CN111509743B - Control method for improving stability of power grid by using energy storage device - Google Patents
Control method for improving stability of power grid by using energy storage device 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
- H02J3/28—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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
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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
- 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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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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Abstract
The invention relates to the technical field of smart power grids, and discloses a control method for improving the stability of a power grid by using an energy storage device. The method adopts a double-layer control method, a stable control layer is controlled in a short time scale, control factors are system stability, wind power and photovoltaic output of a system and load and voltage fluctuation values of power users are tracked, energy storage active power and reactive power are obtained through tide calculation and a particle swarm algorithm, the energy storage active power and reactive power are fed back to an energy storage device grid-connected inverter interface to serve as reference values, and when load mutation occurs, the energy storage system can give response in preference to other power generation equipment of the system according to the reference values. The optimization control layer is used for long-time scale control, the system stability, economy and the real-time state and service life of the energy storage system are comprehensively considered, the charge and discharge power and the residual capacity of the energy storage are obtained through a particle swarm algorithm, the result obtained by the stability control layer is optimized, the energy storage detection control module is uploaded, and the operation mode and the charge and discharge power are finally determined.
Description
Technical Field
The invention relates to a method for improving new energy consumption to improve the stability of a power grid, in particular to a control method for improving the stability of the power grid by applying an energy storage device.
Background
At present, new energy development is rapid, a large amount of wind power and photovoltaic are connected into a power grid, some areas even all rely on the new energy to supply power to power users, but the connection of a large amount of intermittent energy can lead to severe fluctuation of power grid voltage and frequency, and the electric energy system generated by the new energy can not be completely consumed, so that energy waste is caused, and the energy storage system is established at the power grid side. The response speed of the energy storage system is very rapid, the energy storage system can timely output according to the change of the load and the output conditions of other power supplies of the system, can bear the influence of abrupt load on the stability of the system, and plays an important role in improving the stability of a power grid, increasing new energy consumption and reducing the output of thermal power generation.
The energy storage detection control module is additionally arranged in the power distribution network system with the same voltage level, so that the real-time state of each node connected with the energy storage power station under the voltage level can be effectively monitored, unified allocation is carried out according to the availability of the residual capacity, unnecessary charge and discharge times of energy storage are reduced, and the service life of the energy storage system is prolonged.
The BESS charge and discharge optimization control model in the active power distribution network is provided in the optimal charge and discharge strategy of a battery energy storage system in the active power distribution network (40 th roll, 20 th page and 49 th page of power system automation). The method mainly aims at economy, considers the difference of time-of-use electricity price and selling electricity price, and aims at minimum sum of electricity purchase cost of the distribution network and BESS equivalent cost in the running process. Although the method realizes economic operation of the BESS, the BESS is only taken as a control condition when the charge and discharge depth of the stored energy is considered, a specific charge and discharge control strategy mode is not proposed, and the energy storage system in the power distribution network system cannot be planned in an overall mode.
A method and a device for controlling the output of an energy storage system of a power grid (Chinese patent: CN 107872065B) provide an output mode of the energy storage system. The energy storage system mainly tracks the output of the generator set, and the energy storage system has the functions of reducing the operation cost and prolonging the operation life of the energy storage according to the mutual adjustment between different operation modes of the energy storage and the output deviation of the generator set. However, the method only focuses on the generator set, and does not connect various power generation systems in the power distribution system with each other, so that the power deviation between each power generation system and the load is reduced by utilizing the energy storage system from the power distribution network as a whole, and the purpose of running economy is achieved.
Disclosure of Invention
The invention aims to: aiming at the problems in the prior art, the invention provides a control method for improving the stability of a power grid by using an energy storage device, which can timely regulate the severe fluctuation energy generated by sudden load changes of system voltage and frequency through double-layer control and can also improve the economic operation and the distributed energy loss rate of the power grid. The energy storage charging and discharging power and the residual capacity at each moment are solved and optimized in a double-layer mode through a particle swarm algorithm, and are uploaded to an energy storage detection module, and the operation mode of each energy storage power station is finally selected by the energy storage detection module, so that the purpose of reducing the charging and discharging times of an energy storage system is achieved, and the service life of energy storage is prolonged.
The technical scheme is as follows: the invention provides a control method for improving the stability of a power distribution network by using an energy storage device, wherein the power distribution network is internally provided with a distributed energy source, the energy storage device and traditional power generation equipment, and an energy storage detection control module is arranged, and the energy storage device comprises a grid-connected inverter, an energy storage battery pack, a battery management system and an energy management system;
the battery management system of each energy storage power station is in information interconnection with the energy storage detection control module, the real-time state of the SOC is uploaded to the energy storage detection control module, the energy storage detection control module issues a scheduling instruction to each energy storage power station, determines the charge and discharge power and the operation mode at the next moment according to the operation state and the residual capacity state of each energy storage power station at the moment, and issues the charge and discharge power and the operation mode to the energy management system of each energy storage power station;
the control method is a double-layer control mode and is divided into a stable control layer and an optimal control layer, the optimal control layer further optimizes the result of the stable control layer, and the specific control method is as follows:
the stable control layer is an outer layer of the particle swarm algorithm, the system voltage fluctuation suddenly exceeds the safety range, the state is not maintained for a long time, and the control layer acts; selecting impedance values, wind power and photovoltaic grid-connected positions and output among lines of a system, loads of power users, number, positions, power and capacity of energy storage power stations as input conditions, taking a system voltage fluctuation value delta U as an objective function, obtaining active power and reactive power required to be stored and supported by a power grid through load flow calculation and a particle swarm algorithm, and feeding back to a grid-connected inverter interface as a reference value; when the system has load mutation, the energy storage system gives response in preference to the distributed energy sources and the traditional power generation equipment in the system according to the reference value;
the optimization control layer is the inner layer optimization of the particle swarm algorithm, the system stably operates for a long time, and the control layer acts; and the voltage fluctuation is minimum and within a reasonable range, the power support required by the energy storage of the system is solved through the stable control layer, the economical efficiency and the distributed energy loss rate are taken as an objective function, the real-time updating state and the service life of the SOC of the energy storage system are calculated, the energy storage charging and discharging power reference value is solved through a particle swarm algorithm, the result obtained by the stable control layer is optimized, and the charging and discharging power and the running mode of the energy storage system are finally determined through the energy storage detection control module.
Further, the formula of the voltage fluctuation value DeltaU of the objective function system is as follows:
wherein N is nod The node number of the power distribution network; v (V) m_ref A reference value for the voltage at node m; v (V) m Is the actual value of the voltage at node m; v (V) m_max ，V m_min Respectively the highest and lowest limit values of the node voltage amplitude.
Further, the stable control layer is required to function under the following control conditions:
1) The energy storage charge-discharge power and the state of charge SOC need to meet the following control conditions:
P jmin_ch ≤P j_ch ≤P jmax_ch
P jmin_dis ≤P j_dis ≤P jmax_dis
SOC j_min ≤SOC j ≤SOC j_max
wherein P is jmin_ch 、P jmax_ch The minimum value, the maximum value and the P of the charging power of the j energy storage power station jmin_dis 、P jmax_dis The discharge power of the j energy storage power station is minimum value, maximum value and P j_ch 、P j_dis For the charge and discharge power of the j energy storage power station, SOC j_min 、SOC j_max The minimum value, the maximum value and the SOC of the j energy storage power stations j The state of charge of the energy storage power station is j;
2) The state of charge at time i and the state of charge at time i+1 of the energy storage system satisfy the following conditions:
wherein E is j_bess Refers to rated capacity, eta of the j energy storage power station ch Refer to the charging efficiency, eta dis Referring to the discharge efficiency, Δi is the time interval between time i and time i+1;
3) Power balance of each node in the system:
wherein P is m ，Q m Active power and reactive power are respectively injected into the node m; u (U) m ，U n For voltages at nodes m, n, θ m ，θ n For the phase angles of nodes m, n, G mn ，B mn The real part and the imaginary part of m rows and n columns of the node admittance matrix are respectively; y is the number of nodes;
4) The capacity of the j energy storage power station at the moment i meets the following control conditions:
in the method, in the process of the invention,
for the i moment capacity of the j energy storage power station E j_min For minimum capacity of j energy storage power station E j_max And the maximum capacity of the j energy storage power station.
Further, the objective function in the optimization control layer is as follows:
wherein omega 1 、ω 2 For the inertia weight, the Delphi method is adopted for determining the inertia weight, the importance of each index is assessed, and finally the weight coefficients of the active network loss and the distributed energy loss rate are determined;
P loss the effective network loss is an influence factor of economy in the optimal control layer, and the expression is as follows:
wherein N is b The number of branches of the system is the number of branches; g b (m, n) is the conductance of the b-th leg connecting nodes m, n; v (V) m ，V n The voltage amplitudes of nodes m, n, respectively; θ mn Is the voltage phase angle difference between nodes m, n;
W m_new for the distributed energy loss rate in the optimal control layer, the expression is as follows:
N new the number of new energy power stations in the power distribution network;
the predicted value of the active output of the new energy power station hung on the mth node; p (P) m_new And the actual value of the active output of the new energy power station is hung on the ith node.
Further, the energy storage detection control module is provided with five operation modes for giving operation commands to each energy storage power station, wherein the operation commands are a charging only mode, a discharging only mode, a charging rate slowing mode, a discharging rate slowing mode and a normal mode respectively.
Further, the specific execution conditions of the five operation modes of the energy storage detection control module are as follows:
1) Charging onlyMode: when the capacity of the energy storage system is lambda j_low E j_bess When the charging mode is executed, the charging power is the maximum charging power P jmax_ch When the capacity of the energy storage system reaches
When this mode ends; wherein lambda is j_low Refers to the lower limit coefficient set for avoiding overdischarge, < ->
Critical coefficient of energy storage system entering charge slow down mode, E j_bess The capacity of the energy storage power station is j;
2) Discharge only mode: when the capacity of the energy storage system is lambda j_high E j_bess When a discharge-only mode is executed, the discharge power is the maximum discharge power P jmax_dis When the capacity of the energy storage system reaches
This mode ends; wherein lambda is j_high Refers to the upper limit coefficient set for avoiding overcharge, < >>
Is a critical system for the energy storage system to enter a discharge slowing mode.
3) Charge rate slow down mode: when the capacity of the energy storage system is
When the battery still needs to be charged up,
slowing down the charge rate as a buffer zone which will reach the upper charge limit, the charge power at that time
P j_ch The expression is as follows:
4) Discharge rate slowing mode: when the capacity of the energy storage system is
When the discharge is still needed, the discharge rate is slowed down as a buffer zone reaching the upper limit of discharge, and the discharge power P at the moment j_dis The expression is as follows:
5) Normal mode: the energy storage system has the capacity of
At this time, the energy storage system can be charged and discharged, and the charging and discharging power is the maximum charging and discharging power.
The beneficial effects are that:
1. the control mode of the invention is a double-layer control mode, which is divided into a stable control layer and an optimal control layer, and the optimal control layer optimizes the result of the stable control layer. The stable control layer and the optimized control layer are respectively short-time scale control and long-time scale control, so that the energy storage system can rapidly respond to emergency and avoid excessive reaction of the energy storage system.
2. The stable control layer is a particle swarm algorithm outer layer, and is used for maintaining the stability of the system voltage and frequency under the sudden situation of sudden load change and the like, avoiding the serious influence on other power users as the current key point, and the stable control layer can directly feed back the energy storage active power and reactive power solved by the algorithm to the grid-connected inverter interface at the moment, so that the energy storage system can quickly respond by utilizing the characteristics of the energy storage system, and the system response time is reduced.
3. According to the invention, the optimal control layer is a particle swarm algorithm double-layer optimal result, the voltage fluctuation condition of each node is calculated by the outer layer, the running economy of the power grid, the distributed energy consumption rate and the energy storage charge state are considered by the inner layer, the utilization rate of the energy storage system is improved, excessive use is avoided, and the service life of the energy storage device is prolonged.
Drawings
FIG. 1 is a diagram of a distributed power distribution of an IEEE33 node system in accordance with an embodiment of the present invention;
FIG. 2 is an operational mode of the energy storage power station;
fig. 3 is a specific implementation flow of the control method proposed in the present invention.
Detailed Description
The present invention will be described in detail with reference to the accompanying drawings.
In order to more clearly describe the present invention, an IEEE33 node system is taken as an example, and the distribution diagram of the IEEE33 node system is shown in fig. 1. The total active load of the system is 3715kW, the reactive load is 2300kvar, the reference voltage is 12.66kV, and the allowable range of the node voltage is 0.95-1.05 p.u. The system nodes 6 and 25 are connected with photovoltaic power stations in a hanging mode, rated power of each photovoltaic power station is 300kW, the nodes 12 and 29 are connected with wind power stations in a hanging mode, rated power of each wind power station is 400kW, the nodes 7, 13 and 27 are connected with energy storage power stations in a hanging mode, the upper limit of charging and discharging power of each group of energy storage system devices is 500kW, and the capacity of each group of energy storage system devices is 1MW.
It can be seen that the distributed power supply in the system comprises wind power, photovoltaic and energy storage, because wind and photovoltaic power generation is intermittent and cannot follow the required output of the load, not only can a certain impact be generated on the system, but also energy waste can be caused, the phenomenon can be improved by the energy storage power station in the system, the system stability is improved, and the consumption of the distributed energy output in the system is increased. Meanwhile, an energy storage detection control module is additionally arranged in the system and used for allocating each energy storage power station.
In the control method, a distributed energy source, an energy storage device and traditional power generation equipment are integrated in a power distribution network, an energy storage detection control module is arranged, a scheduling instruction is issued to each energy storage power station, the operation mode of each energy storage power station is determined, and the energy storage device comprises a grid-connected inverter, an energy storage battery pack, a battery management system and an energy management system. The battery management system of each energy storage power station is in information interconnection with the energy storage detection control module, the real-time state of the SOC is uploaded to the energy storage detection control module, the energy storage detection control module issues a scheduling instruction to each energy storage power station, and according to the running state and the residual capacity state of each energy storage power station at the moment, the charging and discharging power and the running mode at the next moment are determined and are issued to the energy management system of each energy storage power station.
The control method is a double-layer control mode and is divided into a stable control layer and an optimal control layer, and the optimal control layer further optimizes the result of the stable control layer, and the process is as follows:
1. stability control layer: it is a short time scale control, i.e. the system voltage fluctuation suddenly exceeds the safety range, and this state is not maintained for a long time, and this control layer acts. The control target is system stability, impedance values among all lines of the system, wind power and photovoltaic grid-connected positions and output, loads of power users, the number, positions, power and capacity of energy storage power stations are selected as input conditions, system voltage fluctuation values are used as target functions, active power and reactive power which are needed to be stored and supported by a power grid are obtained through tide calculation and a particle swarm algorithm, and the active power and the reactive power are fed back to an energy storage device grid-connected inverter interface to serve as reference values. When the system is suddenly changed in load, the energy storage system rapidly responds to the reference value in preference to the distributed energy sources and the traditional power generation equipment in the system.
Wherein, the objective function voltage fluctuation value DeltaU of the stable control layer is expressed as follows:
wherein N is nod The node number of the power distribution network; v (V) m_ref A reference value for the voltage at node m; v (V) m Is the actual value of the voltage at node m; v (V) m_max ，V m_min Respectively the highest and lowest limit values of the node voltage amplitude.
The control conditions that the stability control layer needs to meet are as follows:
1) The energy storage charge-discharge power and the state of charge SOC need to meet the following control conditions:
P jmin_ch ≤P j_ch ≤P jmax_ch
P jmin_dis ≤P j_dis ≤P jmax_dis
SOC j_min ≤SOC j ≤SOC j_max
wherein P is jmin_ch 、P jmax_ch The minimum value, the maximum value and the P of the charging power of the j energy storage power station jmin_dis 、P jmax_dis The discharge power of the j energy storage power station is minimum value, maximum value and P j_ch 、P j_dis For the charge and discharge power of the j energy storage power station, SOC j_min 、SOC j_max The minimum value, the maximum value and the SOC of the j energy storage power stations j And the state of charge of the energy storage power station j.
2) The state of charge at time i and the state of charge at time i+1 of the energy storage system satisfy the following conditions:
wherein E is j_bess Refers to rated capacity, eta of the j energy storage power station ch Refer to the charging efficiency, eta dis Refers to the discharge efficiency.
3) Power balance of each node in the system:
wherein P is m ，Q m Active power and reactive power are respectively injected into the node m; u (U) m ，U n For voltages at nodes m, n, θ m ，θ n For the phase angles of nodes m, n, G mn ，B mn The real part and the imaginary part of m rows and n columns of the node admittance matrix are respectively; y is the number of nodes.
4) The capacity of the j energy storage power station at the moment i meets the following control conditions:
in the method, in the process of the invention,
for the i moment capacity of the j energy storage power station E j_min For minimum capacity of j energy storage power station E j_max And the maximum capacity of the j energy storage power station.
The stable control layer realizes the following specific processes:
the stable control layer is essentially an outer layer of a particle swarm algorithm, a system node model is built through inputting specific information of impedance values among lines of a system, wind power and photovoltaic grid-connected positions and output, loads of power users, the number, positions, power and capacity of energy storage power stations, active power and reactive power of each energy storage power station when voltage fluctuation is minimum under the constraint of the control conditions, and the active power and the reactive power are used as an inverter interface input reference value. When the sudden fluctuation of the system voltage and frequency caused by the sudden change of the load occurs, the active power and reactive power of the energy storage power station hung on each node are solved by a particle swarm algorithm according to the fluctuation condition of the voltage of each node, and each grid-connected inverter adjusts the voltage and frequency through droop control according to the solving value. The energy storage system responds rapidly in preference to other power generation equipment of the system due to the characteristic of high response speed.
2. Optimizing a control layer: it is a long time scale control, i.e. the system is running steadily for a long time, this control layer acts. The method comprises the steps of taking economical efficiency and distributed energy loss rate as objective functions, considering the real-time updating state and service life of the SOC of the energy storage system, solving an energy storage charging and discharging power reference value through a particle swarm algorithm, optimizing a result obtained by a stable control layer, and finally determining the working mode and the workload of the energy storage system through an energy storage detection control module.
The economic influence factor in the optimized control layer is the active network loss P loss The expression is as follows:
wherein N is b The number of branches of the system is the number of branches; g b (m, n) is the conductance of the b-th leg connecting nodes m, n; v (V) m ，V n The voltage amplitudes of nodes m, n, respectively; θ mn Is the voltage phase angle difference between nodes m, n.
The distributed energy loss rate W of the optimal control layer m_new The expression is as follows:
wherein N is new The number of new energy power stations in the power distribution network;
the predicted value of the active output of the new energy power station hung on the mth node; p (P) m_new And the actual value of the active output of the new energy power station is hung on the ith node.
In summary, the objective function of the optimization control layer is as follows:
wherein omega 1 、ω 2 For the inertia weight, a Delphi method is adopted for determining the inertia weight, and an expert evaluates the importance of each index to finally determine the weight coefficients of the active network loss and the distributed energy loss rate.
Therefore, the control procedure of the optimization control layer is as follows:
the optimization control layer is the inner layer optimization of the particle swarm algorithm, and under the premise of ensuring stability, namely that voltage fluctuation is minimum and within a reasonable range, the power support required by the energy storage of the system is solved through the stability control layer, and then the energy storage input or output power reference value and the working mode are determined by combining economy and distributed energy loss rate. The highest economical efficiency is the minimum net loss, the minimum net loss and the minimum distributed energy loss rate are taken as objective functions, the inner layer solves the charging and discharging power of different energy storage, the result of the stable control layer is optimized, the solved result is uploaded to the energy storage detection control module, and the final charging and discharging power and the operation mode of the energy storage system are determined.
And when the optimal control layer calculates the input and output power of each energy storage system through a particle swarm algorithm, the energy storage detection control module is arranged in the power distribution network, and the data are uploaded to the energy storage detection control module. The energy storage detection control module is provided with five modes for giving operation commands to each energy storage power station, namely a charging only mode, a discharging only mode, a charging rate slowing mode, a discharging rate slowing mode and a normal mode, and determines the charging and discharging power and the operation mode at the next moment according to the operation state and the residual capacity state of each energy storage power station at the moment and sends the charging and discharging power and the operation mode to an energy management system of each energy storage power station.
The specific execution conditions of the five operation control modes in the dispatching instruction of the energy storage detection control module are as follows:
1) Charging mode only: when the capacity of the energy storage system is lambda j_low E j_bess When the charging mode is executed, the charging power is the maximum charging power P jmax_ch When the capacity of the energy storage system reaches
When this mode ends. Wherein lambda is j_low Refers to the lower limit coefficient set for avoiding overdischarge, < ->
Critical coefficient of energy storage system entering charge slow down mode, E j_bess For the capacity of the j energy storage power station, taking a lithium ion battery as an example, lambda is generally set j_low 0.1 @, @>
0.8.
2) Discharge only mode: when the capacity of the energy storage system is lambda j_high E j_bess When a discharge-only mode is executed, the discharge power is the maximum discharge power P jmax_dis When the capacity of the energy storage system reaches
This mode ends. Wherein lambda is j_high Refers to the upper limit coefficient set for avoiding overcharge, < >>
For the critical system of the energy storage system entering the discharge slowing mode, taking lithium ion battery as an example, lambda is generally set j_high 0.9，/>
0.2.
3) Charge rate slow down mode: when the capacity of the energy storage system is
When the battery still needs to be charged up,
slowing down the charge rate as a buffer zone which will reach the upper charge limit, the charge power at that time
P j_ch The expression is as follows:
4) Discharge rate slowing mode: when the capacity of the energy storage system is
When the discharge is still needed, the discharge rate is slowed down as a buffer zone reaching the upper limit of discharge, and the discharge power P at the moment j_dis The expression is as follows:
5) Normal mode: the energy storage system has the capacity of
At this time, the energy storage system can be charged and discharged, and the charging and discharging power is the maximum charging and discharging power.
Table 1 shows the control method for improving the stability of the power grid by using the energy storage device, and the control method comprises the following steps: 00-22:00P loss The change can be seen that after adopting the double-layer control mode, P loss The operation economy of the power distribution network is improved.
TABLE 1 control method for improving grid stability using energy storage device before and after Ploss variation
Table 2 shows the control method for improving the stability of the power grid by using the energy storage device, and the control method comprises the following steps: the 00-22:00 distributed energy loss condition can be seen that the distributed energy grid-connected power is improved and the energy waste is reduced after the double-layer control mode is adopted.
Table 2 comparison of active losses of distributed energy sources before and after a control method for improving grid stability using an energy storage device
The foregoing embodiments are merely illustrative of the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the present invention and to implement the same, not to limit the scope of the present invention. All equivalent changes or modifications made according to the spirit of the present invention should be included in the scope of the present invention.
Claims (6)
1. The control method for improving the stability of the power distribution network by using the energy storage device is characterized in that a distributed energy source, the energy storage device and traditional power generation equipment are integrated in the power distribution network, and an energy storage detection control module is arranged, wherein the energy storage device comprises a grid-connected inverter, an energy storage battery pack, a battery management system and an energy management system;
the battery management system of each energy storage power station is in information interconnection with the energy storage detection control module, the real-time state of the SOC is uploaded to the energy storage detection control module, the energy storage detection control module issues a scheduling instruction to each energy storage power station, determines the charge and discharge power and the operation mode at the next moment according to the operation state and the residual capacity state of each energy storage power station at the moment, and issues the charge and discharge power and the operation mode to the energy management system of each energy storage power station;
the control method is a double-layer control mode and is divided into a stable control layer and an optimal control layer, the optimal control layer further optimizes the result of the stable control layer, and the specific control method is as follows:
the stable control layer is an outer layer of the particle swarm algorithm, the system voltage fluctuation suddenly exceeds the safety range, the state is not maintained for a long time, and the control layer acts; selecting impedance values, wind power and photovoltaic grid-connected positions and output among lines of a system, loads of power users, number, positions, power and capacity of energy storage power stations as input conditions, taking a system voltage fluctuation value delta U as an objective function, obtaining active power and reactive power required to be stored and supported by a power grid through load flow calculation and a particle swarm algorithm, and feeding back to a grid-connected inverter interface as a reference value; when the system has load mutation, the energy storage system gives response in preference to the distributed energy sources and the traditional power generation equipment in the system according to the reference value;
the optimization control layer is the inner layer optimization of the particle swarm algorithm, the system stably operates for a long time, and the control layer acts; and the voltage fluctuation is minimum and within a reasonable range, the power support required by the energy storage of the system is solved through the stable control layer, the economical efficiency and the distributed energy loss rate are taken as an objective function, the real-time updating state and the service life of the SOC of the energy storage system are calculated, the energy storage charging and discharging power reference value is solved through a particle swarm algorithm, the result obtained by the stable control layer is optimized, and the charging and discharging power and the running mode of the energy storage system are finally determined through the energy storage detection control module.
2. The method for controlling the energy storage device to improve the stability of a power distribution network according to claim 1, wherein the formula of the voltage fluctuation value Δu of the objective function system is as follows:
wherein N is nod The node number of the power distribution network; v (V) m_ref A reference value for the voltage at node m; v (V) m Is the actual value of the voltage at node m; v (V) m_max ，V m_min Respectively the highest and lowest limit values of the node voltage amplitude.
3. The method for controlling the energy storage device to improve the stability of a power distribution network according to claim 1, wherein the following control conditions are satisfied when the stability control layer acts:
1) The energy storage charge-discharge power and the state of charge SOC need to meet the following control conditions:
P jmin_ch ≤P j_ch ≤P jmax_ch
P jmin_dis ≤P j_dis ≤P jmax_dis
SOC j_min ≤SOC j ≤SOC j_max
wherein P is jmin_ch 、P jmax_ch The minimum value, the maximum value and the P of the charging power of the j energy storage power station jmin_dis 、P jmax_dis The discharge power of the j energy storage power station is minimum value, maximum value and P j_ch 、P j_dis For the charge and discharge power of the j energy storage power station, SOC j_min 、SOC j_max The minimum value, the maximum value and the SOC of the j energy storage power stations j The state of charge of the energy storage power station is j;
2) The state of charge at time i and the state of charge at time i+1 of the energy storage system satisfy the following conditions:
wherein E is j_bess Refers to rated capacity, eta of the j energy storage power station ch Refer to the charging efficiency, eta dis Referring to the discharge efficiency, Δi is the time interval between time i and time i+1;
3) Power balance of each node in the system:
wherein P is m ，Q m Active power and reactive power are respectively injected into the node m; u (U) m ，U n For voltages at nodes m, n, θ m ，θ n For the phase angles of nodes m, n, G mn ，B mn The real part and the imaginary part of m rows and n columns of the node admittance matrix are respectively; y is the number of nodes;
4) The capacity of the j energy storage power station at the moment i meets the following control conditions:
in the method, in the process of the invention,
for the i moment capacity of the j energy storage power station E j_min For minimum capacity of j energy storage power station E j_max And the maximum capacity of the j energy storage power station.
4. The method for controlling the energy storage device to improve the stability of the power distribution network according to claim 1, wherein the objective function in the optimized control layer is as follows:
wherein omega 1 、ω 2 For the inertia weight, the Delphi method is adopted for determining the inertia weight, the importance of each index is assessed, and finally the weight coefficients of the active network loss and the distributed energy loss rate are determined;
P loss to be the instituteThe economic influence factor in the optimization control layer is effective network loss, and the expression is as follows:
wherein N is b The number of branches of the system is the number of branches; g b (m, n) is the conductance of the b-th leg connecting nodes m, n; v (V) m ，V n The voltage amplitudes of nodes m, n, respectively; θ mn Is the voltage phase angle difference between nodes m, n;
W m_new for the distributed energy loss rate in the optimal control layer, the expression is as follows:
N new the number of new energy power stations in the power distribution network;
the predicted value of the active output of the new energy power station hung on the mth node; p (P) m_new And the actual value of the active output of the new energy power station is hung on the ith node.
5. The method for controlling stability of a power distribution network by using an energy storage device according to claim 1, wherein the energy storage detection control module is provided with five operation modes for issuing operation commands to each energy storage power station, wherein the operation modes are a charging only mode, a discharging only mode, a charging rate slowing mode, a discharging rate slowing mode and a normal mode.
6. The method for controlling the energy storage device to improve the stability of the power distribution network according to claim 5, wherein the five operation modes of the energy storage detection control module specifically execute the following conditions:
1) Charging mode only: when the capacity of the energy storage system is lambda j_low E j_bess When the charging mode is executed, the charging power is the maximum charging power P jmax_ch When the capacity of the energy storage system reaches
When this mode ends; wherein lambda is j_low Refers to the lower limit coefficient set for avoiding overdischarge, < ->
Critical coefficient of energy storage system entering charge slow down mode, E j_bess The capacity of the energy storage power station is j;
2) Discharge only mode: when the capacity of the energy storage system is lambda j_high E j_bess When a discharge-only mode is executed, the discharge power is the maximum discharge power P jmax_dis When the capacity of the energy storage system reaches
This mode ends; wherein lambda is j_high Refers to the upper limit coefficient set for avoiding overcharge, < >>
A critical coefficient for the energy storage system to enter a discharge slowing mode;
3) Charge rate slow down mode: when the capacity of the energy storage system is
When the charging is still needed, the charging rate is slowed down as a buffer zone which reaches the upper charging limit, and the charging power P at the moment j_ch The expression is as follows:
4) Discharge rate slowing mode: when the capacity of the energy storage system is
When the discharge is still needed, the discharge rate is slowed down as a buffer zone reaching the upper limit of discharge, and the discharge power P at the moment j_dis The expression is as follows:
5) Normal mode: the energy storage system has the capacity of
At this time, the energy storage system can be charged and discharged, and the charging and discharging power is the maximum charging and discharging power.
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