CN112270111A - Power system active scheduling method and system for coping with ice disaster - Google Patents
Power system active scheduling method and system for coping with ice disaster Download PDFInfo
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Abstract
The invention discloses an active scheduling method and system for an electric power system in response to ice disasters, wherein the method comprises the steps of firstly quantifying the influence of the ice disasters on the fault probability of elements, then abstracting the topological state transition of the system during the ice disasters into a Markov chain, and completing the analysis of the influence of the ice disasters on the electric power system by utilizing a network rasterized system model; an active scheduling model is established based on a half Markov decision process, and the load flow of the system is scheduled again in advance by considering the recovery process of elements. The invention relates to an active scheduling strategy model of an electric power system for coping with ice disasters, which can calculate the influence degree of the disasters on the electric power system from two aspects of time dimension and space dimension, reduce the threat brought by the disasters from the active scheduling aspect and has good foresight and effect of reducing load reduction.
Description
Technical Field
The invention relates to the field of operation and scheduling of power systems, in particular to an active scheduling method and system for a power system for coping with ice disasters.
Background
The ice disaster weather is an extreme natural disaster, which is very easy to cause large-scale faults in crossed power system areas, and the faults are specifically represented by power transmission line disconnection, insulator flashover, tower collapse of an iron tower, line self-excited vibration and the like. Line icing is a complex physical process of supercooling water drops in the atmosphere under a low-temperature environment, and then the water drops are captured by structures such as transmission conductors and insulators and are frozen into ice. In ice disaster weather, the disaster-causing factor of the power system can be characterized by the ice load of the line. At present, a plurality of model researches for deducing ice load according to historical meteorological data of ice disasters exist, but the model researches are low in universality and complicated in calculation.
In order to research the coping capability of the power system to the ice disaster weather event, the ice disaster event is considered in three stages of before, when and after the ice disaster weather disaster occurs. At present, the research on the power grid dispatching strategy in the power system environment mostly focuses on the strategy for predicting and preventing ice disaster weather before a disaster occurs and the strategy for recovering after the disaster occurs. The research on the scheduling strategy during the ice disaster weather is mostly concentrated on the power distribution network, and the system response strategy is executed after the system response strategy fails during the ice disaster weather. And when the power system has the fault risk, the scheduling research aiming at the power transmission link is more primary, and most of the scheduling research is only aiming at the N-1 event.
In summary, the existing under-disaster scheduling strategy research mostly targets the power distribution network, and the system response strategy is executed after a fault occurs, so the existing under-disaster scheduling method for the power grid is not prospective enough, and an active scheduling method for the power grid under the disaster, which can consider the disaster fault probability and the recovery strategy at the future moment, is lacked. Based on the above, the invention provides an active scheduling strategy for an electric power system in ice disaster, which can evaluate the operation state of the electric power system in real time during the disaster, and adopts an active scheduling method for the electric power system to minimize the load loss of the system during the ice disaster.
Disclosure of Invention
The invention provides an active scheduling method and system for an electric power system in response to ice disasters, which are used for solving the technical problems that the response strategy of the existing system is executed after a fault occurs, so the foresight of the current under-disaster scheduling method for a power grid is not enough, and the active scheduling of the power grid under the disaster, which can simultaneously consider the disaster fault probability and the future time recovery strategy, is lacked.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
an ice disaster coping active scheduling method for an electric power system comprises the following steps:
dividing an electric power system area into a plurality of small grids according to geographical positions;
establishing an ice disaster weather intensity model, and calculating disaster factors and duration of ice disaster weather on elements of the system;
establishing a fault model of the elements of the system based on the disaster-causing factors, calculating the fault probability of the elements and generating a fault set;
establishing a recovery model of an element of the system, and calculating the repair time of the element under the ice disaster by considering the randomness of the ice disaster intensity;
abstracting the topological state transition of the system during the ice disaster into the Markov state of the system based on the state transition of the elements in the fault model and the recovery model of the elements, calculating the state transition probability of the system during the ice disaster weather, and generating a system state scene set;
establishing a load reduction penalty function, and calculating the action instant cost;
establishing an active scheduling optimization model, taking the minimum decision value function as a target function, and taking the conventional operation constraint of the power system as a constraint condition;
and converting the multi-objective optimization problem of the objective function into a single-objective mixed integer linear programming problem by using a linear scalar method, and solving the single-objective mixed integer linear programming problem to determine a scheduling strategy of the power system for corresponding ice disasters.
Preferably, the disaster factor of the ice disaster on the power system includes an ice coating thickness of the line, and the calculation formula is as follows:
in the formula, RitRepresenting the thickness of the ice coating, i.e. the ice load, N being the time for the element to ice, PjFor the precipitation rate at hour j of the ice coating duration,
is the water content of liquid water in the air, vjWind speed, p, for the corresponding line locationiIs ice density, taken at 0.9g/cm3，ρoIs the density of water, taken at 1.0g/cm3。
Preferably, the fault model of the power system component comprises:
when the ice coating thickness M of the element does not exceed the maximum designed ice-resistant thickness M, the element is not influenced to normally operate;
when the icing thickness M of the element is more than or equal to 5M, the element is in failure and stops running;
when the ice coating thickness m of the element is at the maximum designFailure probability p between ice thickness M and 5MfiIncrease exponentially with increasing ice coating thickness:
preferably, the restoration model of the element of the power system comprises:
calculating the repair time of the element under the ice disaster, and calculating the fault repair time TTR under the ice disaster weatherWAs the time TTR for repairing the ice disaster weather intensity and the normal weatherNThe values of interest, wherein:
TTRW＝kW·TTRN
in the formula, kWFor the weather influence factor, the randomness of the repair time corresponding to different ice disaster intensities is considered in the influence factor.
Preferably, the state transition probability is calculated from the state transition probabilities of the elements:
where i and i' are the states of the system at two adjacent times, k is the element number, Si,tAnd Si′,t+1Represents the state of the system at times t and t +1, respectively, omegaS,tRepresents the set of states, Ω, at time t of the systemC,tA set of elements that are potentially failing at time t; sk,tIs the state of element k at time t, where 0 represents a fault condition and 1 represents a normal operating condition; pr (S)i,t,Si′,t+1)、Pr(sk,t,sk,t+1) Respectively, the state transition probabilities of the system and the element at two adjacent moments.
Preferably, a load reduction penalty function is established, and the action instant cost is calculated according to the following calculation formula:
in the formula, PCt(Si,t,Aa,t) At time t Si,tIn action Aa,tImmediate cost under influence, Δ Ln,t,iIndicating node n at time ti,tThe amount of load reduction in the state, Δ T is the interval time between adjacent scheduling times, μL,t,nIs the penalty cost of node n per unit time per unit load.
Preferably, the decision value function is represented by a recursive formula:
i∈ΩS,t,a∈ΩA,a′∈ΩA,t∈ΩT,t+1∈ΩT
where a and a' are scheduling action indexes, Aa,tRepresenting the scheduling action at the time t, namely the rescheduling strategy of the system at the current time; omegaA、ΩTRespectively a set of scheduling actions and scheduling instants; c. Ct(Si,t,Aa,t) Is in state S from time t to endi,tTake action Aa,tAn expected cost of time, the expected cost being a cost due to load shedding; PC (personal computer)t(Si,t,Aa,t) Is at the current time ti,tIn action Aa,tLoad reduction penalty cost under action;
the system is in state S at time ti,tThe following optimal strategy is obtained when the value function is minimum, i.e. the expected cost is minimum as the objective function:
in the formula (I), the compound is shown in the specification,
for the system at time t state Si,tThe minimum expected cost of.
Preferably, a linear scalar method is used to convert the multi-objective optimization problem into the following single-objective mixed integer linear programming problem:
the linear scalar method takes the occurrence probability of each state as the weight of the corresponding state objective function; because the failure probability of each element of the system is different on the ice disaster track, the topology of the system is changed, and the state S of the systemi,tProbability of occurrence Pi,tThe calculation is as follows:
in the formula, pi,r,tIs from an initial state to a state S through a path ri,tThe probability of (a) of (b) being,
is from an initial state to a state Si,tSet of paths of [ omega ]SIs a set of system states, NTIs the number of decision instants.
The constraint conditions meet scheduling conventional constraints, including power balance, upper and lower limits of unit output, line tide, generator climbing, and upper and lower limits of load and power angle constraints.
The present invention also provides a computer system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any of the methods described above when executing the computer program.
The invention has the following beneficial effects:
1. according to the method and the system for actively scheduling the power system in response to ice disasters, firstly, the influence of ice disasters on the fault probability of elements is quantified, then the topological state transition of the system during the ice disasters is abstracted into a Markov chain, and the influence of the ice disasters on the power system is analyzed by utilizing a network rasterized system model; an active scheduling model is established based on a half Markov decision process, and the load flow of the system is scheduled again in advance by considering the recovery process of elements. The invention relates to an active scheduling strategy of an electric power system for coping with ice disasters, which can calculate the influence degree of the disasters on the electric power system from two aspects of time dimension and space dimension, reduce the threat brought by the disasters from the aspect of active scheduling, has good foresight and load reduction effect, can effectively improve the capacity of the system for resisting the ice disasters, and provides reference for the operation process of the system under disasters.
2. In a preferred scheme, the active scheduling method and system for the power system in ice disaster, provided by the invention, are based on an active scheduling model of the power system in ice disaster of a half-Markov decision process, can fully describe a sequential decision process considering uncertainty, comprehensively consider the system states at the current moment and the future moment, and have an active scheduling strategy tending to reschedule the power flow of a line on the track of an ice disaster weather event, thereby reducing potential power loss caused by ice disaster weather.
3. According to the method and the system for actively scheduling the power system in response to ice disasters, a multi-objective optimization problem is converted into a single-objective mixed integer linear programming problem by using a linear scalar method, so that the calculation speed is greatly increased, and the timeliness of actively scheduling strategies in the face of ice disasters is improved.
4. Compared with the traditional passive response scheduling method, the method provided by the invention has good foresight and load reduction effect, can effectively improve the ice disaster resistance of the power system, and has certain guiding significance on the operation process of the power system during the ice disaster weather.
In addition to the objects, features and advantages described above, other objects, features and advantages of the present invention are also provided. The present invention will be described in further detail below with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic flow chart of an active scheduling method of an electric power system for coping with ice disasters according to a preferred embodiment of the present invention;
fig. 2 is a network trellis diagram of an IEEE RTS-79 system of the preferred embodiment 2 of the present invention;
fig. 3 is a scheduling result of each generator set under the scenario of preferred embodiment 2 of the present invention;
fig. 4 is a scheduling result of each generator set in a second scenario in accordance with preferred embodiment 2 of the present invention;
fig. 5 shows the scheduling results of the generator sets in the third scenario in the preferred embodiment 2 of the present invention;
fig. 6 shows the scheduling results of the generator sets in the fourth scenario in the preferred embodiment 2 of the present invention;
FIG. 7 shows the comparison of the load shedding of the example of the present invention and the conventional model.
Detailed Description
The embodiments of the invention will be described in detail below with reference to the drawings, but the invention can be implemented in many different ways as defined and covered by the claims.
Referring to fig. 1, the active scheduling method for the power system in response to ice disasters, provided by the invention, comprises the following steps:
step 1: by using a network grid method, an electric power system area is divided into a plurality of small grids according to geographical positions, and the weather intensity in each grid is set to be consistent. The disaster-stricken system is divided into limited units, so that the influence of various ice disaster weather can be conveniently simulated.
Step 2: establishing an ice disaster weather intensity model, and calculating disaster factors and duration of ice disaster weather to system elements, wherein the disaster factors and duration are as follows:
the disaster factor of ice disaster to the power system can be characterized by the ice coating thickness of the line, namely the ice load. The ice load can be calculated according to the precipitation rate and the wind speed, and the specific calculation model is as follows:
in the formula, RitRepresenting thickness of ice coating, i.e. ice load, N being element ice coatingTime of (P)jFor the precipitation rate at hour j of the ice coating duration,
is the water content of liquid water in the air, vjWind speed, p, for the corresponding line locationiIs ice density, taken at 0.9g/cm3，ρoIs the density of water, taken at 1.0g/cm3。
And step 3: establishing a fault model of the element based on the disaster causing factors in the step 2, calculating the fault probability of the system element, and generating a fault set, wherein the ice disaster weather is specifically as follows:
in ice disaster weather, the strain force causing the fault mainly comes from the ice load caused by the ice coating thickness. The failure model of the element under this condition is as follows. When the ice coating thickness M of the element does not exceed the maximum designed ice-resistant thickness M, the element is not influenced to normally operate; when M is more than or equal to 5M, the element is in failure and stops running; when m is in between, the probability of failure pfiIncreases exponentially with increasing ice coating thickness.
And 4, step 4: establishing a recovery model of the element, calculating the repair time of the element under the ice disaster by considering the randomness of the intensity of the ice disaster weather, and calculating the fault repair time TTR under the ice disaster weatherWConsidered as the intensity of ice disaster weather and the repair time TTR under normal weatherNThe values of interest, wherein:
TTRW＝kW·TTRN
in the formula, kWFor the weather influence factor, the randomness of the restoration time corresponding to different ice disaster intensities can be considered in the influence factor. The intensity of ice weather can be characterized by the rate of precipitation and wind speed. For example, assuming that the repair time of an element in normal weather is 1h, the weather intensity influence factor kWThe value of (d) can be calculated using a random number associated with the ice thickness m of the line in the following equation:
wherein k isWU (a, b) denotes kWObey [ a, b]Are uniformly distributed.
And 5: analyzing the influence of ice disaster weather on the power system based on the state transition of the elements in the steps 3 and 4, defining the system topology as the Markov state of the system, calculating the probability of the state transition of the system during the ice disaster weather, and generating a system state scene set, wherein the method specifically comprises the following steps:
since the component states considered are both faulty and normal, and the state of each constituent component determines the state of the system, the number of system states at time t is
Wherein N isCIs the number of components in the system that may fail at time t.
The system state is determined by the state of its internal elements, and considering the state transition from the state i at time t to the state i' at time t + 1, the states of all elements at time t need to be successfully transitioned to the state corresponding to time t + 1, so the system markov state transition probability can be calculated from the state transition probabilities of the elements:
where i and i' are the states of the system at two adjacent times, k is the element number, Si,tAnd Si′,t+1Represents the state of the system at times t and t +1, respectively, omegaS,tA set of states representing the time t of the system, the number of states being
ΩC,tSet of elements potentially failing at time t, sk,tIs the state of element k at time t (where 0 represents a fault state and 1 represents a normal operation state), Pr (S)i,t,Si′,t+1)、Pr(sk,t,sk,t+1) Respectively, the state transition probabilities of the system and the element at two adjacent moments.
Step 6: establishing a load reduction penalty function at time Ti,tIn action Aa,tThe instant costs under action are:
in the formula,. DELTA.Ln,t,iIndicating node n at time ti,tThe amount of load reduction in the state, Δ T is the interval time between adjacent scheduling times, μL,t,nIs the penalty cost of node n per unit time per unit load.
And 7: and establishing an active scheduling optimization model, taking the minimum decision value function as a target function, and taking the conventional operation constraint of the system power system as a constraint condition.
Wherein the decision value function of each state can be represented by a recursive formula:
i∈ΩS,t,a∈ΩA,a′∈ΩA,t∈ΩT,t+1∈ΩT
where a and a' are scheduling action indexes, Aa,tIndicating the scheduling action at time t, i.e. the rescheduling strategy of the system at the current time. OmegaA、ΩTRespectively a set of scheduling actions and scheduling instants. c. Ct(Si,t,Aa,t) Is in state S from time t to endi,tTake action Aa,tAn expected cost of time, which is the cost due to load shedding. Because the reliability of the system has a higher scheduling priority during ice damage, the cost expected for load shedding is minimal at this time for scheduling purposes. PC (personal computer)t(Si,t,Aa,t) Is at the current time ti,tIn action Aa,tLoad shedding under actionAnd penalizing the cost.
The system is in state S at time ti,tThe following optimal strategy is obtained when the value function is minimum, i.e. the expected cost is minimum as the objective function:
in the formula (I), the compound is shown in the specification,
for the system at time t state Si,tThe minimum expected cost of.
State S of power system at time ti,tWhen the dispatching is carried out again, the dispatching conventional constraints including power balance, upper and lower limits of unit output, line tide, generator climbing, and upper and lower limits of load and power angle are satisfied.
And 8: and converting the multi-objective optimization problem into a single-objective mixed integer linear programming problem by using a linear scalar method to solve, and taking the occurrence probability of each state as the weight of the objective function of the corresponding state. Because the failure probability of each element of the system is different on the ice disaster track, the topology of the system is changed, and the state S of the systemi,tProbability of occurrence Pi,tCan be calculated as:
in the formula, pi,r,tIs from an initial state to a state S through a path ri,tThe probability of (a) of (b) being,
is from an initial state to a state Si,tSet of paths of [ omega ]SIs a set of system states, NTIs the number of decision instants.
Therefore, the original multi-objective optimization problem is converted into a single-objective mixed integer linear programming problem with the following formula as the target
And solving and determining a scheduling strategy of the power system for corresponding ice disasters.
Example 2:
the specific implementation process of this embodiment is as follows:
the verification calculation of the model of the invention is carried out by adopting IEEE RTS-79 system data to carry out example analysis. The test system contains 24 nodes, 38 transmission lines. All nodes and transmission lines in the system are assumed to be exposed to the open air environment.
The method comprises the steps of dividing the area where a system is located into 1600 x 1800 grids by using a network grid method, assuming that the grids are small enough, representing the node position by using coordinates of the grids, setting each grid to represent a 0.5km x 0.5km geographical area, setting the ice disaster influence radius to be 100km, the moving speed of an ice disaster center to be 50km/h, and setting the maximum wind speed and the maximum precipitation to be 12m/s and 35 mm/h. The system is designed to have a maximum ice thickness M of 10 mm. The ice disaster moving track center moves along a straight line from the starting coordinate (230,440) to the end of the coordinate (1360,1570). Fig. 2 is the system network rasterization result, where the white dots are the generator nodes.
The potential fault element considers the nodes of the power transmission line and the generator, the ice coating thickness of the line is calculated by taking the average value of each grid on the line, and the ice coating thickness of each node is obtained by the grid where the node is located. The weather intensity is simulated by taking 0.01h as a simulation step length, the ice melting condition is not considered, and the fault probability can be obtained according to a fault model, as shown in table 1. Wherein L isa-bShowing a line connecting nodes a and b, GcRepresenting generator node c.
TABLE 1 probability of failure of affected element of the System
Table 2 shows four fault scenarios, 6 scheduling times are selected, and the specific scheduling policies corresponding to the four scenarios are shown in fig. 3 to 6. As can be seen from the figure, since G15、G22、G23And (3) the ice disaster path has a fault risk, the output force is kept around the lower limit of power generation for preventing the large fluctuation of load supply, and the power supply is gradually recovered until the fault risk is cancelled. See in particular fig. 3, 4, 5, 6.
TABLE 2 four System Fault scenarios
To examine the effect of the active scheduling model in reducing load shedding, consider a comparison with the traditional passive-response scheduling model, where: PM is the active scheduling model proposed herein; TM is a traditional passive response scheduling model, active rescheduling is not performed in advance, only after a fault scene occurs at each moment, passive response is performed, and load reduction is minimized by considering operation constraint. FIG. 7 shows the load shedding difference between PM and TM. Only scenes with non-zero differences are shown in the figure.
As can be seen from fig. 7, most fault scenarios use less load shedding of the active scheduling model. The active scheduling considers the fault scene which may appear on the ice disaster moving path at the future time, so that part of load supply is sacrificed at the current time in order to reduce load fluctuation caused by the fault at the future time, and if the potential fault does not completely occur in the actual operation at the later time, the load reduction of the active scheduling model is larger under some scenes. However, from the perspective of all scenarios, the active scheduling model is more effective in reducing the effect of load shedding in this icy weather.
The method disclosed by the invention has the advantages that the foresight effect and the load reduction effect of the method in the aspect of scheduling in the ice disaster weather are fully verified.
Example 3:
the present embodiment provides a computer system, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above embodiments when executing the computer program.
In summary, the invention can be used for scheduling the power system in real time during ice disasters, has the effect of reducing load reduction and good foresight, and provides reference for scheduling the power system under natural disasters.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An ice disaster coping active scheduling method for an electric power system is characterized by comprising the following steps:
dividing an electric power system area into a plurality of small grids according to geographical positions;
establishing an ice disaster weather intensity model, and calculating disaster factors and duration of ice disaster weather to elements of the system;
establishing a fault model of the elements of the system based on the disaster causing factors, calculating the fault probability of the elements and generating a fault set;
establishing a recovery model of an element of the system, and calculating the repair time of the element under the ice disaster by considering the randomness of the ice disaster intensity;
abstracting the topological state transition of the system during the ice disaster period into the Markov state of the system based on the state transition of the elements in the fault model and the recovery model of the elements, calculating the state transition probability of the system during the ice disaster weather period, and generating a system state scene set;
establishing a load reduction penalty function, and calculating the action instant cost;
establishing an active scheduling optimization model, taking the minimum decision value function as a target function, and taking the conventional operation constraint of the power system as a constraint condition;
and converting the multi-objective optimization problem of the objective function into a single-objective mixed integer linear programming problem by using a linear scalar method, and solving the single-objective mixed integer linear programming problem to determine a scheduling strategy of the power system for corresponding ice disasters.
2. The ice disaster coping active scheduling method for the power system as recited in claim 1, wherein the disaster causing factor of the ice disaster to the power system includes an ice coating thickness of a line, and a calculation formula is as follows:
in the formula, RitRepresenting the thickness of the ice coating, i.e. the ice load, N being the time for the element to ice, PjFor the precipitation rate at hour j of the ice coating duration,
is the water content of liquid water in the air, vjWind speed, p, for the corresponding line locationiIs ice density, taken at 0.9g/cm3，ρoIs the density of water, taken at 1.0g/cm3。
3. The method according to claim 2, wherein the fault model of the power system element comprises:
when the ice coating thickness M of the element does not exceed the maximum designed ice-resistant thickness M, the element is not influenced to normally operate;
when the icing thickness M of the element is more than or equal to 5M, the element is in failure and stops running;
probability of failure p when element icing thickness M is between maximum design anti-icing thickness M and 5MfiIncrease exponentially with increasing ice coating thickness:
4. the method according to claim 1, wherein the recovery model of the element of the power system comprises:
calculating the repair time of the element under the ice disaster, and calculating the fault repair time TTR under the ice disaster weatherWAs the time TTR for repairing the ice disaster weather intensity and the normal weatherNThe values of interest, wherein:
TTRW＝kW·TTRN
in the formula, kWFor the weather influence factor, the randomness of the repair time corresponding to different ice disaster intensities is considered in the influence factor.
5. The active scheduling method for ice disaster electric power system according to claim 1, wherein the state transition probability is calculated by the state transition probability of the element:
where i and i' are the states of the system at two adjacent times, k is the element number, Si,tAnd Si′,t+1Represents the state of the system at times t and t +1, respectively, omegaS,tRepresents the set of states, Ω, at time t of the systemC,tA set of elements that are potentially failing at time t; sk,tIs the state of element k at time t, where 0 represents a fault condition and 1 represents a normal operating condition; pr (S)i,t,Si′,t+1)、Pr(sk,t,sk,t+1) Respectively, the state transition probabilities of the system and the element at two adjacent moments.
6. The active scheduling method for the power system in response to the ice disaster as claimed in claim 1, wherein the load reduction penalty function is established, and the action immediate cost is calculated according to the following formula:
in the formula, PCt(Si,t,Aa,t) At time t Si,tIn action Aa,tImmediate cost under influence, Δ Ln,t,iIndicating node n at time ti,tThe amount of load reduction in the state, Δ T is the interval time between adjacent scheduling times, μL,t,nIs the penalty cost of node n per unit time per unit load.
7. The active scheduling method for the ice disaster electric power system according to claim 1, wherein the decision value function is expressed by a recursive formula:
i∈ΩS,t,a∈ΩA,a′∈ΩA,t∈ΩT,t+1∈ΩT
where a and a' are scheduling action indexes, Aa,tRepresenting the scheduling action at the time t, namely the rescheduling strategy of the system at the current time; omegaA、ΩTRespectively a set of scheduling actions and scheduling instants; c. Ct(Si,t,Aa,t) Is in state S from time t to endi,tTake action Aa,tAn expected cost of time, the expected cost being a cost due to load shedding; PC (personal computer)t(Si,t,Aa,t) Is at the current time ti,tIn action Aa,tLoad reduction penalty cost under action;
the system is in state S at time ti,tThe following optimal strategy is obtained when the value function is minimum, i.e. the expected cost is minimum as the objective function:
in the formula (I), the compound is shown in the specification,
for the system at time t state Si,tThe minimum expected cost of.
8. The ice disaster coping power system active scheduling method according to claim 7, wherein a linear scalar method is applied to convert the multi-objective optimization problem of the objective function into the following single-objective mixed integer linear programming problem:
the linear scalar method takes the occurrence probability of each state as the weight of the corresponding state objective function; because the failure probability of each element of the system is different on the ice disaster track, the topology of the system is changed, and the state S of the systemi,tProbability of occurrence Pi,tThe calculation is as follows:
in the formula, pi,r,tIs from an initial state to a state S through a path ri,tThe probability of (a) of (b) being,
is from an initial state to a state Si,tSet of paths of [ omega ]SIs a set of system states, NTIs the number of decision instants.
9. The ice disaster coping power system active scheduling method according to claim 1, wherein the constraint conditions meet scheduling general constraints, including power balance, upper and lower limits of unit output, line power flow, generator climbing, and upper and lower limits of load and power angle constraints.
10. A computer system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the steps of the method of any one of claims 1 to 9 are performed when the computer program is executed by the processor.
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