A method for simulating load side demand response regulation potential

Abstract

The application provides a load side demand response adjustment potential simulation calculation method, and belongs to the field of power system automation, and comprises the following steps: step 1, a load regulation potential calculation model is constructed, the model is composed of a load power change function and a demand response regulation function; step 2, the load power change function is obtained by fitting data; step 3, the demand response regulation function is determined according to parameters such as action time, adjustment time and sustainable time of the regulation response process; and step 4, the demand response power change value is solved according to the demand response time based on the regulation potential calculation model. The application unifies the calculation of demand response and controllable characteristics, and can realize real-time calculation of the instantaneous power of the load adjustment process through operation curve fitting combined with the load demand response regulation function. Based on the application, the power fluctuation of the regulation process and the sustainability of the load adjustment can be considered, and the demand response power deviation can be reduced.

Description

Technical Field

[0001] This invention relates to the field of power system automation, specifically a method for simulating and calculating the load-side demand response adjustment potential. Background Technology

[0002] Demand response is a crucial aspect of power system operation, and demand response simulation is an effective way to evaluate the response effectiveness of loads that can participate in demand response. Since demand response always occurs at a future point in time, it is necessary to first report the adjustability potential of load resources during the demand response period. Adjustability potential includes the adjustable power and controllable modes at the demand response time. Existing methods only consider the load operating power characteristics during demand response, neglecting controllability characteristics. This leads to errors in the timing of demand response and insufficient consideration of load response sustainability, resulting in biased demand response results. Summary of the Invention

[0003] To address the aforementioned technical problems, the present invention provides a method for simulating and calculating the load-side demand response adjustment potential. This invention unifies the calculation of demand response and controllability characteristics, and by combining curve fitting with a control function, it can calculate the instantaneous power during the load adjustment process in real time. Demand response calculations based on this invention can take into account power fluctuations during the control process and the sustainability of load adjustment, thereby reducing demand response power deviation.

[0004] A method for simulating and calculating load-side demand response adjustment potential includes the following steps:

[0005] Step 1: Construct a regulation potential calculation model. The model consists of two parts: a load power change function and a demand response regulation function. The load power change function is a function of power with respect to time.

[0006] Step 2: Obtain the load power change function by fitting the data;

[0007] Step 3: Determine the demand response control function based on parameters such as the action time, adjustment time, and duration of the control response process;

[0008] Step 4: Based on the regulation potential calculation model, calculate the change in demand response power according to the demand response time.

[0009] Furthermore, the calculation model for the regulatory potential in step 1 is as follows:

[0010] f(t) = g(t) + k(t)

[0011] Where t is time, f(t) represents the demand response potential calculation function, g(t) represents the load power change function, g(t) is a power function with respect to time, and k(t) represents the demand response control function, which is a power correction function for the load adjustment process generated by the controllable characteristics.

[0012] Furthermore, the load power change function is generated by fitting historical load operation data. Assuming the historical load operation data contains m sample points, the corresponding time and power dataset is: {(t1, y1), (t2, y2)…(t… m y m )}, where m represents the number of sample points, (t1, y1) represents the power value y1 at time t1, (t2, y2) represents the power value y2 at time t2, and so on;

[0013] Fitting using polynomials

[0014]

[0015] in, Let a0, a1, ..., a represent the fitted load power. n The coefficients representing different powers of time, t n , t n-1 ,…t represents the power of time, and n is the largest power of time;

[0016] The power data of the input load is fitted to minimize the residual:

[0017]

[0018] Where μ represents the residual, y i This represents the power value at time i.

[0019] Preferably, n=5.

[0020] Furthermore,

[0021] k(t)=c(t-t0)P′

[0022] Where t0 represents the demand response start time, c is the controllable mode parameter, c is 1 when it is controllable, and c is 0 otherwise, P′ represents the current power;

[0023] (1) When t-t0 <t a When P′ = 0;

[0024] (2) When t l >t-t0≥t a hour,

[0025] (3) When tl ≤t-t0 <t s At that time, P′=P l ;

[0026] (4) When t-t0>t s When P′ = 0;

[0027] Among them, t a Indicates the load control response start-up time, t l Indicates the control time, t s Indicates the duration of the regulation. P represents the power at the previous moment, α is the power fluctuation coefficient, and P l This indicates the maximum load correction amount.

[0028] Preferably, the millisecond-level response load is t. a =0.01, t l =0.1, second-level response load t a =1,t l =10, minute-level response load t a =60,t l =300.

[0029] Preferably, the load power change function obtained through fitting calculation is:

[0030] g(t) = -5917.6t 5 +13697t 4 -11029t 3 +3662.5t 2 -420.5t+66.421.

[0031] Preferably, for air conditioning load:

[0032] k(t)=(t-0.01)P′

[0033]

[0034] Preferably, for chemical loads:

[0035] k(t)=(t-0.01)P′

[0036]

[0037] Compared with existing technologies, the beneficial effects of this invention are as follows: To solve the above-mentioned technical problems, the technical solution adopted by this invention is to provide a method for simulating and calculating the load-side demand response adjustment potential. This invention unifies the calculation of demand response and controllability characteristics, and by combining curve fitting with the control function, it can calculate the instantaneous power of the load adjustment process in real time. Based on this invention, demand response calculations can take into account power fluctuations and the sustainability of load adjustment during the control process, thereby reducing demand response power deviation. Attached Figure Description

[0038] Figure 1 This is a flowchart illustrating the steps of a load-side demand response adjustment potential simulation calculation method according to the present invention.

[0039] Figure 2 This is a schematic diagram of load data fitting for the present invention;

[0040] Figure 3 This is the air conditioning load demand response curve of the present invention;

[0041] Figure 4 This is the chemical load demand response curve of this invention. Detailed Implementation

[0042] The following detailed description of the load-side demand response adjustment potential simulation calculation method of the present invention, in conjunction with the accompanying drawings and specific implementation methods, provides further details.

[0043] This invention provides a method for simulating and calculating the load-side demand response adjustment potential, such as... Figure 1 As shown. This method establishes the general power characteristics of load demand response through power fitting, and then corrects them by establishing the power characteristics of load regulation response, so that the load demand response calculation can reflect the power changes of the load during the system regulation process, thus reducing the demand response power deviation. The specific scheme is as follows:

[0044] 1) Model

[0045] The model for calculating regulatory potential is defined as follows:

[0046] f(t) = g(t) + k(t)

[0047] f(t) represents the demand response potential calculation function; g(t) is the load power change function; k(t) represents the load adjustment process power correction function generated by the controllable characteristics. t is time.

[0048] This model definition allows us to consider the impact of the regulation process power on the load power characteristics, making the power calculation for the load's participation in the demand response process more accurate.

[0049] 2) Determination of g(t)

[0050] g(t) is generated by fitting historical load operation data. Let's assume the historical load operation data contains m points, which we'll call sample points.

[0051] {(t1, y1), (t2, y2)…(t m y m )}

[0052] Where t represents time and y represents power. (t1, y1) represents the power value y1 at time t1, and so on.

[0053] Fitting using polynomials

[0054]

[0055] in Let a0, a1, ..., a represent the fitted load power. n t represents the coefficients of different powers. n , t n-1 ,…t represents the time variable.

[0056] Minimize the residual:

[0057]

[0058] Where μ represents the residual, y i This represents the power value at time i.

[0059] In this scheme, a fifth-order fitting is used, that is, n in formula (2) is 5, and the power data of the load is input to perform data fitting.

[0060] 3) Determination of k(t)

[0061] k(t) represents the power change characteristics of the load regulation process and is a correction quantity. Since it is difficult to collect detailed model information for each load component, it is challenging to establish a physical model of the regulation process. Furthermore, in the demand response process, due to the diversity of loads involved, it is unnecessary to perform detailed modeling for every component of each load. Therefore, modeling is based on parameters including adjustability, response time, and duration. Thus, the following function is designed:

[0062] k(t)=c(t-t0)P′

[0063] Where t represents time. When t-t0 <t a When t, P′=0; when t l >t-t0≥t a hour, When t l ≤t-t0 <t s At that time, P′=P lWhen t - t0 > t s When P′ = 0;

[0064] Where c is the controllable mode parameter, which is 1 when it is controllable, and 0 otherwise.

[0065] t0 represents the start time of the demand response, t a Indicates the load control response start-up time, t l Indicates the control time, t s This indicates the duration of regulation. When it is less than the response start time, the power P′ remains the same as the power at the previous moment. α is the power fluctuation coefficient, P l This represents the maximum load correction. Due to the limited power adjustment time during demand response, a linear simulation is used, which does not significantly deviate from the demand response results and is therefore acceptable. After adjustment, operation is based on the maximum correction; after the allowable time has elapsed, operation returns to the original power. Since the recovery process generally does not affect grid power supply, power change is no longer considered. The configuration of several parameters is defined according to different loads. For millisecond-level response loads, t is used. a =0.01, t l =0.1, second-level response load t a =1,t l =10, minute-level response load t a =60,t l =300. The duration can be configured according to the load characteristics. The continuous production load takes a value between 30 and 120, while the interruptible load can be infinite.

[0066] Using the methods described above, a load regulation model adapted to control can be established in the simulation system.

[0067] Taking load A as an example:

[0068] 1) Collect historical load operation data

[0069] The power values ​​collected from load A are as follows:

[0070]

[0071]

[0072] 2) Find g(t)

[0073] like Figure 2 As shown, the following function is obtained through 5-order curve fitting.

[0074] g(t) = -5917.6t 5 +13697t 4 -11029t 3+3662.5t 2 -420.5t +66.421

[0075] 3) Find k(t)

[0076] The parameters are configured mainly based on the load type.

[0077] Assuming load A is an air conditioning load, which is a controllable load with a control action time in milliseconds and power adjustable to 0, we obtain:

[0078] k(t)=(t-0.01)P′

[0079] α=(g(t t＝t0+0.01 )-0) / 0.01, when the demand response begins at time t0 = 10, α = 6776.954.

[0080] Assuming load A is a chemical load, a controllable load, with a control action response time of 5 minutes, a response completion time of 30 minutes, and a power adjustable to 20 kW for a duration of 30 minutes, we obtain:

[0081] k(t)=(t-0.01)P′

[0082] α=(g(t t＝t0+5 )-20) / 30, when the demand response starts at t0 = 10 o'clock, the active power at 10:05 is 67.62476, so α = 1.59 / min.

[0083] 4) Potential Calculation

[0084] When load A is an air conditioning load, the calculated adjustability potential value is as follows: Figure 3 In other words, the air conditioning load is an instantaneous response load. At the start of the demand response period, the air conditioning load can quickly respond, reduce its power to zero, and continue until the end of the demand response period.

[0085] When load A is a chemical load, the calculated adjustable potential value is as follows: Figure 4 In other words, the chemical load is a continuous production load, and the demand response start-up time is relatively long, taking 5 minutes to initiate. The load reduction process is also slow, requiring 30 minutes to reduce to the minimum load of 20%. After 30 minutes, the chemical load must resume operation. Compared to air conditioning load, the adjustment process for the chemical load is slower and shorter in duration.

[0086] Therefore, the method described in this article can fully reflect the controllability of different load regulation processes, and the demand response process can basically reflect the actual load changes, thus achieving higher accuracy and reducing the deviation of demand response.

[0087] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for simulating and calculating the load-side demand response adjustment potential, characterized in that, Includes the following steps: Step 1: Construct a regulation potential calculation model. The model consists of two parts: a load power change function and a demand response regulation function. The load power change function is a function of power with respect to time. Step 2: Obtain the load power change function by fitting the data; Step 3: Determine the demand response control function based on the action time, adjustment time, and duration parameters of the control response process; Step 4: Based on the regulation potential calculation model, calculate the change in demand response power according to the demand response time; The calculation model for the regulation potential in step 1 is as follows: ； in, For time, This represents the function for calculating demand response potential. Let g(t) represent the load power change function, where g(t) is a function of power with respect to time. The demand response control function is a power correction function for the load regulation process generated by the controllability characteristics. ； in, This indicates the start time of the demand response. 'c' is a controllable mode parameter; 'c' is 1 when the condition is controllable, and 0 otherwise. Indicates the current power; (1) When hour, ; (2) When hour, ; (3) When hour, ; (4) When hour, ; in, Indicates the load control response start time. Indicates the adjustment period. Indicates the duration of the regulation. Indicates the power at the previous moment. For power fluctuation coefficient, This indicates the maximum load correction amount.

2. The method for simulating and calculating load-side demand response adjustment potential according to claim 1, characterized in that, The load power variation function is generated by fitting historical load operation data. Assuming the historical load operation data contains m sample points, the corresponding time and power dataset is as follows: , where m represents the number of sample points. express Power value at time , express Power value at time And so on; Fitting using polynomials ； in, This represents the fitted load power. , , ..., Coefficients representing different powers of time. , t represents the power of time, and n is the largest power of time; The power data of the input load is fitted to minimize the residual: ； in, Represents the residual. This represents the power value at time i.

3. The method for simulating and calculating the load-side demand response adjustment potential according to claim 2, characterized in that: n=5。 4. The method for simulating and calculating load-side demand response adjustment potential according to claim 1, characterized in that: Millisecond response load , Second-level response load Minute-level response load .

5. The method for simulating and calculating the load-side demand response adjustment potential according to claim 3, characterized in that: The load power variation function obtained through fitting calculation is: g(t) = -5917.6t 5 + 13697t 4 – 11029t 3 + 3662.5t 2 - 420.5t+ 66.421。 6. The method for simulating and calculating the load-side demand response adjustment potential according to claim 5, characterized in that: For air conditioning load: ； 。 7. The method for simulating and calculating load-side demand response adjustment potential according to claim 6, characterized in that: For chemical load: ； 。

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