High permeation new energy supports grid voltage dynamic reactive power control system and method

Abstract

The application discloses a kind of high penetration new energy support grid voltage dynamic reactive power control system and method, belong to new energy grid-connected technology field, solve how to eliminate high penetration new energy output disturbance under the condition of grid-connected point voltage fluctuation and over-limit problem, the reactive voltage prediction model of high penetration new energy field station is established by the present application;According to the expression of reactive power that high penetration new energy field station injects into power grid and the expression of grid-connected voltage d-axis component, the state space equation expression of high penetration new energy field station reactive voltage control is established;The prediction model under continuous state is discretized and changed to incremental, and the discrete state space incremental model is obtained;Predict the future 3-step output state of the system, realize rolling optimization control;The reactive voltage control system is described as closed-loop system expression, and the weight coefficient is selected to make the closed-loop system stable operation;The application is suitable for when high penetration new energy is connected to power grid output disturbance, eliminates grid-connected point voltage fluctuation and over-limit problem, facilitates engineering application.

Description

Technical Field

[0001] The present invention belongs to the technical field of grid connection of new energy stations, and in particular relates to a dynamic reactive power control system and method for supporting grid voltage with high-penetration new energy. Background Art

[0002] The transition to clean energy is accelerating, with traditional energy sources like coal and oil gradually being replaced by new energy sources like photovoltaics and wind power. High penetration of new energy and grid-connected operation will become a key feature of the future power generation structure.

[0003] Reactive power-voltage control is a prominent issue faced during the grid integration of high-penetration renewable energy. On the one hand, the output power of photovoltaic and wind farms varies with environmental factors such as location, sunlight intensity, and wind speed. This fluctuation inevitably causes system voltage instability. On the other hand, Gobi and other desert regions in my country are the primary destinations for photovoltaic power generation, and these areas often have low power demand. Therefore, photovoltaic power generation must be transmitted over long distances via high-voltage transmission lines to locations with higher loads. During this transmission process, the inherent uncertainty of sunlight and the long transmission distances can affect the reactive power balance of the system, causing significant fluctuations in the busbar voltage that transmits photovoltaic power, which is detrimental to system voltage stability.

[0004] At the same time, the dynamic reactive power control capabilities within photovoltaic and wind power clusters are weak, and their reactive power output capacity is currently underutilized, increasing the reactive power regulation burden on the connected grid and resulting in poor voltage stability across the entire system. Furthermore, several factors in actual projects complicate the active support control of grid-connected photovoltaic and wind power clusters. These factors include the lack of high / low voltage ride-through capability within photovoltaic and wind power clusters; inappropriate control strategies for reactive power compensation devices, which lack rapid automatic adjustment capabilities and are therefore inefficient; and the fact that most units in photovoltaic and wind power clusters operate at unity power factor, leaving their reactive power underutilized.

[0005] According to current national standards, to ensure the safe and stable operation of high-penetration photovoltaic and wind power clusters connected to the grid, the grid voltage must be maintained within a safe range of 0.9pu to 1.1pu. Therefore, further improving the dynamic reactive power control capabilities of photovoltaic and wind power cluster sites to support the safe and stable operation of grid voltage is an important part of and a necessary condition for building a robust renewable energy power system.

[0006] To sum up, in the context of high-penetration new energy access to traditional power grids, by fully tapping the dynamic reactive power control capabilities of photovoltaic and wind power clusters, supporting the safe and stable operation of grid voltage, using reasonable control strategies, and effectively coordinating existing resources to overcome the adverse effects of high-penetration photovoltaic and wind power cluster access on the power system, it is of great significance to improving the power quality of the power system, ensuring safety, stability and economic operation. Summary of the Invention

[0007] The present invention is used to solve the problem of how to eliminate voltage fluctuation and over-limit at the grid connection point when high-penetration new energy is connected to the grid and output disturbance occurs.

[0008] The present invention solves the above technical problems through the following technical solutions:

[0009] A dynamic reactive power control system for a high-penetration new energy supporting grid voltage comprises: a high-penetration new energy station (1), a collector line equivalent impedance (2), a PLL phase-locked loop (3), an abc / dq converter (4), a power calculation module (5), a droop controller (6), an MPC control module (7), a coordinated distribution control (8), and a grid-side control module (9); the MPC control module (7) comprises: an MPC controller (71) and a first adder (72); the grid-side control module (9) comprises: a first subtractor (911), a first PI controller (912), a second subtractor (913), a second PI controller (914), a third subtractor (915), a second adder (921), a reference current calculation module (922), a fourth subtractor (923), a third PI controller (924), a third adder (925), a dq / abc converter (93), and a PWM phase-shift carrier modulator (94);

[0010] Collect the grid-side three-phase voltage E of the high-penetration new energy station (1) a 、E b 、E c and the three-phase grid current i flowing through the equivalent impedance of the collector line (2) a 、i b 、i c , the grid side three-phase voltage E a 、E b 、E c Input to the PLL phase-locked loop (3) to obtain the phase angle θ and angular frequency ω, and convert the grid-side three-phase voltage E a 、E b 、E c , three-phase current i a 、i b 、i c The phase angle θ is input to the abc / dq converter (4) for Park transformation to obtain the actual d-axis and q-axis voltages E of the synchronous rotating coordinate system.d 、E q and the actual d-axis and q-axis current i d 、i q , output the actual value of reactive power Q through the power calculation module (5) e ;

[0011] The actual value of the PCC grid-connected point voltage U PCC,e Input into the droop controller (6) to obtain △Q1, and at the same time output the actual value of reactive power Q e Actual value of voltage at PCC grid connection point U PCC,e At the same time, △Q2 is input into the MPC controller (71), △Q1 and △Q2 are added together by the first adder (72) to obtain △Q, and △Q is used to distribute the reactive capacity between the n photovoltaic units in the station through the coordinated distribution control (8) to obtain the reactive capacity △Q generated by the n-th new energy station. n The grid-level dispatching reactive power reference value Q ref The output reactive power command value Q is generated by adding the second adder (921) m , output reactive power command value Q m Input into the reference current calculation module (922) to obtain the q-axis current instruction i of the synchronous rotating coordinate system q,ref At the same time, the DC bus voltage reference instruction U dc,ref With the actual value U dc The d-axis current instruction i of the synchronous rotating coordinate system is obtained by performing a difference through the first subtractor (911) and then negatively feeding back to the first PI controller (912). d,ref , thereby achieving outer loop control of DC voltage and reactive power within high-penetration new energy stations;

[0012] The actual d-axis and q-axis currents i of the synchronous rotating coordinate system are d 、i q The d-axis and q-axis current instructions i of the synchronous rotating coordinate system d,ref 、i q,ref After the corresponding difference is made through the second subtractor (913) and the fourth subtractor (923), the negative feedback is respectively given to the second PI controller (914) and the third PI controller (924), and the actual d-axis and q-axis currents i of the synchronous rotating coordinate system are simultaneously converted into d 、i q Multiplying by ωL gives ωLi d ωLi q ωLi q The actual d-axis voltage E of the synchronously rotating coordinate system d After being subtracted by the third subtractor (915), the output is added to the output of the second PI controller (914) to obtain the d-axis reference voltage value E of the synchronous rotating coordinate system.d,ref ωLi d The actual q-axis voltage E of the synchronously rotating coordinate system q After being added by the third adder (925), the output of the third PI controller (924) is added to obtain the q-axis reference voltage value E of the synchronous rotating coordinate system. q,ref ; through ωLi q With ωLi d dq decoupling and E d 、E q Feedforward compensation realizes the internal current inner loop control of high-penetration new energy stations;

[0013] Finally, the d-axis and q-axis reference voltage values ​​E of the synchronous rotating coordinate system are d,ref 、E q,ref , input to the dq / abc converter (93), and after Park inverse transformation, the three-phase voltage reference value E is obtained. a,ref 、E b,ref 、E c,ref , and then input into the PWM phase-shift carrier modulator (94) to generate a PWM wave, thereby controlling the high-penetration new energy station (1) with multiple machines connected in parallel.

[0014] A control method for a dynamic reactive power control system applied to the above-mentioned high-penetration renewable energy-supported grid voltage includes the following steps:

[0015] S1. Establish a reactive power and voltage prediction model for high-penetration renewable energy stations. Based on the expression of the reactive power injected into the grid by the high-penetration renewable energy stations and the expression of the d-axis component of the grid-connected voltage, establish the state-space equation expression for reactive power and voltage control of the high-penetration renewable energy stations. Discretize the continuous state prediction model and convert it into an incremental model to obtain a discrete state-space incremental model.

[0016] S2. At time k, measure and read the current state of the system, predict the output state Y(k+1|k) of the system for the next three steps, obtain the optimal control sequence at time k, and input the first input of the optimal control sequence at time k into the control system; at time k+1, update the current state and feed it back to the control system, re-predict and plan the output state for the next three steps after time k+1, obtain the optimal control sequence at time k+1, and input the first input of the optimal control sequence at time k+1 into the system, thereby realizing rolling optimization control;

[0017] S3. Describe the reactive voltage control system as a closed-loop system expression, and select weight coefficients to ensure stable operation of the closed-loop system. According to the output changes of high-penetration renewable energy stations, absorb or emit corresponding reactive power, thereby supporting the grid-connected voltage to prevent fluctuations and over-limits.

[0018] Furthermore, the formula of the reactive voltage prediction model is:

[0019]

[0020] Among them, U Δ =U ref -U PCC,e is the voltage deviation, U ref is the grid voltage reference value, U PCC,e is the actual value of the grid voltage, is the derivative of the voltage deviation, Q Δ =Q ref -Q e is the reactive power deviation, Q ref is the reactive power reference value, Q e is the reactive power output, is the derivative of reactive deviation; S Qu is the coupling coefficient, f(i dq ) is the nonlinear component related to the current, f(i dq ) is the derivative of .

[0021] Furthermore, the reactive power expression injected into the grid by the high-penetration new energy station is:

[0022]

[0023] The expression of the d-axis component of the grid-connected voltage is:

[0024] U jd =U i +f(i dq )

[0025] Where Z ij ,θ ij is the line impedance and phase angle, U i is the system output voltage of a photovoltaic cluster station, U j is the grid voltage, δ ij The power angle.

[0026] Furthermore, the state space equation expression of reactive power voltage control of the high penetration new energy station is:

[0027]

[0028] In the formula, a, b, and c correspond to different coefficients respectively. Let x(t)=U Δ (t),

[0029] Furthermore, the method of discretizing the continuous state prediction model and changing it to an incremental model to obtain a discrete state space incremental model is as follows:

[0030] Discretize the prediction model in the continuous state, that is:

[0031]

[0032] Where Δt is the controller sampling time;

[0033] Substituting the discretized prediction model into the state space equation expression of reactive power and voltage control of high-penetration new energy stations, we can obtain:

[0034]

[0035] Where k is the time, x(k), u(k), y(k), and d(k) are the state quantity, control input quantity, output quantity, and disturbance quantity, respectively. A = Δt·a+1, B = Δt·b, D = Δt, and C = 1.

[0036] Changing to incremental form, the discrete state space incremental model is obtained as follows:

[0037]

[0038] Among them, Δx(k)=x(k)-x(k-1), Δu(k)=u(k)-u(k-1), Δd(k)=d(k)-d(k-1).

[0039] Furthermore, the expression of the output state Y(k+1|k) of the prediction system in the next three steps is:

[0040] Y(k+1|k)=S x Δx(k)+Iy(k)+S d Δd(k)+S u ΔU(k)

[0041] Among them, the predicted output vector Y(k+1|k)=[y(k+1|k)y(k+2|k)y(k+3|k)] T , predicted input vector ΔU(k)=[Δu(k)Δu(k+1)Δu(k+2)] T ,

[0042] Furthermore, the expression of the optimal control sequence at time k is:

[0043] ΔU(k)=(S u T W u T Wu S u +W Q T W Q ) -1 S u T W u T W u E p (k+1)

[0044] Among them, the weight coefficient W u =diag(q,q,q),q>0; weight coefficient W Q =diag(r, r, r), r>0; E p (k+1)=-[S x Δx(k)+IW u +S d Δd(k)].

[0045] Furthermore, the closed-loop system expression is:

[0046] Δx(k+1)=(A-BK mpc (S x +IC))Δx(k)+RΔζ(k)+(D-BK mpc S d )Δd(k)-BK mpc ICx(k-1)

[0047] Among them, Δζ(k) is the unmeasurable external disturbance, the weight coefficient factor r = 0.1, the weight coefficient factor q = 10000, and the predictive control increment K mpc =

[100] (S u T W u T W u S u +W Q T W Q ) -1 S u T W u T W u , B=10 -3 , C=1, D=1.

[0048] The advantages of the present invention are:

[0049] The technical solution of the present invention adopts the method of joint control of droop control and MPC controller to quickly control reactive voltage. The droop control is based on the reactive power ΔQ1 output by the high penetration new energy station and the grid connection point voltage U PCC,e The droop characteristic of the high-penetration new energy station, on the basis of meeting the reactive power limit range requirements of the high-penetration new energy station, enables the high-penetration new energy station to absorb or emit reactive power ΔQ1, which plays a certain supporting role in the grid connection point voltage, so that the grid connection point voltage can work normally within the allowable working range; however, the reactive voltage droop control strategy has a weak voltage regulation ability. On the basis of droop control, the MPC controller makes full use of the local optimization characteristics of the model predictive control considering the optimal input state in the next few steps to realize reactive voltage optimization control, as well as the rolling optimization characteristics of the model predictive control, to adjust the controller parameters in real time, and to realize fast and accurate control of the voltage under the condition of output disturbance of the high-penetration new energy station; the technical solution of the present invention is suitable for eliminating the voltage fluctuation and over-limit problems of the grid connection point when the high-penetration new energy is connected to the power grid, which is convenient for engineering application. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a structural diagram of a dynamic reactive power control system for supporting grid voltage with high penetration of new energy sources according to the present invention;

[0051] Figure 2 Schematic diagram of reactive power regulation capability of the dynamic reactive power control system for high-penetration renewable energy supporting grid voltage according to the present invention;

[0052] Figure 3 It is a droop curve diagram of the dynamic reactive power control method of the high-penetration new energy supported grid voltage of the present invention;

[0053] Figure 4 This is an equivalent circuit model diagram of the photovoltaic station grid-connected according to the present invention;

[0054] Figure 5 is a flow chart of the reactive voltage control method based on model predictive control of the present invention;

[0055] Figure 6 This is a simulation diagram of a two-region power grid with high penetration of new energy in the present invention;

[0056] Figure 7 This is a comparison diagram of the MPC and constant power control waveforms of the high-penetration new energy two-region power grid of the present invention;

[0057] Figure 8 This is a comparison chart of the dual control effects of the high-penetration new energy two-region power grid droop control plus MPC in the present invention;

[0058] Figure 9 This is a comparison chart of the reactive capacity generated under the control of the two regional power grids with high penetration of new energy in the present invention. DETAILED DESCRIPTION

[0059] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0060] The technical solution of the present invention is further described below with reference to the accompanying drawings and specific embodiments:

[0061] 1. Dynamic reactive power control system for grid voltage supported by high penetration of new energy

[0062] like Figure 1 As shown, the dynamic reactive power control system for high-penetration new energy supporting grid voltage of the present invention comprises: a high-penetration new energy station (1), a collector line equivalent impedance (2), a PLL phase-locked loop (3), an abc / dq converter (4), a power calculation module (5), a droop controller (6), an MPC control module (7), a coordinated distribution control (8), and a grid-side control module (9); the MPC control module (7) comprises: an MPC controller (71) and a first adder (72); the grid-side control module (9) comprises: a first subtractor (911), a first PI controller (912), a second subtractor (913), a second PI controller (914), a third subtractor (915), a second adder (921), a reference current calculation module (922), a fourth subtractor (923), a third PI controller (924), a third adder (925), a dq / abc converter (93), and a PWM phase-shift carrier modulator (94).

[0063] Collect the grid-side three-phase voltage E of the high-penetration new energy station (1) a 、E b 、E c and the three-phase grid current i flowing through the equivalent impedance of the collector line (2) a 、i b 、i c , the grid side three-phase voltage E a 、E b 、E c Input to the PLL phase-locked loop (3) to obtain the phase angle θ and angular frequency ω, and convert the grid-side three-phase voltage E a 、E b 、E c , three-phase current i a 、i b 、i cThe phase angle θ is input to the abc / dq converter (4) for Park transformation to obtain the actual d-axis and q-axis voltages E of the synchronous rotating coordinate system. d 、E q and the actual d-axis and q-axis current i d 、i q , output the actual value of reactive power Q through the power calculation module (5) e , The actual value of the PCC grid-connected point voltage U PCC,e Input into the droop controller (6) to obtain △Q1, and at the same time output the actual value of reactive power Q e Actual value of voltage at PCC grid connection point U PCC,e At the same time, △Q2 is input into the MPC controller (71), △Q1 and △Q2 are added together by the first adder (72) to obtain △Q, and △Q is used to distribute the reactive capacity between the n photovoltaic units in the station through the coordinated distribution control (8) to obtain the reactive capacity △Q of the nth new energy station. n The grid-level dispatching reactive power reference value Q ref The output reactive power command value Q is generated by adding the second adder (921) m , output reactive power command value Q m Input into the reference current calculation module (922) to obtain the q-axis current instruction i of the synchronous rotating coordinate system q,ref , At the same time, the DC bus voltage reference instruction U dc,ref With the actual value U dc The d-axis current instruction i of the synchronous rotating coordinate system is obtained by performing a difference through the first subtractor (911) and then negatively feeding back to the first PI controller (912). d,ref , thereby realizing the outer loop control of DC voltage and reactive power inside high-penetration new energy stations.

[0064] The actual d-axis and q-axis currents i of the synchronous rotating coordinate system are d 、i q The d-axis and q-axis current instructions i of the synchronous rotating coordinate system d,ref 、i q,ref After the corresponding difference is made through the second subtractor (913) and the fourth subtractor (923), the negative feedback is respectively given to the second PI controller (914) and the third PI controller (924), and the actual d-axis and q-axis currents i of the synchronous rotating coordinate system are simultaneously converted into d 、i q Multiplying by ωL gives ωLi d ωLi q ωLi q The actual d-axis voltage E of the synchronously rotating coordinate system dAfter being subtracted by the third subtractor (915), the output is added to the output of the second PI controller (914) to obtain the d-axis reference voltage value E of the synchronous rotating coordinate system. d,ref ωLi d The actual q-axis voltage E of the synchronously rotating coordinate system q After being added by the third adder (925), the output of the third PI controller (924) is added to obtain the q-axis reference voltage value E of the synchronous rotating coordinate system. q,ref ; through ωLi q With ωLi d dq decoupling and E d 、E q The feedforward compensation realizes the internal current inner loop control of high-penetration new energy stations.

[0065] Finally, the d-axis and q-axis reference voltage values ​​E of the synchronous rotating coordinate system are d,ref 、E q,ref , input to the dq / abc converter (93), and after Park inverse transformation, the three-phase voltage reference value E is obtained. a,ref 、E b,ref 、E c,ref , and then input into the PWM phase-shift carrier modulator (94) to generate a PWM wave, thereby controlling the high-penetration new energy station (1) with multiple machines connected in parallel.

[0066] 2. Analysis of reactive power regulation capability and droop control in high-penetration new energy systems

[0067] 2.1 Analysis of reactive power regulation capability

[0068] Taking the study of reactive power and voltage control at photovoltaic stations as an example, the first step is to analyze the reactive power regulation capabilities of the PV station. Due to the stress of power electronic devices, the current tolerance of the aforementioned control structures is generally weak. To prevent the triggering of current limiting control while fully utilizing the maximum available capacity S and its regulation capability of the PV station, the charging and discharging reactive power capabilities of the PV station should meet the reactive power limit of the PV station constrained by the maximum available capacity.

[0069] like Figure 2 As shown, Q m,max is the maximum reactive power output value of the photovoltaic station, P m,max is the maximum active output value of the photovoltaic station, P m is the current active power output value of the photovoltaic station, S is the maximum available capacity of the photovoltaic station, φ max The maximum allowable power factor angle of the photovoltaic station grid-connected standard. The reactive power regulation capability range of the photovoltaic station is the fan-shaped area formed by AOC.

[0070] The maximum reactive power output of a photovoltaic station can be expressed as:

[0071]

[0072] From this, the reactive output regulation range of the photovoltaic station can be obtained, which is expressed as:

[0073] Q m =[-Q m,min ,Q m,max ] (2)

[0074] 2.2 Reactive power voltage droop control

[0075] Comprehensively consider the reactive power limit of photovoltaic stations [-Q m,min , Q m,max ] and the power factor cosφ standard range of [-0.95, 0.95] of the photovoltaic station grid connection point, a reactive power-voltage droop control method based on the grid connection point voltage amplitude is adopted. The control goal of this method is to make the photovoltaic station absorb or emit reactive power ΔQ1 on the basis of meeting the reactive power limit range requirements of the photovoltaic station, thereby playing a certain supporting role in the grid connection point voltage. The specific reactive power-voltage control is as follows Figure 3 shown.

[0076] Depend on Figure 3 It can be seen that when the grid-connected point voltage is within the normal voltage range (0.98, 1.02), the photovoltaic station does not need to provide reactive power; when the grid-connected point voltage is in the left voltage range (0.95, 0.98), the photovoltaic station will send the corresponding reactive power ΔQ1 to U according to the voltage range. PCC,e Adjustment plays a supporting role, thereby increasing the grid connection point voltage; when the grid connection point voltage is in the right voltage range (1.02, 1.05), the photovoltaic station will absorb the corresponding reactive power ΔQ1 according to the voltage range to adjust the grid connection point voltage amplitude U PCC,e Adjustment plays a supporting role, thereby reducing the voltage at the grid connection point. According to the droop characteristics of reactive power and voltage, the reactive power of the photovoltaic station is set as a function expression:

[0077]

[0078] 3. Reactive power and voltage control method for high-penetration renewable energy systems based on model predictive control

[0079] 3.1 Establishment of voltage prediction model

[0080] Take the grid-connected operation of photovoltaic stations as an example. Figure 4 The equivalent output model is shown. Among them, L ij 、R ij are the equivalent inductance and resistance of the grid-connected line of the photovoltaic station, respectively.

[0081] The grid-connected equation is expressed as:

[0082]

[0083] Where U jd 、U jq are the grid-connected voltage components in the synchronous rotating coordinate system; i d 、i q are the grid-connected current components in the synchronous rotating coordinate system; U i is the output voltage of the photovoltaic station; ω is the output angular frequency of the phase-locked loop. According to formula (4), the output voltage of the photovoltaic station and the d-axis component of its grid-connected voltage are not in a simple linear relationship. Therefore, the expression of the d-axis component of the grid-connected voltage is simplified to:

[0084] U jd =U i +f(i dq ) (5)

[0085] Where, f(i dq ) is the nonlinear component related to the current.

[0086] The reactive power injected into the grid by the photovoltaic station can be expressed as:

[0087]

[0088] Where Z ij ,θ ij is the line impedance and phase angle, δ ij is the power angle. Further, near the steady-state operating point (E0, δ0), Equation (6) is expressed as a small signal model:

[0089]

[0090] Where S Qδ 、S Qu is the coupling coefficient; S Qu =U j cos(δ ij +θ ij ) / Z ij Ignoring the influence of power angle, the change in reactive power is positively correlated with the change in voltage.

[0091] Combined with the above analysis, a reactive power voltage prediction model for photovoltaic stations is established:

[0092]

[0093] Where U Δ =U ref -U PCC,e is the voltage deviation, U ref is the grid voltage reference value, U PCC,e is the actual value of the grid voltage, is the derivative of the voltage deviation; Q Δ =Q ref -Q e is the reactive power deviation, Q ref is the reactive power reference value, Q e is the actual value of output reactive power, is the derivative of reactive deviation; is the nonlinear component related to the current f(i dq ) is the derivative of .

[0094] From this, we can get the grid-connected voltage control model of the photovoltaic station:

[0095]

[0096] make x(t)=U Δ (t), The state space equation expression of the reactive power voltage control of the photovoltaic station is:

[0097]

[0098] In the formula, a, b, and c correspond to different coefficients respectively. For the set disturbance, y(t) outputs the response.

[0099] 3.2 Voltage prediction model solution

[0100] First, the prediction model in the continuous state is discretized, that is:

[0101]

[0102] Where Δt is the controller sampling time. Substituting Equation (11) into Equation (10), we can obtain the linear discrete state space model of the system:

[0103]

[0104] Where k is the system time, x(k), u(k), y(k), and d(k) are the state variable, control input variable, output variable, and disturbance variable, respectively; A = Δt·a+1, B = Δt·b, D = Δt, and C = 1.

[0105] All states of the system can be measured. In order to reduce static errors, equation (12) can be changed to an incremental equation as follows:

[0106]

[0107] in,

[0108]

[0109] According to the basic principle of predictive control, the future dynamics of the system are predicted based on formula (13). To this end, the system prediction time domain is set to N p , the control time domain is N c And N c ≤N p In order to derive the prediction equation of the system, the following assumptions need to be made:

[0110] Outside the control time domain, the control quantity remains unchanged, that is, Δu(k+i)=0, i=N c ,N c +1,…N p -1;

[0111] The measurable interference remains unchanged after time k, that is, Δd(k+i)=0, i=1,2,…,N p -1.

[0112] The present invention takes the prediction time domain and the control time domain to be equal and equal to 3, that is, N c =N p =3, then based on the state at time k, the states at time k+1, k+2, and k+3 can be predicted by a recursive method:

[0113]

[0114] Furthermore, predict the controlled output at time k+1, k+2, and k+3:

[0115]

[0116] The prediction output vector and input vector are defined as follows:

[0117]

[0118] Then, the output of the system's 3-step prediction can be calculated by the following prediction equation:

[0119] Y(k+1|k)=S x Δx(k)+Iy(k)+S d Δd(k)+S u ΔU(k) ​​(18)

[0120] Where,

[0121]

[0122] The objective function of the controlled system is defined as:

[0123]

[0124] The first term in (20) reflects the system's ability to track the reference trajectory, where W u Represents the weight of the first term. The second term reflects the control ability of the control quantity change, where W Q Represents the weight of the second item.

[0125] The weight coefficient W u , W Q The matrix is ​​expressed as follows:

[0126]

[0127] Where q and r are weight coefficient factors.

[0128] In order to facilitate the calculation of formula (20), the auxiliary variable λ is defined as:

[0129]

[0130] Then the objective function (20) is simplified to:

[0131] f=λ T λ (23)

[0132] Substituting formula (18) into formula (22) and simplifying it, we can get:

[0133]

[0134] Where:

[0135]

[0136] Substituting equations (24) (24) and (25) into equation (23) (23) yields the extreme value solution:

[0137] Z=(G T G) -1 G T b (26)

[0138] Substituting Equation (25) into Equation (26) yields the solution of the optimal control sequence at time k:

[0139] ΔU(k)=(S u T W u T W u S u +W Q T W Q ) -1 S u T W u T W u Ep (k+1) (27)

[0140] According to the above theory, the control strategy flow chart can be obtained as follows Figure 5 shown.

[0141] 3.3 Control Stability Analysis

[0142] According to the basic principle of model predictive control, the first element of the optimization solution acts on the control system, namely:

[0143] Δu(k)=

[100] ΔU(k)=K mpc E p (k+1) (28)

[0144] Define the predictive control gains:

[0145] K mpc =

[100] (S u T W u T W u S u +W Q T W Q ) -1 S u T W u T W u (29)

[0146] Taking into account some uncertain factors, the controlled system is further described as shown in formula (30):

[0147] Δx(k+1)=A·Δx(k)+B·Δu(k)+D·Δd(k)+R·Δζ(k) (30)

[0148] Where Δζ(k) is the unmeasurable external interference.

[0149] Substituting equations (12) and (25) into equation (28), the expression for closed-loop system predictive control is obtained as follows:

[0150] Δu(k)=-K mpc (S x +IC)Δx(k)-K mpc ICx(k-1)-K mpc S d Δd(k) (31)

[0151] Substituting equation (31) into equation (30), the closed-loop system expression is:

[0152] Δx(k+1)=(A-BK mpc (S x +IC))Δx(k)+RΔζ(k)+(D-BK mpc S d )Δd(k)-BK mpc ICx(k-1)(32)

[0153] Define the intermediate variable η as follows:

[0154] η=A-BK mpc (S x +IC) (33)

[0155] In the present invention B=10 -3 , C = 1, D = 1. According to formula (33), when the absolute value of η is less than 1, the closed-loop system is stable, so r = 0.1, q = 10000.

[0156] Based on the weight coefficients r and q obtained above, the reactive voltage controller based on model prediction can quickly and accurately support the grid connection point voltage under the condition of photovoltaic station output disturbance. The above analysis shows the feasibility and correctness of the controller method designed by the present invention.

[0157] 4. System test simulation

[0158] This embodiment is based on MATLAB / Simulink. Figure 6 The two-region simulation system shown is suitable for a high-penetration new energy active support grid. The new energy power generation system is based on a photovoltaic cluster composed of multiple photovoltaic stations in parallel. The control method uses a dynamic reactive voltage control method based on the combination of droop control and model predictive control. The reactive voltage control target is to support the grid-connected voltage of the photovoltaic station to operate within the allowable range and suppress grid-connected voltage fluctuations and over-limit problems. The specific simulation parameters are shown in Table 1 below.

[0159] Table 1 Simulation parameters

[0160]

[0161] In the two-area simulation model, the conditions are: the output power of the photovoltaic station remains unchanged in a short period of time and is in a power-limited operation state. At simulation t = 5s, the load suddenly increases by 200MVar. The simulation results are shown in the figure below. Figure 7 , Figure 8 , Figure 9 shown.

[0162] Depend on Figure 7It can be seen that: 1) When the photovoltaic station adopts constant power control, when the system increases the load by 200MVar, the system's lowest grid-connected point voltage is lower than 0.88pu, endangering the safe and stable operation of the system; in steady-state conditions, the grid-connected point voltage is stable at 0.961. 2) When the photovoltaic station adopts reactive-voltage MPC control, the reactive capacity will be instantly increased during the transient process to suppress the grid-connected point voltage drop, which has a certain improvement effect. In steady-state conditions, the photovoltaic station will increase a certain amount of reactive capacity to restore the voltage to the reference range.

[0163] Depend on Figure 8 It can be seen that: 1) When the photovoltaic station adopts a droop control strategy based on reactive power and voltage, the voltage setting will control the photovoltaic station to increase the reactive power capacity generated according to the set reactive power-voltage curve to support the regulation of the grid voltage at the grid connection point. The voltage drops as low as 0.9 and stabilizes again after 8 seconds. The voltage is about 0.97 after stabilization. 2) When the droop control plus MPC control strategy is adopted, the voltage drops as low as 0.91, and the transient effect is better. The voltage stabilizes again after 8 seconds, and the voltage is about 0.972 after stabilization.

[0164] Depend on Figure 9 It can be seen that: 1) When the photovoltaic station adopts a droop control strategy based on reactive power and voltage, the photovoltaic station adds 25MVar of reactive capacity to support the regulation of the grid voltage at the grid connection point; 2) When the droop control plus MPC control strategy is adopted, the photovoltaic station adds 30MVar of reactive capacity to support the regulation of the grid voltage at the grid connection point.

[0165] To sum up, the present invention is based on the reactive voltage droop control method, and the proposed photovoltaic station grid-connected voltage improvement method based on model predictive control is suitable for high-penetration new energy active support power grids. It can make the grid-connected voltage operate in a suitable working range, facilitate engineering applications, and achieve ideal control effects.

[0166] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A dynamic reactive power control system for a high-penetration new energy grid voltage, characterized in that: include: High-penetration new energy station (1), collector line equivalent impedance (2), PLL phase-locked loop (3), abc / dq converter (4), power calculation module (5), droop controller (6), MPC control module (7), collaborative distribution control (8), grid-side control module (9); the MPC control module (7) includes: an MPC controller (71), a first adder (72); the grid-side control module (9) includes: a first subtractor (911), a first PI controller (912), a second subtractor (913), a second PI controller (914), a third subtractor (915), a second adder (921), a reference current calculation module (922), a fourth subtractor (923), a third PI controller (924), a third adder (925), a dq / abc converter (93), and a PWM phase-shift carrier modulator (94); Collect the grid-side three-phase voltage E of the high-penetration new energy station (1) a 、E b 、E c and the three-phase grid current i flowing through the equivalent impedance of the collector line (2) a 、i b 、i c , the grid side three-phase voltage E a 、E b 、E c Input to the PLL phase-locked loop (3) to obtain the phase angle θ and angular frequency ω, and convert the grid-side three-phase voltage E a 、E b 、E c , three-phase current i a 、i b 、i c The phase angle θ is input to the abc / dq converter (4) for Park transformation to obtain the actual d-axis and q-axis voltages E of the synchronous rotating coordinate system. d 、E q and the actual d-axis and q-axis current i d 、i q , the actual value of reactive power Q is output through the power calculation module (5) e ; The actual value of the PCC grid-connected point voltage U PCC,e Input into the droop controller (6) to obtain △Q1, and at the same time output the actual value of reactive power Q e Actual value of voltage at PCC grid connection point U PCC,e At the same time, △Q2 is input into the MPC controller (71), △Q1 and △Q2 are added together by the first adder (72) to obtain △Q, and △Q is used to distribute the reactive capacity between the n photovoltaic units in the station through the coordinated distribution control (8), and the reactive capacity △Q generated by the n-th new energy station is obtained. n , △Q n The grid-level dispatching reactive power reference value Q ref The output reactive power command value Q is generated by adding the second adder (921) m , output reactive power command value Q m Input into the reference current calculation module (922) to obtain the q-axis current instruction i of the synchronous rotating coordinate system q,ref At the same time, the DC bus voltage reference instruction U dc,ref With the actual value U dc The d-axis current instruction i of the synchronous rotating coordinate system is obtained by performing a difference through the first subtractor (911) and then negatively feeding back to the first PI controller (912). d,ref , thereby achieving outer loop control of DC voltage and reactive power within high-penetration new energy stations; The actual d-axis and q-axis currents i of the synchronous rotating coordinate system are d 、i q The d-axis and q-axis current instructions i of the synchronous rotating coordinate system d,ref 、i q,ref After the corresponding difference is made through the second subtractor (913) and the fourth subtractor (923), the negative feedback is respectively given to the second PI controller (914) and the third PI controller (924), and the actual d-axis and q-axis currents i of the synchronous rotating coordinate system are simultaneously converted into d 、i q Multiplying by ωL gives ωLi d ωLi q ωLi q The actual d-axis voltage E of the synchronously rotating coordinate system d After being subtracted by the third subtractor (915), the output is added to the output of the second PI controller (914) to obtain the d-axis reference voltage value E of the synchronous rotating coordinate system. d,ref ωLi d The actual q-axis voltage E of the synchronously rotating coordinate system q After being added by the third adder (925), the output of the third PI controller (924) is added to obtain the q-axis reference voltage value E of the synchronous rotating coordinate system. q,ref ; through ωLi q With ωLi d dq decoupling and E d 、E q Feedforward compensation realizes the internal current inner loop control of high-penetration new energy stations; Finally, the d-axis and q-axis reference voltage values ​​E of the synchronous rotating coordinate system are d,ref 、E q,ref , input to the dq / abc converter (93), and after Park inverse transformation, the three-phase voltage reference value E is obtained. a,ref 、E b,ref 、E c,ref , and then input into the PWM phase-shift carrier modulator (94) to generate a PWM wave, thereby controlling the high-penetration new energy station (1) with multiple machines connected in parallel.

2. A control method for a dynamic reactive power control system for a high-penetration new energy-supported grid voltage according to claim 1, characterized in that: The following steps are involved: S1. Establish a reactive power and voltage prediction model for high-penetration renewable energy stations. Based on the expression of reactive power injected into the grid by high-penetration renewable energy stations and the expression of the d-axis component of the grid-connected voltage, establish the state-space equation expression for reactive power and voltage control of high-penetration renewable energy stations. Discretize the continuous state prediction model and change it to incremental form to obtain a discrete state space incremental model; S2. At time k, measure and read the current state of the system, predict the output state Y(k+1|k) of the system for the next three steps, obtain the optimal control sequence at time k, and input the first input of the optimal control sequence at time k into the control system; at time k+1, update the current state and feed it back to the control system, re-predict and plan the output state for the next three steps after time k+1, obtain the optimal control sequence at time k+1, and input the first input of the optimal control sequence at time k+1 into the system, thereby realizing rolling optimization control; S3. Describe the reactive voltage control system as a closed-loop system expression, and select weight coefficients to ensure stable operation of the closed-loop system. According to the output changes of high-penetration renewable energy stations, absorb or emit corresponding reactive power, thereby supporting the grid-connected voltage to prevent fluctuations and over-limits.

3. The control method according to claim 2, characterized in that: The formula of the reactive voltage prediction model is: Among them, U Δ =U ref −U PCC,e is the voltage deviation, U ref is the grid voltage reference value, U PCC,e is the actual value of the grid voltage, is the derivative of the voltage deviation, Q Δ =Q ref −Q e is the reactive power deviation, Q ref is the reactive power reference value, Q e is the reactive power output, is the derivative of reactive deviation; S Qu is the coupling coefficient, f(i dq ) is the nonlinear component related to the current, f(i dq ) is the derivative of .

4. The control method according to claim 3, characterized in that: The reactive power expression of the high-penetration new energy station injected into the power grid is: The expression of the d-axis component of the grid-connected voltage is: Where Z ij 、 ij is the line impedance and phase angle, U i Output voltage of high penetration new energy station system, U j is the grid voltage, δ ij The power angle.

5. The control method according to claim 4, characterized in that: The state space equation expression of reactive power voltage control of the high penetration new energy station is: In the formula, a, b, and c correspond to different coefficients respectively. Let , , , .

6. The control method according to claim 5, characterized in that: The method of discretizing the continuous state prediction model and changing it to an incremental model to obtain a discrete state space incremental model is as follows: Discretize the prediction model in the continuous state, that is: Where Δt is the controller sampling time; Substituting the discretized prediction model into the state space equation expression of reactive power and voltage control of high-penetration new energy stations, we can obtain: Where k is the time, x(k), u(k), y(k), and d(k) are the state quantity, control input quantity, output quantity, and disturbance quantity, respectively. A=Δt·a+1, B=Δt·b, D=Δt, and C=1. Changing to incremental form, the discrete state space incremental model is obtained as follows: in, .

7. The control method according to claim 6, characterized in that: The expression of the output state Y(k+1|k) of the prediction system in the next three steps is: Among them, the predicted output vector , predict the input vector , , , .

8. The control method according to claim 7, characterized in that: The expression of the optimal control sequence at time k is: Among them, the weight coefficient W u =diag(q,q,q),q>0; weight coefficient W Q =diag(r, r, r), r>0; E p (k+1)=-[S x Δx(k)+IW u +S d Δd(k)], q and r are weight coefficient factors.

9. The control method according to claim 8, characterized in that: The closed-loop system expression is: Among them, Δζ(k) is the unmeasurable external disturbance, the weight coefficient factor r=0.1, the weight coefficient factor q=10000, and the predictive control increment , , , , .

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