A two-stage dispatch control strategy for energy storage considering photovoltaic output characteristics

Abstract

In recent years, with the continuous improvement of my country's railway transportation network, the increasing traction load and the sharp increase in regenerative braking energy have brought higher requirements for the stable, safe and economical operation of the power system, and the dual-carbon policy of the new era has also brought severe challenges to the low-carbon and green operation of the power system. If the photovoltaic system is connected to the traction power supply system, and the photovoltaic consumption level is improved while the traction load is peak-cut, it can not only reduce the demand for traditional energy on electrified railways to a certain extent, achieve energy conservation and emission reduction, but also further improve the effect of traction load peak-cutting, and bring certain economic benefits. The present invention provides a two-stage energy storage scheduling control strategy considering the photovoltaic output characteristics. The method divides the traction load into two stages based on the photovoltaic output characteristics, establishes the optimal economic model for stage I to obtain the energy storage control strategy; for stage II, it is divided into 11 execution conditions according to the traction load characteristics and the energy storage Soc value, and formulates corresponding energy storage control strategies for each condition. The hybrid energy storage control strategy obtained by the present invention not only improves the peak-cutting effect of the traction load, but also promotes the photovoltaic consumption and the recovery of regenerative braking energy.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to an energy management method for a traction power supply system including photovoltaics and hybrid energy storage. Background Art

[0002] Energy shortage and environmental pollution are becoming increasingly serious, and the world's energy is accelerating its transformation to diversification, cleanliness and low carbon. In recent years, my country's railway transportation network has been continuously improved, the number of electric locomotives has been increasing, and the traction load has been rising. At present, promoting the construction of "green transportation" is the development direction of the new era. The realization of low-carbon railway transportation mainly lies in reducing the traditional energy consumption of the traction power supply system. Photovoltaic power generation, as a representative of renewable and clean energy, has entered people's field of vision and gradually replaced traditional energy with obvious advantages to become the new favorite of the times. If the photovoltaic system is connected to the traction power supply system and the photovoltaic consumption level is improved while shaving the traction load, it can not only reduce the demand for traditional energy of electrified railways to a certain extent, achieve energy conservation and emission reduction, but also further improve the effect of traction load peak shaving, bringing certain economic benefits. However, in the current energy management of traction power supply systems containing photovoltaics, photovoltaic power generation is generally only used as an energy model and put into the optimization model to obtain energy storage output. There is a lack of analysis of photovoltaic output characteristics and the impact of photovoltaic output characteristics on traction load peak shaving. Summary of the invention

[0003] The present invention provides a two-stage energy storage scheduling control strategy that takes into account the photovoltaic output characteristics. The method divides the traction load into two time periods based on the photovoltaic output characteristics, and formulates a corresponding energy storage control strategy for each time period, which not only improves the peak shaving effect of the traction load, but also promotes the consumption of photovoltaics.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions, including:

[0005] Obtain the measured load data of the traction substation and the measured output data of the photovoltaic power station during the day;

[0006] Based on the characteristics of “no-yes-no” of photovoltaic output within a day, the traction load is divided into two stages with and without photovoltaic output in terms of timing;

[0007] For phase I, the optimal economic model is established to cut the peak of traction load and obtain the energy storage output;

[0008] For Phase II, the total execution conditions are divided according to the energy storage SOC and traction load conditions, and corresponding energy storage control strategies are formulated for each condition. For some conditions, the load and photovoltaic output in the future short time scale are considered. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1Typical daily data for traction load and photovoltaic output;

[0010] Figure 2 It is the traction load after stage division;

[0011] Figure 3 It is divided into the total execution conditions;

[0012] Figure 4 This is the block diagram of the overall energy storage control strategy. DETAILED DESCRIPTION

[0013] In order to make the present invention more obvious and understandable, the present invention is further described in detail below with reference to the accompanying drawings.

[0014] Step 1: According to the timing characteristics of photovoltaic output "no-on-no", the period from the evening of the day to the early morning of the next day is regarded as stage I, photovoltaic power is not used, and only regenerative braking energy is used to cut the peak; the period from the early morning to the evening of the next day is regarded as stage II, photovoltaic power is used, and photovoltaic and regenerative braking energy are used to cut the peak, such as Figure 1 shown.

[0015] Step 2: For stage I, take the lowest operating cost in this stage as the goal and find the peak shaving line P 1 、Battery energy storage minimum discharge times N bat And the minimum initial Soc of the supercapacitor is Its objective function is as follows:

[0016]

[0017] Among them C 1 For electricity charges,

[0018]

[0019] C 2 For demand electricity charges,

[0020]

[0021] C 3 For the operation and maintenance costs of energy storage and photovoltaics,

[0022]

[0023] C 4 For peak shaving subsidies,

[0024]

[0025] where c ec ,c dem ,c es ,c pv,c cp They are the unit electricity cost, unit demand electricity cost, unit energy storage operation and maintenance cost, unit photovoltaic operation and maintenance cost and unit peak reduction subsidy income. In addition, the objective function needs to meet the following constraints:

[0026]

[0027]

[0028]

[0029]

[0030]

[0031]

[0032]

[0033] 0≤N bat,1 ≤15 (13)

[0034] Phase I mainly focuses on peak load shaving and regenerative braking energy recovery for traction loads, and improves the mobility of photovoltaic consumption in Phase II. The optimal value is the minimum starting Soc that meets the peak shaving requirement of phase I, which relaxes the Soc final value constraint of phase II to a certain extent. bat The optimal solution is to use the minimum amount of battery energy storage when assisting supercapacitors in peak shaving, so that the battery can discharge while meeting the constraints of its charge and discharge times in phase II, thereby gaining more energy storage capacity margin for photovoltaic consumption.

[0035] Step 3: Divide the total operating conditions according to the traction load and the supercapacitor Soc value, and formulate corresponding energy storage control strategies for each sub-operating condition to promote the consumption of photovoltaic power and the recovery of regenerative braking energy when the load is peaked. Step 3 can be further divided into the following sub-steps:

[0036] Step 301: The total execution working condition is divided according to the three working conditions of traction load, no-load and braking and the three working conditions of high, medium and low supercapacitor Soc values. Figure 1 As shown, the operating conditions are divided into: traction conditions A, B, C, braking condition D, no-load condition E, among which the traction condition can be further divided into A1 (high load and high SOC condition), A2, A3, B1 (medium load and medium SOC condition), B2, B3, C1 (low load and high SOC condition), C2, C3, a total of 11 conditions.

[0037] in is the high load marker line, and the peak shaving line P obtained by optimization in stage I 1 Generally speaking, the load peak of phase I is lower than that of phase II. That is, the peak-cutting line in phase II will not be lower than the peak-cutting line in phase I. 1 As the peak shaving mark line, the peak shaving can be performed to the maximum extent according to the specific conditions of each working condition to meet the peak shaving needs. It is the low load marking line, with the highest power output from photovoltaic power That is, after the load below the low load mark line directly absorbs photovoltaic power, there is a surplus of photovoltaic power output. However, after the load between the high and low load mark lines directly absorbs photovoltaic power, there is no surplus photovoltaic power output. is the high SOC marker line, which is determined by the maximum tolerance for continuous regenerative braking energy recovery. is the low SOC marker line, which is determined by the maximum tolerance to meet the continuous load peak shaving requirement.

[0038]

[0039]

[0040] Where N peak ·Δt is the duration of the continuous peak load, N valley Δt is the total time interval between adjacent or consecutive braking conditions.

[0041] Step 302: Preliminarily formulate corresponding control strategies according to various working conditions.

[0042] Under A1 (high load, high SOC) conditions, photovoltaic power is directly absorbed by the load and the UC is fully discharged.

[0043]

[0044] Under A2 (high load, medium SOC) conditions, photovoltaic power is directly absorbed by the load, and UC discharges more

[0045]

[0046]

[0047] Under A3 (high load, low SOC) conditions, photovoltaics are directly consumed by loads, and Bat assists UC discharge

[0048]

[0049]

[0050] Under B3 (medium load, low SOC) conditions, all photovoltaic power is absorbed by supercapacitors.

[0051]

[0052] Under C1 (low load, high SOC) conditions, photovoltaic power is directly consumed first, and supercapacitors are discharged to the maximum extent.

[0053]

[0054] Under C2 (low load, medium SOC) conditions, photovoltaic power is directly consumed first, and supercapacitors and battery energy storage are not used.

[0055]

[0056] Under C3 (low load, low SOC) conditions, all photovoltaic power is absorbed by supercapacitors

[0057]

[0058] Under D (braking) conditions, the supercapacitor absorbs photovoltaic energy and regenerative braking energy first, and the remaining energy is absorbed by the battery energy storage

[0059]

[0060]

[0061] Under E (no-load) conditions, the supercapacitor absorbs photovoltaic energy first, and the remaining energy is absorbed by the battery energy storage

[0062]

[0063]

[0064] in They represent the direct photovoltaic power consumption, supercapacitor output and battery energy storage output respectively. Represent the Soc values ​​of supercapacitor and battery energy storage respectively. Represent the upper and lower limits of Soc for supercapacitor and battery energy storage respectively. Represent the rated power and rated capacity of supercapacitor and battery energy storage respectively.

[0065] Step 303: Formulate control strategies for some operating conditions taking into account the load conditions in the short term in the future

[0066] Under B1 (medium load, high SOC) condition, the current time is t 0 , considering the future N s Load in the time interval Δt P pro express That is its mean.

[0067] like Photovoltaic is directly absorbed by traction load to avoid energy storage Soc exceeding the limit

[0068]

[0069] like Photovoltaic directly absorbs the load, and supercapacitors discharge to the maximum extent

[0070]

[0071]

[0072] like Photovoltaic directly absorbs the load, supercapacitor discharges, and energy storage batteries can be discharged under certain constraints to prepare for subsequent photovoltaic or regenerative braking energy recovery. The corresponding control strategy is

[0073]

[0074]

[0075] Under the B2 (medium load, medium SOC) condition, the current time is t 0 , considering the future N s Load in the time interval Δt P pro express That is its mean.

[0076] like Photovoltaic energy is directly absorbed through energy storage, not directly consumed by load, to prepare for subsequent continuous peak shaving. The corresponding control strategy is:

[0077]

[0078]

[0079] like Photovoltaic is directly consumed by load, and energy storage does not work

[0080]

[0081] like Photovoltaic is directly absorbed by the load, UC is discharged, and Bat can be discharged under certain constraints to prepare for subsequent photovoltaic or regenerative braking energy recovery. The corresponding control strategy is

[0082]

[0083]

[0084] In addition, the output of the energy storage in step 302 and step 303 must meet the following constraints:

[0085]

[0086] Where N bat,2 is the number of discharges of the battery energy storage in Phase II, is the starting Soc of the supercapacitor in stage II.

Claims

1. A two-stage energy storage dispatch control strategy considering photovoltaic output characteristics, comprising the following steps: Obtain the measured load data of the traction substation and the measured output data of the photovoltaic power station during the day; Based on the characteristics of "no-yes-no" of photovoltaic output within a day, the traction load is divided into two stages with and without photovoltaic output in terms of time sequence; For stage I, the optimal economic model is established to cut the peak of the traction load to obtain the energy storage output. Taking the lowest operating cost in this stage as the goal, the peak cutting line P1 and the minimum discharge times N of the battery energy storage are obtained. bat And the minimum initial Soc of the supercapacitor is Its objective function is as follows: Among them, C1 is the electricity fee, C2 is the demand electricity fee, C3 is the operation and maintenance cost of energy storage and photovoltaics. C4 is the peak shaving subsidy. where c ec , c dem , c es , c pv and c cp They are the unit electricity cost, unit demand electricity cost, unit energy storage operation and maintenance cost, unit photovoltaic operation and maintenance cost and unit peak reduction subsidy income; in addition, the objective function needs to meet the following constraints: 0≤N bat,1 ≤15(13) For Phase II, the total execution conditions are divided according to the energy storage SOC and traction load conditions, and corresponding energy storage control strategies are formulated for each condition. For some conditions, the load and photovoltaic output in the future short time scale are considered.

2. The energy storage two-stage dispatching control strategy as described in claim 1, wherein the two-stage division method of the traction load is characterized in that, according to the timing characteristics of photovoltaic output "no-yes-no", the period from the evening of the same day to the early morning of the next day is regarded as stage I, photovoltaic output is not performed, and only regenerative braking energy is used to cut the peak; the period between the early morning and the evening of the second day is regarded as stage II, photovoltaic output, and photovoltaic and regenerative braking energy are used to cut the peak.

3. The energy storage two-stage dispatching control strategy as claimed in claim 1, which divides the total execution working condition according to the energy storage SOC and traction load working condition in stage II, is characterized in that based on the three working conditions of traction load traction, no-load and braking and the three working conditions of high, medium and low supercapacitor SOC values, the working conditions are divided into: traction working conditions A, B, C, braking working condition D and no-load working condition E, wherein the traction working condition can be subdivided into high load high SOC working condition A1, high load medium SOC working condition A2, high load low SOC working condition A3, medium load high SOC working condition B1, medium load medium SOC working condition B2, medium load low SOC working condition B3, low load high SOC working condition C1, low load medium SOC working condition C2, and low load low SOC working condition C3, a total of 11 working conditions; in is the high load marking line, which is determined by the peak shaving line P1 obtained by optimizing the stage I. Generally speaking, the load peak of stage I is lower than that of stage II. If the same optimization standard is used, That is, the peak shaving line in stage II will not be lower than the peak shaving line in stage I. Taking P1 as the peak shaving mark line, the peak shaving can be performed to the maximum extent according to the specific conditions of each working condition to meet the peak shaving demand. It is the low load marking line, with the highest power output from photovoltaic power It is determined that after the load below the low load mark line directly absorbs photovoltaic power, there is a surplus of photovoltaic power output, while after the load between the high and low load mark lines directly absorbs photovoltaic power, there is no surplus photovoltaic power output. is the high SOC marker line, which is determined by the maximum tolerance for continuous regenerative braking energy recovery, where is the low SOC marker line, which is determined by the maximum tolerance to meet the continuous load peak shaving requirement. Where N peak ·Δt is the duration of the continuous peak load, N valley Δt is the total time interval between adjacent or consecutive braking conditions.

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