CN116599060B - Integrated scheduling method, system, terminal equipment and medium for active power distribution network - Google Patents

Integrated scheduling method, system, terminal equipment and medium for active power distribution network Download PDF

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CN116599060B
CN116599060B CN202310875539.0A CN202310875539A CN116599060B CN 116599060 B CN116599060 B CN 116599060B CN 202310875539 A CN202310875539 A CN 202310875539A CN 116599060 B CN116599060 B CN 116599060B
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CN116599060A (en
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王明强
刘佳楠
杨明
王孟夏
王成福
董晓明
王勇
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Shandong University
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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
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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
    • H—ELECTRICITY
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    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

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Abstract

The application belongs to the technical field of power system dispatching, and particularly discloses an integrated dispatching method, system, terminal equipment and medium of an active power distribution network, wherein the method comprises the following steps: establishing an integrated rolling scheduling model with variable time granularity by taking the minimum comprehensive cost of the power system as an optimization target; introducing network reconfiguration constraint, start-stop plan locking time constraint, output plan locking time constraint, start-stop state maintenance time constraint and output state maintenance time constraint; and carrying out linearization treatment on the integrated rolling scheduling model, and solving the integrated rolling scheduling model through a mixed integer linear programming algorithm to obtain an optimal unit start-stop and output plan and an optimal network topology structure of the power distribution network. According to the application, the adjusting frequency of the equipment is limited by setting the planned locking time and the state maintaining time of each adjustable resource, so that the flexibility of the equipment is improved and the scheduling cost of the active power distribution network is reduced while the service life of the equipment is maintained.

Description

Integrated scheduling method, system, terminal equipment and medium for active power distribution network
Technical Field
The application relates to the technical field of power system dispatching, in particular to an integrated dispatching method, system, terminal equipment and medium for an active power distribution network.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The power distribution network scheduling is one of important working contents of the power system, and a reasonable and effective power distribution network scheduling strategy is an important guarantee for power supply and demand balance and system safety and economy operation. The method is different from a power transmission network, the resistance and reactance values of a distribution line are relatively close, active power and reactive power have a strong coupling relation, and the traditional active and reactive independent optimization research has certain unilateral performance. Along with the continuous improvement of permeability of renewable energy sources such as wind power, photovoltaic and the like in a power distribution network, a distributed power supply and an energy storage device are connected into the power distribution network for the purpose of coping with active balance; aiming at reactive power balance, devices such as a static reactive power compensator, a grouping switching capacitor and the like are connected; in addition, network reconfiguration can improve the reliability and economy of the system by changing the topology of the power distribution system. Thus, the concept of active distribution networks has evolved. Active distribution networks contain a variety of active management measures, and their network structure can be changed. How to effectively coordinate various elements with different regulation characteristics in an active power distribution network and adopt an active-reactive cooperative optimization strategy to ensure the safe operation of the power distribution network while fully absorbing renewable energy and reduce the operation cost as much as possible is a problem to be solved.
Because renewable energy output is difficult to accurately predict in advance on a long time scale and prediction errors thereof can be accumulated continuously along with time extension, existing active power distribution network operation researches generally divide the whole scheduling process into a plurality of stages such as a day-ahead stage, an intra-day stage and a real-time stage on a time scale. However, with significant increases in volatility and uncertainty within the distribution network, coupling between different phases in the sequential scheduling is significantly enhanced, and conventional sequential scheduling is likely to cause joint conflicts of the different scheduling phases, resulting in high readjustment costs and even wind, light and load shedding costs. Compared with a power transmission system, the active power distribution network comprises more controllable distributed power sources and equipment with time characteristics needing to be considered for adjustment, and the connection problem between different stages of the active power distribution network is not fully solved.
Disclosure of Invention
In order to solve the problems, the application provides an active power distribution network integrated scheduling method, system, terminal equipment and medium considering plan locking and state maintenance constraint, and establishes an integrated scheduling model comprising plan locking time constraint and state maintenance time constraint of various adjustable resources newly generated due to time granularity upgrading. The shorter the schedule lock time and the state maintenance time, the higher the adjustment flexibility of the adjustable resource. Two newly created constraints can ensure that even under the integrated scheduling of a high-frequency rolling power system, participants with low adjustment flexibility can meet the requirements of self start-stop and power adjustment frequency by reporting the locking time and the state maintaining time of own scheduling plans, thereby smoothly participating in an integrated model and further improving the rationality of various adjustable resource scheduling decisions in a power distribution network.
In some embodiments, the following technical scheme is adopted:
an integrated scheduling method of an active power distribution network, comprising the following steps:
establishing an integrated rolling scheduling model with variable time granularity by taking the minimum comprehensive cost of the power system as an optimization target; introducing network reconstruction constraint, start-stop plan locking time constraint, output plan locking time constraint, start-stop state maintaining time constraint and output state maintaining time constraint into the integrated rolling scheduling model;
and carrying out linearization treatment on the integrated rolling scheduling model, and solving the integrated rolling scheduling model through a mixed integer linear programming algorithm to obtain an optimal unit start-stop and output plan and an optimal power distribution network topology structure.
After the locking time constraint of the start-stop plan is a certain moment, once the start-stop plan of the decision object is determined, the plan is not allowed to be changed any more in a given period of time;
after the output plan locking time constraint is a certain moment, once the output plan of the decision object is determined, the plan is not allowed to be changed any more in a given period of time.
The start-stop state maintaining time is limited to the state that the state is not allowed to change any more in a given period of time after the adjustable resource is started, stopped or adjusted in gear;
the force state maintenance time constraint is that once the force of the adjustable resource is determined, the force remains unchanged for a given period of time thereafter.
The comprehensive cost of the power system comprises: the start-stop cost and the running cost of the controllable unit, the electricity purchasing cost of the upper power grid, the wind discarding punishment cost, the light discarding punishment cost, the load shedding punishment cost and the energy storage cost.
In other embodiments, the following technical solutions are adopted:
an active power distribution network integrated scheduling system, comprising:
the model construction module is used for establishing an integrated rolling scheduling model with variable time granularity by taking the minimum comprehensive cost of the power system as an optimization target; introducing network reconstruction constraint, start-stop plan locking time constraint, output plan locking time constraint, start-stop state maintaining time constraint and output state maintaining time constraint into the integrated rolling scheduling model;
and the model optimization solving module is used for carrying out linearization treatment on the integrated rolling scheduling model, and solving the integrated rolling scheduling model through a mixed integer linear programming algorithm to obtain an optimal unit start-stop and output plan and an optimal power distribution network topological structure.
In other embodiments, the following technical solutions are adopted:
a terminal device comprising a processor and a memory, the processor for implementing instructions; the memory is used for storing a plurality of instructions adapted to be loaded by the processor and to perform one of the active power distribution network integrated scheduling methods described above.
In other embodiments, the following technical solutions are adopted:
a computer readable storage medium having stored therein a plurality of instructions adapted to be loaded by a processor of a terminal device and to perform an active distribution network integrated scheduling method as described above.
Compared with the prior art, the application has the beneficial effects that:
(1) The application builds an integrated rolling scheduling model of the power system, integrates the previous scheduling, the intra-day scheduling and the real-time scheduling which originally have different time scales, time granularity and rolling frequency, and performs rolling operation. In order to finely characterize uncertainty characteristics of output and load of renewable energy sources and ensure calculation efficiency, the integrated scheduling model after fusion has variable time granularity, long look-ahead time scale and fastest rolling frequency, and connection conflict of sequential scheduling is naturally eliminated. Meanwhile, the variable time granularity can better describe fluctuation of output and load of renewable energy sources, and the calculation efficiency is improved.
(2) The integrated rolling scheduling model of the application introduces the planned locking time constraint and the state maintenance time constraint of active management measures, such as a controllable generator set, energy storage, a static reactive compensator, a parallel capacitor, an on-load voltage regulating transformer, network reconstruction and the like, in order to ensure that various adjustable resources with different time inertias can be reasonably scheduled under fine time granularity. The model is built more comprehensively, the scheduling result is more practical, the solving speed is higher, and the engineering application value of the active power distribution network scheduling is improved.
(3) According to the method, the alternating current method is adopted to analyze the power flow of the power distribution network, compared with the direct current method, the method can analyze the influence of node voltage and phase angle on the line flow at the same time, linearizes the alternating current flow, and improves the calculation efficiency of the model.
(4) The application expands the time points of the unit and other adjustable resources which are allowed to be adjusted, and limits the adjusting frequency of the equipment by setting the planned locking time and the state maintaining time of each adjustable resource, thereby greatly improving the flexibility of various adjustable equipment while maintaining the service life of the equipment, and further reducing the dispatching cost of the active power distribution network. The scheduling result is closer to real life, safe and economic operation of the active power distribution network can be realized, and the method can be effectively adapted to the new situation of the current power distribution network development.
Additional features and advantages of the application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application.
Drawings
FIG. 1 is a schematic diagram of an integrated power system scheduling method taking into account plan lock and state maintenance constraints in an embodiment of the present application;
FIG. 2 is a schematic diagram of an integrated scheduling model of a power system that considers plan lock and state maintenance constraints in an embodiment of the present application;
FIG. 3 is a schematic diagram of a unit plan lock time constraint and a state maintenance time constraint in an embodiment of the present application; wherein, (a) is a schematic diagram of a unit start-stop plan locking time constraint; (b) a schematic diagram of a unit output plan locking time constraint; (c) maintaining a time constraint schematic diagram for a start-stop state of the unit; (d) maintaining a time constraint schematic diagram for the output state of the unit;
FIG. 4 is a schematic diagram of a piecewise linearization of the operating cost of a controllable generator set in an embodiment of the application;
fig. 5 is a schematic diagram of linearization of transmission capacity constraints of a distribution line in an embodiment of the application.
Detailed Description
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the application. 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.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present application. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
Example 1
The power distribution network scheduling is one of important contents of the power system, and a reasonable and effective power distribution network scheduling strategy is an important guarantee for power supply and demand balance and system safety and economy operation. Active distribution network scheduling may be defined as follows: the active power distribution network achieves the requirements of improving the reliability level of the power distribution system and reducing the operation cost by coordinating and optimizing various active management measures such as a distributed power supply, an energy storage system, a static reactive compensator, a parallel capacitor, an on-load voltage regulating transformer, a user side demand response resource and the like. As large-scale renewable energy sources are accessed into a power distribution network, the fluctuation and uncertainty of renewable energy source output and load will cause the reliability level of the power distribution network to decrease. Therefore, how to effectively coordinate devices with different regulation characteristics in the power distribution network, an active-reactive cooperative optimization strategy is adopted to ensure safe and economical operation of the power distribution network, and the consumption of renewable energy sources as much as possible becomes a research hot spot.
Given that renewable energy output and load are difficult to accurately predict in advance on a long time scale, and that prediction errors thereof can accumulate continuously over time, traditional sequential scheduling faces a strong engagement conflict problem. Therefore, how to utilize more accurate prediction data and ensure calculation efficiency, reasonably and effectively schedule various adjustable resources in a power distribution network, so that participants with arbitrary adjustment flexibility can access the power distribution network in a friendly way, and the power distribution network is a problem to be solved urgently.
Based on this, in one or more embodiments, an active power distribution network integrated scheduling method considering plan locking and state maintenance constraints is disclosed, and in combination with fig. 1, the method specifically includes the following procedures:
s101: establishing an integrated rolling scheduling model with variable time granularity by taking the minimum comprehensive cost of the power system as an optimization target; introducing network reconfiguration constraint, start-stop plan locking time constraint, output plan locking time constraint, start-stop state maintenance time constraint and output state maintenance time constraint into the integrated rolling scheduling model;
in the embodiment, three-stage scheduling models of day-ahead scheduling, day-in scheduling and real-time scheduling with different time scales and different time granularities are unified into an integrated rolling scheduling model with variable time granularities and long-looking time scale characteristics, so that the problem of connection of each stage in sequential scheduling is avoided.
The multi-stage scheduling model at the current stage is usually a combination of day-ahead scheduling (24 h time scale, 1h time granularity), day-in scheduling (4 h time scale, 15min time granularity, rolling execution) and real-time scheduling (1 h time scale, 5min time granularity), a unit start-stop plan is determined before day, the output of the unit is determined in day and in real time, scheduling conflict among different modules is easily caused, and a scheduling result is a suboptimal solution. Therefore, multi-module scheduling with different time scales, time granularity and rolling frequency is integrated and rolled to run, so that the amount connection conflict among different modules is eliminated, the time point when a unit can decide start and stop is expanded, and the scheduling flexibility is improved.
The long look-ahead time scale is 24h, which is the longest look-ahead time scale in real-time scheduling.
The variable time granularity specifically refers to: fine time granularity of 5min, 15min, and 30min is adopted in sequence for the first three hours in the scheduling period; and the time granularity of 1h is adopted in the rest scheduling period so as to better describe the fluctuation of the output and the load of the renewable energy source and improve the calculation efficiency.
The comprehensive cost of the power system of this embodiment includes: the start-stop cost and the running cost of the controllable unit, the electricity purchasing cost of the upper power grid, the wind discarding punishment cost, the light discarding punishment cost, the load shedding punishment cost and the energy storage cost.
The embodiment researches establish new expressions of all constraints in the original three-stage scheduling in an integrated rolling scheduling model with the characteristic of variable time granularity; a schedule lock time constraint, a state maintenance time constraint, is introduced that includes various adjustable resources that are newly generated due to time granularity upgrades.
The plan locking time constraint comprises a start-stop plan locking time constraint and an output plan locking time constraint, and after the start-stop plan locking time constraint is a certain moment, the start-stop plan of the decision object is determined once, and the plan is not allowed to be changed in a given period of time. After the output plan locking time constraint is a certain moment, once the output plan of the decision object is determined, the plan is not allowed to be changed any more in a given period of time.
The state-sustaining time constraints include a start-stop state-sustaining time constraint and an output state-sustaining time constraint. The start-stop state maintenance time constraint means that once an adjustable resource is started, shut down or adjusted in gear, the start-stop state is not allowed to change any more within a given period of time thereafter; the output state maintenance time constraint refers to that once the output of the adjustable resource is determined, the output remains unchanged for a given period of time thereafter.
The shorter the schedule lock time and the state maintenance time, the higher the adjustment flexibility of the adjustable resource. Two newly created constraints can ensure that even under the high-frequency rolling integrated scheduling, participants with low adjustment flexibility can meet the requirements of self start-stop and power adjustment frequency by reporting the self scheduling plan locking time and the state maintaining time, thereby smoothly participating in the integrated rolling scheduling model and further improving the rationality of various adjustable resource scheduling decisions in the power distribution network.
In combination with the active power distribution network integrated scheduling model shown in fig. 2, the embodiment fuses the longest look-ahead time scale in the three modules for 24 hours in order scheduling, and adopts non-uniform time granularity, wherein the first hour adopts 5 minutes of time granularity, the second hour adopts 15 minutes of time granularity, the third hour adopts 30 minutes of time granularity, and then adopts 1 hour of time granularity, and rolling optimization decision is performed at a rolling frequency of 5 minutes/time.
As a specific implementation manner, the objective function of the active power distribution network integrated rolling scheduling model of the embodiment is specifically to minimize the sum of the start-stop cost and the running cost of a controllable generator set in a power system, the electricity purchasing cost of an upper-level power grid, the wind and light discarding and load shedding punishment cost and the energy storage running cost. The specific expression is as follows:
（1）
（2）
（3）
（4）
（5）
（6）
wherein,for the operation cost of the active distribution network, the operation cost of the controllable generator set is +>And the electricity purchasing cost of the upper power grid ∈>；/>Punishment cost for the active power distribution network comprises light discarding punishment cost, wind discarding punishment cost and load shedding punishment cost; />The energy storage running cost; />To optimize the number of time periods; />The method comprises the steps of collecting controllable generator sets; />Is thattOptimizing the duration of the time period; />、/>、/>Respectively controllable generator setsgSecondary, primary, and constant term cost coefficients; />Is a controllable generator setgReactive cost coefficients of (2); />Is a controllable generator setgThe single start-up cost of (2); />And->Respectively controllable generator setsgAt the position oftActive and reactive forces within a time period; />For identifying controllable generator setsgAt the position oftBinary variable whether to activate during a period, +.>Indicating machine setgAt the position oftStarting in a period of time, and not starting otherwise; />Is a superior power grid set; />On the upper-level power gridtElectricity prices of the time periods; />And->Respectively istTime period distribution network upper level electric networkfPurchased active and reactive power; />And->Respectively collecting a photovoltaic power station and a wind power plant; />The node set is a power distribution network node set; />、/>And->The unit light discarding, wind discarding and load shedding penalty costs are respectively adopted; />And->Respectively istPhotovoltaic power station in time periodpIs used for the amount of waste and wind farmwIs provided with the air discarding quantity; />And->Respectively istNode in time periodiThe amount of reduction in active and reactive loads; />Is an energy storage set; />To store energyeIs set in the unit operation cost of the equipment; />And->Respectively istEnergy storage during time periodeAnd a discharge power.
In this embodiment, the network reconfiguration means that the reliability and the load balance of the system are improved by changing the network topology structure of the power system. The network reconfiguration constraint is mainly embodied by the change of node power balance and line power flow calculation formula, namely binary variables are introduced in the following formulas (7), (8) and (9)S ij,t And radiation line constraints, equation (13). By introducing binary variablesS ij,t Can embody the result of network reconstruction whenS ij,t When=1, it indicatestTime lineijIs closed.
Constraint conditions of the integrated rolling scheduling model of the embodiment are as follows:
(1) Node power balance type
（7）
（8）
Wherein,s(j)to be at a nodejA set of end nodes that is a head end node;e(j)to be at a nodejA head end node set that is an end node;to identify connecting nodesijIs on the line switch of (2)tBinary variable of time period on/off, +.>Indicating line closure->Indicating a line break; />And->Respectively istLine in time periodijActive power and reactive power;i、j、kall refer to indexes of power system nodes, < ->And->Respectively istLine in time periodjkActive power and reactive power; />To identify connecting nodesjkIs on the line switch of (2)tBinary variable of time period on/off; />And->Respectively at the nodesjA superior power grid and a controllable generator set; />And->Respectively at the nodesjIs a photovoltaic power station and wind farm set; />To be located at the nodejIs a set of stored energy; />And->Respectively at the nodesjA set of static var compensators and parallel capacitor banks; />And->Respectively istUpward power grid in time periodfPurchased active power and reactive power; />And->Respectively istControllable generator set in time periodgActive power and reactive power emitted;and->Respectively istPhotovoltaic power station in time periodpActive power and reactive power actually emitted; />And->Respectively istWind farm in time periodwActive power and reactive power actually emitted; />And->Respectively istNode in time periodjActive and reactive loads of (a); />And->Respectively istNode in time periodjActive cut load amount and reactive cut load amount of (2); />Andrespectively istStatic reactive compensator in time periodsvcAnd parallel capacitor bankcbReactive power emitted.
(2) Alternating current trend linearization expression
（9）
（10）
Wherein,i、j、kare all indexes referring to the nodes of the power system,、/>、/>respectively istNode in time periodi、j、 kIs set to the node voltage of (1); />And->Respectively the linesijIs a conductivity and susceptance of (a); />And->Respectively the linesjkIs a conductivity and susceptance of (a);、/>is thattLine in time periodij、jkIs a phase angle difference of (2); />、/>Is thattNode in time periodi、jIs a reference node->The phase angle of (2) is set to 0.
(3) Node voltage constraint
（11）
Wherein,and->The lower voltage limit and the upper voltage limit of the node i are respectively.
(4) Line transmission capacity constraints
（12）
Wherein,is a circuitijUpper limit of transmission capacity of (c).
(5) Radial line constraint for power distribution network
（13）
Wherein,the method comprises the steps of collecting lines of a power distribution network;nthe number of nodes of the power distribution network is counted.
(6) Wind power and photovoltaic output constraints
（14）
Wherein,and->Respectively istWind farm in time periodwAnd photovoltaic power stationpActive power prediction value of (a); />Andrespectively wind farmwAnd photovoltaic power stationpIs a function of the installed capacity of the device.
(7) Logic variable constraint of controllable generator set
（15）
（16）
Wherein,for identifying controllable generator setsgAt the position oftBinary variable of whether to shut down during a period, +.>Indicating machine setgAt the position oftShutting down in a period of time, otherwise, not shutting down; />To reflect the machine setgAt the position oftBinary variable of start-stop state in time interval, representing unitgIn operation, otherwise, the units are indicatedgIs in a shutdown state; />To reflect machineGroup ofgAt the position oft-a binary variable of start-stop status during period 1; />To represent the unitsgBinary variables of the initial operating state; />Is a unitgIs>A positive number indicates that the unit is in operation and its value indicates the length of time the unit has been operated, +.>A negative value indicates that the unit is in an off-stream condition and an absolute value indicates a length of time that the unit has been out of operation.
(8) Unit start-stop plan locking time constraint
（17）
Wherein,is a unitgStart-stop plan lock time at time t; />Represent the firstnSecondary scrolling optimization initial opportunity setgIs locked by the start-stop plan;muas same asnLikewise, an index characterizing the scroll optimization process; />To at the firstmuUnit determined during sub-rolling optimizationgStart-stop plan reference trajectory during scheduling time, when +.>=/>At the time, the unit is scheduled in future timegDecision making is carried out again on the start-stop plan of (a), and the start-stop plan reference curve is updated +.>And thenAnd executing according to the start-stop plan in a time range.
(9) Unit output plan locking time constraint
（18）
Wherein,is a unitgIs a planned output lock time; />Represent the firstnSecondary scrolling optimization initial opportunity setgIs locked out;mpas same asnLikewise, an index characterizing the scroll optimization process; />To at the firstmpUnit determined during sub-rolling optimizationgOutput plan reference trajectory within schedule time, when +.>=/>At the time, the unit is scheduled in future timegDecision making is carried out again on the start-stop plan of (a), and the start-stop plan reference curve is updated +.>And in the following->In accordance with the start in the time rangeAnd stopping planning execution.
(10) Unit start-stop state maintenance time constraint
（19）
Wherein,indicating machine setgAt intervals of timetIn time intervals; />Indicating machine setgAt intervals of timetIn time intervals.
(11) Initial unit start-stop state maintenance time constraint
（20）
Wherein,indicating machine setgA minimum number of time intervals required to maintain an operational state; />Indicating machine setgA minimum number of time intervals is required to maintain the off-stream condition.
(12) Unit climbing rate constraint
（21）
（22）
（23）
（24）
Wherein,and->Respectively the unitsgAn up-climbing rate and a down-climbing rate of (a); />Is a unitgLower limit of the active force; />And->Respectively the unitsgMinimum start-up and shut-down times of (2);t，t-1 respectively representstTime and time oft-1 time.
(13) Unit output constraint
（25）
（26）
Wherein,is a unitgIs set to the rated installed capacity of the engine; />Is a unitgUpper limit of active force, < >>Is a unitgLower limit of the active force.
(14) Constraints on air rejection, amount of rejection and cut load
（27）
Wherein,、/> and->Respectively istPhotovoltaic power station in time periodpIs used for the amount of waste and wind farmwIs a waste air quantity of the air conditioner.
(15) Unit output maintenance time constraint
（28）
（29）
Wherein,is set to 1 multiplied by 10 -4 ；/>Is a unitgAt the position oftThe time period needs to maintain the time period number that the output remains unchanged;is a unitgActive force in the initial stage; t and tt are both optimization period indexes; />And->Is a controllable generator setgAt the position oftAndt-active force in period 1.
(16) Energy storage operation constraint
（30）
（31）
（32）
（33）
（34）
Wherein,and->Respectively are energy storage deviceseAt the position oftEnergy stored at time period and initial time; />And->Respectively are energy storage deviceseCharging efficiency and discharging efficiency of (a); />To identify the energy storage deviceeAt the position oftBinary variable of whether or not in charge state during a period, < >>Indicating charging, otherwise indicating non-charging; />To identify the energy storage deviceeAt the position oftBinary variable of whether or not in discharge state during the period, < >>Indicating discharge, otherwise indicating no discharge; />And->Respectively are energy storage deviceseA minimum charge amount and a maximum charge amount of (a); />、/>Respectively are energy storage deviceseAt the position oftAn upper limit of charge power and an upper limit of discharge power for the period.
(17) Static var compensator restraint
（35）
Wherein,and->Respectively static reactive compensatorsvcLower and upper reactive limits that can be issued.
(18) Parallel capacitor bank CB constraint
（36）
（37）
Wherein,for parallel capacitor bankscbAt the position oftIn gear during a period of timehThe number of capacitor banks put into operation at that time;reactive power for a single set of capacitors; />And->Respectively, identification parallel capacitor bankcbAt the position oftTime period oft-1 is in gearhBinary variable of>Representation oftTime period ofcbIn gear positionhOn the contrary, the gear is not located, < ->And the same is done; />For parallel capacitor bankscbAt intervals of timetIn time intervals; tt and t are both indexes representing time periods, both having the same meaning; />To identify parallel capacitor bankscbWhether or not to be in gear at the initial momenthA value of 1 representing the initial momentcbIn gear positionhAnd otherwise, the gear is not in the gear.
(19) On-load voltage regulating transformer OLTC constraint
（38）
（39）
（40）
Wherein,at the root nodetActual voltage values over a period of time; />A reference voltage value for the root node; />The transformation ratio of the on-load voltage regulating transformer; />Is an on-load voltage-regulating transformeroltcAt the position oftIn gear during a period of timeoThe amount of adjustment at that time;on-load voltage regulating transformer for identificationoltcAt the position oftWhether or not to be in gear in a period of timeoBinary variable of>Representation oftTime period ofoltcIn gear positionoOn the contrary, the gear is not located; />Is an on-load voltage-regulating transformeroltcAt intervals of timetIn time intervals.
(20) Line switch constraints
（41）
（42）/>
Wherein,identification distribution lineijOn/off state at initial time, +.>Indicating closure and/or->Indicating disconnection; />And->Respectively, line switchesijAt intervals of timetThe minimum running time and the minimum stopping time of the system are taken as a unit of time interval number; tt and t are both indexes representing time periods, both having the same meaning; />And->To identify connecting nodesijIs on the line switch of (2)tTime period oft-1 binary variable on/off, < >>Indicating line closure->Indicating a disconnection of the line->And the same is true.
Taking the plan lock time constraint and the state maintenance time constraint of the unit as examples, in conjunction with (a) - (d) in fig. 3, where (a) in fig. 3 represents the start-stop plan lock time constraint of the unit, specifically refers to: with unit start-stop schedule lock timeIs a parameter, namely, once the unit start-stop plan is locked, in +.>Following the start-stop plan in a time range; fig. 3 (b) shows a unit output plan lock time constraint, specifically: locking time by unit output plan>Once locked, the set output schedule is set to be parameters +.>Compliance with the output schedule over a time horizon; fig. 3 (c) shows a unit start-stop state maintenance time constraint, specifically: maintenance time of unit operation (off-line)>（/>) As a parameter, the unit will be in +.>（/>) The time range is in an operation (off-line) state and can not be shut down (started); fig. 3 (d) shows a unit output state maintaining time constraint, specifically: output maintenance time of unit->As a parameter, the unit will be at +.>The force is maintained over a range of durations.
S102: linearizing the integrated rolling scheduling model;
in this embodiment, a specific linearization process is as follows:
(1) Piecewise linearization of controllable generator set operating cost
In the objective function, the running cost of the controllable generator set is in a quadratic polynomial form, and is processed in a common three-piecewise linearization mode, as shown in fig. 4.
（43）
（44）
（45）
（46）
（47）
（48）/>
（49）
（50）
Wherein,mfor the segment number index, m=1, 2,3;is a unitgAt the position oftWithin the time period ofmSegmented active power; />Is a unitgAt the position ofmMaximum active power of the segment; />Is a unitgAt the position ofmA segmented active power minimum; />For marking unitsgAt the position oftThe state of the mth segment at the moment; />Is a unitgRunning cost at the lower limit of the output; />Is a unitgAt the position ofmSlope within segment, & gt>、/>Respectively the unitsgUpper and lower limits of the active force;
(2) Multiplication of 0/1 variable by continuous variable
Existence of a node power balancing in the present disclosure such asAnd->The component of the multiplication of the 0/1 variable and the continuous variable, to which the intermediate variable +.>And->And makes it satisfy:
（51）
（52）
（53）
（54）
wherein,and->The lower and upper limit values of the active power flow of the line ij,/respectively>、/>Respectively a lower limit value and an upper limit value of the reactive power flow of the line ij;
(3) Relaxation of power flow calculation formula of distribution network
Because the line load flow calculation formula is only suitable for closed branches, that is, the condition that the optimization solver is still not used for directly solving, the embodiment adopts a large M method, and inequality constraint is introduced to relax the load flow calculation formula.
（55）
Wherein,is a maximum parameter in the large M method, +.>Is a nodeiAt the position oftNode voltage of the period.
(4) Linearization of distribution line capacity constraints
For the case that the line transmission capacity constraint (12) is a square term constraint, the present embodiment adopts a power circle linearization method to linearize the constraint. Distribution line transmission capacity constraint typeFrom a geometrical point of view it represents the point +.>Is positioned at a radius of +.>As shown in fig. 5. Wherein (1)>For the active power flow of line ij at time t, -/->Is the reactive power flow of the line ij at the time t. Dividing the circle m equally and obtaining m-sided shapes with equal inscription, wherein the larger the m value is, the more the m-sided shapes with equal inscription are close to the circle. A, B is provided as two adjacent vertexes of an m-sided polygon with circular inscription, and the radian angles are respectively +.>And->Then->、/>Wherein->. From this, A, B two-point coordinates are +.>And->The edge AB of an m-sided polygon inscribed in a circle can be expressed as:
（56）
based on the analytical geometry theory, the distribution line capacity constraint can be linearized as:
（57）
s103: and solving the integrated rolling scheduling model through a mixed integer linear programming algorithm to obtain an optimal unit start-stop and output plan, a cooperative scheduling scheme of various active management measures and a network topology structure of the power distribution network.
The network topology of the power distribution network of this embodiment is a binary variable determined by decisionS ij,t Is constructed from the values of (a) and (b),S ij,t =1 indicates a lineijAt the position oftThe time period is closed, and vice versa.
The model is converted into a mixed integer linear programming model, and can be solved through a CPLEX business solver, so that an optimal unit start-stop and output plan is finally obtained, and unit operation is controlled.
Example two
In one or more embodiments, an active power distribution network integrated scheduling system is disclosed, specifically including:
the model construction module is used for establishing an integrated rolling scheduling model with variable time granularity by taking the minimum comprehensive cost of the power system as an optimization target; introducing network reconstruction constraint, start-stop plan locking time constraint, output plan locking time constraint, start-stop state maintaining time constraint and output state maintaining time constraint into the integrated rolling scheduling model;
and the model optimization solving module is used for carrying out linearization treatment on the integrated rolling scheduling model, and solving the integrated rolling scheduling model through a mixed integer linear programming algorithm to obtain an optimal unit start-stop and output plan and an optimal power distribution network topological structure.
It should be noted that, the specific implementation manner of each module is the same as that in the first embodiment, and will not be described in detail here.
Example III
In one or more embodiments, a terminal device is disclosed, including a server, where the server includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the active distribution network integrated scheduling method in embodiment one when executing the program. For brevity, the description is omitted here.
It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general purpose processors, digital signal processors DSP, application specific integrated circuits ASIC, off-the-shelf programmable gate array FPGA or other programmable logic device, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may include read only memory and random access memory and provide instructions and data to the processor, and a portion of the memory may also include non-volatile random access memory. For example, the memory may also store information of the device type.
In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or by instructions in the form of software.
Example IV
In one or more embodiments, a computer-readable storage medium is disclosed, in which a plurality of instructions are stored, the instructions being adapted to be loaded by a processor of a terminal device and to perform the active power distribution network integrated scheduling method described in embodiment one.
While the foregoing description of the embodiments of the present application has been presented in conjunction with the drawings, it should be understood that it is not intended to limit the scope of the application, but rather, it is intended to cover all modifications or variations within the scope of the application as defined by the claims of the present application.

Claims (6)

1. An integrated scheduling method for an active power distribution network is characterized by comprising the following steps:
establishing an integrated rolling scheduling model with variable time granularity by taking the minimum comprehensive cost of the power system as an optimization target; introducing network reconstruction constraint, start-stop plan locking time constraint, output plan locking time constraint, start-stop state maintaining time constraint and output state maintaining time constraint into the integrated rolling scheduling model;
carrying out linearization treatment on the integrated rolling scheduling model, and solving the integrated rolling scheduling model through a mixed integer linear programming algorithm to obtain an optimal unit start-stop and output plan and an optimal power distribution network topology structure;
after the locking time constraint of the start-stop plan is a certain moment, once the start-stop plan of the decision object is determined, the plan is not allowed to be changed any more in a given period of time;
after the output plan locking time constraint is a certain moment, once the output plan of the decision object is determined, the plan is not allowed to be changed any more in a given period of time;
the start-stop state maintaining time is limited to the state that the state is not allowed to change any more in a given period of time after the adjustable resource is started, stopped or the gear is adjusted once;
the output state maintaining time constraint is that once the output of the adjustable resource is determined, the output is kept unchanged within a given period of time thereafter;
wherein, the integrated rolling scheduling model sequentially adopts fine time granularity of 5min, 15min and 30min in the first three hours in the scheduling period; adopting time granularity of 1h in the rest scheduling period;
the integrated rolling scheduling model specifically comprises the following steps:
wherein,for the operation cost of the active distribution network, the operation cost of the controllable generator set is +>And the electricity purchasing cost of the upper power grid ∈>；/>Punishment cost for the active power distribution network comprises light discarding punishment cost, wind discarding punishment cost and load shedding punishment cost; />The energy storage running cost; />To optimize the number of time periods; />The method comprises the steps of collecting controllable generator sets; />Optimizing the duration of the period for t; />、/>、/>The cost coefficients of a secondary term, a primary term and a constant term of the controllable generator set g are respectively; />The reactive cost coefficient of the controllable generator set g; />The single start cost of the controllable generator set g; />And->The active output and the reactive output of the controllable generator set g in the t period are respectively; />To identify the binary variable whether the controllable generator set g is started in the t period +.>Indicating that the unit g is started in the period t, and is not started otherwise; />Is a superior power grid set; />The electricity price of the superior power grid in the period t is calculated; />And->Active power and reactive power purchased from the power distribution network at the t period to the upper power grid f respectively; />And->Respectively collecting a photovoltaic power station and a wind power plant; />The node set is a power distribution network node set; />、/>And->The unit light discarding, wind discarding and load shedding penalty costs are respectively adopted; />And->The amount of waste light of the photovoltaic power station p and the amount of waste air of the wind power station w in the t period are respectively; />And->The reduction amounts of the active load and the reactive load of the node i in the t period are respectively; />Is an energy storage set; />The unit operation cost of the energy storage e; />And->And respectively charging power and discharging power of the energy storage e in the t period.
2. An integrated scheduling method for an active power distribution network according to claim 1, wherein the comprehensive cost of the power system comprises: the start-stop cost and the running cost of the controllable unit, the electricity purchasing cost of the upper power grid, the wind discarding punishment cost, the light discarding punishment cost, the load shedding punishment cost and the energy storage cost.
3. The integrated scheduling method of an active power distribution network according to claim 1, wherein the integrated rolling scheduling model is subjected to linearization processing, and specifically comprises:
carrying out linearization treatment on a nonlinear item of the running cost of the controllable generator set in a piecewise linearization mode;
under the influence of network reconstruction, multiplying a 0/1 variable existing in an alternating current power flow linearization expression by a continuous variable to perform error-free linear conversion;
carrying out linearization treatment on an alternating current power flow linearization expression which is obtained by multiplying a 0/1 variable by a continuous variable and is only suitable for a closed circuit by adopting a large M method;
and linearizing the transmission capacity constraint of the distribution line by adopting a power circle linearization method.
4. An active power distribution network integrated scheduling system, comprising:
the model construction module is used for establishing an integrated rolling scheduling model with variable time granularity by taking the minimum comprehensive cost of the power system as an optimization target; introducing network reconstruction constraint, start-stop plan locking time constraint, output plan locking time constraint, start-stop state maintaining time constraint and output state maintaining time constraint into the integrated rolling scheduling model;
the model optimization solving module is used for carrying out linearization treatment on the integrated rolling scheduling model, and solving the integrated rolling scheduling model through a mixed integer linear programming algorithm to obtain an optimal unit start-stop and output plan and an optimal power distribution network topological structure;
after the locking time constraint of the start-stop plan is a certain moment, once the start-stop plan of the decision object is determined, the plan is not allowed to be changed any more in a given period of time;
after the output plan locking time constraint is a certain moment, once the output plan of the decision object is determined, the plan is not allowed to be changed any more in a given period of time;
the start-stop state maintaining time is limited to the state that the state is not allowed to change any more in a given period of time after the adjustable resource is started, stopped or the gear is adjusted once;
the output state maintaining time constraint is that once the output of the adjustable resource is determined, the output is kept unchanged within a given period of time thereafter;
wherein, the integrated rolling scheduling model sequentially adopts fine time granularity of 5min, 15min and 30min in the first three hours in the scheduling period; adopting time granularity of 1h in the rest scheduling period;
the integrated rolling scheduling model specifically comprises the following steps:
wherein,for the operation cost of the active distribution network, the operation cost of the controllable generator set is +>And the electricity purchasing cost of the upper power grid ∈>；/>Punishment cost for the active power distribution network comprises light discarding punishment cost, wind discarding punishment cost and load shedding punishment cost; />The energy storage running cost; />To optimize the number of time periods; />The method comprises the steps of collecting controllable generator sets; />Optimizing the duration of the period for t; />、/>、/>The cost coefficients of a secondary term, a primary term and a constant term of the controllable generator set g are respectively; />The reactive cost coefficient of the controllable generator set g; />The single start cost of the controllable generator set g; />And->The active output and the reactive output of the controllable generator set g in the t period are respectively; />To identify the binary variable whether the controllable generator set g is started in the t period +.>Indicating that the unit g is started in the period t, and is not started otherwise; />Is a superior power grid set; />The electricity price of the superior power grid in the period t is calculated; />And->Active power and reactive power purchased from the power distribution network at the t period to the upper power grid f respectively; />And->Respectively collecting a photovoltaic power station and a wind power plant; />The node set is a power distribution network node set; />、/>And->The unit light discarding, wind discarding and load shedding penalty costs are respectively adopted; />And->The amount of waste light of the photovoltaic power station p and the amount of waste air of the wind power station w in the t period are respectively; />And->The reduction amounts of the active load and the reactive load of the node i in the t period are respectively; />Is an energy storage set; />The unit operation cost of the energy storage e; />And->And respectively charging power and discharging power of the energy storage e in the t period.
5. A terminal device comprising a processor and a memory, the processor for implementing instructions; a memory for storing a plurality of instructions, wherein the instructions are adapted to be loaded by a processor and to perform an active power distribution network integrated scheduling method according to any one of claims 1-3.
6. A computer readable storage medium having stored therein a plurality of instructions adapted to be loaded by a processor of a terminal device and to perform an active power distribution network integrated scheduling method according to any one of claims 1-3.
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