CN112821427A - Distributed frequency modulation auxiliary service system design method - Google Patents
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Abstract
The invention discloses a method for designing a distributed frequency modulation auxiliary service system, which comprises the following steps: s1, constructing a distributed frequency modulation system based on the block chain, wherein the distributed frequency modulation system comprises a load center, a scheduling center and a plurality of generator sets; s2, calculating the frequency modulation integral of each generator set based on the global frequency modulation effect of the power system and the individual frequency modulation performance of the generator sets; s3, constructing a frequency response model of the distributed frequency modulation system; s4, carrying out frequency modulation on the power system based on the distributed frequency modulation system frequency response model, adjusting the secondary frequency modulation gain of each generator set based on the self-learning process in the process of carrying out frequency modulation on the power system, and updating the frequency modulation integral of each generator set; and S5, settling the frequency modulation integral of each generator set through the dispatching center to finish the frequency modulation of the power system. The invention can effectively complete the frequency modulation task and the integral settlement function of the power system and fully mobilize the enthusiasm of the frequency modulation unit, thereby promoting the efficient utilization of distributed frequency modulation resources.
Description
Technical Field
The invention relates to the technical field of power system frequency modulation auxiliary service, in particular to a distributed frequency modulation auxiliary service system design method.
Background
With the continuous expansion of the scale of the current power system and the continuous increase of the new energy ratio, the problem of power frequency stability is increasingly highlighted. Due to the diversity and complexity of the load, the frequency modulation effect based on the demand response is greatly different due to different load properties of each area, and new cost is required to be generated for specific demand response analysis aiming at the load characteristics of different areas. With the deep execution of supply side reform in a new electricity generation reform, the frequency modulation task is redirected from the load side to the supply side, however, as the frequency modulation process is uniformly arranged by a superior dispatching department, all frequency modulation units cannot be guaranteed to achieve the optimal benefit during frequency modulation distribution, and the frequency modulation effect is influenced by the actual power system operating environment, so that the settlement of the frequency modulation benefit cannot be unified.
Disclosure of Invention
The invention aims to provide a design method of a distributed frequency modulation auxiliary service system, which aims to solve the technical problems in the prior art, effectively complete the frequency modulation task and the integral settlement function of a power system and fully mobilize the enthusiasm of a frequency modulation unit, thereby improving the efficient utilization of distributed frequency modulation resources.
In order to achieve the purpose, the invention provides the following scheme: the invention provides a design method of a distributed frequency modulation auxiliary service system, which is used for carrying out auxiliary frequency modulation on a power system and comprises the following steps:
s1, constructing a distributed frequency modulation system based on the block chain, wherein the distributed frequency modulation system comprises a load center, a scheduling center and a plurality of generator sets;
s2, calculating the frequency modulation integral of each generator set based on the global frequency modulation effect of the power system and the individual frequency modulation performance of the generator sets;
s3, constructing a distributed frequency modulation system frequency response model based on the frequency change of the power system and the output change of each generator set;
s4, carrying out frequency modulation on the power system based on the distributed frequency modulation system frequency response model, adjusting the secondary frequency modulation gain of each generator set based on a self-learning process in the process of carrying out frequency modulation on the power system, and updating the frequency modulation integral of each generator set;
and S5, settling the frequency modulation integral of each generator set through the dispatching center to finish the frequency modulation of the power system.
Preferably, in S2, the global frequency modulation effect of the power system is determined by a global effect factor ατThe individual frequency modulation performance of the generator set is represented by an individual performance factor betag,τRepresents;
global effect factor alphaτIs calculated as shown in equation 1:
wherein f isssIn order to obtain a frequency modulation dead zone, delta t is the time length of each frequency modulation of the generator set, delta f (t) is the frequency variation of the power system at the moment t, and delta f (t) is f (t) -fNF (t) is the frequency of the power system at time t, fNIs rated power;
individual performance factor betag,τIs calculated as shown in equation 2:
wherein, Δ Pg(t) is the active power variation of the generator set G, namely the output variation of the generator set G, and G belongs to [1, G ]]G is the number of generator sets; delta PL(t) is the load active power variation of the load center; q. q.sgFor the frequency modulation product of the generator set g, qg∈[0,1]；
Integral delta of frequency modulation of generator set g in the Tth frequency modulationg,τIs calculated as shown in equation 3:
δg,τ＝ω·ατ+(1-ω)·βg,τ… … … … … … … … … 3 where ω is a weight coefficient, ω ∈ [0,1 ]]ω and qgNegative correlation, as shown in equation 4:
qg＝1-bg·ω……………………………4
wherein, bgRepresenting the value of the positive coefficient, bg∈[0,1]。
Preferably, in S2, the calculation of the frequency modulation integral is performed by an intelligent contract of the block chain, where the input of the intelligent contract is Δ Pg(t)、Δf(t)、ΔPL(t) output is ατ、βg,τ、δg,τ。
Preferably, in S3, the frequency of the power system varies according to formula 5:
wherein H is an inertia constant, D is a damping coefficient, and delta PG(t) represents the total active power variation of the generator set at the time t, as shown in equation 6:
and the output change of the generator set is restricted by a speed regulating system of the generator set.
Preferably, in S4, the method for modulating the frequency of the power system includes:
s4.1, monitoring the frequency change of the power system in real time by each generator set, receiving the load fluctuation of the load center, and actively performing output response by each generator set based on the frequency change of the power system and the load fluctuation of the load center;
and S4.2, updating the frequency variation of the power system through the frequency response model of the distributed frequency modulation system, and repeating the step S4.1 until the frequency modulation of the power system is completed.
Preferably, each generator set adjusts the secondary frequency modulation gain of the generator set through a self-learning process, and actively performs output response according to the adjustment result of the secondary frequency modulation gain of the generator set.
Preferably, in S5, the specific method for settling the frequency modulation integral of each generator set includes:
s5.1, acquiring an examination unit after each frequency modulation is finished;
s5.2, giving out an output variation curve of the checking unit in the frequency modulation process of the current round through the dispatching center, sending the output variation curve in the frequency modulation process of the current round to the checking unit through each power generating unit, and calculating a frequency variation curve of the power system in the frequency modulation process of the current round through the checking unit;
s5.3, based on the comparison result of the calculated value and the actual value of the frequency change curve of the power system, the checking unit is used for checking malicious units and updating frequency modulation integral, the updating result of the frequency modulation integral is uploaded to the block chain, and the frequency modulation integral is broadcasted to the whole network;
and S5.4, after the total frequency modulation integral of the distributed frequency modulation system reaches a preset threshold value, initiating an application to the dispatching center through the examination unit, transferring the frequency modulation integral in a mode of transferring accounts to the block chain of the dispatching center, and finishing the settlement of the frequency modulation integral.
Preferably, in S5.1, the censorship unit is alternately replaced in all generator units participating in frequency modulation and having the right to obtain the interest of frequency modulation points.
Preferably, the dispatching center collects actual output variation curves of the generator sets.
Preferably, in S5.3, the specific method for the censoring unit to censore the malicious unit and update the frequency modulation integral includes:
if the calculated value of the frequency change curve of the power system is consistent with the actual value, no malicious unit exists, and the frequency modulation integral is updated based on the intelligent contract; otherwise, the malicious units exist, the output variation curves of all the generator sets are sent to the dispatching center through the inspection unit for secondary verification, the malicious units are found out, the actual output variation curves of all the generator sets are sent to the inspection unit, the malicious units are continuously inspected through the inspection unit until the calculated value of the frequency variation curve of the power system is consistent with the actual value, the output variation of the malicious units is assigned to be 0, and then the frequency modulation integral is updated based on the intelligent contract.
The invention discloses the following technical effects:
(1) the distributed frequency modulation system is constructed based on the block chain, and each generator set actively carries out output response based on the frequency change of the power system and the load fluctuation of the load center, so that the computational power consumption generated by optimized scheduling of the scheduling center can be greatly reduced, the delay time from the load change to the execution of frequency modulation of the generator set is reduced, and the frequency modulation effect is improved;
(2) the settlement of the integral of each unit in the distributed frequency modulation system can comprehensively consider the overall frequency modulation effect of the power system and the individual performance of each generator set, thereby ensuring that the frequency modulation task is met, fully mobilizing the frequency modulation activity of each generator set, and flexibly adjusting the weight of the two generator sets according to the actual requirement;
(3) the settlement process of the points adopts a multi-party consensus mode, the checking units are selected in turn to verify and check the point results, the market participation degree of the frequency modulation units and the authenticity of the results can be improved, the whole system achieves a good co-treatment system, and the extra cost generated by system operation maintenance, settlement disputes and the like can be reduced.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a schematic diagram of the overall operation mode of a distributed frequency modulation system according to the present invention;
FIG. 2 is a schematic diagram of the input and output streams of the intelligent contract for frequency modulation integral calculation according to the present invention;
FIG. 3 is a schematic diagram of a distributed FM frequency response model of the present invention;
FIG. 4 shows the invention kr,gA self-learning process schematic diagram;
FIG. 5 is a flow chart of the FM credit settlement of the present invention;
FIG. 6 is a graph of variation of gain of the second order FM of the unit during 200 trains in accordance with an embodiment of the present invention;
FIG. 7 is a diagram illustrating the variation of the integral of each unit during 200 training sessions according to an embodiment of the present invention;
FIG. 8 is a graph comparing frequency fluctuations in 4 frequency modulations according to an embodiment of the present invention;
FIG. 9 is a graph comparing frequency fluctuations at different ω according to the embodiment of the present invention;
FIG. 10 is a graph of the integrated and chirped gain variation for different omega times in an embodiment in accordance with the present invention;
FIG. 11 is a graph illustrating the variation of the load and the unit output in the 80 th frequency modulation according to the embodiment of the present invention;
fig. 12 is a graph of the variation of the integral and the profit of each unit for 100 frequency modulations in the embodiment of the present invention, wherein fig. 12(a) is a graph of the variation of the integral, and fig. 12(b) is a graph of the variation of the profit;
FIG. 13 is a graph comparing the frequency fluctuation of the present invention method with that of the prior art centralized frequency modulation method.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
The overall architecture of the distributed frequency modulation system comprises the following components:
in the invention, the overall architecture of the distributed frequency modulation system is realized based on the block chain community thinking.
1. Block chain community thinking:
while the block chain technology is developed, the thinking mode brought by the block chain technology also has extremely high reference value. The block chain community thinking aims at constructing a community containing distributed individuals, community members have a common target, and the system enables the community members to spontaneously contribute to the productivity of the community members through a certain incentive mode, so that the difficulty of the overall target is simplified, the community achieves a self-organization state, and the community members can achieve a win-win situation.
The block chain community thinking has significance for value transfer and production transformation. The existing internet architecture is regarded as an information internet as a machine for connecting everything, realizing free flow of information. The block chain is used as a decentralized, non-falsifiable and traceable technology, distributed individuals are further connected from a value level on the basis of the information internet, a large-scale high-precision cooperative intelligent body is formed, and the value internet is realized. Meanwhile, from the production angle, the existing technologies such as cloud computing, big data, artificial intelligence and the like become important chips for improving productivity through a unique computing mode, and the technology is a revolution of productivity; the block chain technology changes the structure of the existing productivity according to the distributed characteristics, changes the coordination relationship between the existing productivity through means such as a consensus mechanism, a miner mechanism and the like, and is a revolution of production relationship.
2. And (3) integrating degree analysis of the distributed frequency modulation system and the block chain:
the power system frequency modulation is an important means for maintaining the balance and stability of the power system and can be effectively executed by means of block chain community thinking. The overall operation mode of the distributed frequency modulation system based on the thought of the blockchain community is shown in fig. 1. A decentralized frequency modulation network is constructed through a block chain distributed thinking, the frequency modulation network is different from a traditional system which is executed by a unit after a central scheduling center issues a frequency modulation command, unit nodes in the network can be used as independent individuals to participate in division work cooperation, under the promotion of an excitation mode, own output decision is made, and the frequency stabilization and active response are achieved together. The blockchain system and the distributed frequency modulation system have a fit relationship in three important aspects of data disclosure, value mining and example integration, and the comparison relationship is shown in table 1.
1) Data disclosure: in blockchains, information is tagged spatio-temporally, packed from one block to another, and propagated by an infinite set of copies to all nodes of the network, thereby leaving the information ubiquitous. In the distributed frequency modulation system, the frequency is used as a main target of frequency modulation, and natural public and distributed characteristics are presented, namely, in a system with a limited range, the frequency quantity with the same value can be detected anywhere, and the supply and demand balance condition of the current power system is judged by comparing the actual value with a rated value.
2) Value mining: the block chain can generate new value through reconfiguration of resources, so that idle resources which are not valuable in the supply side originally are considered to be alive, the utilization rate of the resources is effectively improved, and the purpose of matching supply and demand of social resources is achieved. Under the original frequency modulation mechanism, a scheduling center issues a frequency modulation command according to a certain scheduling criterion, and part of units often cannot participate in frequency modulation, so that resources are not fully utilized, and the enthusiasm of the units for next frequency modulation is easily contused. In the distributed frequency modulation system designed by the invention, each unit can participate in frequency modulation according to self-intention, so that the full utilization of resources is achieved.
3) And (4) integrating calculation power: the block chain realizes integration of distributed computing power by giving mine excavation rewards to miners, divides a problem which can be solved only by huge computing power into a plurality of small parts, then distributes the small parts to a plurality of computer terminals for processing, and finally summarizes the computing results to obtain a final result. Under the original frequency modulation mode, frequency modulation is often taken as an economic scheduling problem, and the essence is to solve a resource allocation equation to ensure that the economic benefit is optimal. With the enlargement of the system scale, the complex equation can be solved only by continuously increasing the computational power. Although the conventional scheduling center has great convenience in grasping a lot of resources and information, the conventional scheduling center often has difficulty in giving an optimal solution in resource configuration due to insufficient calculation. In the distributed frequency modulation system, the right of resource allocation is distributed to each unit, and the token incentive thinking is utilized to feed back the frequency modulation effects of different units, so that each unit is debugged by taking the optimal frequency modulation effect as one of the targets, and the total calculation power is far higher than that of a single centralized scheduling center. The block chain distributed thinking enables all frequency modulation units to participate in calculation, full utilization of distributed calculation is achieved, distributed frequency modulation resources are enabled to obtain real value return, and community co-treatment is achieved.
TABLE 1
"frequency modulation integration" design:
in order to excite the frequency modulation unit to better participate in frequency modulation, a reasonably open excitation and punishment mechanism must be established. The method is an important way for realizing the mechanism design by quantifying the frequency modulation effect of the unit and converting the frequency modulation effect into the digital assets of the unit. The block chain can realize the digitization of the assets to a great extent and expand the circulation of the digital assets, thereby breaking through the existing boundary of the digital assets in the past.
For this reason, the invention designs a 'frequency modulation integral' to measure the digital assets of each generating set, and the 'frequency modulation integral' is taken as a token and has the characteristic of limited circulation range, namely, the token is only used in a limited-range frequency modulation system. The frequency modulation integral is determined by the frequency modulation performance of the corresponding unit, if the frequency modulation behavior is favorable for the balance of supply and demand of the power system, the corresponding frequency modulation integral is increased, otherwise, the frequency modulation integral is reduced.
The circulation of the frequency modulation integration mainly comprises three parts of incentive generation, full value cashing and on-chain transaction. And excitation generation, namely generating corresponding amount of frequency modulation integrals by quantizing the frequency modulation performance of the unit and sending the corresponding amount of frequency modulation integrals to the account of the corresponding unit. Meanwhile, in order to ensure that the frequency modulation credit has the characteristics of a value-stable token, namely, to ensure that the digital assets are continuously held in the future and are not devalued due to the expansion of the currency caused by continuous generation, a full-value cashing mechanism is designed, and after the credit reaches an upper limit value, the corresponding credit is cashed into the actual currency of the corresponding amount. The last part is the on-chain transaction, because the blockchain is essentially a distributed account book, the mutual transaction of the frequency modulation points can be carried out between different units through the blockchain, an intelligent contract is generated according to the transaction rules agreed by all the generator sets of the community, and the intelligent contract automatically realizes the redistribution of the frequency modulation points between the units according to the change of transaction data.
(II) designing a frequency modulation excitation model:
the frequency modulation of the generator set is a quick response mechanism for adjusting the output of the generator set by the generator set so as to keep the frequency of a power grid stable in a reasonable range. In order to increase the enthusiasm of the frequency modulation unit for participating in frequency modulation, it is necessary to quantify the contribution of the frequency modulation unit to the power grid and excite the frequency modulation unit.
Referring to fig. 2 to 5, the present embodiment provides a method for designing a distributed fm auxiliary service system, including the following steps:
s1, frequency modulation integral calculation:
the existing frequency modulation performance indexes for evaluating the generator set mainly comprise response precision and response speed. The response precision is the deviation between the final generated power of the generator set and a target value given by a superior level, and the response rate refers to the adjustment rate of the generated power of the generator set within the time range from the response delay to the next adjustment instruction given by the scheduling automation system. Essentially, the genset frequency modulation service represents a rapid adjustment of the generated power within a specified regulation time frame to meet system operationThe adjustment requirement of the deviation. Therefore, in the calculation process of the frequency modulation integral, the invention comprehensively considers the global frequency modulation effect of the power system and the individual frequency modulation performance of the generator set to determine the performance factor deltag,τThe calculation method of (2) calculates the frequency modulation integral, and the specific process is as follows:
in the distributed frequency modulation system, the total number of G generator sets is G on the assumption that each time of the generator sets is delta t seconds, the frequency deviation of each moment cannot be guaranteed to be 0 because real-time fluctuation is generated on the supply and demand sides of the power system, and a dead zone f is set during frequency adjustment of the power system in order to prevent the frequency control from being too frequentssWhen the frequency fluctuation is in the dead zone range, the frequency change is only influenced by the inertia of the system, namely the frequency is in a relatively stable range and does not need to be adjusted. Therefore, the frequency deviation exceeds f in the frequency modulation periodssThe less, the better the global effect of frequency modulation. In the Tth frequency modulation, the global frequency modulation effect of the power system is determined by a global effect factor alphaτRepresenting, the global effect factor alphaτIs calculated as shown in equation (1):
wherein Δ f (t) is the frequency variation of the power system at time t, i.e.
Δf(t)＝f(t)-fN
Wherein f (t) is the frequency of the power system at time t, fNIs the rated power, typically 50 Hz.
ατThe larger value of the denominator and the denominator can ensure alphaτIn [0,1 ]]Within the range, and avoid causing alpha when Δ f (t) approaches 0τNumerical stability is missing.
The individual frequency modulation performance of the generator set is represented by an individual performance factor betag,τExpressing that the individual expression factor beta is quantized according to the ratio of the generated power change quantity to the load change quantity of the generator set in the frequency modulation timeg,τAs shown in formula (2):
wherein, Δ Pg(t) is the active power variation of the genset g (i.e., the change in genset g output), Δ PL(t) is the amount of change in active power of the load, qgExtremely high frequency-modulation product for the generator set g, in [0,1 ]]Within the range. The system is organized to frequency modulate assuming that there is a load deviation and the load deviation does not change sign within a frequency modulation period, so that betag,τThe denominator position will not be 0. It can be seen that when Δ P isg(t) and Δ PL(t) with the same sign, i.e. the generator set changes following the direction of change of the load, betag,τPositive, otherwise negative.
In conclusion, on the basis of the global frequency modulation effect of the system, the invention comprehensively considers the contribution electric quantity of the generator set and integrates the frequency modulation delta of the generator set g in the tau-th frequency modulationg,τAs an index for evaluating the performance of the frequency modulation of the generator set per cycle, δg,τIs calculated as shown in equation (3):
δg,τ＝ω·ατ+(1-ω)·βg,τ……………………(3)
wherein, omega is a weight coefficient and takes the value of [0, 1%]The larger ω is, the more heavily the fm integral is concerned about the global fm effect, otherwise, the more heavily the fm performance is concerned about the individual fm performance. For a single generator set, when the system selects larger omega, the participation activity of the system is reduced due to smaller benefit proportion brought by the improvement of individual frequency modulation performance, namely omega and qgNegative correlation, assuming a linear relationship between the two, as shown in equation (4):
qg＝1-bg·ω…………………………(4)
wherein, bgRepresents the value of the aggressiveness index, since qgIn [0,1 ]]In the range, therefore bgThe value is also [0,1 ]]Within the range, the activeness of different generator sets is changed differently due to attitude change caused by weight coefficient change, so that the b of different generator setsgDifferent.
Intelligent contracts as the core of blockchainsThe intelligent contract has important code thinking, automatically executes the contract agreed by the community members together through absolute machine language, and can effectively avoid the problems of interest dispute, tampering and the like. The frequency modulation integral of each generator set reflects the attitude and the participation of the generator set in the construction of the power system, and is directly hooked with the benefit of the generator set, if the frequency modulation integral calculation link has loopholes and trust problems, the enthusiasm of the generator set actively participating in frequency modulation is seriously contused. For this purpose, the calculation of the above-mentioned frequency modulation integral is performed by a blockchain intelligent contract, the input and output streams of which are shown in fig. 2, wherein fssAnd delta t are constants, and when the distributed frequency modulation system has a determined weight coefficient omega, the frequency modulation activity q of each unitgAs determined accordingly. After each frequency modulation is finished, calling an intelligent contract and inputting delta P in the frequency modulation processg(t), Δ f (t) and Δ PL(t) calculating the intelligent contract according to the methods of the formula (1) to the formula (4) fixedly to obtain a system alphaτAnd each generator set betag,τAnd further calculating the frequency modulation integral delta of each generator setg,τAnd uniformly packaging the frequency modulation integral values of the generator sets to generate a new block, thereby finishing the frequency modulation integral settlement of one frequency modulation period.
S2, constructing a frequency response model of the distributed frequency modulation system:
the distributed generator set can monitor frequency indexes in real time and respond, distributed computing power is concentrated, and computing power cost generated by complex optimization computation performed by a dispatching center is saved. Meanwhile, in an actual frequency modulation system, two kinds of delay often exist, namely communication delay and calculation delay, wherein the communication delay refers to the delay of actual load change and the information received by the system, and the maximum delay is 500ms under the existing communication technical condition. The calculation delay refers to delay time generated by scheduling calculation after the central scheduling center receives load change and then issuing an output decision to each unit, and the calculation delay usually reaches several seconds. The distributed frequency modulation mode has communication delay for receiving information, but the effect brought by the self constraint of the generator set and the introduction of the evaluation frequency modulation integral is only needed to be considered, and a scheduling center does not need to wait for calculation and then issue a scheduling instruction, so that the delay is not calculated.
Assuming that the generator sets are all conventional thermal power generating units and are all in an open state, the change of the frequency of the power system is a dynamic process, local differences caused by electromechanical transient and oscillation are ignored, the frequency dynamics of the power system is determined by a swing equation, and the equation (5) shows
Wherein H is an inertia constant, D is a damping coefficient, and delta PG(t) represents the total active power variation of the generator set at the time t, as shown in equation (6):
wherein, the output change of the generator set is delta Pg(t) is constrained by the speed regulating system per se, as shown in formula (7), and the parameters of the speed regulating system of the generator set are shown in table 2:
TABLE 2
Wherein,
respectively represent the pair Δ Pg、ΔPf、ΔPv、ΔPrefA first derivative is performed.
The equations (5) to (7) form a distributed frequency modulation frequency response model according to the present invention, as shown in fig. 3. The generator sets can detect the frequency quantity of the same numerical value at any place, the actual numerical value is compared with the rated value, the current supply and demand balance condition of the power system is judged, the frequency change of the power system is monitored in real time by each generator set, after the load fluctuation at the initial moment of frequency modulation is received, the response is actively carried out according to the detection result, the G generator sets replace the formula (5) together with the load change after the active power change of the G generator sets are superposed, the new delta f (t) is obtained, and the process is repeated until the frequency is stable.
S3 self-learning process based on secondary frequency modulation gain
In the distributed frequency modulation, the generator set aims to obtain more integrals, and as can be seen from equation (3), the integral value of the generator set in the frequency modulation is related to the frequency deviation and the output decision of the generator set. The frequency modulation performed by actively changing the output decision in response to the load change is secondary frequency modulation, so that each generator set needs to obtain as many integrals as possible in distributed frequency modulation, and the secondary frequency modulation gain needs to be continuously adjusted and is recorded as kr,g，kr,gIs limited by the characteristics of the generator set such as output power and the like, and meets the following constraint
Wherein k isr,g·qgAfter training and adjustment for multiple times, the generator set obtains k which is beneficial to obtaining more integralsr,gIn a new frequency modulation period, k can be obtained according to trainingr,gAnd (3) output adjustment is carried out, through the self-learning process, the distributed generator set can obtain more integrals, the frequency of the power system is stable, and a dispatching center is not required to plan and calculate power consumption. k is a radical ofr,gThe self-learning process specifically comprises the following steps:
initial k for each gensetr,gIs 0, k after each frequency modulation is finishedr,gStarting to gradually increase by a fixed step length and calculating delta in corresponding frequency modulation timeg,τStopping until the constraint of the formula (8) is not satisfied; at this time, delta is selectedg,τK at maximumr,gTo the optimum k of the corresponding generator setr,gGo to finishTo kr,gThe self-learning process is shown in fig. 4.
Training the generator set to obtain k suitable for the generator setr,gThen, at the initial moment of the frequency modulation period, the generator set refers to the weight coefficient, the participation product is determined by the formula (4), and the output change of the whole system shows delta PG(t) overall effect. Further, as can be seen from the equation (5), the frequency variation Δ f (t) of the power system is changed accordingly, thereby achieving the frequency modulation effect. And after the frequency modulation period is finished, settling the frequency modulation performance of each generator set in the period, and refreshing the frequency modulation integral value of each generator set.
Although the integral of the frequency modulation obtained by each generator set fluctuates in a short time, after a certain time, the generator set is according to kr,gThe strategy is continuously adjusted in the self-learning process, finally, all the generator sets are executed according to the optimal strategy of the generator sets, the strategy is not changed at the cost of integral reduction, namely the benefits of all the generator sets are optimal under the output strategy of other generator sets, and the whole distributed frequency modulation system achieves a Nash equilibrium state.
S4, settlement flow of frequency modulation integration:
as can be seen from the formulas (1) to (4), the integral of each generator set in one round of frequency modulation is composed of two parts, and the global effect factor alphaτThe individual performance factor beta of each generator set is determined by the frequency of the power system and cannot be falsified by the generator sets with malicious tendenciesg,τThere is a possibility of multi-report and misrepresentation, and the unit with multi-report and misrepresentation behavior is called a malicious unit. In order to ensure the good operation of the distributed frequency modulation system and the fair and fair frequency modulation integral calculation, the settlement process of the frequency modulation integral is shown in fig. 5. And selecting a generator set as a checking set in each turn according to the roles of miners in the block chain, and alternately replacing the checking set in all the generator sets which participate in frequency modulation and are authorized to obtain the rights and interests of frequency modulation points so as to prevent the rights of the checking set from being excessively fixed and concentrated to lose system fairness.
After each round of frequency modulation is finished, the dispatching center gives the delta P of the current round of examining machine setg(t) curve, while other generator sets will modulate Δ within timePg(t) sending the curve to a checking unit, calculating the curve of the current round delta f (t) by the checking unit according to the formulas (5) to (6), comparing the curve with an actual value, and if the curve of the current round delta f (t) is consistent with the actual value, considering that all the generator sets are reported to be delta P faithfullyg(t) curve, at which time the censorship unit will Δ Pg(t), Δ f (t) and Δ PL(t) inputting the frequency modulation integral calculation intelligent contract in the step S1, otherwise, checking the delta P of all the generator sets by the generator setg(t) the curve is sent to a dispatching center, the dispatching center carries out secondary verification to find out the generator set which is reported maliciously, and the delta P collected by the dispatching center is usedgAnd (t) sending the curve to an examination unit, and continuing examination by the examination unit until the calculated delta f (t) is consistent with the actual situation. Then, the checking unit calls an intelligent contract to trigger the frequency modulation integral calculation function of the checking unit, and if the round has malicious nodes, the checking unit enables the delta P of the checking unit to be changedg(t) input smart contracts with a value of 0. After the intelligent contract is called, the frequency modulation integral settlement result is synchronously uploaded to a block chain network, a new block chain is generated and broadcasted to the whole network, and the result is further guaranteed to be public and fair.
Particularly, although the dispatching center is consistent with the physical rights of the existing dispatching center, that is, the dispatching center can acquire the output conditions of all the generator sets, the dispatching center does not need to perform optimization calculation before frequency modulation, does not need to perform frequency modulation integral settlement after frequency modulation, and only needs to give the delta P of the checking unit during each frequency modulationg(t) curve, while checking the remaining gensets for delta P when examining the gensetsg(t) when the curves do not coincide, using the locally detected Δ PgAnd (t) comparing the data with the data reported by each generator set. The method greatly reduces the calculation power of the centralized scheduling center, and avoids the collusion of malicious nodes with the scheduling center in the frequency modulation integral calculation link, so as to seek private profit.
The frequency modulation integral is essentially equivalent to virtual currency in a block chain system, so that the frequency modulation integral corresponds to accounts of the generator sets in the block chain one by one, and after the frequency modulation integral settlement is completely finished, the frequency modulation total integral S of each generator set is refreshed through an equation (9):
Sg,τ+1＝Sg,τ+δg,τ…………………………(9)
wherein S isg,τRepresenting the integral value of the initial frequency modulation of the generator set g before the tau frequency modulation, Sg,τ+1And (4) representing the frequency modulation integral value of the generator set g after the tau frequency modulation.
Under the existing frequency modulation mode, the generator set carries out frequency modulation in a mode of participating in a power frequency modulation auxiliary service market, and a power grid dispatching center pays corresponding rewards. Therefore, when the distributed frequency modulation mode is implemented, the total points of the generator set also initiate an application to the dispatching center after reaching a certain number, and the points are transferred in a block chain account transfer mode of the dispatching center so as to exchange cash value money. The power dispatching center can not only dispatch the frequency modulation enthusiasm of the unit, but also obtain certain profit as long as reasonably deciding the exchange rate of the integral and the actual currency, namely, the investment on the distributed frequency modulation system, such as the system operation cost, the excitation on active frequency modulation users and the like, can not exceed the total gain obtained by the system, including the reduced computational power consumption and the like due to the implementation of the distributed frequency modulation system.
The effectiveness of the distributed frequency modulation auxiliary service system design method of the invention is verified by the following calculation example:
1. scene design
Suppose 5 generating sets participate in frequency modulation, 5 generating sets remove secondary frequency modulation gain kr,gThe other conventional parameters are all equal, and the parameters of the speed regulating system of the generator set and the conventional parameters of the generator set are shown in table 3. The secondary frequency modulation gain upper limit and the positive degree calculation coefficient of each generator set are shown in Table 4, wherein b of the generator sets 1 and 4gThe value is 1, and as can be seen from the formula (4), when ω is 1, the generator sets 1 and 4 do not participate in frequency modulation.
TABLE 3
TABLE 4
2. Self-learning process
Suppose that 5 generating sets perform self-learning process for 200 times, and the load increment received by the power system is delta P at each frequency modulation initial timeL0.5MW (i.e. 6% step response) followed by randomly evenly distributed fluctuations between 0.001 and 0.01MW, with a weight factor ω of 0.5 and a frequency-modulation interval Δ t of 60s per round.
Actual secondary frequency modulation gain k of each generator setr,g·qgAs shown in FIG. 6, the generator set k varies with the number of training timesr,gEach time, 0.002MW/Hz · s is added, but the actual gain of the secondary frequency modulation is increased at different speeds due to the extreme difference of the generator volumes, such as b of the generator set 3gMinimum, thus qgAnd the maximum is the slope of the increase of the actual secondary frequency modulation gain in the training process. Meanwhile, if the actual secondary frequency modulation gain of each generator set exceeds the limit shown in the formula (7), the frequency is modulated according to the upper limit value of the actual secondary frequency modulation gain, and the actual secondary frequency modulation gain is kept unchanged in subsequent training.
Fig. 7 further shows the variation of the integral of each generator set in 200 training sessions, and it can be seen from fig. 7 that the frequency modulation integral is positive as long as the generator set is involved in frequency adjustment in compliance with load variation. In the 80 th training, all genset integrals reached a maximum. Then, the frequency modulation integral calculation considers the output ratio of the generator set and the frequency modulation effect of the whole power system, so that the frequency modulation effect of the system is deteriorated due to the excessive secondary frequency modulation gain, and the frequency modulation integral of all the generator sets is gradually reduced. Referring to fig. 6, it can be seen that by the 171 st training, the generator set No. 1 with the largest secondary frequency modulation gain reaches its upper frequency modulation limit value, and all the generator sets have their largest secondary frequency modulation integral gain k in the following trainingr,gAnd (4) performing frequency modulation, so that the frequency modulation integral of all the generator sets is not changed after 171 th time.In conclusion, the system has the best effect in the 80 th training. The actual secondary frequency modulation gains of the generator sets 1-5 are respectively 0.080, 0.096, 0.104, 0.080 and 0.088 MW.
Further, 1 st, 100 th, 200 th, τg bestFig. 8 shows the fluctuation of the frequency in the four frequency modulations, as can be seen from fig. 8, when τ is 1, the gain of the second frequency modulation of each generator set is 0, and after the system is stabilized, a significant frequency deviation occurs, and when τ is 200, that is, when the gain of the second frequency modulation of each generator set takes an upper limit value, although the frequency is stabilized within 60s, the fluctuation of the previous frequency is the largest, and the fluctuation of the 80 th training result is the smallest, which has the best performance.
3. Self-learning effect under different weight coefficients
When the weight coefficient omega takes different values, the self-learning process is repeated, and the best k learned when omega is 0, 0.5 and 1 respectively is selectedr,gFrequency modulation is carried out, namely three scenes, namely 'only relation individual frequency modulation performance', 'individual performance and global effect proportion are consistent' and 'only attention is paid to global frequency modulation effect', different frequency adjustment results are obtained, as shown in fig. 9, it can be seen that the effect obtained when omega is 0.5 in the three scenes is the best, and analysis is as follows, when omega is 0, although each unit can actively participate in frequency modulation, the frequency modulation effect which needs to be considered in the global situation is ignored, the adjustment force is large, and the frequency adjustment effect is poor; when ω is 1, although the global frequency adjustment effect is completely used as the purpose, the activity of the unit participation is seriously reduced, the frequency adjustment cannot be effectively performed when the load fluctuates, and the frequency adjustment effect is also poor, but the global frequency adjustment effect is still used as the sole purpose, so the frequency adjustment effect is better than the circumstance that ω is 0.
In order to further explore the difference of the time group integrals when omega takes different values, the total frequency modulation integral, the individual frequency modulation expression integral, the global frequency modulation effect integral and the secondary frequency modulation gain are shown in fig. 10, the integral value under each omega is the sum of the integrals corresponding to 5 generator sets, and the frequency modulation gain is the sum of the gains corresponding to 5 generator sets. When omega is 0-0.2, each generator set has higher frequency modulation product, kr,gAre all taken as kr,g maxThe frequency modulation integral is stabilized within the range of 1.72-1.75, slight difference is caused only by random fluctuation of each load, and when omega is 0.3-0.9, the product of each generator is extremely influenced by bgThe difference produces the decline of different degrees, but secondary frequency modulation gain still can maintain at the stable level, and global frequency modulation effect promotes to some extent, and when omega 0.9 ~ 1.0, the generating set volume extremely continues to descend, and frequency modulation effect obviously worsens, and total frequency modulation integral also reduces thereupon. In summary, when ω is 0.3 to 0.9, the frequency modulation effect of the power system is stable and high, and when ω is 0.9, the total frequency modulation integral is the largest, because the frequency modulation integral value corresponding to the individual expression is small compared to the global effect, and the larger ω is, the larger the proportion of the global effect is, and thus the larger the total frequency modulation integral is.
4. Actual frequency modulation process
And (3) carrying out actual frequency modulation by using the 80 th training result in the self-learning process, wherein the load fluctuation and the frequency modulation time interval are unchanged, and the weight coefficient is still selected to be 0.5. Fig. 11 shows the load variation in the actual frequency modulation and the output variation of each generator set. It can be seen that each generator set determines output according to its own actual secondary frequency modulation gain, and the actual secondary frequency modulation gain of the generator set 3 is the largest, so that in a steady state, the occupied ratio of the load is the largest, 0.1174MW load fluctuation is shared, and the generator sets 1, 2, 4 and 5 share 0.0904, 0.1084, 0.0904 and 0.0994MW loads respectively. Finally, the output of all the generator sets is stable, and the total output change is equal to the load change, so that stable balance is achieved.
It is assumed that 1000 yuan of income can be exchanged for every 10 frequency modulation points, and all the generator set frequency modulation points are exchanged after being filled with 10. As can be seen from the point settlement process shown in fig. 5, the lie output variation curve is easily detected by the censor, and when the secondary frequency modulation point contribution is judged to be 0, therefore, in the actual frequency modulation shown in the example, it is assumed that all the generator sets are faithfully involved in the frequency modulation. Fig. 12 shows the integral change of 5 gensets after 100 frequency modulations. As can be seen from fig. 12, the generator set 3 has the highest degree of aggressiveness and the highest output in the frequency modulation process, so that the frequency modulation integral increases fastest in 100 frequency modulations, the generator sets 1 and 4 are relatively slow, and the benefit is also low. After 100 frequency modulation, the integral and income conditions of each generating set are shown in table 5, the equivalent income of 5 generating sets is obtained after the residual integral is equivalent to exchangeable cash, the generating set 3 has the maximum actual secondary frequency modulation gain, and the highest equivalent income is obtained 3159.83 yuan in the same way.
TABLE 5
Meanwhile, in order to compare the frequency modulation effects of the distributed frequency modulation method and the existing centralized scheduling method, assuming that the communication delay is 0, the calculation delays of the centralized scheduling are respectively 3s and 5s, i.e. the frequency modulation is executed after the calculation delays, and the comparison result is shown in fig. 13, it can be seen that when a delay process is included, the initial Δ f is linearly reduced due to the increase of the load, and the longer the delay is, the larger the reduction degree is, and the larger the frequency fluctuation range in the subsequent frequency modulation is.
When the delay time is 5s, the maximum fluctuation of the frequency is close to 1.2Hz, and the instability and even disconnection of the power system are possibly caused by the frequency modulation effect. Therefore, the method can effectively adjust the frequency and reduce the frequency fluctuation caused by delay.
The above-described embodiments are merely illustrative of the preferred embodiments of the present invention, and do not limit the scope of the present invention, and various modifications and improvements of the technical solutions of the present invention can be made by those skilled in the art without departing from the spirit of the present invention, and the technical solutions of the present invention are within the scope of the present invention defined by the claims.
Claims (10)
1. A distributed frequency modulation auxiliary service system design method is used for carrying out auxiliary frequency modulation on a power system, and is characterized by comprising the following steps:
s1, constructing a distributed frequency modulation system based on the block chain, wherein the distributed frequency modulation system comprises a load center, a scheduling center and a plurality of generator sets;
s2, calculating the frequency modulation integral of each generator set based on the global frequency modulation effect of the power system and the individual frequency modulation performance of the generator sets;
s3, constructing a distributed frequency modulation system frequency response model based on the frequency change of the power system and the output change of each generator set;
s4, carrying out frequency modulation on the power system based on the distributed frequency modulation system frequency response model, adjusting the secondary frequency modulation gain of each generator set based on a self-learning process in the process of carrying out frequency modulation on the power system, and updating the frequency modulation integral of each generator set;
and S5, settling the frequency modulation integral of each generator set through the dispatching center to finish the frequency modulation of the power system.
2. The method for designing a distributed frequency modulation auxiliary service system according to claim 1, wherein in S2, the global frequency modulation effect of the power system is defined by a global effect factor ατThe individual frequency modulation performance of the generator set is represented by an individual performance factor betag,τRepresents;
global effect factor alphaτIs calculated as shown in equation 1:
wherein f isssIn order to obtain a frequency modulation dead zone, delta t is the time length of each frequency modulation of the generator set, delta f (t) is the frequency variation of the power system at the moment t, and delta f (t) is f (t) -fNF (t) is the frequency of the power system at time t, fNIs rated power;
individual performance factor betag,τIs calculated as shown in equation 2:
wherein, Δ Pg(t) is the active power variation of the generator set G, namely the output variation of the generator set G, and G belongs to [1, G ]]G is the number of generator sets; delta PL(t) is the load active power variation of the load center; q. q.sgFor the frequency modulation product of the generator set g, qg∈[0,1]；
Integral delta of frequency modulation of generator set g in the Tth frequency modulationg,τIs calculated as shown in equation 3:
δg,τ＝ω·ατ+(1-ω)·βg,τ………………………3
wherein, omega is a weight coefficient, omega belongs to [0,1 ]]ω and qgNegative correlation, as shown in equation 4:
qg＝1-bg·ω……………………………4
wherein, bgRepresenting the value of the positive coefficient, bg∈[0,1]。
3. A method for designing a distributed frequency modulation assistance service system according to claim 2, wherein in S2, the calculation of the frequency modulation integral is performed by an intelligent contract of the block chain, and an input of the intelligent contract is Δ Pg(t)、Δf(t)、ΔPL(t) output is ατ、βg,τ、δg,τ。
4. A method for designing a distributed frequency modulation auxiliary service system according to claim 2, wherein in S3, the frequency variation of the power system is as shown in formula 5:
wherein H is an inertia constant, D is a damping coefficient, and delta PG(t) represents the total active power variation of the generator set at the time t, as shown in equation 6:
and the output change of the generator set is restricted by a speed regulating system of the generator set.
5. The method for designing a distributed frequency modulation auxiliary service system according to claim 4, wherein in the step S4, the method for modulating the frequency of the power system is as follows:
s4.1, monitoring the frequency change of the power system in real time by each generator set, receiving the load fluctuation of the load center, and actively performing output response by each generator set based on the frequency change of the power system and the load fluctuation of the load center;
and S4.2, updating the frequency variation of the power system through the frequency response model of the distributed frequency modulation system, and repeating the step S4.1 until the frequency modulation of the power system is completed.
6. The method for designing a distributed frequency modulation auxiliary service system according to claim 5, wherein each generator set adjusts its own secondary frequency modulation gain through a self-learning process, and actively performs output response according to the result of the adjustment of its own secondary frequency modulation gain.
7. A method for designing a distributed frequency modulation auxiliary service system according to claim 3, wherein in S5, the specific method for settling the frequency modulation integral of each generator set includes:
s5.1, acquiring an examination unit after each frequency modulation is finished;
s5.2, giving out an output variation curve of the checking unit in the frequency modulation process of the current round through the dispatching center, sending the output variation curve in the frequency modulation process of the current round to the checking unit through each power generating unit, and calculating a frequency variation curve of the power system in the frequency modulation process of the current round through the checking unit;
s5.3, based on the comparison result of the calculated value and the actual value of the frequency change curve of the power system, the checking unit is used for checking malicious units and updating frequency modulation integral, the updating result of the frequency modulation integral is uploaded to the block chain, and the frequency modulation integral is broadcasted to the whole network;
and S5.4, after the total frequency modulation integral of the distributed frequency modulation system reaches a preset threshold value, initiating an application to the dispatching center through the examination unit, transferring the frequency modulation integral in a mode of transferring accounts to the block chain of the dispatching center, and finishing the settlement of the frequency modulation integral.
8. A distributed fm auxiliary service system design method according to claim 7, wherein in S5.1, the censorship units are alternately replaced among all the generating units participating in fm and authorized to obtain fm credit.
9. A distributed fm assisted service system design method as claimed in claim 7, wherein said dispatch center collects actual output variation curves for each of said generator sets.
10. The method for designing a distributed frequency modulation auxiliary service system according to claim 9, wherein in S5.3, the specific method for the censoring unit to censore the malicious unit and update the frequency modulation credits includes: if the calculated value of the frequency change curve of the power system is consistent with the actual value, no malicious unit exists, and the frequency modulation integral is updated based on the intelligent contract; otherwise, the malicious units exist, the output variation curves of all the generator sets are sent to the dispatching center through the inspection unit for secondary verification, the malicious units are found out, the actual output variation curves of all the generator sets are sent to the inspection unit, the malicious units are continuously inspected through the inspection unit until the calculated value of the frequency variation curve of the power system is consistent with the actual value, the output variation of the malicious units is assigned to be 0, and then the frequency modulation integral is updated based on the intelligent contract.
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