CN110994695A - Intraday optimal scheduling method and system for power distribution network - Google Patents
Intraday optimal scheduling method and system for power distribution network Download PDFInfo
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Abstract
The invention relates to a method and a system for day-to-day optimal scheduling of a power distribution network. The method comprises the following steps: and acquiring ultra-short-term prediction data of the power load of the power distribution network and power load data in a day-ahead scheduling plan of the power distribution network. And solving a pre-established day-to-day optimized scheduling model of the power distribution network by using the ultra-short-term prediction data of the power consumption load of the power distribution network and the power consumption load data in the day-ahead scheduling plan of the power distribution network, and acquiring the day-to-day schedulable capacity of each type of schedulable resource in the power distribution network. And performing scheduling correction in the day according to the scheduling capacity in the day of each type of schedulable resource in the power distribution network and the ultra-short-term prediction data of the power load of the power distribution network. The types of the schedulable resources comprise a distributed power generation unit, an energy storage unit and a controllable load unit. The technical scheme that this application provided, based on the correction to the scheduling of the day before the distribution network, give the guidance scheme of scheduling in the day, can make scheduling in the day more reasonable, can realize the high-efficient operation of distribution network.
Description
Technical Field
The invention relates to full resource coordination optimization of a power distribution network, in particular to a day-to-day optimization scheduling method and system of the power distribution network.
Background
With the advance of intelligent power distribution network construction, the requirement on power distribution network resource optimization configuration is continuously enhanced, and higher requirements are provided for scheduling operation and scheduling optimization.
Most of the traditional power distribution network dispatching plans are stopped at day-ahead dispatching plans. After entering the day, the dispatcher begins to execute the dispatching plan made by the day. However, the actual operation process of the power system is always different from the prediction in the day, such as the change of the load. Particularly, after the new energy power generation unit is connected to a power grid, the power generation capacity of the new energy power generation unit is closely related to real-time weather change or other factors. Therefore, the day-ahead scheduling plan can only be used as a guide for day scheduling, and cannot be executed according to the day-ahead scheduling plan. Therefore, it is highly desirable to invent an in-day optimized scheduling method based on a day-ahead scheduling plan.
Disclosure of Invention
Therefore, it is necessary to provide a day-ahead scheduling optimization scheduling method and system based on the power distribution network day-ahead scheduling for the existing day-ahead scheduling method of the power distribution network.
A method of intra-day scheduling of a power distribution network, the method comprising:
s1: acquiring ultra-short-term prediction data of the power consumption load of the power distribution network and power consumption load data in a power distribution network day-ahead scheduling plan;
s2: solving a pre-established day-to-day optimized scheduling model of the power distribution network by using the ultra-short-term prediction data of the power consumption load of the power distribution network and the power consumption load data in the day-ahead scheduling plan of the power distribution network, and acquiring the day-to-day schedulable capacity of each type of schedulable resource in the power distribution network;
s3: performing scheduling correction in the day according to the scheduling capacity in the day of each type of schedulable resource in the power distribution network and the ultra-short-term prediction data of the power load of the power distribution network;
the types of the schedulable resources comprise a distributed power generation unit, an energy storage unit and a controllable load unit.
In one embodiment, in S2, the establishing the intra-day optimized scheduling model of the pre-established power distribution grid includes:
the establishing of the intraday optimal scheduling objective function of the power distribution network comprises the following steps: and establishing a power load deviation minimum objective function of the power distribution network and establishing each type of schedulable resource execution deviation minimum objective function.
In one embodiment, in S2, the establishing the intra-day optimized scheduling model of the pre-established power distribution network further includes: establishing a constraint condition of an in-day optimized scheduling objective function of the power distribution network;
the constraint condition for establishing the intraday optimal scheduling objective function of the power distribution network comprises the following steps: establishing a power flow constraint, establishing a distributed generation unit regulation capacity constraint and establishing a controllable load unit power constraint.
In one embodiment, the establishing a power load deviation minimum objective function of the power distribution network includes:
establishing a minimum objective function min f of the power load deviation of the power distribution network according to the following formula1:
min f1＝min(|Pl_sstlf-Pl_dpso|)
Wherein, Pl_sstlfUltra-short-term prediction data, P, for the electrical load of an electrical distribution networkl_dpsoAnd dispatching the power utilization load data in the plan for the distribution network day ahead.
In one embodiment, the establishing of the minimum objective function of execution deviation of each type of schedulable resource includes:
establishing the minimum objective function min f of execution deviation of each type of schedulable resource according to the following formula2：
min f2＝ω1·min f′+ω2·min f″
Wherein min f 'is the minimum value of the execution deviation of the distributed power generation unit, min f' is the minimum value of the execution deviation of the controllable load, and omega1Adjusting an importance weight coefficient, omega, for a distributed power generation unit2The importance weight coefficient is adjusted for the controllable load unit.
In one embodiment, the establishing the distributed power generation unit adjustment capacity constraint comprises:
the adjusting capacity of the distributed generating units is smaller than or equal to the maximum value of the adjusting capacity of the distributed generating units preset by the microgrid, larger than or equal to the minimum value of the adjusting capacity of the distributed generating units preset by the microgrid and larger than or equal to the threshold value of the minimum adjusting capacity of the distributed generating units.
In one embodiment, the establishing the controllable-load power constraint includes:
the adjusting power of the controllable load unit is less than or equal to the maximum value of the adjusting power of the controllable load unit preset by the AMI system, is greater than or equal to the minimum value of the adjusting power of the controllable load unit preset by the AMI system, and is greater than or equal to the threshold value of the minimum adjusting power of the controllable load unit.
In one embodiment, the S3 includes:
and when the ultra-short-term prediction data of the power load of the power distribution network is equal to the power load data in the power distribution network day-ahead scheduling plan, executing a power generation plan and a power utilization plan in the power distribution network day-ahead scheduling plan.
In one embodiment, the S3 includes:
when the ultra-short-term prediction data of the power load of the power distribution network is larger than the power load data in the current dispatching plan of the power distribution network, increasing the output of the distributed power generation unit; if the output of the distributed unit cannot meet the power load deviation, the energy storage unit is switched to a discharging state; and if the output force of the energy storage unit switched to the discharging state cannot meet the power load deviation, reducing the power load of the controllable load unit.
In one embodiment, the S3 includes:
when the ultra-short-term prediction data of the power load of the power distribution network is smaller than the power load data in the day-ahead scheduling plan of the power distribution network, increasing the power load of the controllable load; if the increased electric load can not absorb the electric load deviation, the energy storage unit is switched to a charging state; and if the energy storage unit is switched to the charging state and cannot absorb the electric load deviation, reducing the output of the distributed power generation unit.
An intra-day dispatch system for a power distribution network, the system comprising:
the first acquisition module is used for acquiring ultra-short-term prediction data of the power consumption load of the power distribution network and the power consumption load data in a power distribution network day-ahead scheduling plan;
the second acquisition module is used for solving a pre-established day-by-day optimized scheduling model of the power distribution network by using the ultra-short-term prediction data of the power consumption load of the power distribution network and the power consumption load data in the day-by-day scheduling plan of the power distribution network to acquire the day-by-day schedulable capacity of each type of schedulable resource in the power distribution network;
the scheduling module is used for performing scheduling correction in the day according to the scheduling capacity in the day of each type of schedulable resource in the power distribution network and the ultra-short-term prediction data of the power load of the power distribution network;
the types of the schedulable resources comprise a distributed power generation unit, an energy storage unit and a controllable load unit.
The embodiment of the application provides a day-to-day optimization scheduling method for a power distribution network, which comprises the following steps: and acquiring ultra-short-term prediction data of the power load of the power distribution network and power load data in a day-ahead scheduling plan of the power distribution network. And solving a pre-established day-to-day optimized scheduling model of the power distribution network by using the ultra-short-term prediction data of the power consumption load of the power distribution network and the power consumption load data in the day-ahead scheduling plan of the power distribution network, and acquiring the day-to-day schedulable capacity of each type of schedulable resource in the power distribution network. And performing scheduling correction in the day according to the scheduling capacity in the day of each type of schedulable resource in the power distribution network and the ultra-short-term prediction data of the power load of the power distribution network. The types of the schedulable resources comprise a distributed power generation unit, an energy storage unit and a controllable load unit. According to the technical scheme, when the day scheduling is started, a guidance scheme of the day scheduling is given based on real-time correction of the day-ahead scheduling of the power distribution network, so that the day scheduling is more reasonable, and efficient operation of the power distribution network can be realized.
Drawings
Fig. 1 is a flowchart of a method for optimizing scheduling of a power distribution network in the day according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of an intra-day optimal scheduling system of a power distribution network according to an embodiment of the present application.
Detailed Description
To facilitate an understanding of the present application, the present application will now be described more fully with reference to the accompanying drawings. Preferred embodiments of the present application are shown in the drawings. This application may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
The running characteristics of the power distribution network and the fluctuation of various schedulable resources determine that the arrangement of the power utilization plan and/or the power generation plan of various schedulable resources is a continuous rolling correction process. The problem that the intra-day scheduling needs to be studied seriously is that the relation among the intra-day power generation plan, the real-time power generation plan and the day-ahead scheduling and a system load deviation decomposition strategy of the intra-day scheduling are researched, and the load deviation is decomposed to various schedulable resources by utilizing safety constraints according to rules.
As shown in fig. 1, an embodiment of the present application provides a method for intraday optimal scheduling of a power distribution network, where the method includes:
s1: acquiring ultra-short-term prediction data of the power consumption load of the power distribution network and power consumption load data in a power distribution network day-ahead scheduling plan;
s2: and solving a pre-established day-to-day optimized scheduling model of the power distribution network by using the ultra-short-term prediction data of the power consumption load of the power distribution network and the power consumption load data in the day-ahead scheduling plan of the power distribution network, and acquiring the day-to-day schedulable capacity of each type of schedulable resource in the power distribution network.
S3: and performing in-day adjustment and correction according to in-day schedulable capacity of each type of schedulable resource in the power distribution network and ultra-short-term prediction data of the power load of the power distribution network.
Specifically, the day is the actual scheduling day. The scheduling in the embodiment can be realized by starting the scheduling plan every 15 minutes, making the scheduling plans of various schedulable resources for 4 hours in the future every time, and performing rolling calculation all day long. This mode of operation allows for load bias cancellation on a periodic basis.
The ultra-short term prediction is typically within 1-4 hours of the future.
The types of the schedulable resources comprise a distributed power generation unit, an energy storage unit and a controllable load unit. The distributed power generation unit generally includes a solar photovoltaic power generation unit, a wind power generation unit, a micro gas turbine power generation unit, and the like.
In one embodiment, in S2, the establishing the intra-day optimized scheduling model of the pre-established power distribution grid includes: and establishing an in-day optimized dispatching objective function of the power distribution network and a constraint condition of the in-day optimized dispatching objective function of the power distribution network. The establishing of the intraday optimal scheduling objective function of the power distribution network comprises the following steps: and establishing a power load deviation minimum objective function of the power distribution network and establishing each type of schedulable resource execution deviation minimum objective function. The constraint conditions of the day-to-day optimized scheduling objective function of the power distribution network comprise: the method comprises the following steps of power flow constraint, distributed generation unit regulation capacity constraint and controllable load unit power constraint.
Specifically, the embodiment adopts a joint optimization model of a plurality of objective functions and a plurality of constraint conditions, and can realize efficient, energy-saving and effective operation of the power distribution network system under the condition of meeting the safety of the power distribution network system. Compared with the day-ahead scheduling plan, the scheduling resources participating in the optimized scheduling are different. The day-ahead scheduling phase includes all schedulable resources in the power distribution network. And the deviation of the scheduling stage in the day is mainly the adjustment load deviation. Therefore, the controllable resources can be selected to participate in the adjustment of the daily load balance. Meanwhile, the daily scheduling plan has some special constraints. The flexible and efficient constraint of the multi-constraint condition combination can improve the calculation efficiency of the optimal scheduling model in the whole day.
In one embodiment, the establishing a power load deviation minimum objective function of the power distribution network includes: establishing a minimum objective function min f of the power load deviation of the power distribution network according to the following formula1:
min f1＝min(|Pl_sstlf-Pl_dpso|)
Wherein, Pl_sstlfUltra-short-term prediction data, P, for the electrical load of an electrical distribution networkl_dpsoAnd dispatching the power utilization load data in the plan for the distribution network day ahead.
In one embodiment, the establishing of the minimum objective function of execution deviation of each type of schedulable resource includes: establishing the minimum objective function min f of execution deviation of each type of schedulable resource according to the following formula2：
min f2＝ω1·min f′+ω2·min f″
Wherein min f 'is the minimum value of the execution deviation of the distributed power generation unit, min f' is the minimum value of the execution deviation of the controllable load, and omega1Adjusting an importance weight coefficient, omega, for a distributed power generation unit2The importance weight coefficient is adjusted for the controllable load unit.
In one embodiment, the establishing the distributed power generation unit adjustment capacity constraint comprises: the adjusting capacity of the distributed generating units is smaller than or equal to the maximum value of the adjusting capacity of the distributed generating units preset by the microgrid, larger than or equal to the minimum value of the adjusting capacity of the distributed generating units preset by the microgrid and larger than or equal to the threshold value of the minimum adjusting capacity of the distributed generating units.
In one embodiment, the establishing the controllable-load power constraint includes: the adjusting power of the controllable load unit is less than or equal to the maximum value of the adjusting power of the controllable load unit preset by the AMI system, is greater than or equal to the minimum value of the adjusting power of the controllable load unit preset by the AMI system, and is greater than or equal to the threshold value of the minimum adjusting power of the controllable load unit.
In one embodiment, the daily scheduling link needs to monitor the execution condition of the load and power utilization plan of the power distribution network on the day. And under the condition that the day-ahead scheduling plan deviates from the actual power load, adjusting the power utilization deviation by utilizing various schedulable resources in time. The in-day scheduling does not override the last time scale power generation/utilization plan, but further checks and corrects the in-day scheduling plan based on the day-ahead scheduling plan. In the scheduling process in the day, the priorities of various schedulable resources are different under different running states. Specifically, the method comprises the following steps:
(1) and when the ultra-short-term prediction data of the power utilization load of the power distribution network is equal to the power utilization load data in the power distribution network day-ahead scheduling plan, executing respective day-ahead scheduling power generation plans and/or power utilization plans without adjusting various schedulable resources.
(2) And when the ultra-short-term prediction data of the power consumption load of the power distribution network is larger than the power consumption load data in the day-ahead scheduling plan of the power distribution network, the power consumption load of the power distribution network is increased, and the power supply is insufficient. At the moment, the generated energy of various distributed generation units is preferably adjusted, and the output of the distributed generation units is increased. And if the output of the distributed power generation unit is adjusted to the maximum schedulable range and the power supply of the power distribution network is still insufficient, adjusting the working state of the energy storage unit to the discharging state. If the power supply is insufficient when the adjustable capacity of the energy storage unit in the power distribution network reaches the limit value, the power load of the controllable load unit needs to be reduced at the moment until the power supply requirement of the power distribution network is met.
(3) And when the ultra-short-term prediction data of the power consumption load of the power distribution network is smaller than the power consumption load data in the day-ahead scheduling plan of the power distribution network, the power consumption load of the power distribution network is reduced, and the power supply is excessive. At the moment, the power loads of various controllable load units are increased preferentially, so that the power loads of the power distribution network are increased to absorb redundant electric quantity. And if the controllable load units are all put into the working state and the power distribution network still supplies excessive power, the working state of the energy storage unit is switched to the energy storage state. If the adjustment capacity of only the controllable load unit and the energy storage unit cannot meet the adjustment requirement of the power load deviation of the power distribution network, the power generation plan of the distributed power generation unit needs to be controlled, and the power generation output is reduced within the allowable range of the distributed power generation unit until the power supply and demand of the power distribution network are balanced.
As shown in fig. 2, one embodiment of the present application provides an intraday optimization system for a power distribution network, the system comprising: the device comprises a first acquisition module, a second acquisition module and a scheduling module. The first acquisition module is used for acquiring ultra-short-term prediction data of the power consumption load of the power distribution network and the power consumption load data in the power distribution network day-ahead scheduling plan. And the second acquisition module is used for solving a pre-established in-day optimized scheduling model of the power distribution network by using the acquired ultra-short-term prediction data of the power consumption load of the power distribution network and the power consumption load data in the power distribution network day-ahead scheduling plan, and acquiring in-day schedulable capacity of each type of schedulable resource in the power distribution network. And the scheduling module is used for performing in-day adjustment and correction according to in-day schedulable capacity of each type of schedulable resource in the power distribution network and ultra-short-term prediction data of the power load of the power distribution network. The types of the schedulable resources comprise a distributed power generation unit, an energy storage unit and a controllable load unit.
In one embodiment, the second obtaining module includes: a first establishing unit and a second establishing unit. The first establishing unit is used for establishing an intraday optimal scheduling objective function of the power distribution network. The second establishing unit is used for establishing constraint conditions of the day-to-day optimized dispatching objective function of the power distribution network. Wherein the first establishing unit specifically: the method is used for establishing the power load deviation minimum objective function of the power distribution network and establishing the schedulable resource execution deviation minimum objective function of each type. The second establishing unit is specifically configured to: establishing a power flow constraint, establishing a distributed generation unit regulation capacity constraint and establishing a controllable load unit power constraint.
In one embodiment, the scheduling module comprises: the system comprises a first scheduling unit, a second scheduling unit and a third scheduling unit. The first scheduling unit is specifically configured to: and when the ultra-short-term prediction data of the power load of the power distribution network is equal to the power load data in the power distribution network day-ahead scheduling plan, executing a power generation plan and a power utilization plan in the power distribution network day-ahead scheduling plan. The second scheduling unit is specifically configured to: when the ultra-short-term prediction data of the power load of the power distribution network is larger than the power load data in the current dispatching plan of the power distribution network, increasing the output of the distributed power generation unit; if the output of the distributed unit cannot meet the power load deviation, the energy storage unit is switched to a discharging state; and if the output force of the energy storage unit switched to the discharging state cannot meet the power load deviation, reducing the power load of the controllable load unit. The third scheduling unit is specifically configured to increase the power load of the controllable load when the ultra-short-term prediction data of the power load of the power distribution network is smaller than the power load data in the power distribution network day-ahead scheduling plan; if the increased electric load can not absorb the electric load deviation, the energy storage unit is switched to a charging state; and if the energy storage unit is switched to the charging state and cannot absorb the electric load deviation, reducing the output of the distributed power generation unit.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (11)
1. An in-day optimal scheduling method for a power distribution network, the method comprising:
s1: acquiring ultra-short-term prediction data of the power consumption load of the power distribution network and power consumption load data in a power distribution network day-ahead scheduling plan;
s2: solving a pre-established day-to-day optimized scheduling model of the power distribution network by using the ultra-short-term prediction data of the power consumption load of the power distribution network and the power consumption load data in the day-ahead scheduling plan of the power distribution network, and acquiring the day-to-day schedulable capacity of each type of schedulable resource in the power distribution network;
s3: performing scheduling correction in the day according to the scheduling capacity in the day of each type of schedulable resource in the power distribution network and the ultra-short-term prediction data of the power load of the power distribution network;
the types of the schedulable resources comprise a distributed power generation unit, an energy storage unit and a controllable load unit.
2. The method according to claim 1, wherein in the step S2, establishing the pre-established day-to-day optimized dispatching model of the distribution network comprises:
establishing an intraday optimal scheduling objective function of the power distribution network;
the establishing of the intraday optimal scheduling objective function of the power distribution network comprises the following steps: and establishing a power load deviation minimum objective function of the power distribution network and establishing each type of schedulable resource execution deviation minimum objective function.
3. The method according to claim 1, wherein in the step S2, establishing the in-day optimized scheduling model of the pre-established distribution network further comprises: establishing a constraint condition of an in-day optimized scheduling objective function of the power distribution network;
the constraint condition for establishing the intraday optimal scheduling objective function of the power distribution network comprises the following steps: establishing a power flow constraint, establishing a distributed generation unit regulation capacity constraint and establishing a controllable load unit power constraint.
4. The method of claim 2, wherein establishing the electrical load deviation minimization objective function for the power distribution grid comprises:
establishing a minimum objective function min f of the power load deviation of the power distribution network according to the following formula1:
min f1＝min(|Pl_sstlf-Pl_dpso|)
Wherein, Pl_sstlfUltra-short-term prediction data, P, for the electrical load of an electrical distribution networkl_dpsoAnd dispatching the power utilization load data in the plan for the distribution network day ahead.
5. The method of claim 2, wherein the establishing the minimum objective function of execution deviation of each type of schedulable resource comprises:
establishing the minimum objective function min f of execution deviation of each type of schedulable resource according to the following formula2：
min f2＝ω1·min f′+ω2·min f″
Wherein min f 'is the minimum value of the execution deviation of the distributed power generation unit, min f' is the minimum value of the execution deviation of the controllable load, and omega1Adjusting an importance weight coefficient, omega, for a distributed power generation unit2The importance weight coefficient is adjusted for the controllable load unit.
6. The method of claim 3, wherein establishing a distributed power generation unit adjustment capacity constraint comprises:
the adjusting capacity of the distributed generating units is smaller than or equal to the maximum value of the adjusting capacity of the distributed generating units preset by the microgrid, larger than or equal to the minimum value of the adjusting capacity of the distributed generating units preset by the microgrid and larger than or equal to the threshold value of the minimum adjusting capacity of the distributed generating units.
7. The method of claim 3, wherein establishing a controllable load power constraint comprises:
the adjusting power of the controllable load unit is less than or equal to the maximum value of the adjusting power of the controllable load unit preset by the AMI system, is greater than or equal to the minimum value of the adjusting power of the controllable load unit preset by the AMI system, and is greater than or equal to the threshold value of the minimum adjusting power of the controllable load unit.
8. The method according to claim 1, wherein the S3 includes:
and when the ultra-short-term prediction data of the power load of the power distribution network is equal to the power load data in the power distribution network day-ahead scheduling plan, executing a power generation plan and a power utilization plan in the power distribution network day-ahead scheduling plan.
9. The method according to claim 1, wherein the S3 includes:
when the ultra-short-term prediction data of the power load of the power distribution network is larger than the power load data in the current dispatching plan of the power distribution network, increasing the output of the distributed power generation unit; if the output of the distributed unit cannot meet the power load deviation, the energy storage unit is switched to a discharging state; and if the output force of the energy storage unit switched to the discharging state cannot meet the power load deviation, reducing the power load of the controllable load unit.
10. The method according to claim 1, wherein the S3 includes:
when the ultra-short-term prediction data of the power load of the power distribution network is smaller than the power load data in the day-ahead scheduling plan of the power distribution network, increasing the power load of the controllable load; if the increased electric load can not absorb the electric load deviation, the energy storage unit is switched to a charging state; and if the energy storage unit is switched to the charging state and cannot absorb the electric load deviation, reducing the output of the distributed power generation unit.
11. An intraday optimal scheduling system for a power distribution network, the system comprising:
the first acquisition module is used for acquiring ultra-short-term prediction data of the power consumption load of the power distribution network and the power consumption load data in a power distribution network day-ahead scheduling plan;
the second acquisition module is used for solving a pre-established day-by-day optimized scheduling model of the power distribution network by using the ultra-short-term prediction data of the power consumption load of the power distribution network and the power consumption load data in the day-by-day scheduling plan of the power distribution network to acquire the day-by-day schedulable capacity of each type of schedulable resource in the power distribution network;
the scheduling module is used for performing scheduling correction in the day according to the scheduling capacity in the day of each type of schedulable resource in the power distribution network and the ultra-short-term prediction data of the power load of the power distribution network;
the types of the schedulable resources comprise a distributed power generation unit, an energy storage unit and a controllable load unit.
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