Low-voltage distributed photovoltaic district source load storage regulation and control method and system

Abstract

The invention discloses a low-voltage distributed photovoltaic district source load storage regulation and control method and system, and the method comprises the steps: building a control architecture of source network load storage of a low-voltage district, and determining the constraint conditions of distributed photovoltaic and energy storage; and based on the control architecture and the constraint condition, controlling the photovoltaic grid-connected power of the low-voltage transformer area through two-stage MPC, including: controlling a user load through a first-stage MPC1 so as to carry out consumption of photovoltaic predicted output; active power and reactive power of energy storage rapid charging and discharging are controlled through the second-stage MPC2, so that the user load offset is finely adjusted, and correction of photovoltaic prediction output errors is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of low-voltage distributed photovoltaic control, and more specifically, to a low-voltage distributed photovoltaic area source-load-storage control method and system. Background Art

[0002] Photovoltaic power generation is random and uncertain. The peak time interval of photovoltaic power generation often does not coincide with the peak time interval of electricity consumption, resulting in an imbalance in power supply and demand. This application aims to solve the complex control problem between power generation and power consumption in low-voltage distributed photovoltaic stations, and proposes a source-load-storage coordinated optimization control method for new power systems, which can effectively improve the low-voltage distributed photovoltaic power consumption level on the station side and reduce the abandonment rate.

[0003] MPC is a model-based finite-time closed-loop optimal multivariable control algorithm. This method is easy to model, has good control effects, strong robustness, and can effectively handle nonlinear, time-varying, and uncertain issues in the system. This predictive control algorithm has been widely used in chemical plants, refineries, and power systems, and combined with intelligent optimization technology, it has a wider range of applications.

[0004] MPC mainly consists of three parts: prediction model, feedback correction and rolling optimization. Applying it to the optimization control between distributed photovoltaics and energy storage has better effect. The algorithm optimizes the predictive control principle as follows: each time sampling, based on the current state of the system and the future state obtained by the prediction model, the optimal control within a limited time is solved online to obtain the control behavior at the current time and the future time. Only the first step of the control strategy is executed. At the next sampling time, based on the new system state and new measurement information, the calculation is repeated from the new current state. Summary of the invention

[0005] The technical solution of the present invention provides a low-voltage distributed photovoltaic area source-load-storage control method and system to solve the problem of how to control the low-voltage distributed photovoltaic area source-load-storage based on two-level model predictive control.

[0006] In order to solve the above problems, the present invention provides a method for regulating source-load-storage in a low-voltage distributed photovoltaic area, the method comprising:

[0007] Establish the control architecture of source, grid, load and storage in low-voltage areas and determine the constraints of distributed photovoltaic and energy storage;

[0008] Based on the control architecture and constraints, the photovoltaic grid-connected power of the low-voltage area is controlled through two-level MPC, including: controlling the user load through the first-level MPC1 to absorb the photovoltaic predicted output;

[0009] The second-level MPC2 controls the active power and reactive power of the energy storage for rapid charging and discharging, so as to fine-tune the user load offset and correct the photovoltaic predicted output error.

[0010] Preferably, the control architecture of the source, grid, load and storage in the low-voltage area is established to determine the constraints of distributed photovoltaic and energy storage, including:

[0011] Limit the slope change of photovoltaic and energy storage power generation to less than 10% per sampling period:

[0012] P Rate (ESS[t]+PV[t])∈[-10%PV max ,+10% PV max ]

[0013] Among them, at time t, ESS[t] is the energy storage power, PV[t] is the total power generation of low-voltage distributed photovoltaic power in the substation, and PV max is the total installed capacity of low-voltage distributed photovoltaic power generation, P Rate (ESS[t]+PV[t]) is the slope change produced by photovoltaic and energy storage power generation.

[0014] Preferably, the control architecture of the source, grid, load and storage in the low-voltage area is established to determine the constraints of distributed photovoltaic and energy storage, including:

[0015] The charge and discharge rate and state of charge of energy storage per minute are limited to:

[0016] ESS[t]∈[ESS min ,ESS max ]

[0017] SoC[t]∈[SoC min ,SoC max ]

[0018] Among them, ESS[t] is the energy storage power at time t, ESS min and ESS max They are the upper and lower limits of energy storage power, SOC min and SOC max is the available domain of SOC, SOC[t] is the state of charge at time t, and ESS total is the maximum capacity of energy storage;

[0019]

[0020] Preferably, the controlling of user loads by the first-level MPC1 to absorb the predicted photovoltaic output includes:

[0021] The first-level MPC1 calculates and optimizes the user's active and reactive load power, and minimizes the difference between the main grid supply power required by the low-voltage area, the predicted photovoltaic power generation power of the low-voltage area, and the user's load at each sampling point. In each rolling optimization window, the minimization cost function J1 is solved to calculate the user's optimal load control input:

[0022]

[0023] in, is the supplied power, pw Load Optimize the window for scrolling, is the active load, is the reactive load;

[0024] The optimization calculation is performed within the control window and the rolling optimization is performed until the end of the specified operation cycle. The first-level MPC1 objective function and constraints are:

[0025]

[0026] in, is the load forecasting window for rolling optimization, J1 is the minimization cost function, R[f P ,f Q ] is the combination matrix of active and reactive power calculation functions, f P is the active power calculation function, f Q is the reactive power calculation function, Load[t] is the user adjustable load, and there is a limit constraint at time t.

[0027] min(Load) is the minimum load limit, max(Load) is the maximum load limit;

[0028] f P =RP P [t]-(Load P [t]+PV 预测 [t]),

[0029] f Q =RP Q [t]-Load Q [t],

[0030]

[0031] Among them, RP P [t] is the active power demand at time t, Load P [t] is the active load at time t, PV 预测 [t] is the predicted power generation at time t, RP Q [t] is the reactive power demand at time t, Load Q[t] is the reactive load at time t.

[0032] Preferably, the second-level MPC2 is used to control the active power and reactive power of the energy storage fast charge and discharge to fine-tune the user load offset and realize the correction of the photovoltaic predicted output error, including:

[0033] The second-level MPC2 controls the active power and reactive power of the energy storage system to charge and discharge rapidly, and minimizes the difference between the photovoltaic prediction of the substation and the user load at each sampling point. That is, the cost function J2 of the second-level MPC2 is used to calculate the optimal energy storage control input:

[0034]

[0035] in Predict the energy storage charging and discharging power for the rolling optimization window, pw ESS Optimize the window for scrolling, It is the active power of energy storage charging and discharging. Charge and discharge reactive power for energy storage;

[0036] At the same time, the charging and discharging constraints and the state of charge constraints of the energy storage unit are met, and the rate of change control is enforced through the cost function to achieve the purpose of user-side power slope control. The second-level MPC2 objective function and constraints are as follows:

[0037]

[0038] Among them, g P is the energy storage charging and discharging active power calculation function, g Q is the calculation function of reactive power of energy storage charging and discharging, R[g P , g Q ] is the combined matrix of the active and reactive power calculation functions of energy storage, P Rate is the power change rate, ESS Q [t] is the reactive power of energy storage charging and discharging at time t, ESSP max is the maximum active power of energy storage charging and discharging at time t, ESSQ max is the maximum reactive power of energy storage charging and discharging at time t, SoC[t] indicates that there is a constraint on the energy storage charge state at time t, P Rate (ESS P [t]+PV 预测 [t]) is the power output change rate constraint that the energy storage meets in the coordinated photovoltaic power generation, ESS P [t]Limited by the size of energy storage capacity;

[0039]

[0040] Based on another aspect of the present invention, the present invention provides a low-voltage distributed photovoltaic area source-load-storage control system, the system comprising:

[0041] Establish a unit to establish the control architecture of the source, grid, load and storage in the low-voltage area and determine the constraints of distributed photovoltaic and energy storage;

[0042] A control unit is used to control the photovoltaic grid-connected power of the low-voltage area through two-level MPC based on the control architecture and constraint conditions, including: controlling the user load through the first-level MPC1 to consume the photovoltaic predicted output;

[0043] The second-level MPC2 controls the active power and reactive power of the energy storage for rapid charging and discharging, so as to fine-tune the user load offset and correct the photovoltaic predicted output error.

[0044] Preferably, the establishment unit is used to establish a control architecture of source, grid, load and storage in the low-voltage area and determine the constraints of distributed photovoltaic and energy storage, including:

[0045] Limit the slope change of photovoltaic and energy storage power generation to less than 10% per sampling period:

[0046] P Rate (ESS[t]+PV[t])∈[-10%PV max ,+10% PV max ]

[0047] Among them, at time t, ESS[t] is the energy storage power, PV[t] is the total power generation of low-voltage distributed photovoltaic power in the substation, and PV max is the total installed capacity of low-voltage distributed photovoltaic power generation, P Rate (ESS[t]+PV[t]) is the slope change produced by photovoltaic and energy storage power generation.

[0048] Preferably, the establishment unit is used to establish a control architecture of source, grid, load and storage in the low-voltage area and determine the constraints of distributed photovoltaic and energy storage, including:

[0049] The charge and discharge rate and state of charge of energy storage per minute are limited to:

[0050] ESS[t]∈[ESS min ,ESS max ]

[0051] SoC[t]∈[SoC min ,SoC max ]

[0052] Among them, ESS[t] is the energy storage power at time t, ESS min and ESS maxThey are the upper and lower limits of energy storage power, SOC min and SOC max is the available domain of SOC, SOC[t] is the state of charge at time t, and ESS total is the maximum capacity of energy storage;

[0053]

[0054] Preferably, the control unit is used to control the user load through the first-level MPC1 to consume the predicted photovoltaic output, including:

[0055] The first-level MPC1 calculates and optimizes the user's active and reactive load power, and minimizes the difference between the main grid supply power required by the low-voltage area, the predicted photovoltaic power generation power of the low-voltage area, and the user's load at each sampling point. In each rolling optimization window, the minimization cost function J1 is solved to calculate the user's optimal load control input:

[0056]

[0057] in, is the supplied power, pw Load Optimize the window for scrolling, is the active load, is the reactive load;

[0058] The optimization calculation is performed within the control window and the rolling optimization is performed until the end of the specified operation cycle. The first-level MPC1 objective function and constraints are:

[0059]

[0060] in, is the load forecasting window for rolling optimization, J1 is the minimization cost function, R[f P , f Q ] is the combination matrix of active and reactive power calculation functions, f P is the active power calculation function, f Q is the reactive power calculation function, Load[t] is the user adjustable load, there is a limit constraint at time t, min(Load) is the minimum load limit, and max(Load) is the maximum load limit;

[0061] f P =RP P [t]-(Load P [t]+PV 预测 [t]),

[0062] f Q =RP Q [t]-Load Q[t],

[0063]

[0064] Among them, RP P [t] is the active power demand at time t, Load P [t] is the active load at time t, PV 预测 [t] is the predicted power generation at time t, RP Q [t] is the reactive power demand at time t, Load Q [t] is the reactive load at time t.

[0065] Preferably, the control unit is used to control the active power and reactive power of the energy storage fast charging and discharging through the second-level MPC2 to fine-tune the user load offset and realize the correction of the photovoltaic predicted output error, including:

[0066] The second-level MPC2 controls the active power and reactive power of the energy storage system to charge and discharge rapidly, and minimizes the difference between the photovoltaic prediction of the substation and the user load at each sampling point. That is, the cost function J2 of the second-level MPC2 is used to calculate the optimal energy storage control input:

[0067]

[0068] in Predict the energy storage charging and discharging power for the rolling optimization window, pw ESS Optimize the window for scrolling, It is the active power of energy storage charging and discharging. Charge and discharge reactive power for energy storage;

[0069] At the same time, the charging and discharging constraints and the state of charge constraints of the energy storage unit are met, and the rate of change control is enforced through the cost function to achieve the purpose of user-side power slope control. The second-level MPC2 objective function and constraints are as follows:

[0070]

[0071] Among them, g P is the energy storage charging and discharging active power calculation function, g Q is the calculation function of reactive power of energy storage charging and discharging, R[g P ,g Q ] is the combined matrix of the active and reactive power calculation functions of energy storage, P Rate is the power change rate, ESS Q [t] is the reactive power of energy storage charging and discharging at time t, ESSP max is the maximum active power of energy storage charging and discharging at time t, ESSQ maxis the maximum reactive power of energy storage charging and discharging at time t, SoC[t] indicates that there is a constraint on the energy storage charge state at time t, P Rate (ESS P [t]+PV 预测 [t]) is the power output change rate constraint that the energy storage meets in the coordinated photovoltaic power generation, ESS P [t]Limited by the size of energy storage capacity;

[0072]

[0073] The technical solution of the present invention provides a source-load-storage control method and system for low-voltage distributed photovoltaic power stations, wherein the method includes: establishing a source-grid-load-storage control architecture for low-voltage power stations, and determining the constraints of distributed photovoltaic and energy storage; based on the control architecture and constraints, controlling the photovoltaic grid-connected power of the low-voltage power station through two-level MPC, including: controlling the user load through the first-level MPC1 to absorb the photovoltaic predicted output; controlling the active power and reactive power of the energy storage fast charge and discharge through the second-level MPC2 to control the fine-tuning of the user load offset, and correcting the error of the photovoltaic predicted output. The technical solution of the present invention utilizes the distributed photovoltaic and energy storage coordinated scheduling mechanism to improve the local absorption rate of photovoltaic power generation in the power station, and provides a low-voltage distributed photovoltaic grid-connected peak-shaving and valley-filling optimization means to achieve source-load-storage coordinated interaction, improve the utilization rate of distributed photovoltaics, and improve the stability of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] A more complete understanding of exemplary embodiments of the present invention may be obtained by referring to the following drawings:

[0075] Figure 1 A flow chart of a low-voltage distributed photovoltaic area source-load-storage control method according to a preferred embodiment of the present invention;

[0076] Figure 2 A schematic diagram of a source-grid-load-storage communication control architecture based on a substation according to a preferred embodiment of the present invention;

[0077] Figure 3 A schematic diagram of a user load regional control method according to a preferred embodiment of the present invention;

[0078] Figure 4 A schematic diagram of a two-stage MPC control structure according to a preferred embodiment of the present invention;

[0079] Figure 5 A flow chart of a photovoltaic power generation optimization control strategy based on two-level MPC in a metropolitan area according to a preferred embodiment of the present invention; and

[0080] Figure 6The structure diagram of a low-voltage distributed photovoltaic area source-load-storage control system according to a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0081] Now, exemplary embodiments of the present invention are described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely and to fully convey the scope of the present invention to those skilled in the art. The terms used in the exemplary embodiments shown in the accompanying drawings are not intended to limit the present invention. In the accompanying drawings, the same units / elements are marked with the same reference numerals.

[0082] Unless otherwise specified, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0083] Figure 1 The present invention is a flow chart of a method for regulating source, load and storage in a low-voltage distributed photovoltaic area according to a preferred embodiment of the present invention.

[0084] The present invention utilizes the coordinated dispatching mechanism of distributed photovoltaic and energy storage to improve the local consumption rate of photovoltaic power generation in the substation area, provides a low-voltage distributed photovoltaic grid-connected peak-shaving and valley-filling optimization means, realizes the coordinated interaction of source, load and storage, improves the utilization rate of distributed photovoltaic, and improves the stability of the power grid.

[0085] like Figure 1 As shown, the present invention provides a method for regulating source-load-storage in a low-voltage distributed photovoltaic area, the method comprising:

[0086] Step 101: Establish a control architecture of source, grid, load and storage in the low-voltage area and determine the constraints of distributed photovoltaic and energy storage;

[0087] Preferably, a control architecture of source, grid, load and storage is established in the low-voltage area to determine the constraints of distributed photovoltaic and energy storage, including:

[0088] Limit the slope change of photovoltaic and energy storage power generation to less than 10% per sampling period:

[0089] P Rate (ESS[t]+PV[t])∈[-10%PV max ,+10% PV max ]

[0090] Among them, at time t, ESS[t] is the energy storage power, PV[t] is the total power generation of low-voltage distributed photovoltaic power in the substation, and PV maxis the total installed capacity of low-voltage distributed photovoltaic power generation, P Rate (ESS[t]+PV[t]) is the slope change produced by photovoltaic and energy storage power generation.

[0091] Preferably, a control architecture of source, grid, load and storage is established in the low-voltage area to determine the constraints of distributed photovoltaic and energy storage, including:

[0092] The charge and discharge rate and state of charge of energy storage per minute are limited to:

[0093] ESS[t]∈[ESS min ,ESS max ]

[0094] SoC[t]∈[SoC min ,SoC max ]

[0095] Among them, ESS[t] is the energy storage power at time t, ESS min and ESS max They are the upper and lower limits of energy storage power, SOC min and SOC max is the available domain of SOC, SOC[t] is the state of charge at time t, and ESS total is the maximum capacity of energy storage;

[0096]

[0097] In the source-grid-load-storage architecture of the present invention, the energy storage unit and the photovoltaic array have separate DC-to-AC inverters and are connected to the DC side of the inverter. The distributed photovoltaic and energy storage are controlled by the grid-connected energy meter or the photovoltaic collection and monitoring unit. When the photovoltaic and energy storage power generation is insufficient, they are supplemented by the grid. This method can achieve coordinated regulation between the grid power consumption, photovoltaic power generation, energy storage charging and discharging, and user load on the user side, improve the utilization rate of low-voltage distributed photovoltaics, and reduce energy storage losses. The architecture diagram is shown in the figure below. Figure 2 As shown, after the acquisition terminal collects the data required by this method, it executes the scheduling strategy and sends it to the electric energy meter or photovoltaic acquisition control unit to perform flexible regulation of photovoltaic and energy storage; user loads give priority to using photovoltaic power generation resources, and when there is a shortage, they are supplemented from the main power grid of the low-voltage area.

[0098] The power self-generation of the power grid is defined as positive, and the load consumption is defined as negative. The grid area containing distributed photovoltaic and energy storage is composed as follows:

[0099] (1) Low-voltage distributed photovoltaic: The output of low-voltage distributed photovoltaic power generation is uncertain due to environmental changes. Statistics of all energy storage units in the substation area help smooth the fluctuation of photovoltaic power generation and limit the slope changes generated by photovoltaic and energy storage power generation to less than 10% in each sampling period.

[0100] P Rate (ESS[t]+PV[t])∈[-10%PV max ,+10% PV max ]

[0101] Among them, at time t, ESS[t] is the energy storage power (kW), PV[t] is the total power generation of low-voltage distributed photovoltaic power in the substation (kW), and PV max is the total installed capacity of low-voltage distributed photovoltaic power generation (kW).

[0102] (2) Energy storage: The energy storage unit acts as a negative load when charging and as a positive load when discharging. To maintain high efficiency, the charge and discharge rate per minute and the state of charge are limited as follows:

[0103] ESS[t]∈[ESS min ,ESS max ]

[0104] SoC[t]∈[SoC min ,SoC max ]

[0105] Where ESS[t] is the energy storage power at time t, ESS min and ESS max They are the upper and lower limits of power, SOC min and SOC max is the available domain of SOC, SOC[t] is the state of charge at time t, ESS total is the maximum capacity of the energy storage unit.

[0106]

[0107] User load: User load can be divided into controllable load and uncontrollable load. The user load can be classified into rigid and flexible control. The specific control methods are divided into regional types, such as Figure 3 shown.

[0108] Step 102: Based on the control architecture and constraints, the photovoltaic grid-connected power in the low-voltage area is controlled through the two-level MPC, including: controlling the user load through the first-level MPC1 to absorb the photovoltaic predicted output;

[0109] Preferably, the user load is controlled by the first-level MPC1 to consume the predicted photovoltaic output, including:

[0110] The first-level MPC1 calculates and optimizes the user's active and reactive load power, and minimizes the difference between the main grid supply power required by the low-voltage area, the predicted photovoltaic power generation power of the low-voltage area, and the user's load at each sampling point. In each rolling optimization window, the minimization cost function J1 is solved to calculate the user's optimal load control input:

[0111]

[0112] in, is the supplied power, pw Load Optimize the window for scrolling, is the active load, is the reactive load;

[0113] The optimization calculation is performed within the control window and the rolling optimization is performed until the end of the specified operation cycle. The first-level MPC1 objective function and constraints are:

[0114]

[0115] in, is the load forecasting window for rolling optimization, J1 is the minimization cost function, R[f P ,f Q ] is the combination matrix of active and reactive power calculation functions, f P is the active power calculation function, f Q is the reactive power calculation function, Load[t] is the user adjustable load, there is a limit constraint at time t, min(Load) is the minimum load limit, and max(Load) is the maximum load limit;

[0116] f P =RP P [t]-(Load P [t]+PV 预测 [t]),

[0117] f Q =RP Q [t]-Load Q [t],

[0118]

[0119] Among them, RP P [t] is the active power demand at time t, Load P [t] is the active load at time t, PV 预测 [t] is the predicted power generation at time t, RP Q [t] is the reactive power demand at time t, Load Q [t] is the reactive load at time t.

[0120] The control framework of the present invention is shown in FIG. Figure 4 The optimization problem in the control method shown is solved in two steps, represented by MPC1 and MPC2. MPC1 controls the user's adjustable load to absorb the predicted photovoltaic output, but there are problems such as long absorption time and load regulation lag, while MPC2 controls the energy storage system to form rapid charging and discharging, forming a fine-tuning mechanism for the load offset, which is used to smooth the photovoltaic power output and solve the defect that MPC1 cannot meet the regulation in a short time. Since MPC control is based on photovoltaic power generation prediction, MPC2 will correct the prediction error in time after fine-tuning, thereby reducing the error of the overall system.

[0121] At each sampling moment, the MPC controller attempts to adjust the user controllable load {Load P [k],Load Q [k]} and energy storage power {ESS P [k],ESS Q [k]} to reduce the requested power {RP P [k],RP Q [k]} and the total load {P Total [k],Q Total [k]} between the tracking error {E P [k],E Q [k]}:

[0122] E p [k] = RP p [k]-P Total [k],

[0123] E Q [k] = RP Q [k]-Q Total [k],

[0124] in

[0125] P Total [k]=Load p [k]-ESS p [k]-PV[k],

[0126] Q Total [k]=Load Q [k]-ESS Q [k].

[0127] First-level MPC controller design (MPC1): This controller calculates and optimizes the active and reactive load power of users, and minimizes the difference between the power supply of the main grid required by the substation, the predicted power of photovoltaic power generation in the substation, and the user load at each sampling point. That is, in each rolling optimization window, the minimization cost function J1 is solved to calculate the optimal load control input for users. The optimization calculation is performed within the control window and the rolling optimization is performed until the specified operation cycle ends. The MPC1 objective function and constraints are as follows:

[0128]

[0129] in,

[0130] f P =RP P [t]-(Load P [t]+PV 预测 [t]),

[0131] f Q =RP Q [t]-Load Q [t],

[0132]

[0133] Load[t] is the user adjustable load, which has a limit constraint at time t. f represents the function that MPC1 needs to solve to minimize the difference between the main grid supply power, the predicted photovoltaic power generation power in the substation, and the user load.

[0134] Step 103: Control the active power and reactive power of the energy storage fast charging and discharging through the second-level MPC2 to fine-tune the user load offset and correct the photovoltaic predicted output error.

[0135] Preferably, the active power and reactive power of the energy storage system that is rapidly charged and discharged are controlled by the second-level MPC2 to control the fine-tuning of the user load offset, thereby correcting the error of the photovoltaic predicted output, including:

[0136] The second-level MPC2 controls the active power and reactive power of the energy storage system to charge and discharge rapidly, and minimizes the difference between the photovoltaic prediction of the substation and the user load at each sampling point. That is, the cost function J2 of the second-level MPC2 is used to calculate the optimal energy storage control input:

[0137]

[0138] in Predict the energy storage charging and discharging power for the rolling optimization window, pw ESS Optimize the window for scrolling, It is the active power of energy storage charging and discharging. Charge and discharge reactive power for energy storage;

[0139] At the same time, the charging and discharging constraints and the state of charge constraints of the energy storage unit are met, and the rate of change control is enforced through the cost function to achieve the purpose of user-side power slope control. The second-level MPC2 objective function and constraints are as follows:

[0140]

[0141] Among them, g P is the energy storage charging and discharging active power calculation function, g Q is the calculation function of reactive power of energy storage charging and discharging, R[g P ,g Q ] is the combined matrix of the active and reactive power calculation functions of energy storage, P Rate is the power change rate, ESS Q [t] is the reactive power of energy storage charging and discharging at time t, ESSP max is the maximum active power of energy storage charging and discharging at time t, ESSQ max is the maximum reactive power of energy storage charging and discharging at time t, SoC[t] indicates that there is a constraint on the energy storage charge state at time t, P Rate (ESS P [t]+PV 预测 [t]) is the power output change rate constraint that the energy storage meets in the coordinated photovoltaic power generation, ESS P [t]Limited by the size of energy storage capacity;

[0142]

[0143] The second-level MPC controller design (MPC2) of the present invention: This controller calculates and optimizes the active and reactive power of the energy storage unit during charging and discharging, minimizes the difference between the photovoltaic prediction of the station area and the user load at each sampling point, that is, the cost function J2 of MPC2, and calculates the optimal energy storage control input. At the same time, the charging and discharging constraints and the state of charge constraints of the energy storage unit are met, and the rate of change control is enforced through the cost function to achieve the purpose of user-side power slope control. (Detailed explanation of constraints) The MPC2 objective function and constraints are as follows:

[0144]

[0145] in,

[0146]

[0147] SoC[t] indicates that there is a storage state of charge constraint at time t, P Rate (ESSP [t]+PV 预测 [t]) represents the power output change rate constraint that energy storage meets in conjunction with photovoltaic power generation, ESS P [t] is limited by the size of the energy storage capacity. g represents the function of minimizing the difference between the photovoltaic forecast of the substation and the user load during the regulation process of MPC2.

[0148] The two-stage MPC flow chart of the present invention is as follows: Figure 5 shown.

[0149] This application can be applied to low-voltage areas containing distributed photovoltaics and energy storage. With the source-load-storage communication architecture and related equipment, it can achieve power smoothing and optimization control of power generation output and power demand in low-voltage photovoltaic areas, effectively improve the utilization efficiency of low-distributed photovoltaic power generation, meet power demand to the greatest extent, and achieve supply and demand balance. Considering the economics of the power grid and the absorption rate of distributed photovoltaics, this solution can theoretically reduce the abandoned rate of distributed photovoltaics in the area by 5%-10%.

[0150] Figure 6 The structure diagram of a low-voltage distributed photovoltaic area source-load-storage control system according to a preferred embodiment of the present invention.

[0151] like Figure 6 As shown, the present invention provides a low-voltage distributed photovoltaic area source-load-storage control system, the system comprising:

[0152] Establishing unit 601, used to establish the control architecture of source, grid, load and storage in the low voltage area, and determine the constraints of distributed photovoltaic and energy storage;

[0153] Preferably, the establishment unit 601 is used to establish a control architecture of source, grid, load and storage in the low-voltage area and determine the constraints of distributed photovoltaic and energy storage, including:

[0154] Limit the slope change of photovoltaic and energy storage power generation to less than 10% per sampling period:

[0155] P Rate (ESS[t]+PV[t])∈[-10%PV max ,+10% PV max ]

[0156] Among them, at time t, ESS[t] is the energy storage power, PV[t] is the total power generation of low-voltage distributed photovoltaic power in the substation, and PV max is the total installed capacity of low-voltage distributed photovoltaic power generation, P Rate (ESS[t]+PV[t]) is the slope change produced by photovoltaic and energy storage power generation.

[0157] Preferably, the establishment unit 601 is used to establish a control architecture of source, grid, load and storage in the low-voltage area and determine the constraints of distributed photovoltaic and energy storage, including:

[0158] The charge and discharge rate and state of charge of energy storage per minute are limited to:

[0159] ESS[t]∈[ESS min ,ESS max ]

[0160] SoC[t]∈[SoC min ,SoC max ]

[0161] Among them, ESS[t] is the energy storage power at time t, ESS min and ESS max They are the upper and lower limits of energy storage power, SOC min and SOC max is the available domain of SOC, SOC[t] is the state of charge at time t, and ESS total is the maximum capacity of energy storage;

[0162]

[0164] The control unit 602 is used to control the photovoltaic grid-connected power of the low-voltage area through two-level MPC based on the control architecture and constraint conditions, including: controlling the user load through the first-level MPC1 to consume the photovoltaic predicted output;

[0165] The second-level MPC2 controls the active power and reactive power of the energy storage for rapid charging and discharging, so as to control the fine-tuning of the user load offset and correct the error in the predicted photovoltaic output.

[0166] Preferably, the control unit 602 is used to control the user load through the first-level MPC1 to consume the predicted photovoltaic output, including:

[0167] The first-level MPC1 calculates and optimizes the user's active and reactive load power, and minimizes the difference between the main grid supply power required by the low-voltage area, the predicted photovoltaic power generation power of the low-voltage area, and the user's load at each sampling point. In each rolling optimization window, the minimization cost function J1 is solved to calculate the user's optimal load control input:

[0168]

[0169] in, is the supplied power, pw Load Optimize the window for scrolling, is the active load, is the reactive load;

[0170] The optimization calculation is performed within the control window and the rolling optimization is performed until the end of the specified operation cycle. The first-level MPC1 objective function and constraints are:

[0171]

[0172] in, is the load forecasting window for rolling optimization, J1 is the minimization cost function, R[f P ,f Q ] is the combination matrix of active and reactive power calculation functions, f P is the active power calculation function, f Q is the reactive power calculation function, Load[t] is the user adjustable load, there is a limit constraint at time t, min(Load) is the minimum load limit, and max(Load) is the maximum load limit;

[0173] f P =RP P [t]-(Load P [t]+PV 预测 [t]),

[0174] f Q =RP Q [t]-Load Q [t],

[0175]

[0176] Among them, RP P [t] is the active power demand at time t, Load P [t] is the active load at time t, PV 预测 [t] is the predicted power generation at time t, RP Q [t] is the reactive power demand at time t, Load Q [t] is the reactive load at time t.

[0177] Preferably, the control unit 602 is used to control the active power and reactive power of the energy storage system for rapid charging and discharging through the second-level MPC2 to control the fine adjustment of the user load offset to correct the error of the photovoltaic predicted output, including:

[0178] The second-level MPC2 controls the active power and reactive power of the energy storage system to charge and discharge rapidly, and minimizes the difference between the photovoltaic prediction of the substation and the user load at each sampling point. That is, the cost function J2 of the second-level MPC2 is used to calculate the optimal energy storage control input:

[0179]

[0180] in Predict the energy storage charging and discharging power for the rolling optimization window, pw ESS Optimize the window for scrolling, It is the active power of energy storage charging and discharging. Charge and discharge reactive power for energy storage;

[0181] At the same time, the charging and discharging constraints and the state of charge constraints of the energy storage unit are met, and the rate of change control is enforced through the cost function to achieve the purpose of user-side power slope control. The second-level MPC2 objective function and constraints are as follows:

[0182]

[0183] Among them, g P is the energy storage charging and discharging active power calculation function, g Q is the calculation function of reactive power of energy storage charging and discharging, R[g P ,g Q ] is the combined matrix of the active and reactive power calculation functions of energy storage, P Rate is the power change rate, ESS Q [t] is the reactive power of energy storage charging and discharging at time t, ESSP max is the maximum active power of energy storage charging and discharging at time t, ESSQ max is the maximum reactive power of energy storage charging and discharging at time t, SoC[t] indicates that there is a constraint on the energy storage charge state at time t, P Rate (ESS P [t]+PV 预测 [t]) is the power output change rate constraint that the energy storage meets in the coordinated photovoltaic power generation, ESS P [t]Limited by the size of energy storage capacity;

[0184]

[0185] A low-voltage distributed photovoltaic area source-load-storage control system of a preferred embodiment of the present invention corresponds to a low-voltage distributed photovoltaic area source-load-storage control method of another preferred embodiment of the present invention, which will not be repeated here.

[0186] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0187] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks 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 processes in the flowchart and / or block diagram. 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.

[0188] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate 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 A function specified in one or more boxes.

[0189] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0190] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0191] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

[0192] The invention has been described above with reference to a few embodiments. However, it is readily apparent to a person skilled in the art that other embodiments than the ones disclosed above are equally within the scope of the invention, as defined by the appended patent claims.

[0193] Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to "a / said / the [means, components, etc.]" are to be openly interpreted as at least one instance of the means, components, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not necessarily have to be performed in the exact order disclosed, unless explicitly stated otherwise.

Claims

1. A method for regulating source, load and storage in a low-voltage distributed photovoltaic area, the method comprising: Establish the control architecture of source, grid, load and storage in low-voltage areas and determine the constraints of distributed photovoltaic and energy storage; Based on the control architecture and constraints, the photovoltaic grid-connected power of the low-voltage area is controlled through two-level MPC, including: controlling the user load through the first-level MPC1 to absorb the photovoltaic predicted output; The second-level MPC2 controls the active power and reactive power of the energy storage for rapid charging and discharging, so as to fine-tune the user load offset and correct the photovoltaic predicted output error.

2. According to the method of claim 1, the control architecture of the source, grid, load and storage in the low-voltage area is established to determine the constraints of distributed photovoltaic and energy storage, including: Limit the slope change of photovoltaic and energy storage power generation to less than 10% per sampling period: P Rate (ESS[t]+PV[t])∈[-10%PV max ,+10%PV max ] Among them, at time t, ESS[t] is the energy storage power, PV[t] is the total power generation of low-voltage distributed photovoltaic power in the substation, and PV max is the total installed capacity of low-voltage distributed photovoltaic power generation, P Rate (ESS[t]+PV[t] is the slope change of photovoltaic and energy storage power generation.

3. According to the method of claim 1, the control architecture of source, grid, load and storage in the low-voltage area is established to determine the constraints of distributed photovoltaic and energy storage, including: The charge and discharge rate and state of charge of energy storage per minute are limited to: ESS[t]∈[ESS min ,ESS max ] SoC[t]∈[SoC min ,SoC max ] Among them, ESS[t] is the energy storage power at time t, ESS min and ESS max They are the upper and lower limits of energy storage power, SOC min and SOC max is the available domain of SOC, SOC[t] is the state of charge at time t, and ESS total is the maximum capacity of energy storage; 4. The method according to claim 3, wherein the controlling the user load by the first-level MPC1 to absorb the predicted photovoltaic output comprises: The first-level MPC1 calculates and optimizes the user's active and reactive load power, and minimizes the difference between the main grid supply power required by the low-voltage area, the predicted photovoltaic power generation power of the low-voltage area, and the user's load at each sampling point. In each rolling optimization window, the minimization cost function J1 is solved to calculate the user's optimal load control input: in, is the supplied power, pw Load Optimize the window for scrolling, is the active load, is the reactive load; The optimization calculation is performed within the control window and the rolling optimization is performed until the end of the specified operation cycle. The first-level MPC1 objective function and constraints are: in, is the load forecasting window for rolling optimization, J1 is the minimization cost function, R[f P , f Q ] is the combination matrix of active and reactive power calculation functions, f P is the active power calculation function, f Q is the reactive power calculation function, Load[t] is the user adjustable load, there is a limit constraint at time t, min(Load) is the minimum load limit, and max(Load) is the maximum load limit; f P =RP P [t]-(Load P [t]+PV 预测 [t]), f Q =RP Q [t]-Load Q [t], Among them, RP P [t] is the active power demand at time t, Load P [t] is the active load at time t, PV 预测 [t] is the predicted power generation at time t, RP Q [t] is the reactive power demand at time t, Load Q [t] is the reactive load at time t.

5. The method according to claim 4, wherein the second-level MPC2 is used to control the active power and reactive power of the energy storage fast charge and discharge to fine-tune the user load offset and realize the correction of the photovoltaic predicted output error, comprising: The second-level MPC2 controls the active power and reactive power of the energy storage system to charge and discharge rapidly, and minimizes the difference between the photovoltaic prediction of the substation and the user load at each sampling point. That is, the cost function J2 of the second-level MPC2 is used to calculate the optimal energy storage control input: in Predict the energy storage charging and discharging power for the rolling optimization window, pw ESS Optimize the window for scrolling, It is the active power of energy storage charging and discharging. Charge and discharge reactive power for energy storage; At the same time, the charging and discharging constraints and the state of charge constraints of the energy storage unit are met, and the rate of change control is enforced through the cost function to achieve the purpose of user-side power slope control. The second-level MPC2 objective function and constraints are as follows: Among them, g P is the energy storage charging and discharging active power calculation function, g Q is the calculation function of reactive power of energy storage charging and discharging, R[g P , g Q ] is the combined matrix of the active and reactive power calculation functions of energy storage, P Rate is the power change rate, ESS Q [t] is the reactive power of energy storage charging and discharging at time t, ESSP max is the maximum active power of energy storage charging and discharging at time t, ESSQ max is the maximum reactive power of energy storage charging and discharging at time t, SoC[t] indicates that there is a constraint on the energy storage charge state at time t, P Rate (ESS P [t]+PV 预测 [t]) is the power output change rate constraint that the energy storage meets in the coordinated photovoltaic power generation, ESS P [t]Limited by the size of energy storage capacity; 6. A low-voltage distributed photovoltaic area source-load-storage control system, the system comprising: Establish a unit to establish the control architecture of the source, grid, load and storage in the low-voltage area and determine the constraints of distributed photovoltaic and energy storage; A control unit is used to control the photovoltaic grid-connected power of the low-voltage area through two-level MPC based on the control architecture and constraint conditions, including: controlling the user load through the first-level MPC1 to consume the photovoltaic predicted output; The second-level MPC2 controls the active power and reactive power of the energy storage for rapid charging and discharging, so as to fine-tune the user load offset and correct the photovoltaic predicted output error.

7. The system according to claim 6, wherein the establishment unit is used to establish a control architecture of source, grid, load and storage in the low-voltage area and determine the constraints of distributed photovoltaic and energy storage, including: Limit the slope change of photovoltaic and energy storage power generation to less than 10% per sampling period: P Rate (ESS[t]+PV[t])∈[-10%PV max ,+10%PV max ] Among them, at time t, ESS[t] is the energy storage power, PV[t] is the total power generation of low-voltage distributed photovoltaic power in the substation, and PV max is the total installed capacity of low-voltage distributed photovoltaic power generation, P Rate (ESS[t]+PV[t]) is the slope change produced by photovoltaic and energy storage power generation.

8. The system according to claim 6, wherein the establishment unit is used to establish a control architecture of source, grid, load and storage in the low-voltage area and determine the constraints of distributed photovoltaic and energy storage, including: The charge and discharge rate and state of charge of energy storage per minute are limited to: ESS[t]∈[ESS min ,ESS max ] SoC[t]∈[SoC min ,SoC max ] Among them, ESS[t] is the energy storage power at time t, ESS min and ESS max They are the upper and lower limits of energy storage power, SOC min and SOC max is the available domain of SOC, SOC[t] is the state of charge at time t, and ESS total is the maximum capacity of energy storage; 9. The system according to claim 8, wherein the control unit is used to control the user load through the first-level MPC1 to consume the predicted photovoltaic output, comprising: The first-level MPC1 calculates and optimizes the user's active and reactive load power, and minimizes the difference between the main grid supply power required by the low-voltage area, the predicted photovoltaic power generation power of the low-voltage area, and the user's load at each sampling point. In each rolling optimization window, the minimization cost function J1 is solved to calculate the user's optimal load control input: in, is the supplied power, pw Load Optimize the window for scrolling, is the active load, is the reactive load; The optimization calculation is performed within the control window and the rolling optimization is performed until the end of the specified operation cycle. The first-level MPC1 objective function and constraints are: in, is the load forecasting window for rolling optimization, J1 is the minimization cost function, R[f P ,f Q ] is the combination matrix of active and reactive power calculation functions, f P is the active power calculation function, f Q is the reactive power calculation function, Load[t] is the user adjustable load, there is a limit constraint at time t, min(Load) is the minimum load limit, and max(Load) is the maximum load limit; f P =RP P [t]-(Load P [t]+PV 预测 [t]), f Q =RP Q [t]-Load Q [t], Among them, RP P [t] is the active power demand at time t, Load P [t] is the active load at time t, PV 预测 [t] is the predicted power generation at time t, RP Q [t] is the reactive power demand at time t, Load Q [t] is the reactive load at time t.

10. The system according to claim 9, wherein the control unit is used to control the active power and reactive power of the energy storage fast charging and discharging through the second-level MPC2 to fine-tune the user load offset and realize the correction of the photovoltaic predicted output error, including: The second-level MPC2 controls the active power and reactive power of the energy storage system to charge and discharge rapidly, and minimizes the difference between the photovoltaic prediction of the substation and the user load at each sampling point. That is, the cost function J2 of the second-level MPC2 is used to calculate the optimal energy storage control input: in Predict the energy storage charging and discharging power for the rolling optimization window, pw ESS Optimize the window for scrolling, It is the active power of energy storage charging and discharging. Charge and discharge reactive power for energy storage; At the same time, the charging and discharging constraints and the state of charge constraints of the energy storage unit are met, and the rate of change control is enforced through the cost function to achieve the purpose of user-side power slope control. The second-level MPC2 objective function and constraints are as follows: Among them, g P is the energy storage charging and discharging active power calculation function, g Q is the calculation function of reactive power of energy storage charging and discharging, R[g P , g Q ] is the combined matrix of the active and reactive power calculation functions of energy storage, P Rate is the power change rate, ESS Q [t] is the reactive power of energy storage charging and discharging at time t, ESSP max is the maximum active power of energy storage charging and discharging at time t, ESSQ max is the maximum reactive power of energy storage charging and discharging at time t, SoC[t] indicates that there is a constraint on the energy storage charge state at time t, P Rate (ESS P [t]+PV 预测 [t]) is the power output change rate constraint that the energy storage meets in the coordinated photovoltaic power generation, ESS P [t]Limited by the size of energy storage capacity;

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