CN104037810B - A kind of risk assessment generating-load power method of adjustment of improvement - Google Patents
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Abstract
The invention discloses a kind of risk assessment generation load power regulating method, the steps include: system is carried out Load flow calculation, it is judged that it is out-of-limit whether system exists trend；As out-of-limit in there is trend, then carry out power distribution using out-of-limit branch road as Targeted Tributary to analyze, obtain the electromotor node set to Targeted Tributary conveying power and draw the load bus set of power from Targeted Tributary, and the power that carries to Targeted Tributary of these nodes and the power that draws from this Targeted Tributary；Calculate the load adjustment coefficient of each node in the generation adjustment coefficient of each node in electromotor node set and load bus set；Filter out generation adjustment coefficient and relatively large some the electromotor nodes of load adjustment coefficient and load bus as regulating object；The regulating object filtered out is carried out in proportion power adjustment.Use the present invention can effectively reduce the number of the equipment needing adjustment, save the plenty of time.
Description
Technical Field
The invention belongs to the field of risk assessment of an electric power system, and particularly relates to a risk assessment power generation-load power adjustment method.
Background
At present, the safety evaluation methods of the power system are divided into two categories, namely a deterministic method and an uncertain method.
The deterministic method is based on the analysis of expected accidents, and under the most serious condition of the system, the system safety stability margin aiming at a specific expected accident is obtained.
The uncertainty method includes a probabilistic analysis method and a risk analysis method. The probabilistic analysis method can consider the randomness and uncertainty of each accident, and obtains the variation range and probability distribution of the operation parameters according to the statistical characteristics of random factors in the system, so that the system is relatively comprehensively evaluated, but the method only considers the randomness and uncertainty of system faults, does not consider the severity of consequences caused by the system faults, cannot combine the safety and the economy of the system to consider the safety condition of the system, is only the research result of the transitional stage of the deterministic method and the risk analysis method, and is difficult to adapt to the development requirement of the power market.
Modern power system operation seeks to supply electricity to consumers at an acceptable level of reliability at a lower cost, but generally an increase in reliability often results in a decrease in economy. The risk analysis method applies a risk theory to the safety assessment of the power system, can comprehensively consider the possibility and the severity of accidents, and combines the safety and the economical efficiency of the system operation, so that the power grid can be ensured to face smaller risks while acquiring larger benefits, balance is found between the risks and the benefits, risk indexes can guide operators to strengthen the monitoring and the maintenance of serious fault equipment, and the safe, stable and economical operation of the power grid is ensured.
When risk assessment is carried out, load flow calculation needs to be carried out on the system, and if the load flow exceeds the limit, a certain load flow control strategy needs to be adopted to enable the system to be recovered to a normal state. How to recover the system to a normal state in the shortest time by the least power flow correction measures when the power flow of the system is beyond the limit is a necessary research subject.
Common power flow correction measures can be divided into an optimization planning method, a sensitivity method and a power flow analysis method. The optimization planning algorithm takes a function of load reduction as a target function, considers a power flow correction strategy as a mathematical planning problem, and can be specifically divided into linear planning and nonlinear planning. The former has simple programming and high calculation speed, but has larger error due to neglecting the constraint of node voltage and reactive power flow, while the latter includes all the constraint conditions of the system and accurate model, but has the defects of difficult programming, serious time consumption and the like. The sensitivity method is not concerned enough for calculating the load flow adjustment amount, and the power unbalance amount caused by the output adjustment is borne by the balancing machine, so that the balancing machine is out of limit possibly, and the adjustment scheme is not feasible. The calculation time of the two methods is rapidly increased along with the enlargement of the system scale, which is not consistent with the requirement that the system is required to be recovered to a normal state in a shortest time when the power flow of the system is beyond the limit. Many power adjustment models for power distribution analysis by a power flow analysis method are available, and different power adjustment model principles are different, so that remedial measures taken in the models are not completely the same.
Disclosure of Invention
Aiming at the problems that the programming is difficult, the time consumption is serious, larger errors exist, and the balance machine is out of limit possibly caused by the fact that the power unbalance amount caused by the output adjustment is completely born by the balance machine in the conventional power adjustment method, the invention improves a power reduction model in the risk assessment and provides an improved risk assessment power generation-load power adjustment method so as to achieve the purpose of quickly finding out generators and load nodes with relatively small number which need to be adjusted in the risk assessment process and further enabling the system to be recovered to the normal state.
The invention discloses an improved risk assessment power generation-load power adjustment method, which is used for improving a power reduction model in risk assessment through a power generation adjustment coefficient and a load adjustment coefficient and comprises the following steps:
the method comprises the following steps: inputting system information including network topology, element parameters, power generation, load parameters and faults in an expected accident set of a power system; carrying out load flow calculation on the system, and judging whether the load flow of the system exceeds the limit;
step two: if the system has a load flow out-of-limit, taking the out-of-limit branch as a target branch, and performing power distribution analysis on the target branch by adopting an analytical method so as to obtain a generator node set for transmitting power to the target branch and a load node set for drawing power from the target branch, as well as the power transmitted to the target branch by the generator node in the two sets and the power drawn from the target branch by the load node;
step three: calculating the power generation adjustment coefficient of each node in the generator node set and the load adjustment coefficient of each node in the load node set in the step two; wherein,
the power generation adjustment coefficient of the generator node m includes: the ratio of the power transmitted by the generator node m to the power transmitted by the target branch i to the total power of the generator node mThe ratio of the power transmitted by the generator node m to the power of the target branch iWherein, PGm->iRefers to the power, P, transmitted from the generator node m to the target branch iGmRefers to the power, P, of the generator node miRefers to the power of the target branch i;
the load adjustment coefficient of the load node n comprises: the load node n is a slave targetThe proportion of the power drawn by the branch i to the total power of the load node n isThe proportion of the power drawn by the load node n from the target branch i to the power of the target branch i isWherein, Pi->LnRefers to the power, P, drawn by the load node n from the target branch iLnRefers to the power, P, of the load node niRefers to the power of the target branch i;
step four: some generator nodes and load nodes with relatively large power generation adjustment coefficients and relatively large load adjustment coefficients are screened out from the generator nodes and the load nodes to be used as adjustment objects, and the method for specifically determining the number of the generator nodes and the number of the load nodes which need to be adjusted comprises the following steps: for the generator node, selecting nodes with two proportionality coefficients respectively larger than lambda 1 and lambda 2 in the power generation adjustment coefficient as adjustment objects; for the load nodes, selecting nodes with two proportionality coefficients respectively larger than lambda 3 and lambda 4 in the load adjustment coefficients as adjustment objects; λ 1, λ 2, λ 3, λ 4 correspond to the ratio fa，fb，ga，gbThe value of the coefficient (f) is determined according to the actual condition of the system, the value method is given by taking the value of lambda 1 as an example, and the f of each node in the generator node set obtained in the step two is usedaSorting may be performed byaDivided into two groups A and B, f of group AaF of group BaOne order of magnitude larger, then with the largest f in group BaThe value of (b) is taken as the value of lambda 1; in the same way, the values of lambda 2, lambda 3 and lambda 4 are the same as lambda 1;
step five: and D, performing power adjustment on the adjustment object screened in the step four according to the following proportion: the power to be cut off for the generator node is: pGcut＝(Pi-over/Pi)·PGFor the load node, the power to be cut off is: pLcut＝(Pi-over/Pi)·PLWherein: pi-overFor out-of-limit power of out-of-limit branch i, PGIs the power of the generator node, PiTo limit the power of branch i, PLIs the power of the load node.
Further, in the second step, the out-of-limit branch is used as the target branch, and the power distribution is performed on the target branch i, so as to obtain a set Gi { Gi,1, Gi,2, …, Gi, m } of generator nodes which transmit power to the target branch i, a set Li { Li,1, Li,2, …, Li, n } of load nodes which draw power from the target branch i, and power P transmitted by these nodes to the target branch ii-G＝{PG1->i，PG2->i，…，PGn->iH and the power P drawn from the target branch ii-L＝{Pi->L1，Pi->L2，…，Pi->Ln}。
In the fourth step, if there is only one element in the generator node set or the load node set obtained in the second step, there is one of the following situations: λ 1 is taken to be smaller than the ratio faOr λ 2 is taken to be smaller than the ratio fbOr λ 3 is taken to be less than the ratio gaOr λ 4 is taken to be less than the ratio gbAny value of (a);
otherwise: the value method of the lambda 1 is as follows: the proportion f of each node in the generator node set obtained in the third stepaSorting in descending order, and sorting the ratio f of each nodeaThe group A and the group B are divided according to the following relationship: all ratios f in group AaAll ratios f in the ratio B groupaOne order of magnitude larger, then the largest ratio f in group BaAs the value of λ 1; the value method of lambda 2 is as follows: the proportion f of each node in the generator node set obtained in the third stepbSorting in descending order, and sorting the ratio f of each nodebThe group A and the group B are divided according to the following relationship: all ratios f in group AbAll ratios f in the ratio B groupbOne order of magnitude larger, then the largest ratio f in group BbAs the value of λ 2; the value method of the lambda 3 is as follows: step threeThe ratio g of each node in the load node set obtained in (1)aSorting in descending order, and sorting the sorted proportion g of each nodeaThe group A and the group B are divided according to the following relationship: all proportions g in group AaAll ratios g in group BaOne order of magnitude larger, then g is the largest proportion in group BaAs the value of λ 3; the value method of lambda 4 is as follows: the proportion g of each node in the load node set obtained in the third stepbSorting in descending order, and sorting the sorted proportion g of each nodebThe group A and the group B are divided according to the following relationship: all proportions g in group AbAll ratios g in group BbOne order of magnitude larger, then g is the largest proportion in group BbThe value of (d) is taken as the value of λ 4.
For a target branch i, m generator nodes transmit power to the target branch i, and the power generation adjustment coefficient sets B of the m generator nodesfaAnd a power generation adjustment coefficient set BfbRespectively as follows: b isfa＝{fa1,fa2,...,fam}，Bfb＝{fb1,fb2,...,fbm}; meanwhile, for the target branch i, n load nodes draw power from the target branch i, and then the load adjustment coefficient sets B of the n load nodesgaAnd load adjustment coefficient set BgbRespectively as follows: b isga＝{ga1,ga2,...,gan}，Bgb＝{gb1,gb2,...,gbnFrom the power generation adjustment coefficient set BfaAnd a power generation adjustment coefficient set BfbSet of load adjustment coefficients BgaAnd load adjustment coefficient set BgbAnd screening out elements respectively larger than lambda 1, lambda 2, lambda 3 and lambda 4, and taking the generator node and the load node corresponding to the elements as adjustment objects.
Compared with the prior art, the invention has the beneficial effects that:
the method is applied to the risk evaluation of the power system, when the load flow of the system exceeds the limit, the limit-exceeding branch is taken as a target branch to carry out power distribution analysis on the target branch, a set of nodes which are associated with the target branch and need to be subjected to power adjustment is found out, two concepts of a power generation adjustment coefficient and a load adjustment coefficient are introduced on the basis, the nodes which have relatively large influence on the target branch and relatively small influence on non-target branches are screened out through related calculation and taken as adjustment objects, and compared with the existing method, the number of devices which need to be adjusted is reduced, and a large amount of time is saved.
Drawings
FIG. 1 is a flow chart of an improved risk assessment power generation-load power adjustment method provided by the present invention;
FIG. 2 is a flow chart of an application of the improved risk assessment power generation-load power adjustment method provided by the present invention in a power system risk assessment;
fig. 3 is a comparison graph of the total number of node adjustments in the process of adjusting the improved risk assessment power generation-load power adjustment method provided by the invention, wherein the control strategy when no coefficient is introduced is compared with the control strategy when a coefficient is introduced.
Detailed Description
The following describes the present invention in detail by taking an IEEE24 node system as an example, with reference to the accompanying drawings and tables.
As shown in fig. 1, the improved risk assessment power generation-load power adjustment method of the present invention is formed by improving a power adjustment model for power distribution analysis by an analytic method by introducing two concepts of a power generation adjustment coefficient and a load adjustment coefficient, and takes an IEEE24 node system as an example, and includes the following specific steps:
the application flow chart of the invention in the risk assessment of the IEEE24 node system is shown in figure 2, faults in an expected accident set are scanned by calling a load flow calculation program, and when the load flow is more limited, the power is adjusted by applying the method provided by the invention.
The method comprises the following steps: inputting system information including network topology, element parameters, power generation, load parameters and faults in an expected accident set of a power system, reading one fault and calling a load flow calculation program to carry out fault scanning on the system, judging whether the load flow of the system is converged, if so, judging whether the load flow exceeds a limit, and if not, carrying out reactive power flow adjustment calculation until the system is converged;
step two: if the power flow of the system does not exceed the limit, storing a fault scanning result, and returning to the step one; if the system has a load flow out-of-limit, taking the out-of-limit branch as a target branch, and performing power distribution analysis on the target branch by adopting an analytical method so as to obtain a generator node set for transmitting power to the target branch and a load node set for drawing power from the target branch, as well as the power transmitted to the target branch by the generator node in the two sets and the power drawn from the target branch by the load node; the specific process is as follows:
the system comprises an out-of-limit branch serving as a target branch, and power distribution analysis is performed on the target branch i to obtain a set Gi ═ Gi,1, Gi,2, …, Gi, m } of generator nodes for transmitting power to the target branch i and a set Li ═ Li,1, Li,2, …, Li, n } of load nodes for drawing power from the target branch i, and power P transmitted by the nodes to the target branch ii-G＝{PG1->i，PG2->i，…，PGn->iH and the power P drawn from the target branch ii-L＝{Pi->L1，Pi->L2，…，Pi->Ln}。
Taking a line 2 and line 16 disconnection fault as an example, when the line 30 is out of limit, the generator node sets for transmitting power to the line 30 are { Bus130, Bus150, Bus160, Bus180, Bus210, Bus220, Bus230, Bus70 }; the set of load nodes drawing power from the line 30 is { Bus30 }.
Step three: calculating the power generation adjustment coefficient of each node in the generator node set and the load adjustment coefficient of each node in the load node set in the step two; wherein,
the power generation adjustment coefficient of the generator node m includes: the ratio of the power transmitted by the generator node m to the power transmitted by the target branch i to the total power of the generator node mThe ratio of the power transmitted by the generator node m to the power of the target branch iWherein, PGm->iRefers to the power, P, transmitted from the generator node m to the target branch iGmRefers to the power, P, of the generator node miRefers to the power of the target branch i;
the load adjustment coefficient of the load node n comprises: the proportion of the power drawn by the load node n from the target branch i to the total power of the load node n isThe proportion of the power drawn by the load node n from the target branch i to the power of the target branch i isWherein, Pi->LnRefers to the power, P, drawn by the load node n from the target branch iLnRefers to the power, P, of the load node niRefers to the power of the target branch i;
the power generation adjustment factors for the nodes in the set of generator nodes delivering power to the line 30 and the load adjustment factors for the nodes in the set of load nodes drawing power from the line 30 are shown in table 1.
TABLE 1 Generation and load adjustment coefficients for each node associated with line 30
| Generator node | Ratio fa | Ratio fb | Load node | Ratio ga | Ratio gb |
| BUS130 | 0.111 | 0.094 | BUS30 | 1 | 1 |
| BUS150 | 0.032 | 0.037 | |||
| BUS160 | 0.09 | 0.075 | |||
| BUS180 | 0.035 | 0.074 | |||
| BUS210 | 0.033 | 0.07 | |||
| BUS220 | 0.06 | 0.096 | |||
| BUS230 | 0.151 | 0.531 |
| BUS70 | 0.019 | 0.03 |
Step four: some generator nodes and load nodes with relatively large power generation adjustment coefficients and load adjustment coefficients are selected from the nodes to be used as adjustment objects, and the method for specifically determining the number of the generator nodes and the number of the load nodes which need to be adjusted comprises the following steps: for the generator node, selecting nodes with two proportionality coefficients respectively larger than lambda 1 and lambda 2 in the power generation adjustment coefficient as adjustment objects; for the load nodes, selecting nodes with two proportionality coefficients respectively larger than lambda 3 and lambda 4 in the load adjustment coefficients as adjustment objects; λ 1, λ 2, λ 3, λ 4 correspond to fa，fb，ga，gbThe coefficient and the value of (2) depend on the actual condition of the system, and the value taking method is given as reference: taking the value of λ 1 as an example, f of each node in the generator node set obtained in the third stepaSorting may be performed byaDivided into two groups A and B, f of group AaF of group BaOne order of magnitude larger, then with the largest f in group BaThe value of (b) is taken as the value of lambda 1, and the methods for taking the values of lambda 2, lambda 3 and lambda 4 are the same as that of lambda 1; the specific content is as follows: for a target branch i, m generator nodes transmit power to the branch, and the power generation adjustment coefficient sets B of the m generator nodesfaAnd a power generation adjustment coefficient set BfbRespectively as follows: b isfa＝{fa1,fa2,...,fam}，Bfb＝{fb1,fb2,...,fbm}; for the target at the same timeIf n load nodes draw power from the branch, the load adjustment coefficient sets B of the n load nodesgaAnd load adjustment coefficient set BgbRespectively as follows: b isga＝{ga1,ga2,...,gan}，Bgb＝{gb1,gb2,...,gbnFrom the power generation adjustment coefficient set BfaAnd a power generation adjustment coefficient set BfbSet of load adjustment coefficients BgaAnd load adjustment coefficient set BgbAnd screening out elements respectively larger than lambda 1, lambda 2, lambda 3 and lambda 4, and taking the generator node and the load node corresponding to the elements as adjustment objects.
From the power generation adjustment coefficient and the load adjustment coefficient of each node in table 1, it is possible to obtain:
Bfa＝{0.111,0.032,0.09,0.035,0.033,0.06,0.151,0.019},Bfb＝{0.094,0.037,0.075,0.074,0.07,0.096,0.531,0.03},Bga＝{1},Bgbif {1}, λ 1, λ 2, λ 3, and λ 4 may be 0.09,0.096,0.9, and 0.9, respectively. Selection of fa，fbGenerator nodes with g larger than λ 1, λ 2, respectivelya，gbLoad nodes respectively larger than lambda 3 and lambda 4, namely a generator node Bus230 and a load node Bus30 are taken as adjusting objects;
step five: and D, performing power adjustment on the adjustment object screened in the step four according to the following proportion: the power to be cut off for the generator node is: pGcut＝(Pi-over/Pi)·PGFor the load node, the power to be cut off is: pLcut＝(Pi-over/Pi)·PLWherein: pi-overFor out-of-limit power of out-of-limit branch i, PGIs the power of the generator node, PiTo limit the power of branch i, PLIs the power of the load node.
The out-of-limit power of the line 30 is 4.04MW, the power to be cut off by the generator node Bus230 is 3.88MW, and the power to be cut off by the load node Bus30 is 3.88 MW;
and after the power reduction is obtained, storing the fault scanning result. And repeating the first step to the fifth step until the expected accident set is traversed, and then outputting a failure state analysis result.
In the risk assessment of the power system, a state enumeration method is usually adopted for scanning N-2 expected accidents, after the power flow of the system exceeds a limit, an optimization planning algorithm control scheme can be respectively adopted, a control scheme for directly reducing power in proportion after a node set is obtained by performing power distribution analysis by using an analytic method, and a control scheme for reducing nodes with large power generation adjustment coefficients and large load adjustment coefficients after a node set is obtained by performing power distribution analysis by using an analytic method for carrying out power flow correction, wherein the following results are comparison results of three control schemes in the case of a few typical line faults, wherein a table 2 is a control scheme in the case of faults of faulty lines 2 and 16, a table 3 is a control scheme in the case of faults of faulty lines 10 and 16, and a table 4 is a control scheme in the case of faults of faulty lines 14 and 19.
Table 2 control scheme in case of fault line 2,16 fault
TABLE 3 control scheme in case of failure of faulty lines 10,16
TABLE 4 control scheme in case of failure of faulty line 14,19
It can be seen from tables 2 to 4 that when the disconnection fault occurs in the branch 2,16, for eliminating the out-of-limit, when the optimization planning algorithm control scheme is adopted, it is necessary to reduce power 16.36MW at the load node BUS30, the generator BUS10 reduces 165MW, the generator BUS130 reduces 262.95MW, the generator BUS160 increases to process 73MW, the generator BUS20 increases to process 246MW, the generator BUS230 increases to output 104MW, and the generator BUS70 reduces power 3 MW.
By adopting the method for reducing the introduction coefficient of the power distribution analysis in proportion, only the power of the load node BUS30 needs to be reduced by 3.88MW, and the power of the generator BUS230 needs to be reduced by 3.88 MW.
It can be seen from tables 2 to 4 that the out-of-limit state can be eliminated by using the three methods, so that the system is restored to the normal state. The optimized planning algorithm control scheme can minimize the reduction amount of power, but the number of nodes needing to be regulated is large, and the power regulation amount of each node is large. By directly reducing the power distribution analysis in proportion, the number of nodes needing to be adjusted is large, but the power adjustment amount of a single node is small. Compared with the former two methods, the method for reducing the introduction coefficient in proportion by utilizing the power distribution analysis has better control strategy, less nodes needing to be adjusted and small power adjustment amount of each node.
In addition, the power unbalance amount caused by the output adjustment of the first optimization planning algorithm control scheme is completely borne by the balancing machine, which may cause the balancing machine to be out of limit, so that the scheme is not feasible. The last two methods (direct proportional reduction after power distribution analysis and introduction of coefficient proportional reduction after power distribution analysis) consider the problem of the balance of the change amounts of the generator node and the load node, and do not increase the power carrying capacity of the balancing machine.
In the aspect of calculating speed, for an IEEE24 node system, a first optimization planning algorithm control scheme is adopted to perform fault scanning once and adjust all out-of-limit conditions, 270s is needed in total, while the method for introducing coefficient proportional reduction by utilizing power distribution analysis of the invention only needs 147s, and it can be seen that the speed of the latter is obviously superior to that of the former on the basis of simultaneously meeting certain precision.
The branches with out-of-limit in all faults of the IEEE24 node system are corrected, and fig. 3 shows the comparison result of the number of nodes that need to be adjusted in two cases of a control strategy without introducing coefficients (which is a direct proportional reduction method after the second power distribution analysis) and a control strategy with introducing coefficients (which is an introduction coefficient proportional reduction method after the power distribution analysis according to the present invention). It can be seen that by introducing two concepts of a power generation adjustment coefficient and a load adjustment coefficient, the number of nodes needing to be adjusted is obviously reduced, adjustment measures for power flow correction are simplified, and much time is saved.
While the present invention has been described with reference to the accompanying drawings, the present invention is not limited to the above-described embodiments, which are illustrative only and not restrictive, and various modifications which do not depart from the spirit of the present invention and which are intended to be covered by the claims of the present invention may be made by those skilled in the art.
Claims (3)
1. An improved risk assessment power generation-load power adjustment method is characterized in that a power reduction model in risk assessment is improved through a power generation adjustment coefficient and a load adjustment coefficient, and the method comprises the following steps:
the method comprises the following steps: inputting system information including network topology, element parameters, power generation, load parameters and faults in an expected accident set of a power system; carrying out load flow calculation on the system, and judging whether the load flow of the system exceeds the limit;
step two: if the system has a load flow out-of-limit, taking the out-of-limit branch as a target branch, and performing power distribution analysis on the target branch by adopting an analytical method so as to obtain a generator node set for transmitting power to the target branch and a load node set for drawing power from the target branch, as well as the power transmitted to the target branch by the generator node in the two sets and the power drawn from the target branch by the load node;
step three: calculating the power generation adjustment coefficient of each node in the generator node set and the load adjustment coefficient of each node in the load node set in the step two; wherein,
the power generation adjustment coefficient of the generator node m includes: the ratio of the power transmitted by the generator node m to the power transmitted by the target branch i to the total power of the generator node mThe ratio of the power transmitted by the generator node m to the power of the target branch iWherein, PGm->iRefers to the power, P, transmitted from the generator node m to the target branch iGmRefers to the total power, P, of the generator node miRefers to the power of the target branch i;
the load adjustment coefficient of the load node n comprises: the proportion of the power drawn by the load node n from the target branch i to the total power of the load node n isThe proportion of the power drawn by the load node n from the target branch i to the power of the target branch i isWherein, Pi->LnRefers to the power, P, drawn by the load node n from the target branch iLnRefers to the total power, P, of the load node niRefers to the power of the target branch i;
step four: a plurality of generator nodes and load nodes with relatively large power generation adjustment coefficients and relatively large load adjustment coefficients are screened from the generator nodes and the load nodes to be used as adjustment objects, and the number of the generator nodes and the number of the load nodes are determined as follows:
for the generator node, selecting nodes with two proportionality coefficients respectively larger than lambda 1 and lambda 2 in the power generation adjustment coefficient as adjustment objects; for the load nodes, selecting nodes with two proportionality coefficients respectively larger than lambda 3 and lambda 4 in the load adjustment coefficients as adjustment objects; λ 1, λ 2, λ 3, λ 4 correspond to the ratio faRatio fbRatio gaAnd the ratio gbThe value of the coefficient (2) depends on the actual condition of the system;
if only one element exists in the generator node set or the load node set obtained in the step two, one of the following situations exists:
λ 1 is taken to be smaller than the ratio faAny of the values of (a), (b), (c), (d,
λ 2 is taken to be smaller than the ratio fbAny of the values of (a), (b), (c), (d,
the ratio of lambda 3 is less than gaAny of the values of (a), (b), (c), (d,
lambda 4 is taken to be less than the ratio gbAny value of (a);
otherwise:
the value method of the lambda 1 is as follows: the proportion f of each node in the generator node set obtained in the third stepaSorting in descending order, and sorting the ratio f of each nodeaThe group A and the group B are divided according to the following relationship: all ratios f in group AaAll ratios f in the ratio B groupaOne order of magnitude larger, then the largest ratio f in group BaAs the value of λ 1;
the value method of lambda 2 is as follows: the proportion f of each node in the generator node set obtained in the third stepbSorting in descending order, and sorting the ratio f of each nodebThe group A and the group B are divided according to the following relationship: all ratios f in group AbAll ratios f in the ratio B groupbOne order of magnitude larger, then the largest ratio f in group BbAs the value of λ 2;
the value method of the lambda 3 is as follows: the load node obtained in the third stepProportion g of each node in the set of pointsaSorting in descending order, and sorting the sorted proportion g of each nodeaThe group A and the group B are divided according to the following relationship: all proportions g in group AaAll ratios g in group BaOne order of magnitude larger, then g is the largest proportion in group BaAs the value of λ 3;
the value method of lambda 4 is as follows: the proportion g of each node in the load node set obtained in the third stepbSorting in descending order, and sorting the sorted proportion g of each nodebThe group A and the group B are divided according to the following relationship: all proportions g in group AbAll ratios g in group BbOne order of magnitude larger, then g is the largest proportion in group BbAs the value of λ 4:
step five: and D, performing power adjustment on the adjustment object screened in the step four according to the following proportion: the power to be cut off for the generator node is: pGcut＝(Pi-over/Pi)·PGFor the load node, the power to be cut off is: pLcut＝(Pi-over/Pi)·PLWherein: pi-overFor out-of-limit power of out-of-limit branch i, PGIs the power of the generator node, PiTo limit the power of branch i, PLIs the power of the load node.
2. The improved risk assessment power generation-load power adjustment method according to claim 1, wherein in step two, with the out-of-limit branch as the target branch, a set Gi { Gi,1, Gi,2, …, Gi, m } of generator nodes delivering power to the target branch i and a set Li { Li,1, Li,2, …, Li, n } of load nodes drawing power from the target branch i are obtained by performing power distribution on the target branch i, and the power P delivered by these nodes to the target branch i is obtainedi-G＝{PG1->i，PG2->i，…，PGn->iH and the power P drawn from the target branch ii-L＝{Pi->L1，Pi->L2，…，Pi->Ln}。
3. The improved risk assessment power generation-load power adjustment method according to claim 1, wherein in step four, for a target branch i, m generator nodes transmit power to the target branch i, and the power generation adjustment coefficient sets B of the m generator nodesfaAnd a power generation adjustment coefficient set BfbRespectively as follows: b isfa＝{fa1,fa2,...,fam}，Bfb＝{fb1,fb2,...,fbm}; meanwhile, for the target branch i, n load nodes draw power from the target branch i, and then the load adjustment coefficient sets B of the n load nodesgaAnd load adjustment coefficient set BgbRespectively as follows: b isga＝{ga1,ga2,...,gan}，Bgb＝{gb1,gb2,...,gbnFrom the power generation adjustment coefficient set BfaAnd a power generation adjustment coefficient set BfbSet of load adjustment coefficients BgaAnd load adjustment coefficient set BgbAnd screening out elements respectively larger than lambda 1, lambda 2, lambda 3 and lambda 4, and taking the generator node and the load node corresponding to the elements as adjustment objects.
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