A method and device for configuring energy storage capacity of a light storage power station

Abstract

The application provides a kind of light storage power station energy storage capacity configuration method and device, obtain the output power of photovoltaic system and the actual load of power system;The output power of photovoltaic system and the actual load of power system are input into the energy storage capacity configuration model constructed in advance, and the linear programming method is used to solve the energy storage capacity configuration model, and the configuration capacity of energy storage system is obtained;Energy storage capacity configuration model is based on the expected and confidence capacity of the climbing light abandonment amount of light storage power station, the application helps to improve the efficient use of energy storage in the process of automatic generation control frequency modulation of light storage power station, and considers the dynamic climbing reliability of light storage power station, helps to reduce the light abandonment amount caused by climbing event of light storage power station through energy storage system, improves the effective load capacity of light storage power station through energy storage, helps to provide the energy storage capacity configuration demand of light storage power station when facing different light storage power station energy storage configuration demand difference, provides the basis for energy storage configuration of light storage power station.

Description

Technical Field

[0001] The present invention relates to the field of renewable energy power generation technology, and in particular to a method and device for configuring energy storage capacity of a photovoltaic power station. Background Art

[0002] In recent years, the photovoltaic power generation industry has developed rapidly, with PV penetration rates increasing. As PV power generation capacity increases, the short-term randomness and volatility of its output lead to significant variations in the ramp rate of PV power generation, which can easily lead to curtailment. This can also negatively impact frequency fluctuations and operational reliability of the power system. Energy storage, with its advantages of fast response and bidirectional regulation, has become an important means of addressing the large, random fluctuations in PV power. Through appropriate energy storage charging and discharging strategies, it can smooth the ramp rate of PV-storage power stations and reduce the resulting curtailment. Therefore, addressing the curtailment caused by the ramp rate of PV-storage power stations, quantifying the dynamic ramping reliability of PV-storage power stations and reducing the amount of curtailment caused by the ramp rate are key issues in PV-storage power station energy storage configuration. While also considering the impact of energy storage charging and discharging on frequency stability and the confidence level of the PV-storage power station, optimizing energy storage configuration and utilizing limited storage capacity to smooth photovoltaic fluctuations will be a key approach to ensuring the safety and stability of PV-storage power stations.

[0003] In the existing technology, the optimal configuration of energy storage for photovoltaic power stations is generally achieved by analyzing the effect of energy storage on smoothing photovoltaic ramp fluctuations during the operation of the photovoltaic power station, formulating a charging and discharging strategy for energy storage operation in the photovoltaic power station, and establishing a battery life quantification model based on the cycle life curve. Finally, the energy storage capacity is determined with the goal of minimizing the average annual cost. Although the confidence capacity of the photovoltaic power station can be optimized, the resulting photovoltaic power station has low ramp reliability and confidence capacity. Summary of the Invention

[0004] In order to overcome the shortcomings of the above-mentioned prior art photovoltaic power stations with low climbing reliability and confidence capacity, the present invention provides a method and device for configuring the energy storage capacity of a photovoltaic power station with storage capacity. The output power of the photovoltaic system and the actual load of the power system are input into a pre-constructed energy storage capacity configuration model, and the linear programming method is used to solve the energy storage capacity configuration model to obtain the configuration capacity of the energy storage system. The energy storage capacity configuration model is constructed based on the expected climbing and abandoned light amount and confidence capacity of the photovoltaic power station. Not only does it take into account the climbing reliability of the photovoltaic power station based on the expected climbing and abandoned light amount, but the confidence capacity of the photovoltaic power station obtained is also relatively high.

[0005] In order to achieve the above-mentioned object of the invention, the present invention adopts the following technical solutions:

[0006] In one aspect, the present invention provides a method for configuring energy storage capacity of a photovoltaic power station, wherein the photovoltaic power station includes a photovoltaic system and an energy storage system. The method includes:

[0007] Obtain the output power of the photovoltaic system and the actual load of the power system;

[0008] The output power of the photovoltaic system and the actual load of the power system are input into the pre-built energy storage capacity configuration model, and the energy storage capacity configuration model is solved using the linear programming method to obtain the configuration capacity of the energy storage system;

[0009] The energy storage capacity configuration model is constructed based on the expected amount of ramping and curtailment of the photovoltaic power station and the confidence capacity.

[0010] The construction of the energy storage capacity configuration model includes:

[0011] The constraints on the confidence capacity of the photovoltaic power station and the actual load of the power system are determined based on the output power of the photovoltaic system and the actual load of the power system. The constraints on the expected amount of curtailed solar power generated by the photovoltaic power station and the output power of the photovoltaic system are also determined based on the output power of the photovoltaic system.

[0012] Determine the constraints satisfied by the configuration capacity of the photovoltaic power station and the constraints satisfied by the automatic generation control demand capacity of the power system;

[0013] And determine the objective function of the energy storage capacity configuration model.

[0014] The constraints that are expected to be met by the amount of curtailed solar power in a PV-storage power station are determined based on the output power of the PV system, including:

[0015] Determine the constraints on the amount of abandoned light in a ramp-up event at a PV power station based on the output power of the PV system;

[0016] The constraint conditions that the amount of abandoned light in the ramping event of the photovoltaic power station is expected to meet are determined based on the constraint conditions that the amount of abandoned light in the ramping event of the photovoltaic power station meets.

[0017] The constraints that the confidence capacity of the PV-storage power station must meet are determined based on the output power of the PV system and the actual load of the power system, including:

[0018] Determine the reference unit capacity that can be replaced by the photovoltaic power station based on the output power of the photovoltaic system and the actual load of the power system;

[0019] The constraints satisfied by the confidence capacity of the photovoltaic power station with storage are determined based on the replaceable reference unit capacity of the photovoltaic power station with storage.

[0020] The objective function is determined as follows:

[0021] minf=ε1Q λ -ε2Q PV +ε3Q AGC +ε4Q ESS

[0022] Where, f is the energy storage configuration objective function of the photovoltaic power station; Qλ is the expected amount of curtailed solar power in the solar-storage power station, Q PV is the confidence capacity of the photovoltaic power station, Q AGC is the automatic generation control demand capacity of the power system, Q ESS is the configured capacity of the energy storage system; ε1 is the expected weight coefficient of the amount of ramping curtailment of the photovoltaic and storage power station, ε2 is the weight coefficient of the confidence capacity of the photovoltaic and storage power station, ε3 is the weight coefficient of the required capacity of the automatic power generation control of the power system, and ε4 is the weight coefficient of the configured capacity of the energy storage system, and ε1+ε2+ε3+ε4=1.

[0023] The constraints that the amount of curtailed solar power in the PV-storage power station is expected to meet are as follows:

[0024]

[0025] Where p λ (t) is the probability of a ramp event occurring in the PV power station at time t, E λ (t) is the amount of abandoned light when a ramp-up event occurs in the PV-storage power station at time t, and T is the time period.

[0026] The constraint condition satisfied by the amount of abandoned light in the ramp-up event of the photovoltaic power station is as follows:

[0027] E λ (t) = P PV (t)+P ESS (t)-[λ v Δt+P PV (t-Δt)+P ESS (t-Δt)]

[0028] Where Δt is the time interval, P PV (t) is the output power of the photovoltaic system at time t, P PV (t-Δt) is the output power of the photovoltaic system at time t-Δt, P ESS (t) is the output power of the energy storage system at time t, P ESS (t-Δt) is the output power of the energy storage system at time t-Δt, λ v is the ramp rate limit.

[0029] The constraints satisfied by the confidence capacity of the photovoltaic power station are as follows:

[0030] Q PV =ΔP PV

[0031] Where, ΔP PV is the reference unit capacity that can be replaced by the photovoltaic and storage power station, which is determined by the effective load carrying capacity model.

[0032] The effective load carrying capacity model is as follows:

[0033] R0=R(P G +P PV +P ESS >P L +ΔP L )=R(P G +ΔP PV >P L +ΔP L )=R(P G >P L )

[0034] Where R0 is the initial reliability of the power system, P G is the basic output of conventional units, P PV is the output power of the photovoltaic system, P ESS is the output power of the energy storage system, P L is the actual load of the power system, ΔP L is the newly added load of the power system, and R(·) is the reliability index calculation function.

[0035] The reliability indicators include the power supply failure probability of the photovoltaic power station and the expected power system loss;

[0036] The power supply failure probability of the photovoltaic power station is determined by the following formula:

[0037]

[0038] Where LOLP is the power supply failure probability of the photovoltaic power station, R s is the probability that the PV-storage power station is in state s, and S is the set of PV-storage power station states that cannot meet the supply demand within a given time period;

[0039] The power system loss amount is expected to be determined by the following formula:

[0040]

[0041] Where q s is the amount of electricity required by the power system that cannot meet the supply demand in state s, and T is the time period.

[0042] The constraint condition satisfied by the automatic generation control demand capacity of the power system is as follows:

[0043] Q AGC =max{Z d (t)}

[0044] Where Z d (t) is the load component amplitude of the power system at time t.

[0045] The Z d (t) Satisfy:

[0046] Z d (t) = P d (t)-P fd (t)

[0047] Where, P d (t) is the equivalent load of the photovoltaic power station at time t, P fd (t) is the equivalent load of the photovoltaic power station after stabilization at time t.

[0048] The P d (t), P fd (t) Satisfy:

[0049] P d (t) = P L (t)-[P PV (t)+P ESS (t)]

[0050]

[0051] Where, P L (t) is the actual load of the power system at time t, and M is the rolling time for solving the problem forward or backward.

[0052] The configuration capacity of the energy storage system satisfies the following constraint:

[0053] 0.2Q ESS =Q 额定

[0054] Where Q 额定 is the rated power of the energy storage system, which is determined according to the output power of the energy storage system.

[0055] On the other hand, the present invention also provides a device for configuring energy storage capacity of a photovoltaic power station, wherein the photovoltaic power station includes a photovoltaic system and an energy storage system, and the device includes:

[0056] An acquisition module is used to obtain the output power of the photovoltaic system and the actual load of the power system;

[0057] A solution module is used to input the output power of the photovoltaic system and the actual load of the power system into a pre-built energy storage capacity configuration model, and solve the energy storage capacity configuration model using a linear programming method to obtain the configured capacity of the energy storage system;

[0058] The energy storage capacity configuration model is constructed based on the expected amount of ramping and curtailment of the photovoltaic power station and the confidence capacity.

[0059] Compared with the closest existing technology, the technical solution provided by the present invention has the following beneficial effects:

[0060] In the method for configuring the energy storage capacity of a photovoltaic power station provided by the present invention, the output power of the photovoltaic system and the actual load of the power system are obtained; the output power of the photovoltaic system and the actual load of the power system are input into a pre-constructed energy storage capacity configuration model, and the energy storage capacity configuration model is solved using a linear programming method to obtain the configured capacity of the energy storage system; the energy storage capacity configuration model is constructed based on the expected amount of ramping and abandoned light of the photovoltaic power station and the confidence capacity, and not only takes into account the ramping reliability of the photovoltaic power station based on the expected amount of ramping and abandoned light, but also takes into account the confidence capacity and expected amount of ramping and abandoned light of the photovoltaic power station, and the obtained confidence capacity of the photovoltaic power station is relatively high;

[0061] The present invention takes into account the smoothing effect of the automatic power generation control of the power system on the frequency fluctuation of the photovoltaic power station, which helps to improve the efficient utilization of stored energy by the photovoltaic power station during the automatic power generation control frequency modulation process;

[0062] The present invention takes into account the dynamic ramp reliability of the photovoltaic power station and helps to reduce the amount of abandoned light caused by the ramp events of the photovoltaic power station through the energy storage system;

[0063] The present invention takes into account the confidence capacity of the photovoltaic storage power station, which helps to improve the effective load capacity of the photovoltaic storage power station through energy storage;

[0064] The present invention targets the confidence capacity and expected amount of curtailed solar power during ramping of photovoltaic power stations, the automatic power generation control demand capacity of the power system, and the configuration capacity of the energy storage system. It helps to provide energy storage capacity configuration requirements that adapt to photovoltaic power stations when faced with differences in energy storage configuration requirements of different photovoltaic power stations, and provides a basis for energy storage configuration of photovoltaic power stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 This is a flow chart of a method for configuring energy storage capacity of a photovoltaic power station according to an embodiment of the present invention;

[0066] Figure 2 is a graph showing photovoltaic output and load fluctuations in an embodiment of the present invention;

[0067] Figure 3 This is a diagram of the energy storage charging and discharging strategy in an embodiment of the present invention;

[0068] Figure 4 is a load fluctuation component diagram in an embodiment of the present invention;

[0069] Figure 5 This is an expected distribution diagram of the amount of abandoned solar power in the PV storage power station during ramping in an embodiment of the present invention. DETAILED DESCRIPTION

[0070] The present invention will be described in further detail below with reference to the accompanying drawings.

[0071] Example 1

[0072] Embodiment 1 of the present invention provides a method for configuring the energy storage capacity of a photovoltaic power station. The specific flow chart is as follows: Figure 1 As shown, the photovoltaic power station includes a photovoltaic system and an energy storage system. The specific process is as follows:

[0073] S101: Obtain the output power of the photovoltaic system and the actual load of the power system;

[0074] S102: Inputting the output power of the photovoltaic system and the actual load of the power system into a pre-built energy storage capacity configuration model, and solving the energy storage capacity configuration model using a linear programming method to obtain the configured capacity of the energy storage system;

[0075] The energy storage capacity configuration model is constructed based on the expected amount of ramping and curtailment of the photovoltaic power station and the confidence capacity.

[0076] The higher the dynamic ramp reliability of a PV-storage power station, the greater the confidence capacity, the smaller the automatic generation control capacity required by the power system, and the smaller the configured capacity of the energy storage system, the more beneficial the energy storage configuration results of the PV-storage power station. The construction of the energy storage capacity configuration model includes:

[0077] The constraints on the confidence capacity of the photovoltaic power station and the actual load of the power system are determined based on the output power of the photovoltaic system and the actual load of the power system. The constraints on the expected amount of curtailed solar power generated by the photovoltaic power station and the output power of the photovoltaic system are also determined based on the output power of the photovoltaic system.

[0078] Determine the constraints satisfied by the configuration capacity of the photovoltaic power station and the constraints satisfied by the automatic generation control demand capacity of the power system;

[0079] And determine the objective function of the energy storage capacity configuration model.

[0080] The constraints that are expected to be met by the amount of curtailed solar power in a PV-storage power station are determined based on the output power of the PV system, including:

[0081] Determine the constraints on the amount of abandoned light in a ramp-up event at a PV power station based on the output power of the PV system;

[0082] The constraint conditions that the amount of abandoned light in the ramping event of the photovoltaic power station is expected to meet are determined based on the constraint conditions that the amount of abandoned light in the ramping event of the photovoltaic power station meets.

[0083] The constraints that the confidence capacity of the PV-storage power station must meet are determined based on the output power of the PV system and the actual load of the power system, including:

[0084] Determine the reference unit capacity that can be replaced by the photovoltaic power station based on the output power of the photovoltaic system and the actual load of the power system;

[0085] The constraints satisfied by the confidence capacity of the photovoltaic power station with storage are determined based on the replaceable reference unit capacity of the photovoltaic power station with storage.

[0086] Therefore, the target is determined as follows:

[0087] min f=ε1Q λ -ε2Q PV +ε3Q AGC +ε4Q ESS

[0088] Where, f is the energy storage configuration objective function of the photovoltaic power station; Q λ is the expected amount of curtailed solar power in the solar-storage power station, Q PV is the confidence capacity of the photovoltaic power station, Q AGC is the automatic generation control demand capacity of the power system, Q ESS is the configured capacity of the energy storage system; ε1 is the expected weight coefficient of the amount of ramping curtailment of the photovoltaic and storage power station, ε2 is the weight coefficient of the confidence capacity of the photovoltaic and storage power station, ε3 is the weight coefficient of the required capacity of the automatic power generation control of the power system, and ε4 is the weight coefficient of the configured capacity of the energy storage system, ε1+ε2+ε3+ε4=1.

[0089] When the ramp rate of the solar power station When the ramp rate is higher than the ramp rate limit, a ramp event occurs in the PV-storage power station, and it is necessary to smooth out or "abandon light". The dynamic ramp reliability of the PV-storage power station is quantified by the expected amount of ramp abandonment of the PV-storage power station, Q λ The smaller it is, the higher the dynamic ramp reliability of the PV-storage power station is. The constraints that the PV-storage power station is expected to meet in terms of the amount of curtailed light during ramping are as follows:

[0090]

[0091] Where p λ (t) is the probability of a ramp event occurring in the PV power station at time t, E λ (t) is the amount of abandoned light when a ramp-up event occurs in the PV-storage power station at time t, and T is the time period.

[0092] The constraints on the amount of abandoned light in a ramp-up event at a PV-storage power station are as follows:

[0093] E λ (t) = P PV (t)+P ESS (t)-[λ v Δt+P PV (t-Δt)+P ESS (t-Δt)]

[0094] Where Δt is the time interval, P PV (t) is the output power of the photovoltaic system at time t, P PV(t-Δt) is the output power of the photovoltaic system at time t-Δt, P ESS (t) is the output power of the energy storage system at time t, P ESS When (t) is positive, it means the energy storage system is discharging, P ESS When (t) is negative, it means the energy storage system is charging; ESS (t-Δt) is the output power of the energy storage system at time t-Δt, λ v is the ramp rate limit.

[0095] The constraints satisfied by the confidence capacity of the photovoltaic power station are as follows:

[0096] Q PV =ΔP PV

[0097] Where, ΔP PV is the reference unit capacity that can be replaced by the photovoltaic and storage power station, which is determined by the effective load carrying capacity model.

[0098] Considering the role of the photovoltaic power station's power generation capacity in improving the power system's ability to bear additional load, while maintaining the reliability level of the photovoltaic power station, the effective load carrying capacity model (ELCC) is as follows:

[0099] R0=R(P G +P PV +P ESS >P L +ΔP L )=R(P G +ΔP PV >P L +ΔP L )=R(P G >P L )

[0100] Where R0 is the initial reliability of the power system, P G is the basic output of conventional units, P PV is the output power of the photovoltaic system, P ESS is the output power of the energy storage system, P L is the actual load of the power system, ΔP L is the newly added load of the power system, and R(·) is the reliability index calculation function.

[0101] Reliability indicators include the probability of power supply failure of the PV-storage power station and the expected amount of power loss in the power system;

[0102] The power supply failure probability of a photovoltaic power station is determined by the following formula:

[0103]

[0104] Where LOLP is the power supply failure probability of the photovoltaic power station, R s is the probability that the PV-storage power station is in state s, and S is the set of PV-storage power station states that cannot meet the supply demand within a given time period;

[0105] The expected amount of power system loss is determined by the following formula:

[0106]

[0107] Where q s is the amount of electricity required by the power system that cannot meet the supply demand in state s, and T is the time period.

[0108] The constraints that the automatic generation control demand capacity of the power system must meet are as follows:

[0109] Q AGC =max{Z d (t)}

[0110] Where Z d (t) is the load component amplitude of the power system at time t, Z d (t) Satisfy:

[0111] Z d (t) = P d (t)-P fd (t)

[0112] Where, P d (t) is the equivalent load of the photovoltaic power station at time t, P fd (t) is the equivalent load of the photovoltaic power station after stabilization at time t,

[0113] Z d (t) can be further expressed as Z d (t) = P L -(P PV +P ESS )-P fd (t), it can be seen that the relationship between the automatic power generation control demand capacity and the energy storage capacity is: energy storage in the photovoltaic power station can effectively reduce the demand for the automatic power generation control demand capacity of the power system. As the configuration capacity of the energy storage system increases, the automatic power generation control demand capacity of the power system gradually decreases.

[0114] P fd (t) is separated by rolling average method d (t) get, P d (t), P fd (t) Satisfy:

[0115] Pd (t) = P L (t)-[P PV (t)+P ESS (t)]

[0116]

[0117] Where, P L (t) is the actual load of the power system at time t, 2M is the solution time domain of the rolling average, and M is the rolling time length of the solution forward or backward.

[0118] The configuration capacity of the energy storage system must meet the following constraints:

[0119] 0.2Q ESS =Q 额定

[0120] Where Q 额定 is the rated power of the energy storage system, which is determined according to the output power of the energy storage system.

[0121] Example 2

[0122] Based on the same inventive concept, embodiment 2 of the present invention further provides a device for configuring the energy storage capacity of a photovoltaic power station. The photovoltaic power station includes a photovoltaic system and an energy storage system. The functions of each component are described in detail below:

[0123] An acquisition module is used to obtain the output power of the photovoltaic system and the actual load of the power system;

[0124] A solution module is used to input the output power of the photovoltaic system and the actual load of the power system into a pre-built energy storage capacity configuration model, and solve the energy storage capacity configuration model using a linear programming method to obtain the configured capacity of the energy storage system;

[0125] The energy storage capacity configuration model is constructed based on the expected amount of ramping and curtailment of the photovoltaic power station and the confidence capacity.

[0126] The device also includes a modeling module, which includes:

[0127] A first determining unit is configured to determine a constraint condition satisfied by the confidence capacity of the photovoltaic power station based on the output power of the photovoltaic system and the actual load of the power system, and to determine a constraint condition satisfied by the amount of ramping curtailment of the photovoltaic power station based on the output power of the photovoltaic system;

[0128] a second determining unit, configured to respectively determine the constraint conditions satisfied by the configuration capacity of the energy storage system and the constraint conditions satisfied by the automatic generation control demand capacity of the power system;

[0129] The third determining unit is used to determine the objective function of the energy storage capacity configuration model.

[0130] The first determining unit is specifically configured to:

[0131] Determine the constraints on the amount of abandoned light in a ramp-up event at a PV power station based on the output power of the PV system;

[0132] The constraint conditions that the amount of abandoned light in the ramping event of the photovoltaic power station is expected to meet are determined based on the constraint conditions that the amount of abandoned light in the ramping event of the photovoltaic power station meets.

[0133] The first determining unit is further specifically configured to:

[0134] Determine the reference unit capacity that can be replaced by the photovoltaic power station based on the output power of the photovoltaic system and the actual load of the power system;

[0135] The constraints satisfied by the confidence capacity of the photovoltaic power station with storage are determined based on the replaceable reference unit capacity of the photovoltaic power station with storage.

[0136] The third determination unit determines the objective function as follows:

[0137] min f=ε1Q λ -ε2Q PV +ε3Q AGC +ε4Q ESS

[0138] Where, f is the energy storage configuration objective function of the photovoltaic power station; Q λ is the expected amount of curtailed solar power in the solar-storage power station, Q PV is the confidence capacity of the photovoltaic power station, Q AGC is the automatic generation control demand capacity of the power system, Q ESS is the configured capacity of the energy storage system; ε1 is the expected weight coefficient of the amount of curtailed solar power in the PV-storage power station, ε2 is the weight coefficient of the confidence capacity of the PV-storage power station, ε3 is the weight coefficient of the required capacity of the automatic generation control of the power system, and ε4 is the weight coefficient of the configured capacity of the energy storage system, ε1+ε2+ε3+ε4=1;

[0139] The constraint condition that the amount of curtailed solar power in the PV-storage power station determined by the first determination unit is expected to satisfy is as follows:

[0140]

[0141] Where p λ (t) is the probability of a ramp event occurring in the PV power station at time t, E λ (t) is the amount of abandoned light when the solar-storage power station experiences a ramp-up event at time t, and T is the time period; λ (t) Satisfy:

[0142] E λ (t) = P PV (t)+PESS (t)-[λ v Δt+P PV (t-Δt)+P ESS (t-Δt)]

[0143] Where Δt is the time interval, P PV (t) is the output power of the photovoltaic system at time t, P PV (t-Δt) is the output power of the photovoltaic system at time t-Δt, P ESS (t) is the output power of the energy storage system at time t, P ESS (t-Δt) is the output power of the energy storage system at time t-Δt, λ v is the climbing rate limit;

[0144] The constraint condition satisfied by the confidence capacity of the photovoltaic power station determined by the first determination unit is as follows:

[0145] Q PV =ΔP PV

[0146] Where, ΔP PV is the replaceable reference unit capacity of the photovoltaic power station with energy storage, which is determined by the effective load carrying capacity model; the effective load carrying capacity model is as follows:

[0147] R0=R(P G +P PV +P ESS >P L +ΔP L )=R(P G +ΔP PV >P L +ΔP L )=R(P G >P L )

[0148] Where R0 is the initial reliability of the power system, P G is the basic output of conventional units, P PV is the output power of the photovoltaic system, P ESS is the output power of the energy storage system, P L is the actual load of the power system, ΔP L is the newly added load of the power system, R(·) is the reliability index calculation function; the reliability index includes the power supply failure probability of the photovoltaic power station and the expected power loss of the power system;

[0149] The power supply failure probability of a photovoltaic power station is determined by the following formula:

[0150]

[0151] Where LOLP is the power supply failure probability of the photovoltaic power station, R s is the probability that the PV-storage power station is in state s, and S is the set of PV-storage power station states that cannot meet the supply demand within a given time period;

[0152] The expected amount of power system loss is determined by the following formula:

[0153]

[0154] Where q s is the power system demand that cannot meet the supply demand in state s, and T is the time period;

[0155] The constraint condition satisfied by the automatic power generation control demand capacity of the power system determined by the second determination unit is as follows:

[0156] Q AGC =max{Z d (t)}

[0157] Where Z d (t) is the load component amplitude of the power system at time t, and Z d (t) Satisfy:

[0158] Z d (t) = P d (t)-P fd (t)

[0159] Where, P d (t) is the equivalent load of the photovoltaic power station at time t, P fd (t) is the equivalent load of the photovoltaic power station after stabilization at time t; d (t), P fd (t) Satisfy:

[0160] P d (t) = P L (t)-[P PV (t)+P ESS (t)]

[0161]

[0162] Where, P L (t) is the actual load of the power system at time t, M is the rolling time for solving the problem forward or backward;

[0163] The constraint condition satisfied by the configuration capacity of the energy storage system determined by the second determination unit is as follows:

[0164] 0.2Q ESS =Q 额定

[0165] Where Q 额定 is the rated power of the energy storage system, which is determined according to the output power of the energy storage system.

[0166] Example 3

[0167] Example 3 of the present invention takes the actual scenario of a photovoltaic power station as an example, and the photovoltaic output and load fluctuation curve is as follows: Figure 2 As shown. In Example 3, the photovoltaic power station has two ramp-up events in one day, the probability of the ramp-up event is 0.0833333, the photovoltaic power station has two power supply failures in one year, Rs is 0.0002283105022, ε1, ε2, ε3 and ε4 are 0.6, 0.1, 0.2 and 0.1 respectively, and it focuses more on reducing the capacity required for automatic power generation control. After the photovoltaic power station is configured with energy storage, the energy storage configuration capacity is 152.532kWh. The charging and discharging strategy on a typical day is as follows Figure 3 As shown in Figure 1, the photovoltaic system is discharged when there is no power output and charged when there is power output. The state of charge remains consistent at the beginning and end of the day, which is convenient for scheduling. The required capacity for automatic power generation control of the power system is 8341.820kW, and its load fluctuation component is as follows: Figure 4 The expected amount of curtailed solar power during ramping is 4671.329 kWh, and its dynamic distribution is as follows: Figure 5 As shown. The confidence capacity of the photovoltaic power station is 4929.151kW. For the same photovoltaic power station, before adopting the energy storage configuration method provided by Example 3 of the present invention, its expected ramping curtailment amount is 4688.498kWh, the required capacity for automatic power generation control is 8348.362kW, and the confidence capacity is 4817.650kW. Compared with the results after adopting the photovoltaic power station energy storage configuration method provided by Example 3, the method provided by Example 3 of the present invention reduces the expected ramping curtailment amount of the photovoltaic power station through the smoothing effect of the photovoltaic power station energy storage on the ramp rate, and improves the dynamic ramping reliability; the required capacity for automatic power generation control is reduced, and the role of photovoltaic power station energy storage in frequency stability is fully utilized. The confidence capacity of the photovoltaic power station is increased, and the effective load capacity of the photovoltaic power station is improved through the energy storage system. In addition, when faced with different preferences of different photovoltaic power stations for the dynamic ramping reliability, confidence capacity, required capacity for automatic power generation control, and energy storage configuration capacity of the photovoltaic power station, the method provided by Example 3 of the present invention can be used to adjust the sizes of the weight coefficients ε1, ε2, ε3, and ε4.

[0168] For the convenience of description, the various parts of the above-mentioned device are divided into various modules or units according to their functions and described separately. Of course, when implementing this application, the functions of each module or unit can be implemented in the same or multiple software or hardware.

[0169] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0170] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0171] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0172] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0173] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Ordinary technicians in the relevant field can still modify or replace the specific implementation methods of the present invention with equivalents by referring to the above embodiments. Any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention are within the scope of protection of the claims of the present invention to be approved.

Claims

1. A method for configuring energy storage capacity of a photovoltaic power station, wherein the photovoltaic power station includes a photovoltaic system and an energy storage system, characterized in that: The method comprises: Obtain the output power of the photovoltaic system and the actual load of the power system; The output power of the photovoltaic system and the actual load of the power system are input into the pre-built energy storage capacity configuration model, and the energy storage capacity configuration model is solved using the linear programming method to obtain the configuration capacity of the energy storage system; The energy storage capacity configuration model is constructed based on the expected amount of curtailed solar power and the confidence capacity of the solar storage power station; The construction of the energy storage capacity configuration model includes: The constraints on the confidence capacity of the photovoltaic power station and the actual load of the power system are determined based on the output power of the photovoltaic system and the actual load of the power system. The constraints on the expected amount of curtailed solar power generated by the photovoltaic power station and the output power of the photovoltaic system are also determined based on the output power of the photovoltaic system. Determine the constraints satisfied by the configuration capacity of the photovoltaic power station and the constraints satisfied by the automatic generation control demand capacity of the power system; and determine the objective function of the energy storage capacity configuration model; The constraint conditions that are expected to be satisfied by determining the amount of curtailed solar power in the PV power station based on the output power of the PV system include: Determine the constraints on the amount of abandoned light in a ramp-up event at a PV power station based on the output power of the PV system; Determine the constraints that the amount of abandoned solar power in the ramping event of the solar power storage station is expected to meet based on the constraints that the amount of abandoned solar power in the ramping event of the solar power storage station meets; The constraint conditions satisfied by determining the confidence capacity of the photovoltaic power station based on the output power of the photovoltaic system and the actual load of the power system include: Determine the reference unit capacity that can be replaced by the photovoltaic power station based on the output power of the photovoltaic system and the actual load of the power system; Determine the constraints satisfied by the confidence capacity of the PV-storage power station based on the replaceable reference unit capacity of the PV-storage power station; The objective function is determined as follows: minf=ε1Q λ -ε2Q PV +ε3Q AGC +ε4Q ESS Where, f is the energy storage configuration objective function of the photovoltaic power station; Q λ is the expected amount of curtailed solar power in the solar-storage power station, Q PV is the confidence capacity of the photovoltaic power station; Q AGC The required capacity for automatic power generation control of the power system; Q ESS is the configured capacity of the photovoltaic and storage power station; ε1 is the expected weight coefficient of the amount of ramping and curtailment of the photovoltaic and storage power station, ε2 is the weight coefficient of the confidence capacity of the photovoltaic and storage power station, ε3 is the weight coefficient of the required capacity of the automatic power generation control of the power system, and ε4 is the weight coefficient of the configured capacity of the photovoltaic and storage power station, and ε1+ε2+ε3+ε4=1.

2. The method for configuring the energy storage capacity of a photovoltaic power station according to claim 1, characterized in that: The constraints that the amount of curtailed solar power in the PV-storage power station is expected to meet are as follows: Where p λ (t) is the probability of a ramp event occurring in the PV power station at time t, E λ (t) is the amount of abandoned light when a ramp-up event occurs in the PV-storage power station at time t, and T is the time period.

3. The method for configuring the energy storage capacity of a photovoltaic power station according to claim 1, characterized in that: The constraint condition satisfied by the amount of abandoned light in the ramp-up event of the photovoltaic power station is as follows: From λ (t)=P PV (t)+P ESS (t)-[λ v Δt+P PV (t-Δt)+P ESS (t-Δt)] Where Δt is the time interval, P PV (t) is the output power of the photovoltaic system at time t, P PV (t-Δt) is the output power of the photovoltaic system at time t-Δt, P ESS (t) is the output power of the energy storage system at time t, P ESS (t-Δt) is the output power of the energy storage system at time t-Δt, λ v is the ramp rate limit.

4. The method for configuring the energy storage capacity of a photovoltaic power station according to claim 1, characterized in that: The constraints satisfied by the confidence capacity of the photovoltaic power station are as follows: Q PV =ΔP PV Where, ΔP PV is the reference unit capacity that can be replaced by the photovoltaic and storage power station, which is determined by the effective load carrying capacity model.

5. The method for configuring the energy storage capacity of a photovoltaic power station according to claim 4, characterized in that: The effective load carrying capacity model is as follows: R0=R(P G +P PV +P ESS >P L +ΔP L )=R(P G +ΔP PV >P L +ΔP L )=R(P G >P L ) Where R0 is the initial reliability of the power system, P G is the output of conventional units, P PV is the output power of the photovoltaic system, P ESS is the output power of the energy storage system, P L is the actual load of the power system, ΔP L is the newly added load of the power system, and R(·) is the reliability index calculation function.

6. The method for configuring the energy storage capacity of a photovoltaic power station according to claim 5, characterized in that: The reliability indicators include the power supply failure probability of the photovoltaic power station and the expected power system loss; The power supply failure probability of the photovoltaic power station is determined by the following formula: Where LOLP is the power supply failure probability of the photovoltaic power station, R s is the probability that the PV-storage power station is in state s, and S is the set of PV-storage power station states that cannot meet the supply demand within a given time period; The power system loss amount is expected to be determined by the following formula: Where q s is the amount of electricity required by the power system that cannot meet the supply demand in state s, and T is the time period.

7. The method for configuring the energy storage capacity of a photovoltaic power station according to claim 1, characterized in that: The constraint condition satisfied by the automatic generation control demand capacity of the power system is as follows: Q AGC =max{Z d (t)} Where Z d (t) is the load component amplitude of the power system at time t.

8. The method for configuring the energy storage capacity of a photovoltaic power station according to claim 7, characterized in that: The Z d (t) Satisfy: Z d (t)=P d (t)-P fd (t) Where, P d (t) is the equivalent load of the photovoltaic power station at time t, P fd (t) is the equivalent load of the photovoltaic power station after stabilization at time t.

9. The method for configuring the energy storage capacity of a photovoltaic power station according to claim 8, characterized in that: The P d (t), P fd (t) Satisfy: P d (t)=P L (t)-[P PV (t)+P ESS (t)] Where, P L (t) is the actual load of the power system at time t, and M is the rolling time for solving the problem forward or backward.

10. The method for configuring energy storage capacity of a photovoltaic power station according to claim 1, characterized in that: The configuration capacity of the energy storage system satisfies the following constraint: 0.2Q ESS =Q 额定 Where Q 额定 is the rated power of the energy storage system, which is determined according to the output power of the energy storage system.

11. A device for configuring energy storage capacity of a photovoltaic power station, the photovoltaic power station comprising a photovoltaic system and an energy storage system, characterized in that: The device comprises: An acquisition module is used to obtain the output power of the photovoltaic system and the actual load of the power system; A solution module is used to input the output power of the photovoltaic system and the actual load of the power system into a pre-built energy storage capacity configuration model, and solve the energy storage capacity configuration model using a linear programming method to obtain the configured capacity of the energy storage system; The energy storage capacity configuration model is constructed based on the expected amount of curtailed solar power and the confidence capacity of the solar storage power station; The construction of the energy storage capacity configuration model includes: The constraints on the confidence capacity of the photovoltaic power station and the actual load of the power system are determined based on the output power of the photovoltaic system and the actual load of the power system. The constraints on the expected amount of curtailed solar power generated by the photovoltaic power station and the output power of the photovoltaic system are also determined based on the output power of the photovoltaic system. Determine the constraints satisfied by the configuration capacity of the photovoltaic power station and the constraints satisfied by the automatic generation control demand capacity of the power system; and determine the objective function of the energy storage capacity configuration model; The constraint conditions that are expected to be satisfied by determining the amount of curtailed solar power in the PV power station based on the output power of the PV system include: Determine the constraints on the amount of abandoned light in a ramp-up event at a PV power station based on the output power of the PV system; Determine the constraints that the amount of abandoned solar power in the ramping event of the solar power storage station is expected to meet based on the constraints that the amount of abandoned solar power in the ramping event of the solar power storage station meets; The constraint conditions satisfied by determining the confidence capacity of the photovoltaic power station based on the output power of the photovoltaic system and the actual load of the power system include: Determine the reference unit capacity that can be replaced by the photovoltaic power station based on the output power of the photovoltaic system and the actual load of the power system; Determine the constraints satisfied by the confidence capacity of the PV-storage power station based on the replaceable reference unit capacity of the PV-storage power station; The objective function is determined as follows: minf=ε1Q λ -ε2Q PV +ε3Q AGC +ε4Q ESS Where, f is the energy storage configuration objective function of the photovoltaic power station; Q λ is the expected amount of curtailed solar power in the solar-storage power station, Q PV is the confidence capacity of the photovoltaic power station; Q AGC The required capacity for automatic power generation control of the power system; Q ESS is the configured capacity of the photovoltaic and storage power station; ε1 is the expected weight coefficient of the amount of ramping and curtailment of the photovoltaic and storage power station, ε2 is the weight coefficient of the confidence capacity of the photovoltaic and storage power station, ε3 is the weight coefficient of the required capacity of the automatic power generation control of the power system, and ε4 is the weight coefficient of the configured capacity of the photovoltaic and storage power station, and ε1+ε2+ε3+ε4=1.

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