User side energy storage optimization method and system considering excitation type demand side response

[0038] Example

[0039] figure 1 It shows a schematic flowchart of a user-side energy storage optimization method considering incentive demand-side response in an embodiment of the present invention, and the method includes the following steps:

[0040] S101. Establish a user-side energy storage economy optimization model;

[0041] (1) Taking the user-side minimum payment of electricity charges and the maximum compensation participating in the demand-side response as the target value, the objective function of the user-side energy storage economy optimization model is determined as:

[0042]

[0043] Among them, F pays the electricity bill this month, C 1 Is the electricity bill for the current month, C 2 Is the electricity demand of the month, C 3 For the subsidy obtained by the user side participating in the demand side response, C i Is the time-of-use electricity price, n is the number of sampling points per month, Load i Is the user load power at the i-th moment, P d,i Is the energy storage and discharge power at the i-th moment, P c,i Is the energy storage charging power at the i-th moment, P demand,max Is the maximum demand value reported by the user side, b is the actual demand value, α i Interruptible load price for demand response, s i Is the electricity price standard corresponding to the regulation time, v i Is the response speed coefficient, P DSM,i Is the reported power value for the i-th participating in the agreed response, and m is the number of demand responses.

[0044] (2) Determine the operating constraint conditions of the user-side energy storage device.

[0045] a. The remaining capacity during the operation of energy storage needs to meet certain constraints. The constraint conditions of the state of charge (SOC) of energy storage at any time are:

[0046] SOC min ≤SOC i ≤SOC max

[0047] b. The constraint conditions for the charging and discharging state of energy storage are:

[0048] 0≤sw ch,t +sw dis,t ≤1

[0049] c. Taking into account the discharge rate of different types of energy storage equipment, excessive current charging and discharging will damage the performance of the equipment and shorten the operating life. Therefore, the energy storage charging and discharging power constraints during operation are:

[0050]

[0051] d. Since the energy storage system can ensure the periodicity of its continuous operation when the stored energy (that is, the state of charge) is consistent at the beginning and end of each scheduling cycle, the continuity constraint condition of the energy storage state of charge is limited to:

[0052]

[0053] Among them, SOC i Is the state of charge of energy storage at time t on day i, SOC min Is the minimum state of charge of energy storage, SOC max Is the maximum state of charge of energy storage, sw dis,t Is the discharge state of the stored energy at the i-th moment (when the value is 1, the stored energy is in the discharged state), sw ch,t Is the charging state of energy storage at the i-th moment (when the value is 1, it means that the energy storage is in the charging state), P rate Is the rated power of the energy storage device on the user side, η c Is the maximum charging efficiency of energy storage, η d Is the maximum discharge efficiency of energy storage, E rate Is the rated capacity of the user-side energy storage device, and Δt is the time interval between charging and discharging the energy storage.

[0054] S102. Obtain the maximum power load on the user side in the previous year, and determine a demand side response baseline based on the maximum power load;

[0055] In the embodiment of the present invention, first, the constraint condition of the demand-side response baseline is set as:

[0056]

[0057] Among them, i is the time period during which the user participates in the demand side response, j is the sampling period of the demand side response baseline, P year,max The maximum load value of the year on the user side;

[0058] Secondly, the background monitoring center collects the user's historical power consumption data in the previous year at a sampling interval of 15 minutes, and filters and outputs the user's annual maximum load value in the previous year to limit the demand-side response baseline ; Finally, using the selected user-side response day as a benchmark, the load curve of the user-side response day 5 days before the user-side response day is defined as the demand-side response baseline.

[0059] S103. Using the demand-side response baseline as the criterion, import relevant parameters of the user-side energy storage device into the user-side energy storage economic optimization model, and combine the mixed integer linear programming algorithm to find the user's optimal reported demand response power .

[0060] The specific implementation process includes: (1) Initializing the mixed integer linear programming algorithm, that is, reading the simulation duration, scheduling period, historical load curve on the power consumption side, and relevant parameters of the energy storage device on the user side; The electrical side historical load curve is divided into 200 populations according to similar characteristics, and each individual in each population includes information on energy storage capacity, energy storage rated power and annual load peak reduction rate; (3) Call the hybrid The integer linear programming algorithm obtains the optimal charge-discharge curve and monthly load cut rate of each individual in all populations during the simulation period during the dispatch period, and combines the corresponding energy storage capacity, energy storage rated power and annual load cut. The peak rate calculates the objective function value corresponding to each individual in all the populations and the period of participation in the demand-side response; (3) The technical staff conducts statistical analysis based on the total electricity bills paid by all populations in each month in the past two years, Each population sets a minimum paid-in fee interval, and judges whether the objective function value corresponding to each individual falls within the corresponding lowest-paid fee interval; (4) Based on individuals whose objective function value falls within the corresponding lowest-paid fee interval , In conjunction with the demand-side response baseline, obtain the optimal reported demand response power of the individual in the corresponding participating demand-side response period; respond to the individual whose objective function value does not fall within the corresponding minimum paid-in fee interval Exception registration.

[0061] Example

[0062] figure 2 A user-side energy storage optimization system considering incentive demand-side response in an embodiment of the present invention is shown, and the system includes:

[0063] The establishment module 201 is used to establish the user-side energy storage economy optimization model;

[0064] In the embodiment of the present invention, the establishment module 201 is used to determine the objective function of the user-side energy storage economy optimization model, and the objective function takes the user-side minimum paid electricity fee and the maximum compensation for participating in the demand-side response as Target value; and determining the operating constraint condition of the user-side energy storage device. The details are as follows:

[0065] (1) Determine the objective function of the user-side energy storage economy optimization model as:

[0066]

[0067]

[0068]

[0069] Among them, F pays the electricity bill this month, C 1 Is the electricity bill for the current month, C 2 Is the electricity demand of the month, C 3 For the subsidy obtained by the user side participating in the demand side response, C i Is the time-of-use electricity price, n is the number of sampling points per month, Load i Is the user load power at the i-th moment, P d,i Is the energy storage and discharge power at the i-th moment, P c,i Is the energy storage charging power at the i-th moment, P demand,max Is the maximum demand value reported by the user side, b is the actual demand value, α i Interruptible load price for demand response, s i Is the electricity price standard corresponding to the regulation time, v i Is the response speed coefficient, P DSM,i Is the reported power value for the i-th participating in the agreed response, and m is the number of demand responses.

[0070] (2) Determine the operating constraint conditions of the user-side energy storage device.

[0071] a. The remaining capacity during the operation of energy storage needs to meet certain constraints. The constraint conditions of the state of charge (SOC) of energy storage at any time are:

[0072] SOC min ≤SOC i ≤SOC max

[0073] b. The constraint conditions for the charging and discharging state of energy storage are:

[0074] 0≤sw ch,t +sw dis,t ≤1

[0075] c. Taking into account the discharge rate of different types of energy storage equipment, excessive current charging and discharging will damage the performance of the equipment and shorten the operating life. Therefore, the energy storage charging and discharging power constraints during operation are:

[0076]

[0077] d. Since the energy storage system can ensure the periodicity of its continuous operation when the stored energy (that is, the state of charge) is consistent at the beginning and end of each scheduling cycle, the continuity constraint condition of the energy storage state of charge is limited to:

[0078]

[0079] Among them, SOC i Is the state of charge of energy storage at time t on day i, SOC min Is the minimum state of charge of energy storage, SOC max Is the maximum state of charge of energy storage, sw dis,t Is the discharge state of the stored energy at the i-th moment (when the value is 1, the stored energy is in the discharged state), sw ch,t Is the charging state of energy storage at the i-th moment (when the value is 1, it means that the energy storage is in the charging state), P rate Is the rated power of the energy storage device on the user side, η c Is the maximum charging efficiency of energy storage, η d Is the maximum discharge efficiency of energy storage, E rate Is the rated capacity of the user-side energy storage device, and Δt is the time interval between charging and discharging the energy storage.

[0080] The obtaining module 202 is configured to obtain the maximum power load of the user side in the previous year, and determine the demand side response baseline based on the maximum power load;

[0081] The specific implementation process includes: firstly setting the constraint conditions of the demand-side response baseline as:

[0082]

[0083] Among them, i is the time period during which the user participates in the demand side response, j is the sampling period of the demand side response baseline, P year,max The maximum load value of the year on the user side;

[0084] Secondly, the background monitoring center collects the user's historical power consumption data in the previous year at a sampling interval of 15 minutes, and filters and outputs the user's annual maximum load value in the previous year to limit the demand-side response baseline ; Finally, using the selected user-side response day as a benchmark, the load curve of the user-side response day 5 days before the user-side response day is defined as the demand-side response baseline.

[0085] The optimization module 203 is configured to use the demand-side response baseline as the evaluation criterion, import relevant parameters of the user-side energy storage device into the user-side energy storage economic optimization model, and combine the mixed integer linear programming algorithm to find the user's optimum Report demand response power.

[0086] The specific implementation process includes: (1) Initializing the mixed integer linear programming algorithm, that is, reading the simulation duration, scheduling period, historical load curve on the power consumption side, and relevant parameters of the energy storage device on the user side; The electrical side historical load curve is divided into 200 populations according to similar characteristics, and each individual in each population includes information on energy storage capacity, energy storage rated power and annual load peak reduction rate; (3) Call the hybrid The integer linear programming algorithm obtains the optimal charge-discharge curve and monthly load cut rate of each individual in all populations during the simulation period during the dispatch period, and combines the corresponding energy storage capacity, energy storage rated power and annual load cut. The peak rate calculates the objective function value corresponding to each individual in all the populations and the period of participation in the demand-side response; (3) The technical staff conducts statistical analysis based on the total electricity bills paid by all populations in each month in the past two years, Each population sets a minimum paid-in fee interval, and judges whether the objective function value corresponding to each individual falls within the corresponding lowest-paid fee interval; (4) Based on individuals whose objective function value falls within the corresponding lowest-paid fee interval , In conjunction with the demand-side response baseline, obtain the optimal reported demand response power of the individual in the corresponding participating demand-side response period; respond to the individual whose objective function value does not fall within the corresponding minimum paid-in fee interval Exception registration.

[0087] In the embodiment of the present invention, the demand side response baseline is set by calling and analyzing the historical power consumption data of the user side, and the response of the user side energy storage economy optimization model to the effective demand is assisted based on the gap between the baseline load and the response daily load The evaluation of energy storage on the user side can improve the economic benefits of the user-side energy storage in responding to the electricity price policy and participating in the incentive demand-side response, which has a certain promotion and application value.

[0088] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above-mentioned embodiments can be completed by a program instructing relevant hardware. The program can be stored in a computer-readable storage medium, and the storage medium can include: Read Only Memory (ROM, Read Only Memory), Random Access Memory (RAM, Random Access Memory), magnetic disk or optical disk, etc.