CN115549216B - Active-reactive coordination control method and system for wind-solar energy storage station - Google Patents
Active-reactive coordination control method and system for wind-solar energy storage station Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/48—Controlling the sharing of the in-phase component
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/50—Controlling the sharing of the out-of-phase component
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/28—The renewable source being wind energy
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/30—Reactive power compensation
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Abstract
The invention relates to an active-reactive coordination control method and system for a wind-solar storage station, wherein the method comprises the following steps: acquiring a real-time value of operation data of the wind-solar energy storage station and a target value issued by a dispatching center; two control modes are designed aiming at the integrated characteristic of the combined power station, active priority or reactive priority control strategies are executed according to the control modes and the running states, a multi-objective optimization model which takes into account active power loss, node voltage deviation, active power and reactive power deviation and active power adjustment cost reduction actively is established based on different control strategies, active and reactive coordination control of the combined power station can be realized, power and voltage distribution in the station is optimized, and running economy and safety stability of the system are effectively improved.
Description
Technical Field
The invention relates to the technical field of active-reactive power regulation, in particular to an active-reactive power coordination control method and system for grid-connected operation of a wind-solar storage station.
Background
Wind-solar energy storage integrated grid connection can effectively stabilize wind-solar energy power fluctuation, promote wind and light absorption level, and in recent years, wind-solar energy storage combined power stations are built in various places in batches, but due to lack of an advanced coordination control strategy and method, the conditions of uneven distribution of collection line voltage or overlarge line loss in the stations generally occur, so that economy is reduced, and potential safety hazards exist.
Disclosure of Invention
The invention aims to provide an active-reactive coordination control method and system for a wind-solar energy storage station.
In order to achieve the above object, the present invention provides the following solutions:
an active-reactive coordination control method for a wind-solar energy storage station comprises the following steps:
acquiring a real-time value of operation data of a wind-solar energy storage station; the operation data comprise voltage, active power, reactive power of a grid-connected point of the wind-solar storage station, voltage of a collecting line, active power and reactive power;
acquiring a target value of wind-light storage station operation data issued by a dispatching center;
if the voltage of the grid-connected point is in a safety interval and is not located at an end point of the safety interval, a first multi-objective optimization model is established according to the real-time value and the target value, and the first multi-objective optimization model comprises a first objective function and constraint conditions; the first objective function comprises a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function and an active power line loss function; the constraint conditions comprise power and voltage range constraint, node power balance constraint and power flow constraint;
solving the first multi-objective optimization model to obtain a first active power adjustment quantity and a first active power adjustment quantity of controlled equipment of each node in the wind-solar storage station; the controlled equipment comprises a wind driven generator, a photovoltaic inverter, an energy storage converter and a static reactive generator;
If the voltage of the point of connection is not in the safety interval and the difference value between the voltage of the point of connection and the end point of the safety interval is smaller than a preset threshold value, a second multi-objective optimization model is established according to the real-time value and the target value, and the second multi-objective optimization model comprises a second objective function and the constraint condition; the second objective function comprises a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function, an active power line loss function and an adjusting cost function when active power is actively reduced;
and solving the second multi-objective optimization model to obtain a second active power adjustment quantity and a second reactive power adjustment quantity of the controlled equipment of each node in the wind-solar storage station.
Optionally, the method further comprises:
selecting a control mode of the wind-solar storage station according to a scheduling instruction issued by a scheduling system; the wind-solar energy storage station control mode comprises a voltage control mode and a reactive power control mode; the voltage control mode is that the voltage of the grid-connected point and the active power reach the target value; and the reactive power control mode is that the active power and the reactive power of the grid-connected point reach the target values, and the grid-connected point voltage is in the safety interval.
Optionally, before the solving the first multi-objective optimization model, the method further includes:
respectively determining first weights of a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function and an active power line loss function in the first objective function according to the control mode of the wind-solar energy storage station;
carrying out weighted summation on a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function and an active power line loss function in the first objective function according to the first weight to obtain an optimized first objective function;
establishing an optimized first multi-objective optimization model according to the optimized first objective function, and taking the optimized first multi-objective optimization model as a new first multi-objective optimization model;
before the solving the second multi-objective optimization model, the method further includes:
determining a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function, an active power line loss function and a second weight of an adjusting cost function when active power is actively reduced in the second objective function according to the control mode of the wind-solar energy storage station;
According to the second weight, carrying out weighted summation on a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function, an active power line loss function and an adjusting cost function when active power is actively reduced in the second objective function, so as to obtain an optimized second objective function;
and establishing an optimized second multi-objective optimization model according to the optimized second objective function, and taking the optimized second multi-objective optimization model as a new second multi-objective optimization model.
Optionally, the expression of the first objective function is:
wherein f 1 As a node voltage deviation function, n i To calculate the number of nodes of voltage deviation, H i For node i voltage deviation weight coefficient, V error，i For deviation of voltage amplitude of node i from target voltage amplitude, f 2 Tracking a deviation function for reactive power of a node, n j To calculate the number of nodes of reactive power deviation, G i For the reactive power deviation weight coefficient of the node i, Q error，i For the deviation of the actual reactive power of the node i from the target reactive power, f 3 Tracking a deviation function for node active power, n k To calculate the node number of the active power deviation, M i For node i active power deviation weight coefficient, P error，i For the deviation of the actual active power of the node i from the target active power, f 4 As active power line loss function, n l To calculate the number of branches of active power loss of the circuit, P loss，l Is the active power loss on line l.
Optionally, the expression of the second objective function is:
wherein f 5 To actively reduce the adjustment cost function, P cur，i Active power actively reduced for device i, T i To adjust the cost coefficient, n c The number of active power sources that actively reduce active power.
Optionally, the power and voltage range constraint is expressed as:
wherein,for the minimum and maximum value of the active power of the controlled power supply at node i, +.> Respectively minimum value and maximum value of reactive power of controlled power supply at node i, +.>The minimum value and the maximum value of the controlled power supply voltage at the node i are respectively, and the controlled power supply comprises a wind driven generator, a photovoltaic inverter and an energy storage converter.
Optionally, the calculation formulas of the minimum value and the maximum value of the active power of the controlled power at the node i and the minimum value and the maximum value of the reactive power of the controlled power at the node i are respectively:
wherein P is i min Active power minimum value of controlled power supply at node i, n wind For the number of wind power generators of the node i, Is the minimum value of the active power of the wind driven generator, n pv For the number of photovoltaic inverters at node i, < +.>Is the minimum value of active power of the photovoltaic inverter, n ess For node i the number of energy storage converters, < >>The active power minimum value of the energy storage converter; p (P) i max For the maximum value of the active power of the controlled power supply at node i, < >>For maximum active power of wind power generator, +.>For maximum active power of the photovoltaic inverter, < +.>The maximum value of active power of the energy storage converter; />For the minimum value of reactive power of the controlled power supply at node i, < > for>Reactive power minimum and maximum of wind power generator respectively, +.>Respectively minimum and maximum reactive power of the photovoltaic inverter, -a->Respectively the minimum value and the maximum value of reactive power of the energy storage converter; n is n svg For the number of static var generators at node i, < >>Reactive power minimum and maximum values for the number of static reactive generators respectively; n is n g The number of reactive devices remaining for node i, +.> And respectively obtaining the minimum value and the maximum value of the reactive power of the residual reactive power equipment of the node i.
Optionally, the expression of the node power balance constraint is:
Q i ＝Q wind，i +Q pv，i +Q ess，i +Q svg，i +Q g，i -Q l，i
wherein P is i And Q i Active and reactive injection power, P, respectively, of node i wind，i And Q wind，i The wind driven generator respectively outputs active power and reactive power for the node i; p (P) pv，i And Q pv，i The output active power and reactive power of the photovoltaic inverter are respectively node i;and->Discharging and charging active power for energy storage of node i, Q ess，i The reactive power is output by the energy storage converter; q (Q) svg，i The output reactive power of the static reactive generator of the node i; q (Q) g，i Reactive power of the remaining reactive devices for node i; p (P) l，i And Q l，i The active load and the reactive load of the node i.
Optionally, the expression of the power flow constraint is:
wherein u (j) is a set of flow direction nodes j; p (P) ij And Q ij Respectively representing the active power and the reactive power of the node i flowing to the node j; r is R ij And X ij Respectively representing the short circuit resistance and the short circuit reactance between the node i and the node j; v (V) i And V j The voltage effective value v (j) representing the node i and the node j is a set of the power flow flowing out of the node j; p (P) jk And Q jk Representing the active power and reactive power of node j flowing to node k, respectively.
An active-reactive coordination control system for a wind-solar energy storage station, comprising:
the real-time value acquisition module is used for acquiring the real-time value of the operation data of the wind-solar storage station; the operation data comprise voltage, active power, reactive power of a grid-connected point of the wind-solar storage station, voltage of a collecting line, active power and reactive power;
The target value acquisition module is used for acquiring a target value of the wind-solar storage station operation data issued by the dispatching center;
the first multi-objective optimization model building module is used for building a first multi-objective optimization model according to the real-time value and the target value if the voltage of the grid-connected point is in a safety interval and is not located at an endpoint of the safety interval, wherein the first multi-objective optimization model comprises a first objective function and constraint conditions; the first objective function comprises a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function and an active power line loss function; the constraint conditions comprise power and voltage range constraint, node power balance constraint and power flow constraint;
the first adjustment quantity acquisition module is used for solving the first multi-objective optimization model to obtain a first active power adjustment quantity and a first active power adjustment quantity of controlled equipment of each node in the wind-solar storage station; the controlled equipment comprises a wind driven generator, a photovoltaic inverter, an energy storage converter and a static reactive generator;
the second multi-objective optimization model building module is used for building a second multi-objective optimization model according to the real-time value and the target value if the voltage of the grid-connected point is not in the safety interval and the difference value between the voltage of the grid-connected point and the end point of the safety interval is smaller than a preset threshold value, wherein the second multi-objective optimization model comprises a second objective function and the constraint condition; the second objective function comprises a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function, an active power line loss function and an adjusting cost function when active power is actively reduced;
And the second adjustment quantity acquisition module is used for solving the second multi-objective optimization model to obtain a second active power adjustment quantity and a second reactive power adjustment quantity of the controlled equipment of each node in the wind-solar storage station.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects: the invention provides an active-reactive coordination control method and system for a wind-solar energy storage station, comprising the following steps: acquiring a real-time value of operation data of a wind-solar energy storage station; acquiring a target value of wind-light storage station operation data issued by a dispatching center; if the voltage of the parallel network point is in the safety interval and is not located at the end point of the safety interval, a first multi-objective optimization model is established according to the real-time value and the target value, and the first multi-objective optimization model comprises a first objective function and constraint conditions; the first objective function comprises a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function and an active power line loss function; constraint conditions comprise power and voltage range constraint, node power balance constraint and tide constraint; solving a first multi-objective optimization model to obtain a first active power adjustment quantity and a first active power adjustment quantity of controlled equipment of each node in the wind-solar storage station; if the voltage of the parallel network point is not in the safety interval and the difference value between the voltage and the end point of the safety interval is smaller than a preset threshold value, a second multi-objective optimization model is established according to the real-time value and the target value, and the second multi-objective optimization model comprises a second objective function and constraint conditions; the second objective function comprises a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function, an active power line loss function and an adjusting cost function when active power is actively reduced; and solving the second multi-objective optimization model to obtain a second active power adjustment quantity and a second reactive power adjustment quantity of the controlled equipment of each node in the wind-solar storage station. According to the invention, a multi-objective optimization model which takes into account active power loss, node voltage deviation, active power and reactive power deviation and actively reduces active power adjustment cost is established according to the grid-connected point voltage, so that the minimum adjustment quantity of the active power and the reactive power is solved, and the active and reactive coordination control of the wind-solar energy storage station is realized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of an active-reactive coordination control method for a wind-solar energy storage station according to embodiment 1 of the present invention;
fig. 2 is a schematic flow chart of an active-reactive coordination control method of a wind-solar energy storage station according to embodiment 1 of the present invention;
FIG. 3 is a graph of active power loss of the wind-solar energy storage combined power station provided in embodiment 1 of the present invention;
fig. 4 is a graph of active power output of the wind-solar energy-storage combined power station provided in embodiment 1 of the present invention;
FIG. 5 is a voltage diagram of a node of a wind-solar energy-storage combined power station provided by the embodiment 1 of the invention;
FIG. 6 is a block diagram of an active-reactive coordination control system of a wind-solar energy storage station according to embodiment 1 of the present invention;
fig. 7 is a block diagram of an active-reactive coordination control system of a wind-solar energy storage station according to embodiment 2 of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide an active-reactive coordination control method and system for a wind-solar storage station, which are used for establishing a multi-objective optimization model for calculating active power loss, node voltage deviation, active power and reactive power deviation and actively reducing active power adjustment cost according to grid-connected point voltage so as to solve the minimum adjustment quantity of the active power and the reactive power and realize the active-reactive coordination control of the wind-solar storage station.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Example 1
The embodiment provides an active-reactive coordination control method for a wind-solar energy storage station, referring to fig. 1 and fig. 2, the method comprises the following steps:
step S1: acquiring a real-time value of operation data of a wind-solar energy storage station; the operation data comprise voltage, active power, reactive power of the grid-connected point of the wind-solar storage station, voltage of a collecting line, active power and reactive power.
Step S2: and acquiring a target value of the operation data of the wind-solar storage station issued by the dispatching center.
In this embodiment, the operation data of the wind-solar energy storage station includes information in the wind-driven generator, the photovoltaic inverter, the energy storage converter, the collection line connected to the Static Var Generator (SVG) and the station grid-connected voltage amplitude, the active power value, the reactive power value and the like of the station. And acquiring scheduling information such as a total active power command value, a voltage command value, a reactive power command value and the like of the station issued by the scheduling center, and taking the acquired scheduling information as a target value of the operation data of the wind-solar energy storage station.
Step S3: if the voltage of the grid-connected point is in a safety interval and is not located at an end point of the safety interval, a first multi-objective optimization model is established according to the real-time value and the target value, and the first multi-objective optimization model comprises a first objective function and constraint conditions; the first objective function comprises a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function and an active power line loss function; the constraint conditions comprise power and voltage range constraint, node power balance constraint and power flow constraint.
Step S4: solving the first multi-objective optimization model to obtain a first active power adjustment quantity and a first active power adjustment quantity of controlled equipment of each node in the wind-solar storage station; the controlled equipment comprises a wind driven generator, a photovoltaic inverter, an energy storage converter and a static reactive generator.
Step S5: if the voltage of the point of connection is not in the safety interval and the difference value between the voltage of the point of connection and the end point of the safety interval is smaller than a preset threshold value, a second multi-objective optimization model is established according to the real-time value and the target value, and the second multi-objective optimization model comprises a second objective function and the constraint condition; the second objective function comprises a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function, an active power line loss function and an adjusting cost function when active power is actively reduced.
Step S6: and solving the second multi-objective optimization model to obtain a second active power adjustment quantity and a second reactive power adjustment quantity of the controlled equipment of each node in the wind-solar storage station. The node refers to a node (including a grid-connected point) with great influence on grid-connected point voltage caused by power change at the node, a wind power plant, a photovoltaic power station, energy storage, SVG (static var generator) access to a collecting line position and the like are generally selected, and other nodes meeting the conditions can be added according to actual conditions. The present embodiment selects the V1, V2, V3, V4, and V5 nodes as shown in fig. 6 for active power-reactive power regulation.
Aiming at active and reactive power dispatching coupling of the wind-solar-storage combined power station, the embodiment designs a plurality of operation modes (control modes) and control strategies:
selecting a control mode of the wind-solar storage station according to a scheduling instruction issued by a scheduling system; the wind-solar energy storage station control mode comprises a voltage control mode and a reactive power control mode; the voltage control mode is that the voltage of the grid-connected point and the active power reach the target value; and the reactive power control mode is that the active power and the reactive power of the grid-connected point reach the target values, and the grid-connected point voltage is in the safety interval. The two control modes are specifically as follows:
In a P-V control mode (namely a voltage control mode), the wind-solar energy storage station is used as an integral controlled object, an active power target value and a grid-connected point voltage target value which are issued by scheduling are received, and all controlled devices in the wind-solar energy storage station are coordinated to enable the integral active output and the grid-connected point voltage to reach the target values.
In the P-Q control mode (namely, reactive power control mode), the whole wind-solar energy storage station is used as a PQ node of a power grid, receives an active power target value and a reactive power target value issued by scheduling, and enables the active power and the reactive power output of a grid-connected point to reach the target values, and the grid-connected point voltage only needs to be met within a safe interval at the moment (according to relevant standards, namely, 220kV buses of a power plant and a 500kV substation are used for normal operation, the voltage allowable deviation is 0-10% of the rated voltage of a system, and 110-35 kV buses of the power plant and the 220kV substation are used for normal operation, and the voltage allowable deviation is-3% -7% of the rated voltage of the corresponding system).
Executing different adjustment control strategies according to the current operation mode and the current operation state of the wind-solar storage station:
strategy one: the voltage of the grid-connected point is in the safety interval and is not positioned at the end point of the safety interval, namely, when the voltage of the grid-connected point is in the safety interval and is not positioned at the edge of the safety interval, the active priority is that:
The control strategy firstly takes the minimum active power tracking deviation as a main target, and simultaneously properly considers the voltage deviations of the respective collecting lines and the grid-connected points of wind, light and storage in the station, and the emphasis is on reducing the active power loss in the station and improving the power generation capacity and economy of the station. A first multi-objective optimization model can be established according to the first control strategy, and the first multi-objective optimization model comprises a first objective function and constraint conditions; the first objective function comprises a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function and an active power line loss function; the constraint conditions comprise power and voltage range constraint, node power balance constraint and power flow constraint, wherein the expression of the first objective function can be:
wherein f 1 As a node voltage deviation function, n i To calculate the number of nodes of voltage deviation, H i For node i voltage deviation weight coefficient, V error，i For deviation of voltage amplitude of node i from target voltage amplitude, f 2 Tracking a deviation function for reactive power of a node, n j To calculate the number of nodes of reactive power deviation, G i For the reactive power deviation weight coefficient of the node i, Q error，i For the deviation of the actual reactive power of the node i from the target reactive power, f 3 Tracking a deviation function for node active power, n k To calculate the node number of the active power deviation, M i For node i active power deviation weight coefficient, P error，i For the actual active power and purpose of node iMarking the active power deviation, f 4 As active power line loss function, n l To calculate the number of branches of active power loss of the circuit, P loss，l Is the active power loss on line l.
In the present embodiment, the voltage amplitude of the node i in the first multi-objective model deviates from the target voltage amplitude by V error，i Deviation Q of actual reactive power of node i from target reactive power error，i Deviation P of actual active power of node i from target active power error，i And active power loss P on line l loss，l The calculation formulas of (a) are respectively as follows:
V error，i ＝V i +C VPi ΔP i +C VQi ΔQ i -V ref，i
Q error，i ＝Q i +ΔQ i -Q ref，i
P error，i ＝P i +ΔP i -P ref，i
wherein V is i For the actual voltage at node i, C VPi The active sensitivity is the influence of the active variation quantity of the node i on the node voltage; c (C) VQi For reactive sensitivity, deltaP i Injecting active power adjustment quantity, deltaQ, for node i i Injecting reactive power adjustment quantity for node i, V ref，i A voltage target value at a node i; q (Q) i Injecting reactive power into node i, Q ref，i The reactive power target value of the node i; p (P) i Injecting active power for node i, P ref，i An active power target value for node i; r is R l For the line resistance, I l Is the line current. C (C) VPi The active sensitivity is the influence of the active variation quantity of the node i on the node voltage; c (C) VQi For reactive sensitivity, the calculation formula of the sensitivity is as follows:
the following is the procedure for establishing the constraint conditions in this embodiment:
(1) The expression for power and voltage range constraints may be:
wherein,for the minimum and maximum value of the active power of the controlled power supply at node i, +.> Respectively minimum value and maximum value of reactive power of controlled power supply at node i, +.>The minimum value and the maximum value of the controlled power supply voltage at the node i are respectively, and the controlled power supply comprises a wind driven generator, a photovoltaic inverter and an energy storage converter.
In this embodiment, the maximum and minimum values of the controlled supply voltage at node i in the power and voltage range constraints described above are determined by real-time values of the operational data of the wind and solar energy storage station. The calculation formulas of the minimum value and the maximum value of the active power of the controlled power at the node i and the minimum value and the maximum value of the reactive power of the controlled power at the node i can be respectively:
wherein P is i min Active power minimum value of controlled power supply at node i, n wind For the number of wind power generators of the node i,is the minimum value of the active power of the wind driven generator, n pv For the number of photovoltaic inverters at node i, < +. >Is the minimum value of active power of the photovoltaic inverter, n ess For node i the number of energy storage converters, < >>The active power of the energy storage converter is the minimum value; p (P) i max For the maximum value of the active power of the controlled power supply at node i, < >>For maximum active power of wind power generator, +.>For maximum active power of the photovoltaic inverter, < +.>The maximum value of active power of the energy storage converter; />For the minimum value of reactive power of the controlled power supply at node i, < > for>Reactive power minimum and maximum of wind power generator respectively, +.>Minimum and maximum reactive power of the photovoltaic inverter, respectively, +.>Respectively the minimum value and the maximum value of reactive power of the energy storage converter; n is n svg For the number of static var generators at node i, < >>Reactive power minimum and maximum values for the number of static reactive generators respectively; n is n g The number of reactive devices remaining for node i, +.> And respectively obtaining the minimum value and the maximum value of reactive power of the residual reactive power equipment of the node i, wherein the residual reactive power equipment refers to reactive power equipment except for a static reactive power generator in the wind-solar storage station.
(2) The expression for the node power balancing constraint may be:
Q i ＝Q wind，i +Q pv，i +Q ess，i +Q svg，i +Q g，i -Q l，i
wherein P is i And Q i Active and reactive injection power, P, respectively, of node i wind，i And Q wind，i The wind driven generator respectively outputs active power and reactive power for the node i; p (P) pv，i And Q pv，i The output active power and reactive power of the photovoltaic inverter are respectively node i;and->Discharging and charging active power for energy storage converter of node i, Q ess，i The reactive power is output by the energy storage converter; q (Q) svg，i The output reactive power of the static reactive generator of the node i; q (Q) g，i Reactive power of the remaining reactive devices for node i; p (P) l，i And Q l，i The active load and the reactive load of the node i.
(3) The expression of the tide constraint can be:
wherein u (j) is a set of flow direction nodes j; p (P) ij And Q ij Respectively represent the active power flowing from node i to node jRate and reactive power; r is R ij And X ij Respectively representing the short circuit resistance and the short circuit reactance between the node i and the node j; v (V) i And V j Representing the voltage effective values of the node i and the node j; v (j) is the set of flows flowing out of node j; p (P) jk And Q jk Representing the active power and reactive power of node j flowing to node k, respectively.
Aiming at the active and reactive coupling characteristics of part of wind, light and storage, the embodiment provides a control strategy II for actively reducing the active power when the available reactive power is insufficient:
the voltage of the grid-connected point is not in the safety interval and the difference value between the voltage of the grid-connected point and the end point of the safety interval is smaller than a preset threshold value, namely the voltage of the grid-connected point is close to the edge of the safety interval, and reactive power is preferential:
And the second control strategy takes stable grid-connected point and in-station node collecting line voltage as main targets, and when power is regulated, reactive power requirements are preferably met. Since wind generators, photovoltaic inverters and energy storage converters have active-reactive coupling characteristics, in which the reactive maximum/minimum range of a portion is inversely proportional to the active real power value, when the reactive capacities of the in-station controllable power supply and reactive devices are insufficient, the active power output of a portion of wind, light and storage is actively reduced to improve the reactive power regulation capacity of the system, and the operation is performed while the adjustment cost of the active power is reduced. And a second multi-objective control model can be established according to a second control strategy, and the expression of the second objective function is as follows:
wherein f 5 To actively reduce the adjustment cost function, P cur，i Active power actively reduced for device i, T i To adjust the cost coefficient, n c The number of active power sources that actively reduce active power.
In this implementation, before the solving the first multi-objective optimization model, the method further includes step S41:
and respectively determining first weights of a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function and an active power line loss function in the first objective function according to the control mode of the wind-solar storage station. And carrying out weighted summation on the node voltage deviation function, the node reactive power tracking deviation function, the node active power tracking deviation function and the active power line loss function in the first objective function according to the first weight to obtain an optimized first objective function. And establishing an optimized first multi-objective optimization model according to the optimized first objective function, and taking the optimized first multi-objective optimization model as a new first multi-objective optimization model.
Before the solving of the second multi-objective optimization model, the method further includes step S61:
and determining a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function, an active power line loss function and a second weight of an adjusting cost function when active power is actively reduced in the second objective function according to the control mode of the wind-solar energy storage station. And carrying out weighted summation on the node voltage deviation function, the node reactive power tracking deviation function, the node active power tracking deviation function, the active power line loss function and the adjusting cost function when active power is actively reduced in the second objective function according to the second weight to obtain an optimized second objective function. And establishing an optimized second multi-objective optimization model according to the optimized second objective function, and taking the optimized second multi-objective optimization model as a new second multi-objective optimization model.
In the present embodiment, step S41 and step S61 may be specifically as follows:
the optimized objective function is as follows:
and the weights satisfy the constraint conditions as shown below:
wherein,the method is characterized in that the method comprises the steps of respectively normalizing a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function, an active power line loss function and an adjusting cost function when active power is reduced, wherein alpha, beta, gamma, theta and lambda are respectively weight coefficients of a power supply deviation function, a reactive deviation function, an active deviation function, a line active loss function and an active power reducing function, different optimization targets can be realized by adjusting a plurality of weight values, when a control strategy is executed, active priority is given, so that lambda is set to 0, and meanwhile, the numerical values of gamma and theta are properly improved; when the second control strategy is executed, reactive priority is given to the proper increase of the values of alpha, beta and lambda. In addition, regardless of the control strategy, the P-Q control mode is adapted to boost the magnitude of the value of β for the selected P-V control mode.
In this embodiment, an intelligent algorithm or a commercial solver is selected to solve the optimized first multi-objective optimization model and the optimized second multi-objective optimization model, so as to obtain an active power adjustment amount and a reactive power adjustment amount, the active power adjustment amount and the reactive power adjustment amount are output to corresponding units, and the next round of optimization calculation is performed by returning to the step S1.
Compared with the conventional wind-solar-storage combined power station control strategy which only focuses on the grid-connected point active output and voltage amplitude, the method adopts the active-reactive coordination control strategy which takes account of node information in the station, establishes a multi-objective optimization model from the global angle, and enables an objective function to be matched with the current working condition according to different switching parameters of the working condition, the method effectively reduces the overall active loss of the system, as shown in figure 3, and causes more energy storage, more charge and less discharge due to the reduction of the active loss, as shown in figure 4, thereby being beneficial to improving the wind-solar absorption capacity and increasing the economic benefit.
Because the global information of the station is considered and a multi-objective optimization model comprising the voltage amplitude deviation of a plurality of nodes in the station is established, compared with the conventional control strategy only focusing on the grid-connected point voltage of the wind-solar storage station, the method can enable the voltage deviation of a plurality of nodes in the station (nodes 1, 2 and 3 in fig. 5 in the embodiment are respectively V1, V2 and V3 in fig. 6) to be maintained in a safe interval and enable the change trend to be smoother, as shown in fig. 5. In addition, the conventional control strategy can ensure that the voltage of a grid-connected point cannot be stably controlled due to insufficient reactive power capacity in a station so as to fluctuate a safety range (the middle area of two dotted lines in fig. 5 is a voltage qualified zone), the invention provides a reactive power regulation capability of a system by reducing the active power of part of equipment (the maximum reactive power and the minimum reactive power of the equipment are inversely proportional to the current active power output of the equipment) aiming at the working condition, so as to ensure that the voltage is always maintained in the safety range, fig. 6 shows an example of an active-reactive coordination control system structure of a wind-solar storage station, wherein V1 is the grid-connected point of the wind-solar storage station, V2 is a wind-driven generator collection line node, V3 is a photovoltaic inverter collection line node, V4 is an energy storage converter collection line node, and V5 is a static reactive power generator collection line node, and 220kV and the grid-point and 35kV collection line represent different voltage levels of the wind-solar storage station.
The invention provides an active-reactive coordination control method for a wind-solar energy storage station. Two control modes are designed aiming at the integrated characteristic of the combined power station, active priority or reactive priority control strategies are executed according to the control modes and the running states, a multi-objective optimization model which takes into account active power loss, node voltage deviation, active power and reactive power deviation and actively reduces the active power adjustment cost is established based on different control strategies, corresponding multi-objective optimization models are switched and solved according to different scenes, active and reactive coordination control of the combined power station can be achieved, power and voltage distribution in the station is optimized, and running economy and safety stability of the system are effectively improved. The invention also provides a control strategy for actively reducing the reactive power output capability of the wind-solar energy storage active power lifting system when the available reactive power in the station is insufficient, and the strategy is beneficial to deeply excavating the reactive power adjustment capability of wind, light and storage, so that the capacity allocation of a reactive power compensation device can be reduced, and the construction and operation costs of the combined power station are saved.
Example 2
The embodiment provides an active-reactive coordination control system of a wind-solar energy storage station, referring to fig. 7, the system comprises:
The real-time value acquisition module T1 is used for acquiring a real-time value of the operation data of the wind-solar storage station; the operation data comprise voltage, active power, reactive power of the grid-connected point of the wind-solar storage station, voltage of a collecting line, active power and reactive power.
The target value obtaining module T2 is used for obtaining a target value of the wind-solar storage station operation data issued by the dispatching center.
The first multi-objective optimization model building module T3 is configured to build a first multi-objective optimization model according to the real-time value and the target value if the voltage of the grid-connected point is within a safe interval and is not located at an endpoint of the safe interval, where the first multi-objective optimization model includes a first objective function and a constraint condition; the first objective function comprises a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function and an active power line loss function; the constraint conditions comprise power and voltage range constraint, node power balance constraint and power flow constraint.
The first adjustment quantity acquisition module T4 is used for solving the first multi-objective optimization model to obtain a first active power adjustment quantity and a first active power adjustment quantity of controlled equipment of each node in the wind-solar storage station; the controlled equipment comprises a wind driven generator, a photovoltaic inverter, an energy storage converter and a static reactive generator.
A second multi-objective optimization model building module T5, configured to build a second multi-objective optimization model according to the real-time value and the target value if the voltage of the point of presence is not within the safety interval and the difference between the voltage of the point of presence and the end point of the safety interval is less than a preset threshold, where the second multi-objective optimization model includes a second objective function and the constraint condition; the second objective function comprises a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function, an active power line loss function and an adjusting cost function when active power is actively reduced.
And the second adjustment quantity acquisition module T6 is used for solving the second multi-objective optimization model to obtain a second active power adjustment quantity and a second reactive power adjustment quantity of the controlled equipment of each node in the wind-solar storage station.
For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (10)
1. An active-reactive coordination control method for a wind-solar energy storage station is characterized by comprising the following steps:
acquiring a real-time value of operation data of a wind-solar energy storage station; the operation data comprise voltage, active power, reactive power of a grid-connected point of the wind-solar storage station, voltage of a collecting line, active power and reactive power;
acquiring a target value of wind-light storage station operation data issued by a dispatching center;
if the voltage of the grid-connected point is in a safety interval and is not located at an end point of the safety interval, a first multi-objective optimization model is established according to the real-time value and the target value, and the first multi-objective optimization model comprises a first objective function and constraint conditions; the first objective function comprises a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function and an active power line loss function; the constraint conditions comprise power and voltage range constraint, node power balance constraint and power flow constraint;
solving the first multi-objective optimization model to obtain a first active power adjustment quantity and a first active power adjustment quantity of controlled equipment of each node in the wind-solar storage station; the controlled equipment comprises a wind driven generator, a photovoltaic inverter, an energy storage converter and a static reactive generator;
If the voltage of the point of connection is not in the safety interval and the difference value between the voltage of the point of connection and the end point of the safety interval is smaller than a preset threshold value, a second multi-objective optimization model is established according to the real-time value and the target value, and the second multi-objective optimization model comprises a second objective function and the constraint condition; the second objective function comprises a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function, an active power line loss function and an adjusting cost function when active power is actively reduced;
and solving the second multi-objective optimization model to obtain a second active power adjustment quantity and a second reactive power adjustment quantity of the controlled equipment of each node in the wind-solar storage station.
2. The active-reactive coordination control method of a wind-solar energy storage station according to claim 1, further comprising:
selecting a control mode of the wind-solar storage station according to a scheduling instruction issued by a scheduling system; the wind-solar energy storage station control mode comprises a voltage control mode and a reactive power control mode; the voltage control mode is that the voltage of the grid-connected point and the active power reach the target value; and the reactive power control mode is that the active power and the reactive power of the grid-connected point reach the target values, and the grid-connected point voltage is in the safety interval.
3. The method of active-reactive coordination control of a wind and solar energy storage farm according to claim 2, further comprising, prior to said solving the first multi-objective optimization model:
respectively determining first weights of a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function and an active power line loss function in the first objective function according to the control mode of the wind-solar energy storage station;
carrying out weighted summation on a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function and an active power line loss function in the first objective function according to the first weight to obtain an optimized first objective function;
establishing an optimized first multi-objective optimization model according to the optimized first objective function, and taking the optimized first multi-objective optimization model as a new first multi-objective optimization model;
before the solving the second multi-objective optimization model, the method further includes:
determining a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function, an active power line loss function and a second weight of an adjusting cost function when active power is actively reduced in the second objective function according to the control mode of the wind-solar energy storage station;
According to the second weight, carrying out weighted summation on a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function, an active power line loss function and an adjusting cost function when active power is actively reduced in the second objective function, so as to obtain an optimized second objective function;
and establishing an optimized second multi-objective optimization model according to the optimized second objective function, and taking the optimized second multi-objective optimization model as a new second multi-objective optimization model.
4. The active-reactive coordination control method of a wind-solar energy storage station according to claim 1, wherein the expression of the first objective function is:
wherein f 1 As a node voltage deviation function, n i To calculate the number of nodes of voltage deviation, H i For node i voltage deviation weight coefficient, V error，i For deviation of voltage amplitude of node i from target voltage amplitude, f 2 Tracking a deviation function for reactive power of a node, n j To calculate the number of nodes of reactive power deviation, G i For the reactive power deviation weight coefficient of the node i, Q error，i For the deviation of the actual reactive power of the node i from the target reactive power, f 3 Tracking a deviation function for node active power, n k To calculate the node number of the active power deviation, M i For node i active power deviation weight coefficient, P error，i For the deviation of the actual active power of the node i from the target active power, f 4 As active power line loss function, n l To calculate the number of branches of active power loss of the circuit, P loss，l Active power loss on line l; ΔP i Injecting active power adjustment quantity, deltaQ, for node i i And injecting reactive power adjustment quantity into the node i.
5. The active-reactive coordination control method of the wind-solar energy storage station according to claim 4, wherein the expression of the second objective function is:
wherein f 5 To actively reduce the adjustment cost function, P cur，i Active power actively reduced for device i, T i To adjust the cost coefficient, n c The number of active power sources that actively reduce active power.
6. The active-reactive coordination control method of a wind-solar energy storage station according to claim 1, wherein the power and voltage range constraint expression is:
wherein,for the minimum and maximum value of the active power of the controlled power supply at node i, +.> Respectively minimum value and maximum value of reactive power of controlled power supply at node i, +.>The minimum value and the maximum value of the controlled power supply voltage at the node i are respectively, and the controlled power supply comprises a wind driven generator, a photovoltaic inverter and an energy storage converter.
7. The active-reactive coordination control method of the wind-solar energy storage station according to claim 6, wherein the calculation formulas of the minimum and maximum active power values of the controlled power supply at the node i and the minimum and maximum reactive power values of the controlled power supply at the node i are respectively:
wherein P is i min Active power minimum value of controlled power supply at node i, n wind For the number of wind power generators of the node i,is the minimum value of the active power of the wind driven generator, n pv For the number of photovoltaic inverters at node i, < +.>Is the minimum value of active power of the photovoltaic inverter, n ess For node i the number of energy storage converters, < >>The active power minimum value of the energy storage converter; p (P) i max For the maximum value of the active power of the controlled power supply at node i, < >>For maximum active power of wind power generator, +.>For maximum active power of the photovoltaic inverter, < +.>The maximum value of active power of the energy storage converter; q (Q) i min For the controlled supply reactive power minimum at node i,the minimum value and the maximum value of reactive power of the wind driven generator are respectively; />Minimum and maximum reactive power of the photovoltaic inverter, respectively, +.>Respectively the minimum value and the maximum value of reactive power of the energy storage converter; n is n svg For the number of static var generators at node i, < > >Reactive power minimum and maximum values for the number of static reactive generators respectively; n is n g The number of reactive devices remaining for node i, +.>And the minimum value and the maximum value of reactive power of the residual reactive power equipment of the node i are respectively, and the residual reactive power equipment is reactive power equipment except a static reactive power generator in the wind-light storage station.
8. The active-reactive coordination control method of a wind-solar energy storage station according to claim 1, wherein the expression of the node power balance constraint is:
Q i ＝Q uind,i +Q pu,i +Q ess,i +Q svg,i +Q g，i -Q l，i
wherein P is i And Q i Active and reactive injection power, P, respectively, of node i wind，i And Q wind，i The wind driven generator respectively outputs active power and reactive power for the node i; p (P) pv，i And Q pv，i The output active power and reactive power of the photovoltaic inverter are respectively node i;and->Discharging and charging active power for energy storage of node i, Q ess，i The reactive power is output by the energy storage converter; q (Q) svg，i The output reactive power of the static reactive generator of the node i; q (Q) g，i Reactive power of the remaining reactive devices for node i; p (P) l，i And Q l，i And the residual reactive equipment is reactive equipment except for a static reactive generator in the wind-light storage station.
9. The active-reactive coordination control method of a wind-solar energy storage station according to claim 1, wherein the expression of the power flow constraint is:
Wherein u (j) is a set of flow direction nodes j; p (P) ij And Q ij Respectively representing the active power and the reactive power of the node i flowing to the node j; r is R ij And X ij Respectively representing the short circuit resistance and the short circuit reactance between the node i and the node j; v (V) i And V j Representing the voltage effective values of the node i and the node j; v (j) is the set of flows flowing out of node j; p (P) jk And Q jk Representing the active power and reactive power of node j flowing to node k, respectively.
10. An active-reactive coordination control system for a wind-solar energy storage station, comprising:
the real-time value acquisition module is used for acquiring the real-time value of the operation data of the wind-solar storage station; the operation data comprise voltage, active power, reactive power of a grid-connected point of the wind-solar storage station, voltage of a collecting line, active power and reactive power;
the target value acquisition module is used for acquiring a target value of the wind-solar storage station operation data issued by the dispatching center;
the first multi-objective optimization model building module is used for building a first multi-objective optimization model according to the real-time value and the target value if the voltage of the grid-connected point is in a safety interval and is not located at an endpoint of the safety interval, wherein the first multi-objective optimization model comprises a first objective function and constraint conditions; the first objective function comprises a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function and an active power line loss function; the constraint conditions comprise power and voltage range constraint, node power balance constraint and power flow constraint;
The first adjustment quantity acquisition module is used for solving the first multi-objective optimization model to obtain a first active power adjustment quantity and a first active power adjustment quantity of controlled equipment of each node in the wind-solar storage station; the controlled equipment comprises a wind driven generator, a photovoltaic inverter, an energy storage converter and a static reactive generator;
the second multi-objective optimization model building module is used for building a second multi-objective optimization model according to the real-time value and the target value if the voltage of the grid-connected point is not in the safety interval and the difference value between the voltage of the grid-connected point and the end point of the safety interval is smaller than a preset threshold value, wherein the second multi-objective optimization model comprises a second objective function and the constraint condition; the second objective function comprises a node voltage deviation function, a node reactive power tracking deviation function, a node active power tracking deviation function, an active power line loss function and an adjusting cost function when active power is actively reduced;
and the second adjustment quantity acquisition module is used for solving the second multi-objective optimization model to obtain a second active power adjustment quantity and a second reactive power adjustment quantity of the controlled equipment of each node in the wind-solar storage station.
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| 风光储电站全景监测与综合控制技术分析;任巍曦;寇建;王婧;吴宇辉;;华北电力技术(10);第52-56页 * |
| 风光储联合发电监控***功能设计与应用;於益军;雷为民;单茂华;庄卫金;滕贤亮;黄华;;电力***自动化(20);第32-38页 * |
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