power.

[0104] Limited by the power electronic characteristics of the electrochemical energy storage inverter, its output power factor has a range constraint. Therefore, the first and second correction functions F v1，2 The purpose is to include the power factor of electrochemical energy storage PCS in the optimization. When the feasible solution leads to the risk of over-limit of electrochemical energy storage power factor, the objective function will reflect the extremely high cost, thus excluding the solution from the optimal solution range. The first and second correction functions F v1，2 The expression is:

[0105]

[0106] Where: M is a very large number, and a maximum over-limit cost is assigned to the power factor over-limit; That is, the power factor of electrochemical energy storage operation; is the lower limit of energy storage power factor; It is the reference coefficient for dimensionless processing of the power factor over-limit level.

[0107] Since the energy storage dispatch correction considering the flow will affect the output active power of the electrochemical energy storage, the upper and lower limit constraints of the state of charge of the electrochemical energy storage need to be included in the algorithm optimization in the objective function. Among them, the second correction function F v2 The calculation formula is:

[0108]

[0109] In the formula, are the charging active power of energy storage and the discharging active power of energy storage, are the charging efficiency and discharging efficiency of energy storage, is the rated battery capacity of the energy storage, and Δt is the real-time corrected scheduling time step. RAfter scheduling SoC D The estimated state of charge SoC of the energy storage after dispatching D The calculation formula is:

[0110]

[0111] Where, SoC R The real-time charge state of the energy storage; and They are respectively the charging active power of the energy storage and the discharging active power of the energy storage; and are the charging efficiency and discharging efficiency of energy storage respectively; is the rated battery capacity of energy storage; Δt is the scheduling time step of real-time correction.

[0112] The third correction function F v3 The purpose is to quantitatively evaluate the voltage over-limit level of each node and each phase under the feasible solution power flow distribution, and take it into account in the objective function, so as to achieve the purpose of minimizing the over-limit level. The calculation formula of the third correction function is:

[0113]

[0114] In the formula, That is, the voltage over-limit cost of the phase of node n under this power flow distribution, which includes the voltage rise over-limit cost and the voltage drop over-limit cost. The voltage rise over-limit cost is the voltage rise over-limit level. Multiply by the unit cost of voltage rise exceeding the limit The voltage drop over-limit cost is the voltage drop over-limit level Multiply by the unit cost of voltage drop exceeding the limit V n，phase That is, the phase voltage of node n under this power flow distribution; V upb 、V lowb are the upper and lower voltage thresholds respectively; It is the reference coefficient for dimensionless voltage over-limit level processing. By calculating the cost of voltage over-limit by phase and node, it can ensure that the three-phase voltage of all visible nodes in the entire substation system is included in the management scope during energy storage operation optimization.

[0115] In order to ensure that the deviation between the active power instruction of the energy storage dispatch after verification and the original active power dispatch plan of the energy storage is minimized and the reactive power of the energy storage dispatch after verification is minimized during the verification of the energy storage dispatch instruction considering the voltage deviation, a fourth correction function F is added to the objective function. v4 , where the calculation formula of the fourth correction function is:

[0116]

[0117] In the formula, The penalty cost for the deviation between energy storage dispatch and target power; is the regulated energy storage active power; is the target power of energy storage; It is the reference coefficient for de-dimensioning the active power deviation. The deviation management of reactive power is similar to that of active power deviation. is the penalty cost for the deviation between the target reactive power and the energy storage dispatch; is the regulated energy storage reactive power; is the target reactive power of energy storage (usually 0); It is the reference coefficient for dimensionless processing of reactive power deviation.

[0118] Step 6: Generate the current scheduling instruction according to the first time scale scheduling plan or the second time scale scheduling plan, and send it to each energy storage device to perform energy storage operation. The current scheduling instruction may refer to the instruction currently related to scheduling energy storage operation. Energy storage operation may refer to the operation of adjusting energy storage, for example, energy storage operation may include controlling the charging and discharging of energy storage equipment and the power of charging and discharging.

[0119] Step 7, determine whether it is still in the current scheduling cycle; if it is in the current scheduling cycle, execute step 3; check the next time point; if it is not in the current scheduling cycle, execute step 1 and perform energy storage scheduling for the next scheduling cycle.

[0120] A heuristic algorithm is used to solve the above scheduling plan (including the first time scale scheduling plan and the second time scale scheduling plan), and the heuristic algorithm includes but is not limited to a particle swarm algorithm, a simulated degradation algorithm, and a genetic algorithm.

[0121] Through a reasonable energy storage dispatching strategy, the energy storage system can smooth out the load fluctuations of the power grid by reducing the peak load, thereby effectively improving the voltage quality. The voltage over-limit situation is effectively solved, and the dispatching algorithm can dynamically respond to load changes to ensure that the voltage remains within the qualified range, and the voltage qualification rate has been significantly improved from the original low level.

[0122] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A voltage management method for low-voltage distribution network with electrochemical energy storage based on heuristic algorithm, characterized in that: include: Step 1, predicting the load of the substation area and obtaining the prediction result; Step 2, formulating a first time scale scheduling plan for the energy storage device according to the prediction results, and planning the energy storage active power at each time point within the first time scale; Step 3, performing high-frequency power flow verification according to the energy storage active power to obtain a verification result; Step 4: based on the verification result, check whether the node voltage has a risk of exceeding the voltage limit; If there is a risk of exceeding the limit, go to step 5; If there is no risk of exceeding the limit, proceed to step 6; Step 5, starting the high-frequency energy storage scheduling plan correction algorithm to obtain a second time scale scheduling plan; Step 6: Generate a current scheduling instruction according to the first time scale scheduling plan or the second time scale scheduling plan, and send it to each energy storage device to perform energy storage operation; Step 7, determine whether it is still in the current scheduling cycle; If it is within the current scheduling cycle, execute step 3; Check the next time point; if it is not in the current scheduling cycle, execute step 1 to perform energy storage scheduling for the next scheduling cycle.

2. The method for voltage management of low-voltage distribution network of electrochemical energy storage based on heuristic algorithm according to claim 1 is characterized in that: The objective function of the first time scale scheduling plan is: min F peakshaving =F p1 +F p2 +F p3 +F p4 ; F p3 =ρ3SoC DV ; Where: F peakshaving is the objective function of the first time scale scheduling plan; min is minimization; F p1 is the first scheduling objective function; F p2 is the second scheduling objective function; F p3 is the third scheduling objective function; F p4 is the fourth scheduling objective function; ρ1 is the weight coefficient of the first scheduling objective function; and They are the maximum power and minimum power of the grid connection point during the dispatch period respectively; is the capacity of the transformer in the substation; ρ2 is the weight coefficient of the second dispatch objective function; ρ3 is the weight coefficient of the third dispatch objective function; SoC DV is the absolute value of the difference between the actual state of charge at the end of the scheduling period and the preset target state of charge; ρ4 is the weight coefficient of the fourth scheduling objective function; is the absolute value of the active power difference between adjacent time periods within the dispatching cycle; t represents the time variable; The constraints of the first time scale scheduling plan are: SoC min ≤SoC t ≤SoC max ; Where: is the active power of the low voltage grid connection point at time t; SoC t Real-time state of charge for electrochemical energy storage; SoC min SoC is the preset minimum state of charge. max The preset maximum state of charge; Real-time charging of active power for electrochemical energy storage; It is an indicator of the charging status of the energy storage system; The minimum charging power allowed by the hardware device; The maximum charging power allowed by the hardware device; Real-time discharge of active power for electrochemical energy storage; It is an indicator of the discharge status of the energy storage system.

3. The method for voltage management of low-voltage distribution network of electrochemical energy storage based on heuristic algorithm according to claim 2 is characterized in that: Maximum and minimum power of the grid connection point during the dispatching period and The calculation formula is: The absolute value of the difference between the actual state of charge and the preset target state of charge at the end of the scheduling period SoC DV The calculation formula is: SoC DV =|SoC tend -SoC target |; The absolute value of the active power difference between adjacent time periods within the dispatch cycle ΔP t tr The calculation formula is: Electrochemical energy storage real-time state of charge SoC t The calculation formula is: In the formula: max means taking the maximum value; min means taking the minimum value; is the grid connection point power at time point t, t represents the time variable, and its value is 1-T, T is the total number of time points in the scheduling cycle; SoC tend The actual state of charge at the end of the scheduling cycle; SoC target is a preset target state of charge; is the active power of the low voltage grid connection point at time t-1; SoC t-1 The real-time charge state of the electrochemical energy storage at time t-1; and are the charging efficiency and discharging efficiency of energy storage respectively; is the rated battery capacity of energy storage; Δt is the scheduling time step of real-time correction.

4. The method for voltage management of low-voltage distribution network of electrochemical energy storage based on heuristic algorithm according to claim 1 is characterized in that: The calculation formula of the energy storage active power is: Where: is the active power of the low voltage grid connection point at time t; It is the real-time active power of the energy storage system; Provide real-time power output for distributed power sources in the area; It is the real-time power demand of the load in the substation.

5. The method for voltage management of low-voltage distribution network of electrochemical energy storage based on heuristic algorithm according to claim 4 is characterized in that: Real-time active power of energy storage system The calculation formula is: Where: Real-time charging of active power for electrochemical energy storage; Real-time discharge of active power for electrochemical energy storage.

6. The method for voltage management of low-voltage distribution network of electrochemical energy storage based on heuristic algorithm according to claim 1 is characterized in that: The objective function of the high-frequency energy storage scheduling plan correction algorithm is: Min F voltage =F v1，1 +F v1，2 +F v2 +F v3 +F v4 ; Where: Min is minimization; F voltage is the objective function of the high-frequency energy storage scheduling correction algorithm; F v1，1 is the first correction function; F v1，2 is the first and second correction function; F v2 is the second correction function; F v3 is the third correction function; F v4 is the fourth correction function; M is a very large number; The apparent power of electrochemical energy storage operation; Power installation for PCS; It is the reference coefficient for dimensionless processing of the over-limit level; Power factor for electrochemical energy storage operation; is the lower limit of energy storage power factor; The reference coefficient for de-dimensionalizing the power factor over-limit level; SoC D SoC is the charge state of energy storage after scheduling; min SoC is the preset minimum state of charge. max The preset maximum state of charge; The reference coefficient for de-dimensionalizing the energy storage state of charge over-limit level; That is, the voltage over-limit cost of node phase n under this power flow distribution; n represents the node variable; N bus Indicates the total number of nodes in the entire area; phase indicates the phase; The penalty cost for the deviation between energy storage dispatch and target power; is the regulated energy storage active power; is the target power of energy storage; Reference coefficient for de-dimensionalization of active deviation; is the regulated energy storage reactive power; is the target reactive power of energy storage; It is the reference coefficient for dimensionless processing of reactive power deviation.

7. The method for voltage management of low-voltage distribution network of electrochemical energy storage based on heuristic algorithm according to claim 6 is characterized in that: Apparent power of electrochemical energy storage operation The calculation formula is: Power Factor of Electrochemical Energy Storage Operation The calculation formula is: State of charge SoC of energy storage after dispatch D The calculation formula is: Under this power flow distribution, the voltage over-limit cost of node n phase is The calculation formula is: Where: SoC R The real-time charge state of the energy storage; and They are respectively the charging active power of the energy storage and the discharging active power of the energy storage; and are the charging efficiency and discharging efficiency of energy storage respectively; is the rated battery capacity for energy storage; Δt is the scheduling time step of real-time correction; The voltage rise exceeds the limit level; Unit cost of voltage rise exceeding the limit; The voltage drop exceeds the limit level; Unit cost of voltage drop exceeding limit; V n，phase Under this power flow distribution, the phase voltage of node n is V upb and V lowb are the upper and lower voltage thresholds respectively; It is the reference coefficient for de-dimensionalizing the voltage over-limit level.

8. The method for voltage management of low-voltage distribution network of electrochemical energy storage based on heuristic algorithm according to claim 1 is characterized in that: Before scheduling, it also includes: Collect and analyze data from the station area; Model the substation and perform power flow calculations.

9. The method for voltage management of low-voltage distribution network of electrochemical energy storage based on heuristic algorithm according to claim 1 is characterized in that: The first time scale is minute level; the second time scale is real time.

10. The method for voltage management of low-voltage distribution network of electrochemical energy storage based on heuristic algorithm according to claim 1 is characterized in that: A heuristic algorithm is used to solve the scheduling plan.

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