Energy storage control and load response method for adjusting peak-valley difference rate of source network load storage system

Abstract

The invention provides an energy storage control and load response method for adjusting the peak-valley difference rate of a source network load storage system, and the method comprises the steps: considering the peak-valley difference rate, the load prediction of a power system, and the capacity of an energy storage system at the same time, determining an optimal energy storage control strategy through an optimization algorithm, making an optimal charging and discharging plan, and then carrying out the calculation of the optimal charging and discharging plan. Further adjustment of the load can be coordinated with a charging and discharging strategy of the energy storage system to further reduce the peak-valley difference rate, namely, a load management and response strategy considering the peak-valley difference rate of the system is specified based on a charging and discharging plan of energy storage, external power receiving characteristics of the system and characteristics of the load; and the final external power receiving peak-valley difference rate of the source network load storage system meets the requirement of a target value. The method has the advantages that the optimal energy storage charging and discharging plan capable of reducing the peak-valley difference rate can be solved through the optimization algorithm, the load response strategy meeting the adjustment requirement is further optimized and solved based on the optimal energy storage charging and discharging plan, and the method is suitable for energy storage and load scheduling scenes in a source network load storage system and has high adjustment efficiency.

Description

Technical Field

[0001] The present invention relates to the field of energy management and control of a source-grid-load-storage integrated system, and in particular to an energy storage control strategy optimization and load response algorithm for adjusting the peak-to-valley difference rate of a source-grid-load-storage system. Background Art

[0002] The source-grid-load-storage integrated system is a system that combines renewable energy generation, grid power supply and energy storage technology. It has the characteristics of tightly integrating distributed generation, grid and energy storage systems. In such a system, the peak-to-valley difference rate refers to the degree of difference between the peak load and valley load of the power system. The following general methods can be used to adjust the peak-to-valley difference rate of the source-grid-load-storage system:

[0003] Peak-valley balancing strategy: By controlling the charging and discharging behavior of the energy storage system, the difference between peak and valley loads is minimized. During the load valley period, the energy storage system is charged to store energy; during the load peak period, the energy storage system releases the stored energy to meet the power demand. This strategy can smooth the load curve and reduce the peak-valley difference rate.

[0004] Electricity price-based strategy: Adjust the energy storage system charging and discharging strategy according to changes in electricity prices. During peak electricity price periods, the energy storage system is charged to utilize electricity during low-price periods; during low electricity price periods, the energy storage system releases stored energy to meet demand during high-price periods. This strategy can reduce electricity costs and reduce peak-to-valley differences.

[0005] Prediction and dispatch coordination: Through the prediction of load and electricity price, as well as the energy state prediction of energy storage system, the peak-valley rate can be adjusted. Based on these prediction results, a reasonable charging and discharging plan is formulated to maximize the balance of load and energy demand.

[0006] Load management and response: Through load management and response strategies, users are encouraged to reduce electricity consumption during peak load periods or increase electricity consumption during low load periods. This can be achieved through differentiated electricity price policies, energy management systems, smart grid technologies, etc. Users' load regulation can be coordinated with the charging and discharging strategies of the energy storage system to further reduce the peak-valley difference rate.

[0007] However, the above regulation method does not optimize the energy storage charging and discharging strategy when adjusting the peak-to-valley difference rate, nor does it solve the load-side response strategy that matches the energy storage control strategy. This results in the energy storage control strategy and load response strategy being unable to achieve a better regulation effect. Summary of the invention

[0008] The purpose of the present invention is to propose an energy storage control strategy optimization and load response algorithm for adjusting the peak-to-valley difference rate of a source-grid-load-storage system. The proposed method simultaneously considers the peak-to-valley difference rate, the load forecast of the power system, and the capacity of the energy storage system and uses an optimization algorithm to determine the best energy storage control strategy and formulate the best charging and discharging plan. Then, further adjustment of the load can be coordinated with the charging and discharging strategy of the energy storage system to further reduce the peak-to-valley difference rate, that is, based on the charging and discharging plan of the energy storage, the external power receiving characteristics of the system and the characteristics of the load itself, a load management and response strategy that considers the peak-to-valley difference rate of the system is specified, so that the peak-to-valley difference rate of the external power receiving of the final source-grid-load-storage system meets the target value requirements.

[0009] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0010] The energy storage control and load response method for adjusting the peak-to-valley difference rate of the source-grid-load-storage system is characterized by comprising the following steps;

[0011] Step 1: Based on the forecast results of the output and load demand of new energy sources such as wind power and photovoltaic power in a control cycle, calculate and compare the natural peak-to-valley difference rate of the load and the peak-to-valley difference rate of the source-grid-load-storage system when the energy storage is adjusted without considering the peak-to-valley difference rate, and obtain the new energy output curve and load curve;

[0012] Step 2: For scenarios where the system peak-to-valley difference rate needs to be further optimized, construct an optimization objective function for the energy storage charging and discharging strategy that takes the peak-to-valley difference rate into consideration;

[0013] Step 3: Using the optimization objective function constructed in step 2, construct and solve the energy storage charging and discharging strategy optimization model that takes into account the peak-to-valley difference rate to obtain the corresponding energy storage charging and discharging strategy;

[0014] Step 4: Based on the energy storage charging and discharging strategy in step 3 and the new energy output curve and load curve in step 1, further demand-side response is performed.

[0015] The load peak-to-valley difference rate is an indicator used to measure the difference between the peak and valley values ​​in the power load curve. The load peak-to-valley difference rate can be calculated using the following formula:

[0016] g(P L )=(P L.max -P L.min ) / P L.max (1.1)

[0017] Among them, g(P L ) represents the natural peak-to-valley difference rate of the load, P L.max Indicates the peak value of the load curve in a day, P L.min Indicates the valley value of the load curve in a day;

[0018] When calculating energy storage without considering the peak-to-valley difference rate, the peak-to-valley difference rate of the source-grid-load-storage integrated system. In the source-grid-load-storage system, the peak-to-valley difference rate is expressed as the ratio of the difference between the peak and valley values ​​of its external power receiving characteristics within a day to the peak value. The calculation model of the peak-to-valley difference rate in the source-grid-load-storage integrated system is:

[0019]

[0020] Where f(P max ,P min ) is the peak-to-valley difference rate of the external power receiving characteristics of the source-grid-load-storage integrated system, P max is the peak value of external power received by the source-grid-load-storage integrated system in one day, P min is the valley value of external power received by the integrated power grid-load-storage system in one day, Max{·} and Min{·} are the operators of maximum and minimum values ​​respectively, P L =[P L (T1),P L (T2),....,P L (T 24 )] T is the active power demand of the load, [T1,T2,....,T 24 ] is 24 moments in a day, with an interval of 1 hour, P G =[P G (T1),P G (T2),....,P G (T 24 )] T Contribute to the development of new energy; b is the charging and discharging power of the energy storage, the sign is positive when charging and negative when discharging. The charging and discharging power of the energy storage at each moment is [P b (T1),P b (T2),....,P b (T 24 )] T ;

[0021] If the peak-to-valley difference rate f(P max ,P min ) is less than the natural peak-to-valley rate of the load g(P L ), it means that the source-load characteristics of the system are highly complementary on that day, and there is no need for energy storage to adjust the peak-to-valley difference rate; on the contrary, if the peak-to-valley difference rate f(P max ,P min ) is greater than the natural peak-to-valley rate of the load g(P L ), it is necessary to further optimize the charging and discharging plan of energy storage and the load response strategy to reduce the peak-to-valley difference rate.

[0022] When the goal is to reduce the peak-to-valley difference rate of the source-grid-load-storage system, it is necessary to first determine the variables to be optimized and the control logic of the energy storage, and calculate the corresponding peak-to-valley difference rate. The specific steps are as follows:

[0023] (1) Since the peak-to-valley difference rate represents the smoothness of the external power received in a control cycle, the higher the peak-to-valley difference rate, the greater the difference between the peak value and the valley value, and the smaller the peak-to-valley difference rate, the smaller the power fluctuation and the smoother the curve. Therefore, when formulating the adjustment target of the external power received at each control moment, the average value of the difference between the initial load and the output of the new energy in a control cycle multiplied by an adjustment coefficient can be used as the reference value for adjustment. Therefore, the target adjustment amount can be calculated as follows:

[0024]

[0025] Where P target is the target external power received during adjustment, P lack is the target adjustment amount, λ is the adjustment coefficient, which is used as the variable to be optimized in the subsequent optimization process, t=1,...,24 are the adjustment moments in a day, and the time interval is one hour;

[0026] (2) Since the load demand may be greater than the output of renewable energy or greater than the output of renewable energy at certain times of the day, this leads to the target adjustment amount P lack It may also be greater than 0 or less than 0. lack When it is greater than 0, energy storage discharge is required to reduce power demand. lack When it is less than 0, energy storage charging is required to increase the power demand. Therefore, P at each moment can be adjusted according to the charging and discharging period of energy storage. lack Divide into n groups as follows, each group represents a series of consecutive moments of charging / discharging:

[0027] {[P lack (1,1),...,P lack (1,k1)],...,[P lack (n,1),...,P lack (n,k n )]}(1.4) where n is the number of charging / discharging periods in a day, k1,...,k n are the number of times for each charging / discharging period, and satisfy k1+...+k n =24;

[0028] (3) Let i = 1;

[0029] (4) For the i-th period, calculate the total target charge / discharge amount:

[0030] P total (i) = P lack(i,1)+...+P lack (i,k i )(1.5)

[0031] Where P total (i) represents the target charge / discharge amount in the i-th period. If P total (i)>0, which means that energy storage discharge is needed in the corresponding period to reduce external power consumption, then go to step (5). Otherwise, if P total (i)≤0, which means that energy storage charging is needed in the corresponding period to increase external power supply, then go to step (6);

[0032] (5) For P total (i)>0, since the actual dischargeable power of the energy storage at the jth moment in the i-th period is related to parameters such as the real-time state of charge and the maximum charge and discharge power of the energy storage, when the remaining power of the energy storage in the i-th period cannot meet the discharge demand, the energy storage at each moment needs to be discharged according to the size of the remaining power and the size of the target discharge power. Therefore, the discharge power of the energy storage can be calculated as:

[0033]

[0034] Where P b (i,j) is the energy storage charging and discharging power at the jth moment in the i-th period, and P b (i,j) is positive, when discharging, P b (i,j) is negative, P b.max is the charging and discharging power limit of energy storage, P lack (i, j) is the target discharge power at the jth moment in the i-th period, SOC is the real-time state of charge of the energy storage, Q b is the capacity of energy storage;

[0035] In addition, in order to ensure the regulation effect of the next day, when i=n, ​​it is necessary to keep the remaining power of the energy storage at the end of the discharge operation in this period greater than the single charge and discharge power P of the energy storage as much as possible. b.max , the discharge amount of energy storage can be calculated as follows:

[0036]

[0037] (6) For P total (i)≤0, since the actual rechargeable power of the energy storage at the jth moment in the i-th period is related to parameters such as the real-time state of charge and the maximum charge and discharge power of the energy storage, when the remaining capacity of the energy storage in the i-th period cannot meet the charging demand, the energy storage at each moment needs to be charged according to the size of the remaining capacity and the size of the target discharge power. Therefore, the charging power of the energy storage can be calculated as:

[0038]

[0039] In addition, in order to ensure the regulation effect of the next day, when i=n, ​​it is necessary to keep the remaining capacity of the energy storage at the end of the charging operation in this period greater than the single charging and discharging power P of the energy storage as much as possible. b.max , the charging power of the energy storage can be calculated as follows:

[0040]

[0041] (7) Let i = i + 1, verify whether i ≤ n holds. If so, return to step (4). If not, end the charging and discharging operation of the energy storage, calculate and return the peak-to-valley difference rate f(P max ,P min ) as the optimization target.

[0042] Taking the peak-to-valley difference rate of the source-grid-load-storage system obtained in step (2) as the optimization target, the energy storage charging and discharging strategy optimization model considering the peak-to-valley difference rate is constructed as follows:

[0043]

[0044] Where f(P max ,P min ) is calculated based on the method described in step 2. By using the particle swarm algorithm to optimize the adjustment coefficient λ, the target adjustment amount in each control cycle can be determined and the specific strategy of energy storage charging and discharging can be finally determined [P b (T1),...,P b (T 24 )];

[0045] For step 4, due to the limited regulation capacity of energy storage, it may not be possible to meet the peak-valley difference regulation requirements in scenarios where the output of new energy sources fluctuates violently. At this time, the load needs to further respond to the demand side based on the existing energy storage regulation strategy so that the final peak-valley difference meets the requirement of not exceeding the natural peak-valley difference of the load. The specific load response strategy is as follows:

[0046] (1) Verify that the load does not participate in the system peak-to-valley difference rate f(P max ,P min )<g(P L ) is established, if established, then the load response process ends, if not established, then proceed to step (2);

[0047] (2) Taking the target minimum load value P L.min and the maximum value P L.maxAs the variable to be optimized, the following optimization model is constructed and solved with the peak-to-valley difference rate not higher than 90% of the natural peak-to-valley difference of the load as the optimization target:

[0048]

[0049] Where ΔP L (t) is the target load adjustment at time t, P(t) is the external power received by the source grid load storage system at time t, and P L.max and P L.min are the target minimum and maximum values ​​of the load, respectively. The above optimization model can be easily solved by using heuristic algorithms such as particle swarm optimization and genetic algorithm, and then the target minimum value of the load P is obtained. L.min and the maximum value P L.max ;

[0050] (3) Correction of load curve:

[0051]

[0052] Where P L ′(t) is the load correction at time t.

[0053] The beneficial results of the present invention are: through an energy storage control strategy optimization and load response algorithm for adjusting the peak-to-valley difference rate of the source-grid-load-storage system, the peak-to-valley difference rate, the load forecast of the power system, and the capacity of the energy storage system can be considered at the same time, and the optimization algorithm can be used to determine the best energy storage control strategy, formulate the best charging and discharging plan, and then, the further adjustment of the load can be coordinated with the charging and discharging strategy of the energy storage system to further reduce the peak-to-valley difference rate. The advantage of the proposed method is that it can solve the optimal energy storage charging and discharging plan that can reduce the peak-to-valley difference rate through the optimization algorithm, and based on this, further optimize and solve the load response strategy that meets the regulation requirements. This method can be applied to the solution of peak-to-valley difference rate energy storage charging and discharging and load response strategies under various complex working conditions in the source-grid-load-storage integrated system. It has a wide range of applications and is easy to solve. It can provide a scientific and reasonable analysis and control solution for the safe and stable operation of the source-grid-load-storage integrated system. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 The annual output curve of wind power according to the embodiment of the present invention;

[0055] Figure 2 The photovoltaic annual output curve of the embodiment of the present invention;

[0056] Figure 3 The load characteristic curve of the previous year of the load response of the embodiment of the present invention;

[0057] Figure 4A comparison diagram of the natural peak-to-valley difference rate of the load and the peak-to-valley difference rate of the source-grid-load-storage system when the energy storage is adjusted without considering the peak-to-valley difference rate in an embodiment of the present invention;

[0058] Figure 5 The annual charge and discharge curve of the energy storage according to the embodiment of the present invention;

[0059] Figure 6 The annual load curve after the load response of the embodiment of the present invention;

[0060] Figure 7 It is a comparison chart of the natural peak-to-valley difference rate of the load and the peak-to-valley difference rate of the source-grid-load-storage system when adjusted by the method proposed in the present invention. DETAILED DESCRIPTION

[0061] The present invention is further explained below in conjunction with the accompanying drawings and specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. After reading the present invention, various equivalent modifications of the present invention by those skilled in the art all fall within the scope defined by the claims attached to this application.

[0062] This embodiment takes a grid-connected source-grid-load-storage integrated system that combines wind and solar power to supply power to a chemical material manufacturing enterprise as an example. In order to verify the effectiveness of the proposed method, the source-grid-load-storage integrated demonstration project in the example plans a total of 150MW wind power and 200MWp photovoltaic power, and is equipped with 25% / 4h energy storage equipment to supply power to chemical enterprises. Therefore, taking the natural peak-to-valley difference rate of the load as the adjustment target, the peak-to-valley difference rate of the source-grid-load-storage integrated system is adjusted according to the charging and discharging strategy of the energy storage. Next, the external power receiving characteristics of the system throughout the year are verified, and the new energy output curve, the load power consumption curve and the corresponding data are selected for analysis, and then it is verified that the peak-to-valley difference rate of the system can be significantly reduced under the adjustment strategy proposed in this patent.

[0063] Wind power, photovoltaic output and load characteristics such as Figure 1 to Figure 3 shown.

[0064] 1. Based on the forecast results of the output and load demand of new energy sources such as wind power and photovoltaic power, calculate the natural peak-to-valley difference rate of the load and the peak-to-valley difference rate of the source-grid-load-storage system when the energy storage is adjusted without considering the peak-to-valley difference rate;

[0065] The load peak-to-valley difference rate is an indicator used to measure the difference between the peak and valley values ​​in the power load curve. The load peak-to-valley difference rate can be calculated using the following formula:

[0066] g(P L )=(P L.max -P L.min ) / P L.max

[0067] Among them, g(PL ) represents the natural peak-to-valley difference rate of the load, P L.max Indicates the peak value of the load curve in a day, P L.min Indicates the valley value of the load curve in a day;

[0068] When calculating energy storage without considering the peak-to-valley difference rate, the peak-to-valley difference rate of the source-grid-load-storage integrated system. In the source-grid-load-storage system, the peak-to-valley difference rate is expressed as the ratio of the difference between the peak and valley values ​​of its external power receiving characteristics within a day to the peak value. The calculation model of the peak-to-valley difference rate in the source-grid-load-storage integrated system is:

[0069]

[0070] Where f(P max ,P min ) is the peak-to-valley difference rate of the external power receiving characteristics of the source-grid-load-storage integrated system, P max is the peak value of external power received by the source-grid-load-storage integrated system in one day, P min is the valley value of external power received by the integrated power grid-load-storage system in one day, Max{·} and Min{·} are the operators of maximum and minimum values ​​respectively, P L =[P L (T1),P L (T2),....,P L (T 24 )] T is the active power demand of the load, [T1,T2,....,T 24 ] is 24 moments in a day, with an interval of 1 hour, P G =[P G (T1),P G (T2),....,P G (T 24 )] T Contribute to the development of new energy; b is the charging and discharging power of the energy storage, the sign is positive when charging and negative when discharging. The charging and discharging power of the energy storage at each moment is [P b (T1),P b (T2),....,P b (T 24 )] T ;

[0071] If the peak-to-valley difference rate f(P max ,P min ) is less than the natural peak-to-valley rate of the load g(P L ), it means that the source-load characteristics of the system are highly complementary on that day, and there is no need for energy storage to adjust the peak-to-valley difference rate; on the contrary, if the peak-to-valley difference rate f(P max ,P min) is greater than the natural peak-to-valley rate of the load g(P L ), it is necessary to further optimize the charging and discharging plan of energy storage and the load response strategy to reduce the peak-to-valley difference rate.

[0072] According to the above method, the natural peak-to-valley difference rate of the load and the peak-to-valley difference rate of the source-grid-load-storage system when the energy storage is adjusted without considering the peak-to-valley difference rate are solved as follows: Figure 4 It can be seen that when the charging and discharging of energy storage does not consider the goal of reducing the peak-valley difference rate, due to the high mismatch between the load and the new energy curve, and the energy storage always releases electricity as much as possible when there is a power shortage, and charges as much as possible when there is surplus electricity, this causes the system peak-valley difference rate to be higher than the natural peak-valley difference rate of the load most of the time. Therefore, it is necessary to further optimize the charging and discharging plan of energy storage and the load response strategy to reduce the peak-valley difference rate.

[0073] 2. Construct the optimization objective of the energy storage charging and discharging strategy optimization model that takes into account the peak-to-valley difference rate.

[0074] When the goal is to reduce the peak-to-valley difference rate of the source-grid-load-storage system, it is necessary to first determine the variables to be optimized and the control logic of the energy storage, and calculate the corresponding peak-to-valley difference rate. The specific steps are as follows:

[0075] (1) Since the peak-to-valley difference rate represents the smoothness of the external power received in a control cycle, the higher the peak-to-valley difference rate, the greater the difference between the peak value and the valley value, and the smaller the peak-to-valley difference rate, the smaller the power fluctuation and the smoother the curve. Therefore, when formulating the adjustment target of the external power received at each control moment, the average value of the difference between the initial load and the output of the new energy in a control cycle multiplied by an adjustment coefficient can be used as the reference value for adjustment. Therefore, the target adjustment amount can be calculated as follows:

[0076]

[0077] Where P lack is the target adjustment amount, λ is the adjustment coefficient, which is used as the variable to be optimized in the subsequent optimization process, T=1,...,24 is the adjustment time in a day, and the time interval is one hour;

[0078] (2) Since the load demand may be greater than the output of renewable energy or greater than the output of renewable energy at certain times of the day, this leads to the target adjustment amount P lack It may also be greater than 0 or less than 0. lack When it is greater than 0, energy storage discharge is required to reduce power demand. lack When it is less than 0, energy storage charging is required to increase the power demand. Therefore, P at each moment can be adjusted according to the charging and discharging period of energy storage. lack Divide into n groups as follows, each group represents a series of consecutive moments of charging / discharging:

[0079] {[Plack (1,1),...,P lack (1,k1)],...,[P lack (n,1),...,P lack (n,k n )]}

[0080] Where n is the number of charging / discharging periods in a day, k1,...,k n are the number of times for each charging / discharging period, and satisfy k1+...+k n =24;

[0081] (3) Let i = 1;

[0082] (4) For the i-th period, calculate the total target charge / discharge amount:

[0083] P total (i) = P lack (i,1)+...+P lack (i,k i )

[0084] Where P total (i) represents the target charge / discharge amount in the i-th period. If P total (i)>0, which means that energy storage discharge is needed in the corresponding period to reduce external power consumption, then go to step (5). Otherwise, if P total (i)≤0, which means that energy storage charging is needed in the corresponding period to increase external power supply, then go to step (6);

[0085] (5) For P total (i)>0, since the actual dischargeable power of the energy storage at the jth moment in the i-th period is related to parameters such as the real-time state of charge and the maximum charge and discharge power of the energy storage, when the remaining power of the energy storage in the i-th period cannot meet the discharge demand, the energy storage at each moment needs to be discharged according to the size of the remaining power and the size of the target discharge power. Therefore, the discharge power of the energy storage can be calculated as:

[0086]

[0087] Where P b (i,j) is the energy storage charging and discharging power at the jth moment in the i-th period, and P b (i,j) is positive, when discharging, P b (i,j) is negative, P b.max is the charging and discharging power limit of energy storage, P lack (i, j) is the target discharge power at the jth moment in the i-th period, SOC is the real-time state of charge of the energy storage, Q bis the capacity of energy storage;

[0088] In addition, in order to ensure the regulation effect of the next day, when i=n, ​​it is necessary to keep the remaining power of the energy storage at the end of the discharge operation in this period greater than the single charge and discharge power P of the energy storage as much as possible. b.max , the discharge amount of energy storage can be calculated as follows:

[0089]

[0090] (6) For P total (i)≤0, since the actual rechargeable power of the energy storage at the jth moment in the i-th period is related to parameters such as the real-time state of charge and the maximum charge and discharge power of the energy storage, when the remaining capacity of the energy storage in the i-th period cannot meet the charging demand, the energy storage at each moment needs to be charged according to the size of the remaining capacity and the size of the target discharge power. Therefore, the charging power of the energy storage can be calculated as:

[0091]

[0092] In addition, in order to ensure the regulation effect of the next day, when i=n, ​​it is necessary to keep the remaining capacity of the energy storage at the end of the charging operation in this period greater than the single charging and discharging power P of the energy storage as much as possible. b.max , the charging power of the energy storage can be calculated as follows:

[0093]

[0094] (7) Let i = i + 1, verify whether i ≤ n holds. If so, return to step (4). If not, end the charging and discharging operation of the energy storage, calculate and return the peak-to-valley difference rate f(P max ,P min ). According to the above method, the objective function is constructed, and the variable to be optimized is the adjustment coefficient λ.

[0095] 3. Construct and solve the energy storage charging and discharging strategy optimization model that takes into account the peak-to-valley difference rate.

[0096] Taking the peak-to-valley difference rate of the source-grid-load-storage system obtained in step 2 as the optimization target, the energy storage charging and discharging strategy optimization model considering the peak-to-valley difference rate is constructed as follows:

[0097] min f(P max ,P min )

[0098] st0≤λ≤2

[0099] Where f(P max ,P min) is calculated based on the method described in step 2. By optimizing the adjustment coefficient λ, the target adjustment amount in each control cycle can be determined and the specific strategy of energy storage charging and discharging can be finally determined. b (T1),...,P b (T 24 )];

[0100] The particle swarm algorithm is used to solve the above optimization model, and the annual energy storage charge and discharge curve is as follows: Figure 5 shown.

[0101] 4. Due to the limited regulation capacity of energy storage, the peak-valley difference rate regulation requirements may not be met in scenarios where the output of new energy sources fluctuates violently. At this time, the load needs to further respond to the demand side based on the existing energy storage regulation strategy so that the final peak-valley difference rate meets the requirement of not exceeding the natural peak-valley difference rate of the load. The specific load response strategy is as follows:

[0102] (1) Verify that the load does not participate in the system peak-to-valley difference rate f(P max ,P min )<g(P L ) is established, if established, then the load response process ends, if not established, then proceed to step (2);

[0103] (2) Taking the target minimum load value P L.min and the maximum value P L.max As the variable to be optimized, the following optimization model is constructed and solved with the peak-to-valley difference rate not higher than 90% of the natural peak-to-valley difference of the load as the optimization target:

[0104]

[0105] stP(T i )=P L (T i )+P G (T i )+P b (T i ),i=1,...,24

[0106] P max =Max{P L +P G +P b}

[0107] P min =Min{P L +P G +P b}

[0108]

[0109] P L.max =P L.min / (1-0.9f(P max ,P min ))

[0110]

[0111] P min ≤P L.min ≤P max

[0112] Where ΔP L (T i ) is T i The target load adjustment at any moment, P(T i ) is T i The external power received by the source grid-load storage system at the moment, P L.max and P L.min are the target minimum and maximum values ​​of the load, respectively. The above optimization model can be easily solved by using heuristic algorithms such as particle swarm optimization and genetic algorithm, and then the target minimum value of the load P is obtained. L.min and the maximum value P L.max ;

[0113] (3) Correction of load curve:

[0114]

[0115] Where P L ′(T i ) is T i The correction amount of the momentary load.

[0116] The load response curve obtained by the above method is as follows: Figure 6 As shown in the figure, the peak-to-valley difference rate after adjusting the energy storage and load using the proposed method is as follows: Figure 7 As shown, it can be seen that the peak-to-valley difference rate of the adjusted system meets the requirement of being less than the natural peak-to-valley difference rate of the load, which verifies the effectiveness of the method proposed in the present invention.

[0117] The above description is only a preferred embodiment of the present invention. All equivalent changes and modifications made according to the scope of the patent application of the present invention should fall within the scope of the present invention.

Claims

1. A method for energy storage control and load response for adjusting the peak-to-valley difference rate of a source-grid-load-storage system, characterized in that: The steps include: Step 1: Based on the forecast results of the output and load demand of new energy in a control cycle, calculate and compare the natural peak-to-valley difference rate of the load and the peak-to-valley difference rate of the source-grid-load-storage system when the energy storage is adjusted without considering the peak-to-valley difference rate, and obtain the new energy output curve and load curve; Step 2: For scenarios where the system peak-to-valley difference rate needs to be further optimized, construct an optimization objective function for the energy storage charging and discharging strategy that takes the peak-to-valley difference rate into consideration; Step 3: Using the optimization objective function constructed in step 2, construct and solve the energy storage charging and discharging strategy optimization model that takes into account the peak-to-valley difference rate to obtain the corresponding energy storage charging and discharging strategy; Step 4: Based on the energy storage charging and discharging strategy in step 3 and the new energy output curve and load curve in step 1, further demand-side response is performed.

2. The energy storage control and load response method for regulating the peak-to-valley difference rate of the source-grid-load-storage system according to claim 1 is characterized in that: The second step is specifically: when the goal is to reduce the peak-to-valley difference rate of the source-grid-load-storage system, it is necessary to first determine the variables to be optimized and the control logic of the energy storage, and calculate the corresponding peak-to-valley difference rate. The specific steps are as follows: (1) When formulating the adjustment target of the external power at each control moment, the average value of the difference between the initial load and the output of new energy in a control cycle multiplied by an adjustment coefficient is used as the reference value for adjustment. The target adjustment amount is calculated as follows: Where P target is the target external power received during adjustment, P lack is the target adjustment amount, P L is the load demand size, P G is the output of new energy, λ is the adjustment coefficient, which is the variable to be optimized in the subsequent optimization process, t=1,...,24 are the adjustment moments in a day, and the time interval is one hour; (2) When P lack When it is greater than 0, energy storage discharge is required to reduce power demand. lack When it is less than 0, energy storage charging is required to increase the power demand, P lack Equal to 0 indicates that the supply and demand are balanced and no energy storage action is needed; according to the charging and discharging period of the energy storage, P at each time of the day lack Divide into n groups as follows, each group represents a series of consecutive moments of charging or discharging: {[P lack (1,1),...,P lack (1,k1)],...,[P lack (n,1),...,P lack (n,k n )]}(1.4) Where n is the number of charging or discharging periods in a day, k1,...,k n is the number of moments in each charging or discharging period, and satisfies k1+...+k n =24; (3) Let i = 1; (4) For the i-th period, calculate the total target charge or discharge amount: P total (i)=P lack (i,1)+...+P lack (i,k i )(1.5) Where P total (i) represents the target charge / discharge amount in the i-th period. If P total (i)>0, then go to step (5), otherwise if P total (i)≤0, go to step (6); (5) For P total (i)>0, when the remaining power of the energy storage in the i-th period cannot meet the discharge demand, it is necessary to discharge the energy storage at each moment of the charging and discharging period according to the size of the remaining power and the size of the target discharge power. Therefore, the discharge power of the energy storage is calculated as: Where P b (i,j) is the energy storage charging and discharging power at the jth moment in the i-th period, and P b (i,j) is positive, when discharging, P b (i,j) is negative, P b.max is the charge and discharge power limit of the energy storage, Plack(i,j) is the target discharge power at the jth moment in the i-th period, SOC is the real-time state of charge of the energy storage, Q b is the capacity of energy storage; When i=n, ​​it is necessary to keep the remaining power of the energy storage at the end of the discharge operation in this period greater than the single charge and discharge power P of the energy storage as much as possible. b.max , the discharge amount of energy storage is calculated as follows: (6) For P total (i)≤0, when the remaining capacity of the energy storage in the i-th period cannot meet the charging demand, it is necessary to charge the energy storage at each moment of the i-th period according to the size of the remaining capacity and the size of the target discharge power. Therefore, the charging power of the energy storage is calculated as: When i=n, ​​it is necessary to keep the remaining capacity of the energy storage at the end of the charging operation in this period greater than the single charging and discharging power P of the energy storage as much as possible. b.max , the charging power of energy storage is calculated as follows: Let i = i + 1, verify whether i ≤ n is established. If yes, return to step (4). If not, end the charging and discharging operation of the energy storage and calculate the peak-to-valley difference rate f(P max ,P min ) as the optimization target, where P max ,P min They are the maximum and minimum values ​​of the external power received by the system respectively.

3. The energy storage control and load response method for regulating the peak-to-valley difference rate of the source-grid-load-storage system according to claim 2 is characterized by: The step three is specifically as follows: Taking the peak-to-valley difference rate of the source-grid-load-storage system obtained in step 2 as the optimization target, the energy storage charging and discharging strategy optimization model considering the peak-to-valley difference rate is constructed as follows: By using the particle swarm algorithm to solve the above optimization model, the target adjustment amount in each control cycle can be determined and the specific strategy of energy storage charging and discharging can be finally determined. b (T1),...,P b (T 24 )].

4. The energy storage control and load response method for regulating the peak-to-valley difference rate of the source-grid-load-storage system according to claim 1 is characterized by: The load response strategy of step 4 is as follows: (1) Verify that the load does not participate in the system peak-to-valley difference rate f(P max ,P min )<g(P L ) is true, g(P L ) is the natural peak-to-valley difference rate of the load. If it is established, the load response process ends. If it is not established, it goes to step (2); (2) Taking the target minimum load value P L.min and the maximum value P L.max As the variable to be optimized, the following optimization model is constructed and solved with the peak-to-valley difference rate not higher than 90% of the natural peak-to-valley difference of the load as the optimization target: Where ΔP L (t) is the target load adjustment at time t, P(t) is the external power received by the source grid load storage system at time t, and P L.max and P L.min are the target minimum and maximum values ​​of the load respectively; Then the target minimum load value P is obtained L.min and the maximum value P L.max ; (3) Correction of load curve: Where P L ′(t) is the load correction at time t.

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