CN116937675A - Energy router control strategy scheduling method, system and device - Google Patents
Energy router control strategy scheduling method, system and device Download PDFInfo
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- 238000004146 energy storage Methods 0.000 claims abstract description 48
- 238000010248 power generation Methods 0.000 claims description 8
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- 230000007717 exclusion Effects 0.000 claims description 3
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Classifications
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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
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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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
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
-
- 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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- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a method, a system and a device for scheduling an energy router control strategy, which belong to the technical field of digital energy, and when an energy router is simultaneously configured with a plurality of energy control strategies, the strategies are classified, managed and comprehensively calculated according to rules to obtain correct control information and then sent to an energy storage and photovoltaic system; dividing an energy control strategy into a target value class mode, a limit value class mode and a photovoltaic dispatching mode; the target value class mode is executed by selecting only one with the highest priority if a plurality of target value class modes are set to be effective at the same time for the same equipment or measurement point; in the limiting value class mode, a plurality of limiting value class modes can be simultaneously effective at the same time, but if the intersection between a plurality of limiting ranges c_bound_i is empty, special processing is required. When the energy router has a plurality of control strategies at the same time, the invention carries out classified management and comprehensive calculation according to the strategy purpose, and correctly controls the operation of the energy storage system.
Description
Technical Field
The invention relates to the technical field of digital energy, in particular to a method, a system and a device for scheduling an energy router control strategy.
Background
New generation power systems featuring high permeability renewable energy, high proportion of power electronics, high growth of dc loads are evolving. An intelligent distributed energy network based on an energy router is formed in the process of converting a traditional power grid into an energy internet, and the energy router is used as core equipment of the energy internet, has the functions of multi-energy conversion, electric energy conversion, energy transfer and routing, realizes the integration of an energy physical system and an information system, can coordinate with an upper layer system, and controls and manages various energy sources, energy storage and loads accessed by the energy router.
In the new energy network system, the direction and magnitude of the energy flow of each node within the distribution network can be precisely controlled as desired by the user due to the high controllability of the power electronics. The energy storage system is used as a supplement of a traditional power grid, and the generated power of the whole power grid is dynamically controlled through the charging or discharging state and the power of the energy storage system. The energy storage system is usually composed of one or more groups of battery packs, when the battery packs are discharged, the generated power of the whole power grid can be increased, the power consumption requirement of a user is met, and when the battery packs are charged, a part of power of the power grid needs to be distributed to the energy storage system, and then the available electric power of the user is correspondingly reduced. The energy storage system is typically dynamically controlled by an energy router, which calculates based on the current real-time status information of the grid system and the received user configuration policy, and sends the calculated control information to the energy storage system in some identifiable format. If a photovoltaic system exists in the current power grid system, the energy router also needs to control the generated power of the photovoltaic system when certain control strategies are started.
The energy control strategy is generally configured by a user according to the self requirements, and common control strategies comprise peak clipping and valley filling, demand control, reverse power protection, dynamic capacity expansion, planning curves, constant connecting lines and the like. The control purposes of the strategies are different, and the energy storage system is charged in the valley period to generate electricity in the peak period according to the characteristics of high electricity price and low electricity price in the valley period of electricity consumption, so that the purpose of saving electricity consumption is achieved. In order to protect the power grid from being under a reasonable load, the energy storage system should timely discharge and split partial load pressure when the power grid is excessively loaded. Reverse power protection is opposite to demand control, and in order to enable the power grid load not to be lower than a certain configuration value, when the power grid load is too low, the energy storage system should be charged timely to increase the load. It can be seen that each control strategy outputs the same type of control information to the energy storage system, and when multiple control strategies are configured simultaneously, the control information may have conflict, so that a scheduling method is needed to comprehensively calculate the control strategies.
Disclosure of Invention
The technical task of the invention is to provide a method, a system and a device for scheduling the control strategy of the energy router, which are used for performing classified management and comprehensive calculation according to the strategy purpose when the energy router has a plurality of control strategies at the same time, so as to accurately control the operation of the energy storage system.
The technical scheme adopted for solving the technical problems is as follows:
when the energy router configures multiple energy control strategies at the same time, the strategy classification management and comprehensive calculation are carried out according to rules to obtain correct control information and the correct control information is sent to an energy storage and photovoltaic system; the implementation mode is as follows:
the energy control strategy is divided into three types of modes, namely a target value type mode, a limiting value type mode and a photovoltaic dispatching mode according to the control mode,
the target value class mode sets a specific output target value V_target at a certain moment, and the control target is that the actual output value V_measure is as close as possible to the target value V_target, namely, the target value V_measure-V_target reaches min|; the target value class mode has mutual exclusion relation to the same equipment or measuring point at the same moment, namely, if a plurality of target value class modes are set to be effective at the same moment, only one with the highest priority is selected to execute the target value class mode;
the limiting value type mode is used for setting an output limiting range C_bound at a certain moment, and the control target is that an actual output value V_measure is within the limiting range C_bound, namely V_measure epsilon C_bound; the limiting value class mode can have a plurality of limiting value class modes to be effective at the same time, but if the intersection between a plurality of limiting ranges C_bound_i is empty, special treatment is needed;
the photovoltaic dispatching mode and the photovoltaic system are controlled in a combined mode with other control strategies under the condition of enabling the photovoltaic system.
The method classifies and manages the control strategy according to the control purpose, and is divided into three working modes; and fully considering the mutual influence relation among various strategies, and accurately calculating the control power meeting all conditions. Therefore, when the energy router has multiple control strategies at the same time, classification management and comprehensive calculation are carried out according to the strategy purpose, and the operation of the energy storage system is correctly controlled.
Preferably, the target value class mode comprises peak clipping and valley filling, a timing mode, a planning curve and a constant tie line strategy.
Preferably, the limiting value class mode comprises a demand control and inverse power protection strategy.
Preferably, the limiting value class mode, the special processing includes selecting several modes with high priority to execute or prompting the customer to reconfigure.
Preferably, in the photovoltaic scheduling mode, the control of the photovoltaic system is affected by a switch of an inverse power protection mode, and if the load and the energy storage cannot consume the power generated by the photovoltaic, the output power of the photovoltaic inverter needs to be reduced, so that the grid-connected point of the power grid meets the requirement of inverse power protection; in other cases, photovoltaic power generation should generally be eliminated as much as possible without actively reducing the output power of the photovoltaic inverter.
Further, the steps in calculating the control information are as follows:
1) If the control mode of the photovoltaic system is enabled, calculating the maximum power generation power P_pv_max of the photovoltaic system;
2) Target value class mode selection: if the control strategy of the target value class mode is configured currently, selecting a power output target value P_target of the control strategy with the highest priority;
3) Limiting value class pattern combination: if the control strategy of the limiting value class mode is configured currently, calculating an intersection InC_bound between limiting ranges C_bound_i of all strategies; if the control mode of the photovoltaic system is enabled, calculating the photovoltaic power generation power at the time of C_bound_i to be considered as P_pv_max; if InC_bound is an empty set, special treatment is needed; for example, selecting several modes with high priority to execute or prompting the customer to reconfigure;
4) And (3) calculating a control range: acquiring an energy storage work control range C_operation;
5) Combining the V_target, the InC_bound and the C_operation to obtain an intersection, and calculating a control value V_control of the energy storage control object;
6) If the V_control is positive, indicating that the energy storage system is in a charging state after control information is issued, and if the dynamic capacity expansion switch is opened, obtaining a final energy storage control value V_control_final according to a configured chargeable threshold value;
7) Setting all inverter power limit ratios to 1 if the photovoltaic control is enabled and reverse power protection is not in effect; if the reverse power protection is effective, calculating whether the photovoltaic meets the reverse power protection requirement at the maximum generated power, and if so, setting the power limiting proportion of all the inverters to be 1; otherwise, the photovoltaic power control power P_pv_control and the power limiting ratio C_inv_k_control need to be calculated, and the C_inv_k_control is issued to each inverter;
8) Control value allocation: and distributing the energy storage control value V_control_final to each battery pack of the energy storage system according to the distribution rule to obtain a control value P_control_i of each battery pack.
Preferably, the control range is calculated, and due to physical limitation of the energy storage system, the control of the charge and discharge power is generally limited to a certain range when leaving the factory, or the user limits the energy storage system to work in a certain range through configuration, so that the C_operation can be obtained.
Preferably, the control value is distributed, and the distribution rule comprises equal distribution or distribution in proportion according to the capacity and the current electric quantity.
The invention also claims an energy router control strategy scheduling system, when the energy router is simultaneously configured with a plurality of energy control strategies, the strategies are classified, managed and comprehensively calculated according to rules to obtain correct control information and then sent to an energy storage and photovoltaic system;
the system realizes the energy router control strategy scheduling by the energy router control strategy scheduling method.
The invention also claims an energy router control strategy scheduling device, which comprises: at least one memory and at least one processor;
the at least one memory for storing a machine readable program;
the at least one processor is configured to invoke the machine-readable program to implement the energy router control policy scheduling method described above.
Compared with the prior art, the energy router control strategy scheduling method, system and device provided by the invention have the following beneficial effects:
by the scheduling method, the energy router can be classified and managed when a plurality of energy control strategies are configured, comprehensive calculation is performed, the mutual influence relationship among the strategies is fully considered, the final control power is accurately calculated, and the accuracy and the reliability of the energy router are greatly improved.
Drawings
Fig. 1 is a distribution diagram of an energy network system according to an energy router control policy scheduling method according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating an implementation of an energy router control policy scheduling method according to an embodiment of the present invention.
Detailed Description
The invention will be further illustrated with reference to specific examples.
For the energy control strategy in the background art, if only one control strategy is adopted, the control power is obtained by calculation according to the algorithm, and if multiple control strategies exist at the same time, the mutual influence among the strategies needs to be considered during calculation. Based on the above, the embodiment of the invention provides an energy router control strategy scheduling method, when an energy router is configured with a plurality of energy control strategies at the same time, the strategies are classified, managed and comprehensively calculated according to rules to obtain correct control information and then sent to an energy storage and photovoltaic system; the implementation mode is as follows:
and dividing the energy control strategy into three types of modes, namely a target value type mode, a limiting value type mode and a photovoltaic dispatching mode according to the control mode.
The target value class pattern includes: strategies such as peak clipping and valley filling, timing mode, planning curve, constant tie line and the like are characterized in that:
1) A specific output target value V_target is set at a certain moment, and the control target is that the actual output value V_measure is as close as possible to the target value V_target, namely, the actual output value V_measure-V_target reaches min|V_measure|;
2) And the target value class modes have mutual exclusion relation to the same equipment or measuring point at the same moment, namely, if a plurality of target value class modes are set to be effective at the same moment, only one with the highest priority is selected to execute the target value class modes.
The limit value class pattern includes: strategies such as demand control, reverse power protection and the like are characterized in that:
1) An output limit range C_bound is set at a certain moment, and the control target is that the actual output value V_measure is within the limit range C_bound, namely V_measure epsilon C_bound;
2) The limiting value class patterns may be simultaneously validated at the same time, but if the intersection between the limiting ranges c_bound_i is empty, special processing measures are required.
The photovoltaic dispatching mode is aimed at the control of a photovoltaic system and is characterized in that:
1) In the case of photovoltaic system enablement, a combination of considerations with other control strategies is required.
2) The control of the photovoltaic system is influenced by a reverse power protection mode switch, and if the load and the energy storage cannot consume the power generated by the photovoltaic, the output power of the photovoltaic inverter needs to be reduced, so that the grid connection point of the power grid meets the requirement of reverse power protection; in other cases, photovoltaic power generation should generally be eliminated as much as possible without actively reducing the output power of the photovoltaic inverter.
Referring to fig. 2, the steps in calculating the control information are as follows:
1) If the control mode of the photovoltaic system is enabled, calculating the maximum power generation power P_pv_max of the photovoltaic system;
2) Target value class mode selection: if the control strategy of the target value class mode is configured currently, selecting a power output target value P_target of the control strategy with the highest priority;
3) Limiting value class pattern combination: if the control strategy of the limiting value class mode is configured currently, calculating an intersection InC_bound between limiting ranges C_bound_i of all strategies; if the control mode of the photovoltaic system is enabled, calculating the photovoltaic power generation power at the time of C_bound_i to be considered as P_pv_max; if inc_bound is an empty set, special processing is needed, such as selecting several modes with high priority to execute, or prompting the customer to reconfigure;
4) And (3) calculating a control range: because of the physical limitation of the energy storage system, the charge and discharge power is generally limited to be controlled in a certain range when leaving the factory, or a user limits the energy storage system to work in a certain range through configuration, so that C_operation can be obtained;
5) Combining the V_target, the InC_bound and the C_operation to obtain an intersection, and calculating a control value V_control of the energy storage control object;
6) If the V_control is positive, indicating that the energy storage system is in a charging state after control information is issued, and if the dynamic capacity expansion switch is opened, obtaining a final energy storage control value V_control_final according to a configured chargeable threshold value;
7) Setting all inverter power limit ratios to 1 if the photovoltaic control is enabled and reverse power protection is not in effect; if the reverse power protection is effective, calculating whether the photovoltaic meets the reverse power protection requirement at the maximum generated power, and if so, setting the power limiting proportion of all the inverters to be 1; otherwise, the photovoltaic power control power P_pv_control and the power limiting ratio C_inv_k_control need to be calculated, and the C_inv_k_control is issued to each inverter;
8) Control value allocation: and (3) distributing the energy storage control value V_control_final to each battery pack of the energy storage system according to a distribution rule (equally distributing or distributing according to the capacity and the current electric quantity in proportion) to obtain a control value P_control_i of each battery pack.
The method classifies and manages the control strategy according to the control purpose, and is divided into three working modes; and fully considering the mutual influence relation among various strategies, and accurately calculating the control power meeting all conditions. Therefore, when the energy router has multiple control strategies at the same time, classification management and comprehensive calculation are carried out according to the strategy purpose, and the operation of the energy storage system is correctly controlled.
The embodiment of the invention also provides an energy router control strategy scheduling system, when the energy router is simultaneously configured with a plurality of energy control strategies, the strategies are classified, managed and comprehensively calculated according to rules to obtain correct control information and then sent to an energy storage and photovoltaic system;
the system realizes the energy router control strategy scheduling by the energy router control strategy scheduling method described in the embodiment.
The embodiment of the invention also provides an energy router control strategy scheduling device, which comprises: at least one memory and at least one processor;
the at least one memory for storing a machine readable program;
the at least one processor is configured to invoke the machine-readable program to implement the energy router control policy scheduling method described in the foregoing embodiment.
The present invention can be easily implemented by those skilled in the art through the above specific embodiments. It should be understood that the invention is not limited to the particular embodiments described above. Based on the disclosed embodiments, a person skilled in the art may combine different technical features at will, so as to implement different technical solutions.
Other than the technical features described in the specification, all are known to those skilled in the art.
Claims (10)
1. The energy router control strategy scheduling method is characterized in that when an energy router is simultaneously configured with a plurality of energy control strategies, the strategies are classified, managed and comprehensively calculated according to rules to obtain correct control information and then sent to an energy storage and photovoltaic system; the implementation mode is as follows:
the energy control strategy is divided into three types of modes, namely a target value type mode, a limiting value type mode and a photovoltaic dispatching mode according to the control mode,
the target value class mode sets a specific output target value V_target at a certain moment, and the control target is that the actual output value V_measure is as close as possible to the target value V_target, namely, the target value V_measure-V_target reaches min|; the target value class mode has mutual exclusion relation to the same equipment or measuring point at the same moment, namely, if a plurality of target value class modes are set to be effective at the same moment, only one with the highest priority is selected to execute the target value class mode;
the limiting value type mode is used for setting an output limiting range C_bound at a certain moment, and the control target is that an actual output value V_measure is within the limiting range C_bound, namely V_measure epsilon C_bound; the limiting value class mode can have a plurality of limiting value class modes to be effective at the same time, but if the intersection between a plurality of limiting ranges C_bound_i is empty, special treatment is needed;
the photovoltaic dispatching mode and the photovoltaic system are controlled in a combined mode with other control strategies under the condition of enabling the photovoltaic system.
2. The energy router control strategy scheduling method according to claim 1, wherein the target value class mode comprises peak clipping and valley filling, timing mode, planning curve and constant tie strategy.
3. The method of claim 1, wherein the constraint value class pattern comprises a demand control, inverse power protection strategy.
4. An energy router control strategy scheduling method according to claim 1 or 3, wherein the limiting value class mode, the special treatment comprises selecting several modes with high priority to execute or prompting the customer to reconfigure.
5. The energy router control strategy scheduling method according to claim 1, wherein in the photovoltaic scheduling mode, the photovoltaic system control is affected by a reverse power protection mode switch, and if the load and the energy storage cannot consume the power generated by the photovoltaic, the output power of the photovoltaic inverter needs to be reduced, so that the grid connection point of the power grid meets the requirement of reverse power protection.
6. An energy router control strategy scheduling method according to claim 1 or 2 or 3 or 5, wherein the step of calculating the control information is as follows:
1) If the control mode of the photovoltaic system is enabled, calculating the maximum power generation power P_pv_max of the photovoltaic system;
2) Target value class mode selection: if the control strategy of the target value class mode is configured currently, selecting a power output target value P_target of the control strategy with the highest priority;
3) Limiting value class pattern combination: if the control strategy of the limiting value class mode is configured currently, calculating an intersection InC_bound between limiting ranges C_bound_i of all strategies; if the control mode of the photovoltaic system is enabled, calculating the photovoltaic power generation power at the time of C_bound_i to be considered as P_pv_max; if InC_bound is an empty set, special treatment is needed;
4) And (3) calculating a control range: acquiring an energy storage work control range C_operation;
5) Combining the V_target, the InC_bound and the C_operation to obtain an intersection, and calculating a control value V_control of the energy storage control object;
6) If the V_control is positive, indicating that the energy storage system is in a charging state after control information is issued, and if the dynamic capacity expansion switch is opened, obtaining a final energy storage control value V_control_final according to a configured chargeable threshold value;
7) Setting all inverter power limit ratios to 1 if the photovoltaic control is enabled and reverse power protection is not in effect; if the reverse power protection is effective, calculating whether the photovoltaic meets the reverse power protection requirement at the maximum generated power, and if so, setting the power limiting proportion of all the inverters to be 1; otherwise, the photovoltaic power control power P_pv_control and the power limiting ratio C_inv_k_control need to be calculated, and the C_inv_k_control is issued to each inverter;
8) Control value allocation: and distributing the energy storage control value V_control_final to each battery pack of the energy storage system according to the distribution rule to obtain a control value P_control_i of each battery pack.
7. The method for scheduling control strategies of energy routers according to claim 6, wherein the control range is calculated, and the control of the charge and discharge power is generally limited to a certain range when leaving the factory due to physical limitations of the energy storage system, or the user limits the energy storage system to work in a certain range by configuration, so that c_operation can be obtained.
8. The method of claim 6, wherein the allocation rule comprises equally dividing or proportionally allocating according to capacity and current power.
9. The energy router control strategy scheduling system is characterized in that when the energy router is simultaneously configured with a plurality of energy control strategies, the strategies are classified, managed and comprehensively calculated according to rules to obtain correct control information and then sent to an energy storage and photovoltaic system;
the system implements energy router control policy scheduling by the energy router control policy scheduling method according to any one of claims 1 to 8.
10. An energy router control strategy scheduling device, comprising: at least one memory and at least one processor;
the at least one memory for storing a machine readable program;
the at least one processor configured to invoke the machine readable program to implement the energy router control policy scheduling method of any one of claims 1 to 8.
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