CN110661250B - Reliability evaluation method and system for wind-solar energy storage and power generation power transmission system - Google Patents

Reliability evaluation method and system for wind-solar energy storage and power generation power transmission system Download PDF

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CN110661250B
CN110661250B CN201910762775.5A CN201910762775A CN110661250B CN 110661250 B CN110661250 B CN 110661250B CN 201910762775 A CN201910762775 A CN 201910762775A CN 110661250 B CN110661250 B CN 110661250B
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power
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power generation
wind
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CN110661250A (en
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程林
田鑫
齐宁
彭方正
江轶
高效海
王智冬
张家宁
张艳
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Tsinghua University
Economic and Technological Research Institute of State Grid Shandong Electric Power Co Ltd
State Grid Economic and Technological Research Institute
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Economic and Technological Research Institute of State Grid Shandong Electric Power Co Ltd
State Grid Economic and Technological Research Institute
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E70/00—Other energy conversion or management systems reducing GHG emissions
    • Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin

Abstract

The invention discloses a reliability evaluation method and a system of a wind-solar energy-storage power transmission system, wherein the method comprises the following steps: constructing an element reliability model based on the source load fluctuation characteristics; acquiring the fault state and the corresponding fault rate of the element according to the reliability model; sampling fault states to form a fault state set, and acquiring a fault rate corresponding to the fault states in the set; performing operation simulation on the wind-light-containing power storage and generation and transmission system based on the reliability model to realize power generation and load power balance; calculating the power flow of a wind-solar energy-storage power transmission system; performing generator tripping load cutting according to a calculation result of the power flow of the wind-light-containing power storage and generation transmission system; and calculating and counting the reliability index of the wind and light storage and power transmission system, and evaluating the reliability of the wind and light storage and power transmission system according to the reliability index. The invention carries out annual operation simulation on the 'source-network-load-storage' system, thereby improving the accuracy of reliability evaluation.

Description

Reliability evaluation method and system for wind-solar energy storage and power generation power transmission system
Technical Field
The invention relates to the technical field of power system reliability evaluation, in particular to a reliability evaluation method and system of a wind-solar energy storage and power generation transmission system.
Background
The rapid development of renewable energy sources has become a global consensus, however, with the continuous improvement of the access permeability of the renewable energy sources, various uncertain factors brought by wind turbines and photovoltaic power generation which are eaten by the heaven also bring great challenges to the planning and operation of power grids. Energy storage is used as a flexible regulation and control resource, source load fluctuation stabilization of a power system can be realized through effective configuration and reasonable regulation and control of the energy storage, the energy storage becomes an indispensable means for coping with renewable energy access, and wind-light-storage combined operation becomes a normal mode of the existing power system.
The reliability evaluation of the power system is a measure of the acceptable quality standard and the capability of supplying power and electric energy to users uninterruptedly according to the required quantity of the power system, and the reliability evaluation result can directly reflect and guide the planning of the power system, thereby becoming an important link in the planning of the power system at present. After "wind-solar-storage" access, the reliability evaluation of the system needs to further consider various complex problems compared with the traditional power system. Therefore, how to fully take the operating characteristics (operating mode + uncertainty) of various devices into account in the reliability assessment provides a set of complete and convenient 'source-network-load-storage' system reliability assessment method and process, and the method has extremely high value and significance.
In recent years, three major industries of wind, light and energy storage, which are influenced by national policies, have been vigorously developed nationwide. By 2018, the installed capacities of the fan, the photovoltaic and the energy storage respectively break through 184.2GW, 174.63GW and 31.2 GW. However, wind and light access faces a large amount of wind and light abandoning problems, the wind and light abandoning rate is higher than 10%, and partial areas are even higher. Therefore, how to fully take the operating characteristics, the power matching and the wind and light abandoning characteristics of the wind and light storage resources into consideration has great value for improving the reliability evaluation of the power generation and transmission system containing the wind and light storage resources.
Currently, reliability evaluation generally includes multiple links such as element reliability mode and parameter selection, system state sampling, load flow calculation, load shedding calculation, and reliability index calculation. In general, during element reliability modeling, reliability modeling of various generator sets and elements is mostly considered, but fluctuation conditions of loads are rarely considered; when the system state is sampled, the wind-solar-energy storage device generally equates the wind-solar-energy storage device to a multi-state model considering various operation modes of the wind-solar-energy storage device, but the multi-state transition parameters of the wind-solar-energy storage device are difficult to determine. Therefore, a complete, reasonable and convenient method for evaluating the reliability of the power generation and transmission system containing wind, light and energy storage resources is lacked.
Disclosure of Invention
In view of the above problems, the present invention provides a method and a system for evaluating reliability of a power transmission system including wind, photovoltaic, energy storage and power generation, so as to overcome the above drawbacks of the prior art and provide a complete, reasonable and convenient method for evaluating reliability.
In order to realize the technical scheme, the invention adopts the following technical scheme:
one aspect of the invention is a reliability evaluation method for a wind-solar energy-storage power generation and transmission system, which comprises the following steps:
step S1, constructing an element reliability model based on the source load fluctuation characteristics;
step S2, acquiring the fault state and the corresponding fault rate of the element according to the reliability model;
step S3, sampling the fault state to form a fault state set and obtaining the fault rate corresponding to the fault state in the set;
step S4, performing operation simulation on the wind-light-containing power storage and generation and transmission system based on the reliability model to realize power generation and load power balance;
step S5, calculating the power flow of the wind-solar energy storage and power generation power transmission system;
step S6, cutting loads by a cutter according to the calculation result of the power flow of the wind-light-storage power generation and transmission system;
and step S7, calculating and counting the reliability index of the wind-solar energy storage and power generation and transmission system, and carrying out reliability evaluation on the wind-solar energy storage and power generation and transmission system according to the reliability index.
Preferably, the constructing the element reliability model based on the source load fluctuation characteristics includes:
for a new energy generator set, the fan output is represented by the following formula:
Figure BDA0002170913370000021
wherein, PWTIndicating fan output, PRIndicating rated output, v, of the faniIndicating cut-in wind speed, vrIndicating rated wind speed, voWhich indicates the cut-out wind speed,
the photovoltaic contribution is represented by:
Figure BDA0002170913370000031
wherein, PPVRepresenting photovoltaic output, K representing the limit of illumination intensity, I representing the illumination intensity, S representing the illumination area, eta representing the conversion efficiency,
for an energy storage system, the response characteristic is shown as follows:
Figure BDA0002170913370000032
wherein, PessThe power of the stored energy is represented,
Figure BDA0002170913370000033
the maximum value of the stored energy power is indicated,
Figure BDA0002170913370000034
denotes the minimum value of the energy storage power, the index i denotes the class, the index T denotes the period, T denotes the total scheduling period, ηessThe efficiency of energy storage charge-discharge is shown,
Figure BDA0002170913370000035
the real-time stored energy is represented,
Figure BDA0002170913370000036
representing rated energy storage capacity, SOCi,maxRepresenting the maximum value of the state of charge of the stored energy, SOCi,minRepresents the minimum value of the energy storage state of charge and at represents the scheduling time interval.
Preferably, in step S1, the energy storage system in the wind-solar energy-storage power generation and transmission system obtains the system reliability by the following formula:
Figure BDA0002170913370000037
where λ represents the failure rate, r represents the average repair time, δ represents the repair rate, the subscript eq represents the equivalent value, the subscript ESU represents the entire energy storage module, and the subscript i represents the class.
Preferably, in step S1, the response characteristic of the load in the wind-solar energy-storage-power-generation power transmission system is as follows:
Figure BDA0002170913370000041
wherein，preIndicating that the load power can be cut down,
Figure BDA0002170913370000042
representing the initial curtailable load power, z the decision variable, a the load reduction rate, index i the category, index t the period,
Figure BDA0002170913370000043
the maximum value of the reduction time is represented,
Figure BDA0002170913370000044
represents the minimum value of the clipping time.
Preferably, in step S4, the simulating operation of the power transmission system including wind and light storage and generation includes: generating a power generation output curve of the system; generating a load curve of the system; and realizing power generation and load power balance according to the power generation output curve and the load curve.
Preferably, the generating a generated output curve of the system comprises: establishing a generator 8760 point output curve based on the typical daily curve; judging whether the energy is a new energy unit or not, and if not, outputting a 8760-point output curve as a system power generation output curve; if the new energy unit is available, judging whether new energy is added for random fluctuation; if no new energy random fluctuation is added, outputting a 8760-point output curve as a system power generation output curve; if the new energy is added to fluctuate randomly, acquiring a random output value on the new energy generator, judging whether a generator bus contains stored energy, if so, correcting the random output value of the generator according to the charge-discharge capacity of the stored energy, and adding the corrected random output value to the new energy unit to generate a power generation output curve of the system; and if the generator bus does not contain stored energy, attaching the obtained random output value to the new energy unit to generate a generated output curve of the system.
Preferably, a load curve of the system is generated, comprising:
judging whether the operation mode is the maximum load mode, establishing a load power curve, if the operation mode is the maximum load mode, establishing a load 8760-point maximum power curve, and if the operation mode is not the maximum load mode, establishing a load 8760-point power curve based on the typical daily curve;
judging whether the additional load fluctuates randomly, if the additional load fluctuates randomly, adding random power to the established load power curve, and judging whether to reduce the load; if no random fluctuation is added, whether load reduction is performed or not is directly judged, if load reduction is performed, load reduction is performed according to the response characteristics of the load, corresponding load power is corrected, a load curve of the system is generated according to the corrected load power, and if no load reduction is performed, the load curve of the system is directly generated.
Preferably, the power generation and load power balancing according to the power generation output curve and the load curve comprises: acquiring power generation and load power according to the power generation output curve and the load curve; and judging whether the power generation and the load power are balanced, if the power generation and the load power are unbalanced, adjusting the power generation output according to a nearby principle and a same-island principle, and adjusting the load power according to the nearby principle, the same-island principle and the energy storage capacity until the power generation and the load power are balanced.
Preferably, the reliability index includes one or more of a new energy power generation limit time expectation, a new energy power generation limit frequency and a new energy power generation limit expectation.
Another aspect of the present invention provides a reliability evaluation system including a wind-solar energy storage and power generation transmission system, including:
the model building module is used for building an element reliability model based on the source load fluctuation characteristics;
the fault state acquisition module is used for acquiring the fault state and the corresponding fault rate of the element according to the reliability model;
the fault state sampling module is used for sampling fault states to form a fault state set and acquiring a fault rate corresponding to the fault states in the set;
the operation simulation module is used for carrying out operation simulation on the wind-light-containing power storage and generation and transmission system based on the reliability model so as to realize power generation and load balance;
the load flow calculation module is used for calculating the load flow of the wind-light-containing power storage and generation transmission system;
the generator tripping load module is used for performing generator tripping load according to the calculation result of the power flow of the wind-light-storage power generation and transmission system;
and the reliability evaluation module is used for calculating and counting the reliability index of the wind-solar energy storage and power generation and transmission system and carrying out reliability evaluation on the wind-solar energy storage and power generation and transmission system according to the reliability index.
Compared with the prior art, the invention has the following advantages and beneficial effects:
according to the reliability evaluation method for the power transmission system containing the wind-light storage and power generation, when reliability evaluation is carried out, the running characteristic of source charge is considered when a reliability model is established, the year-round running simulation is carried out on the 'source-grid-charge-storage' system by considering the wind-light load shedding, the energy storage charge-discharge mode and the load demand response strategy, and the accuracy of the reliability evaluation is improved.
The method is suitable for different scene of wind-solar energy storage resource access in the large power grid range, and can provide basis for reliability evaluation and corresponding planning research of the large power grid under the condition of high-proportion renewable energy access in the future.
Drawings
FIG. 1 is a schematic flow chart of a reliability evaluation method for a wind-solar energy-storage-power-generation power transmission system according to the invention;
FIG. 2 is a schematic flow chart of a method for evaluating reliability of a wind-solar energy-storage-and-power-generation power transmission system according to an embodiment of the invention;
FIG. 3 is a schematic illustration of a typical sunrise curve of a typical wind farm in one embodiment of the invention;
FIG. 4 is a schematic illustration of a typical random daily contribution curve for a typical wind farm in one embodiment of the present invention;
FIG. 5 is a schematic illustration of an exemplary photovoltaic exemplary sunrise force curve in one embodiment of the present disclosure;
FIG. 6 is a schematic illustration of a typical photovoltaic typical random daily output curve in one embodiment of the present disclosure;
FIG. 7 is a schematic flow diagram of a generated output curve for the generation system of the present invention;
FIG. 8 is a schematic flow chart of the load curve of the generating system of the present invention;
FIG. 9 is a schematic flow chart of the present invention for power generation and load power balancing;
FIGS. 10a and 10b are schematic diagrams for comparison before and after installation of new energy with a permeability of 25%, load random fluctuation and 200MWh energy storage operation simulation, respectively;
FIGS. 11a and 11b are schematic processing diagrams of wind power, photovoltaic and energy storage before and after operation simulation, respectively;
fig. 12 is a schematic configuration diagram of the reliability evaluation system of the wind-solar energy-storage-containing power generation and transmission system according to the invention.
Detailed Description
The embodiments of the present invention will be described below with reference to the accompanying drawings. Those of ordinary skill in the art will recognize that the described embodiments can be modified in various different ways, or combinations thereof, without departing from the spirit and scope of the present invention. Accordingly, the drawings and description are illustrative in nature and not intended to limit the scope of the claims. Furthermore, in the present description, the drawings are not to scale and like reference numerals refer to like parts.
The invention provides a reliability evaluation method of a wind-light storage power transmission system considering operation simulation aiming at requirements of wind-light storage resource planning and reliability evaluation under the background of a large power grid of 'source-grid-load-storage'. And considering uncertainty factors of source load, analyzing fluctuation characteristics of the source load and respectively establishing element reliability models for the 'wind-light load' resources. Meanwhile, the wind-solar energy-switching load, the energy storage charging and discharging mode and the load demand response strategy are considered to carry out annual operation simulation on the 'source-network-load-storage' system. And on the basis, the fault rate of the unit is further considered, the reliability of the power generation and transmission system is completely evaluated, and various reliability indexes are calculated.
Fig. 1 is a schematic flow chart of a reliability evaluation method of a wind-solar energy-storage-contained power generation and transmission system of the present invention, and as shown in fig. 1, the reliability evaluation method of the wind-solar energy-storage-contained power generation and transmission system of the present invention includes the following steps:
step S1, constructing an element reliability model based on source load fluctuation characteristics, and determining the operating characteristics and the reliability model of the source load by counting and measuring the source load fluctuation characteristics of the power grid under the condition that high-proportion renewable energy sources are accessed;
step S2, acquiring the fault state and the corresponding fault rate of the element according to the reliability model;
step S3, sampling the fault state to form a fault state set and obtaining the fault rate corresponding to the fault state in the set;
step S4, performing operation simulation on the wind-light-containing power storage and generation and transmission system based on the reliability model to realize power generation and load power balance;
step S5, calculating the power flow of the power transmission system including wind-solar energy storage and generation, wherein the calculation mode of the power flow of the system is not particularly limited, and the calculation mode can be calculation methods such as optimal power flow calculation, dynamic power flow, random power flow, start-up power flow and the like;
step S6, cutting loads by a cutter according to the calculation result of the power flow of the wind-light-storage power generation and transmission system;
and step S7, calculating and counting the reliability index of the wind-solar energy storage and power generation and transmission system, and carrying out reliability evaluation on the wind-solar energy storage and power generation and transmission system according to the reliability index.
Fig. 2 is a schematic flow chart of an embodiment of the method for evaluating reliability of a power transmission system including wind and light energy storage and generation of the present invention, and as shown in fig. 2, the method for evaluating reliability of a power transmission system including wind and light energy storage and generation of the present invention includes:
establishing a generator reliability model, and acquiring a fault rate and a repair rate;
sampling the generator fault states through Monte Carlo simulation to form a generator fault state set, and calculating the generator fault rate through the generator fault state probability;
the method is used for simulating the operation of a wind-solar energy-storage power generation and transmission system based on a reliability model to realize power generation/load power balance, and specifically comprises the following steps: evaluating whether the power generation/load power is balanced in a fault state of the generator, when the power generation/load power is unbalanced, increasing the output of the generator in the same area by a nearby principle, judging whether the power generation/load power is balanced, if so, finishing the evaluation of the generator in the fault state, if not, increasing the output of the generator in the same electric island by a same island principle, then judging whether the power generation/load power is balanced again, if so, finishing the evaluation of the generator in the fault state, if not, reducing the load power in the same area by the nearby principle, then judging whether the power generation/load power is balanced again, if so, finishing the evaluation of the generator in the fault state, if not, reducing the load power in the same electric island by the same island principle, and then, and counting the power generation output adjustment and load power reduction information of each bus in the state, judging whether the evaluation of the generator in the fault state is finished, if so, calculating a reliability index according to the evaluation result, if not, evaluating the next fault state until the evaluation of all fault states in the set is finished, and then calculating the reliability index, thereby further carrying out the reliability evaluation according to the calculation result of the reliability index.
The proximity principle refers to that an element with the closest electrical distance is operated firstly from the view point of a topological structure, and the same-island principle refers to that the same electric island is operated firstly according to the division result of the electric island region.
The method of sampling the generator fault state is not limited to the monte carlo simulation method, and an analytical method may be used.
In the invention, when an element reliability model is constructed based on source load fluctuation characteristics, a power supply side, an energy storage side and a load side need to be considered, wherein the power supply side needs to consider the fluctuation characteristics of faults and wind and light resources, the energy storage side is divided into energy type energy storage and power type energy storage, the energy storage side respectively has corresponding charging and discharging strategies, the faults of the energy storage side and the power type energy storage side need to be considered, and the load side needs to consider load reduction and random fluctuation.
Specifically, the power supply side can be considered as conventional power generation and new energy power generation, wherein the power supply and the power generation equipment for conventional power generation can be regarded as two state models, namely a normal state and a fault state, and parameters such as a fault rate λ, a repair rate δ, an average repair time MTTR and the like need to be counted. Taking the RTS79 generator as an example, the statistical parameters are shown in table 1 below.
TABLE 1
Figure BDA0002170913370000081
Figure BDA0002170913370000091
For a new energy generator set, the unit faults and random output need to be considered at the same time, and the new energy generator set comprises fan power generation and photovoltaic power generation. Specifically, the fan output is represented by the following equation:
Figure BDA0002170913370000092
wherein, PWTIndicating fan output, PRIndicating rated output, v, of the faniIndicating cut-in wind speed, vrIndicating rated wind speed, voIndicating the cut-out wind speed.
Wherein, the wind speed v satisfies the Weibull distribution as shown in the following formula:
Figure BDA0002170913370000093
wherein k and c are both parameters and are obtained by calculating the statistical index mean value mu and variance sigma of the wind speed, as shown in the following formula:
Figure BDA0002170913370000094
in one embodiment of the present invention, k is 2.800388 and c is 5.141682, and typical sunrise and stochastic output curves of a typical wind farm are shown in fig. 3 and 4, respectively. The typical daily random output curve of the typical wind power plant is obtained by sampling Monte Carlo through probability distribution parameters.
The photovoltaic output is mainly related to the illumination area, the conversion efficiency and the illumination intensity, and is represented by the following formula:
Figure BDA0002170913370000101
wherein, PPVThe photovoltaic output is represented, K represents the limit of the illumination intensity, I represents the illumination intensity, S represents the illumination area, and eta represents the conversion efficiency.
Further, in the above formula, the illumination intensity I is a random variable, and the disturbance amount can be increased based on the conventional distribution, as shown in the following formula:
I＝Id+ΔI
wherein, IdRepresenting typical daily values of the intensity of the light, deltai representing the amount of disturbance,
Figure BDA0002170913370000102
in one embodiment of the present invention, a typical photovoltaic typical sunrise force curve and a random force curve are shown in fig. 5 and 6, respectively. The typical photovoltaic typical daily random output curve is obtained by sampling Monte Carlo through probability distribution parameters.
It should be noted that, since the failure of the new energy source unit can be generally equivalent to a multi-state model, but the transition probability and the transition state between the failure states are difficult to set, the failure of the new energy source unit is considered in the operation simulation in the present invention.
The energy storage system can be divided into energy type energy storage and power type energy storage. Energy-based energy storage can be generally expressed in terms of capacity, charge-discharge power, and SOC, while power-based energy storage does not require consideration of SOC. The response characteristic is shown as follows:
Figure BDA0002170913370000103
wherein, PessThe power of the stored energy is represented,
Figure BDA0002170913370000104
the maximum value of the stored energy power is indicated,
Figure BDA0002170913370000105
indicating the minimum value of the stored energy power, the index i indicating the class, the index T indicating the period, T indicating the total scheduling period, typically 24 hours, ηessThe efficiency of energy storage charge-discharge is shown,
Figure BDA0002170913370000111
the real-time stored energy is represented,
Figure BDA0002170913370000112
representing rated energy storage capacity, SOCi,maxRepresenting the maximum value of the state of charge of the stored energy, SOCi,minRepresents the minimum value of the energy storage state of charge and at represents the scheduling time interval.
For the fault characteristics of the energy storage System, the energy storage System is generally composed of 4 parts, namely, an energy storage converter (PCS), a Battery cell (BS), an energy storage Management System (BMS), and a Transformer (TR), and each part belongs to a series-parallel connection form in the connection manner, but each part belongs to a series relationship in the reliability logic, and a fault of any element can cause a fault of the whole energy storage System. Thus, the energy storage system may obtain system reliability by:
Figure BDA0002170913370000113
where λ represents the failure rate, r represents the average repair time, δ represents the repair rate, the subscript eq represents the equivalent value, the subscript ESU represents the entire energy storage module, and the subscript i represents the class.
Are generally considered in the reliability assessment of the systemThe maximum load mode, but the load has larger fluctuation in practice, the operation characteristics of the system can be reflected by considering the fluctuation of the load, and the obtained result is more real. The load fluctuation can be added with random disturbance on the basis of the original maximum load, namely, the disturbance with the mean value of mu and the variance of sigma normal distribution is superposed. Meanwhile, the demand response is considered on the load side, namely, the load is actively reduced, the response characteristic is shown as the following formula, and the load reduction rate alpha needs to be countediCutting down the time range
Figure BDA0002170913370000114
Figure BDA0002170913370000115
Wherein the content of the first and second substances,reindicating that the load power can be cut down,
Figure BDA0002170913370000116
representing the initial curtailable load power, z the decision variable, a the load reduction rate, index i the category, index t the period,
Figure BDA0002170913370000121
the maximum value of the reduction time is represented,
Figure BDA0002170913370000122
represents the minimum value of the clipping time.
In the invention, the reliability evaluation accuracy of the wind-light storage-power generation and transmission system is improved by running simulation. Preferably, in step S4, the simulating operation of the power transmission system including wind and light storage and generation includes: generating a power generation output curve of the system; generating a load curve of the system; and realizing power generation and load power balance according to the power generation output curve and the load curve.
Fig. 7 is a schematic flow chart of a generated output curve of a generating system according to the present invention, and as shown in fig. 7, in an embodiment of the present invention, the generated output curve of the generating system includes:
establishing a generator 8760 point output curve based on the typical daily curve;
judging whether the energy is a new energy unit (only a fan and a photovoltaic are considered as the new energy unit), and if not, outputting a 8760-point output curve as a system power generation output curve; if the new energy unit is available, judging whether new energy is added for random fluctuation; if no new energy random fluctuation is added, outputting a 8760-point output curve as a system power generation output curve; if the new energy is added to fluctuate randomly, acquiring a random output value on the new energy generator, judging whether a generator bus contains stored energy, if so, correcting the random output value of the generator according to the charge-discharge capacity of the stored energy, and adding the corrected random output value to the new energy unit to generate a power generation output curve of the system; and if the generator bus does not contain stored energy, attaching the obtained random output value to the new energy unit to generate a generated output curve of the system.
When the random output value of the generator is corrected, the energy storage parameter is obtained according to the energy storage charging and discharging capacity, and the energy storage power is superposed on the random output value of the generator, for example, the energy storage power is subtracted from the random output value of the generator during charging, and the energy storage power is increased from the random output value of the generator during discharging.
It should be noted that, in the case of a new energy unit, new energy is generally added to fluctuate randomly.
Fig. 8 is a schematic flow chart of the load curve of the system generated in the present invention, and as shown in fig. 8, the load curve of the system generated includes:
judging whether the operation mode is the maximum load mode, establishing a load power curve, if the operation mode is the maximum load mode, establishing a load 8760-point maximum power curve, and if the operation mode is not the maximum load mode, establishing a load 8760-point power curve based on the typical daily curve;
judging whether the additional load fluctuates randomly, if the additional load fluctuates randomly, adding random power to the established load power curve, and judging whether to reduce the load; if no random fluctuation is added, whether load reduction is performed or not is directly judged, if load reduction is performed, load reduction is performed according to the response characteristics of the load, corresponding load power is corrected, a load curve of the system is generated according to the corrected load power, and if no load reduction is performed, the load curve of the system is directly generated.
The operation mode is not limited to the maximum load mode, and may be any set load mode.
In an embodiment of the present invention, the power generation and load power balancing according to the generated output curve and the load curve includes:
acquiring power generation and load power according to the power generation output curve and the load curve;
and judging whether the power generation and the load power are balanced, if the power generation and the load power are unbalanced, adjusting the power generation output according to a nearby principle and a same-island principle, and adjusting the load power according to the nearby principle, the same-island principle and the energy storage capacity until the power generation and the load power are balanced.
Preferably, when the power generation and the load are unbalanced in power, the power generation is adjusted first, and then the load is adjusted. Fig. 9 is a schematic flow chart of realizing power generation and load power balance in the present invention, and as shown in fig. 9, taking an output curve at a Point of the generator 8760 and a power curve at a Point of the load 8760 as an example, starting from Point equal to 0, the power generation and load power at each Point is adjusted one by one until the power generation and power balance at all points is achieved, and statistics and calculation of the reliability index are performed. Specifically, starting from Point being 0, counting the power generation and load power of the Point, judging whether the power generation and load power are balanced, if so, judging whether the Point is smaller than 8760, if not, adjusting the power generation output according to a nearby principle, after adjustment, judging whether the power generation and load power are balanced again, if so, judging whether the Point is smaller than 8760, if not, adjusting the power generation output according to a same island principle, after adjustment, judging whether the power generation and load power are balanced again, if so, judging whether the Point is smaller than 8760, if not, reducing the load power according to the nearby principle, judging whether a load bus contains energy type energy storage, if so, correcting the load reduction according to the energy storage SOC and the discharge capacity, after correction, judging whether the power generation and load power are balanced again, if not, directly judging whether the power generation and load power are balanced again, if the balance is achieved, whether the Point is smaller than 8760 is judged, if the balance is achieved, the load power is reduced according to the same-island principle, whether a load bus contains energy type energy storage is judged again, if the load bus contains the energy type energy storage, the load reduction is corrected according to the energy storage SOC and the discharging capacity, whether the Point is smaller than 8760 is judged again after correction, and if the Point does not contain the energy type energy storage, whether the Point is smaller than 8760 is judged again directly. And if the Point is less than 8760, carrying out statistics and balance judgment on the power generation and load power of the next Point until all the power generation and load power of the Point 8760 are matched and balanced, and if the Point is not less than 8760, carrying out reliability index statistics and calculation.
Fig. 10a and 10b are schematic diagrams respectively comparing before and after simulation of new energy installed + load random fluctuation +200MWh energy storage operation with a permeability of 25%, wherein the system is an IEEE-RTS79 system, and the energy storage parameters are shown in table 2 below.
TABLE 2
Figure BDA0002170913370000141
As can be seen from comparison between fig. 10a and 10b, in fig. 10a, since no operation simulation is performed, the source load is not matched, and the difference is large. After the operation simulation in fig. 10b is performed, the source-to-charge matching is good and the difference is small, and the balance is achieved in consideration of the source-to-charge fluctuation characteristic.
Fig. 11a and 11b are schematic processing diagrams of wind power, photovoltaic power and energy storage before and after operation simulation respectively, and as shown in fig. 11a and 11b, after the operation simulation of the wind-light-containing power storage and transmission system, random output is superimposed on wind-light curves, and the charging and discharging states of the energy storage are normal.
In the invention, when the reliability evaluation is carried out on the wind-light-containing power storage and generation and transmission system, the reliability indexes comprise: the Load shedding Probability (PLC), the Power shortage time Probability (Loss of Load), the Load shedding Frequency (EFLC), the Power shortage Frequency (Loss of Load Frequency, LOLF), the Load shedding Duration (EDLC), the Load shedding Duration per time (ADLC), the Severity Indicator (SI), the Load shedding Expected value (Expected Load shedding, ELC), the Power shortage Expected value (Expected Energy Not Supplied, EENS), and the system Curtailment Power indicator (BPECI).
It should be noted that, in the present invention, the calculation method of each reliability index is not specifically limited, and is not described herein again.
In consideration of the particularity of the wind, light and energy storage resource power system, compared with the existing reliability index, the corresponding reliability index needs to be provided. Preferably, the reliability index further includes:
the new energy Generation electricity limit time expectation (Loss of Generation Probability, LOGP) (hours/year) is obtained by the following formula:
Figure BDA0002170913370000151
wherein N represents the total number of Monte Carlo sampling states, LLDiRepresenting the duration of each new energy power limit;
the new energy Generation Frequency Limit (LOGF) (times/year) is obtained by the following formula:
Figure BDA0002170913370000152
wherein N is the total number of Monte Carlo sampling states, LLTiThe number of times of power limitation of new energy;
the new Energy Generation electricity limit expectation (Loss of Generation Energy, LOEE) (MWh/year) is obtained by the following formula:
Figure BDA0002170913370000153
wherein N is the total number of Monte Carlo sampling states, ENSiThe electricity quantity of the new energy is limited every time.
In an embodiment of the present invention, the statistics and calculation results of the reliability index for the reliability evaluation of the power transmission system including wind and light storage are shown in table 3 below.
TABLE 3
Figure BDA0002170913370000154
Figure BDA0002170913370000161
Fig. 12 is a schematic configuration diagram of the reliability evaluation system of the wind-solar energy-storage-containing power generation and transmission system of the present invention, and as shown in fig. 12, the reliability evaluation system of the wind-solar energy-storage-containing power generation and transmission system of the present invention includes:
the model building module 1 is used for building an element reliability model based on the source load fluctuation characteristics;
the fault state acquisition module 2 is used for acquiring the fault state and the corresponding fault rate of the element according to the reliability model;
the fault state sampling module 3 is used for sampling fault states to form a fault state set and acquiring a fault rate corresponding to the fault states in the set;
the operation simulation module 4 is used for carrying out operation simulation on the wind-light-containing power storage and generation transmission system based on the reliability model so as to realize power generation and load balance;
the power flow calculation module 5 is used for calculating the power flow of the wind-light-containing power storage and generation transmission system;
the generator tripping load module 6 is used for carrying out generator tripping load according to the calculation result of the power flow of the wind-light-storage power generation and transmission system;
and the reliability evaluation module 7 is used for calculating and counting the reliability index of the wind-solar energy storage and power generation and transmission system and evaluating the reliability of the wind-solar energy storage and power generation and transmission system according to the reliability index.
The specific implementation of the reliability evaluation system comprising the wind-solar energy storage and power generation transmission system is similar to that of the reliability evaluation method, and is not described herein again.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (3)

1. A reliability evaluation method for a wind-solar energy-storage power generation and transmission system is characterized by comprising the following steps:
step S1, constructing an element reliability model based on the source load fluctuation characteristics;
step S2, acquiring the fault state and the corresponding fault rate of the element according to the reliability model;
step S3, sampling the fault state to form a fault state set and obtaining the fault rate corresponding to the fault state in the set;
step S4, performing operation simulation on the wind-light-containing power storage and generation and transmission system based on the reliability model to realize power generation and load power balance;
step S5, calculating the power flow of the wind-solar energy storage and power generation power transmission system;
step S6, cutting loads by a cutter according to the calculation result of the power flow of the wind-light-storage power generation and transmission system;
step S7, calculating and counting the reliability index of the power transmission system containing wind and light storage and generation, and evaluating the reliability of the power transmission system containing wind and light storage and generation according to the reliability index,
in step S4, the simulating operation of the power transmission system including wind and light storage and generation includes:
generating a power generation output curve of the system;
generating a load curve of the system;
realizing power generation and load power balance according to the power generation output curve and the load curve,
and realizing power generation and load power balance according to the power generation output curve and the load curve, wherein the power generation and load power balance method comprises the following steps:
acquiring power generation and load power according to the power generation output curve and the load curve;
judging whether the power generation and the load power are balanced, if the power generation and the load power are unbalanced, adjusting the power generation output according to the nearby principle and the same-island principle, adjusting the load power according to the nearby principle, the same-island principle and the energy storage capacity until the power generation and the load power are balanced,
wherein, the constructing the element reliability model based on the source load fluctuation characteristics comprises the following steps:
for a new energy generator set, the fan output is represented by the following formula:
Figure FDA0002779752720000011
wherein, PWTIndicating fan output, PRIndicating rated output, v, of the faniIndicating cut-in wind speed, vrIndicating rated wind speed, voWhich indicates the cut-out wind speed,
the photovoltaic contribution is represented by:
Figure FDA0002779752720000021
wherein, PPVRepresenting photovoltaic output, K representing the limit of illumination intensity, I representing the illumination intensity, S representing the illumination area, eta representing the conversion efficiency,
for an energy storage system, the response characteristic is shown as follows:
Figure FDA0002779752720000022
wherein, PessThe power of the stored energy is represented,
Figure FDA0002779752720000023
the maximum value of the stored energy power is indicated,
Figure FDA0002779752720000024
denotes the minimum value of the energy storage power, the index i denotes the class, the index T denotes the period, T denotes the total scheduling period, ηessThe efficiency of energy storage charge-discharge is shown,
Figure FDA0002779752720000025
the real-time stored energy is represented,
Figure FDA0002779752720000026
representing rated energy storage capacity, SOCi，maxRepresenting the maximum value of the state of charge of the stored energy, SOCi，minRepresents the minimum value of the energy storage state of charge, at represents the scheduling time interval,
wherein generating the generated output curve of the system comprises:
establishing a generator 8760 point output curve based on the typical daily curve;
judging whether the energy is a new energy unit or not, and if not, outputting a 8760-point output curve as a system power generation output curve; if the new energy unit is available, judging whether new energy is added for random fluctuation; if no new energy random fluctuation is added, outputting a 8760-point output curve as a system power generation output curve; if the new energy is added to fluctuate randomly, acquiring a random output value on the new energy generator, judging whether a generator bus contains stored energy, if so, correcting the random output value of the generator according to the charge-discharge capacity of the stored energy, and adding the corrected random output value to the new energy unit to generate a power generation output curve of the system; if the generator bus does not contain stored energy, the obtained random output value is added to the new energy unit to generate a generating output curve of the system,
wherein generating a load curve for the system comprises:
judging whether the operation mode is the maximum load mode, establishing a load power curve, if the operation mode is the maximum load mode, establishing a load 8760-point maximum power curve, and if the operation mode is not the maximum load mode, establishing a load 8760-point power curve based on the typical daily curve;
judging whether the additional load fluctuates randomly, if the additional load fluctuates randomly, adding random power to the established load power curve, and judging whether to reduce the load; if no random fluctuation is added, directly judging whether to perform load reduction, if the load reduction is performed, performing the load reduction according to the response characteristic of the load, correcting the corresponding load power, generating the load curve of the system according to the corrected load power, and if the load reduction is not performed, directly generating the load curve of the system,
in step S1, the energy storage system in the wind-solar energy-storage power generation and transmission system obtains the system reliability according to the following formula:
Figure FDA0002779752720000031
where λ represents the failure rate, r represents the average repair time, δ represents the repair rate, the subscript eq represents the equivalent value, the subscript ESU represents the entire energy storage module, the subscript i represents the class,
in step S1, the response characteristic of the load in the wind-solar energy-storage-power-generation power transmission system is as follows:
Figure FDA0002779752720000032
wherein p isreIndicating that the load power can be cut down,
Figure FDA0002779752720000034
representing the initial curtailable load power, z the decision variable, a the load reduction rate, index i the category, index t the period,
Figure FDA0002779752720000033
the maximum value of the reduction time is represented,
Figure FDA0002779752720000041
represents the minimum value of the clipping time.
2. The method for reliability assessment of a wind-solar energy-storage-power-generation and transmission system according to claim 1, wherein the reliability index comprises one or more of a new energy power generation limit time expectation, a new energy power generation limit frequency and a new energy power generation limit expectation.
3. A reliability evaluation system of a wind-solar power storage and generation transmission system is characterized by comprising:
the model building module is used for building an element reliability model based on the source load fluctuation characteristics;
the fault state acquisition module is used for acquiring the fault state and the corresponding fault rate of the element according to the reliability model;
the fault state sampling module is used for sampling fault states to form a fault state set and acquiring a fault rate corresponding to the fault states in the set;
the operation simulation module is used for simulating the operation of the wind-solar energy storage and power generation and transmission system based on the reliability model to realize power generation and load balance,
the operation simulation of the wind-solar-contained power storage and generation transmission system comprises the following steps:
generating a power generation output curve of the system;
generating a load curve of the system;
realizing power generation and load power balance according to the power generation output curve and the load curve,
wherein, realizing power generation and load power balance according to the power generation output curve and the load curve comprises:
acquiring power generation and load power according to the power generation output curve and the load curve;
judging whether the power generation and the load power are balanced, if the power generation and the load power are unbalanced, adjusting the power generation output according to a nearby principle and a same-island principle, and adjusting the load power according to the nearby principle, the same-island principle and the energy storage capacity until the power generation and the load power are balanced;
the load flow calculation module is used for calculating the load flow of the wind-light-containing power storage and generation transmission system;
the generator tripping load module is used for performing generator tripping load according to the calculation result of the power flow of the wind-light-storage power generation and transmission system;
the reliability evaluation module is used for calculating and counting the reliability index of the wind-solar energy storage and power transmission system and evaluating the reliability of the wind-solar energy storage and power transmission system according to the reliability index,
wherein, the constructing the element reliability model based on the source load fluctuation characteristics comprises the following steps:
for a new energy generator set, the fan output is represented by the following formula:
Figure FDA0002779752720000051
wherein, PWTIndicating fan output, PRIndicating rated output, v, of the faniIndicating cut-in wind speed, vrIndicating rated wind speed, voWhich indicates the cut-out wind speed,
the photovoltaic contribution is represented by:
Figure FDA0002779752720000052
wherein, PPVRepresenting photovoltaic output, K representing the limit of illumination intensity, I representing the illumination intensity, S representing the illumination area, eta representing the conversion efficiency,
for an energy storage system, the response characteristic is shown as follows:
Figure FDA0002779752720000053
wherein, PessThe power of the stored energy is represented,
Figure FDA0002779752720000054
the maximum value of the stored energy power is indicated,
Figure FDA0002779752720000055
denotes the minimum value of the energy storage power, the index i denotes the class, the index T denotes the period, T denotes the total scheduling period, ηessThe efficiency of energy storage charge-discharge is shown,
Figure FDA0002779752720000056
the real-time stored energy is represented,
Figure FDA0002779752720000057
representing rated energy storage capacity, SOCi，maxRepresenting the maximum value of the state of charge of the stored energy, SOCi，minRepresents the minimum value of the energy storage state of charge, at represents the scheduling time interval,
wherein generating the generated output curve of the system comprises:
establishing a generator 8760 point output curve based on the typical daily curve;
judging whether the energy is a new energy unit or not, and if not, outputting a 8760-point output curve as a system power generation output curve; if the new energy unit is available, judging whether new energy is added for random fluctuation; if no new energy random fluctuation is added, outputting a 8760-point output curve as a system power generation output curve; if the new energy is added to fluctuate randomly, acquiring a random output value on the new energy generator, judging whether a generator bus contains stored energy, if so, correcting the random output value of the generator according to the charge-discharge capacity of the stored energy, and adding the corrected random output value to the new energy unit to generate a power generation output curve of the system; if the generator bus does not contain stored energy, the obtained random output value is added to the new energy unit to generate a generating output curve of the system,
wherein generating a load curve for the system comprises:
judging whether the operation mode is the maximum load mode, establishing a load power curve, if the operation mode is the maximum load mode, establishing a load 8760-point maximum power curve, and if the operation mode is not the maximum load mode, establishing a load 8760-point power curve based on the typical daily curve;
judging whether the additional load fluctuates randomly, if the additional load fluctuates randomly, adding random power to the established load power curve, and judging whether to reduce the load; if no random fluctuation is added, directly judging whether to perform load reduction, if the load reduction is performed, performing the load reduction according to the response characteristic of the load, correcting the corresponding load power, generating the load curve of the system according to the corrected load power, and if the load reduction is not performed, directly generating the load curve of the system,
in step S1, the energy storage system in the wind-solar energy-storage power generation and transmission system obtains the system reliability according to the following formula:
Figure FDA0002779752720000061
where λ represents the failure rate, r represents the average repair time, δ represents the repair rate, the subscript eq represents the equivalent value, the subscript ESU represents the entire energy storage module, the subscript i represents the class,
in step S1, the response characteristic of the load in the wind-solar energy-storage-power-generation power transmission system is as follows:
Figure FDA0002779752720000071
wherein p isreIndicating that the load power can be cut down,
Figure FDA0002779752720000074
representing the initial curtailable load power, z representing the decision variable, alpha tableThe load reduction rate is shown, the index i indicates the kind, the index t indicates the period,
Figure FDA0002779752720000072
the maximum value of the reduction time is represented,
Figure FDA0002779752720000073
represents the minimum value of the clipping time.
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* Cited by examiner, † Cited by third party
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CN112701707B (en) * 2020-12-02 2022-07-08 国家电网有限公司 Method for evaluating starting capacity of energy storage converter with asynchronous motor load
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103699805A (en) * 2013-12-31 2014-04-02 国家电网公司 Method of assessing reliability of micro-grid in isolated island operation state
CN104851053A (en) * 2015-05-14 2015-08-19 上海电力学院 Wind-photovoltaic-energy-storage-contained method for power supply reliability evaluation method of distribution network
CN106056305A (en) * 2016-06-14 2016-10-26 中国电力工程顾问集团中南电力设计院有限公司 Power generation system reliability rapid assessment method based on state clustering
CN106875127A (en) * 2017-03-07 2017-06-20 国网江苏省电力公司经济技术研究院 THE UPFC Reliability modeling and its access system adequacy evaluation method
CN107292516A (en) * 2017-06-21 2017-10-24 合肥工业大学 It is a kind of to count and load rating and the load reliability estimation method of energy scheduling

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2015048737A1 (en) * 2013-09-30 2015-04-02 Do Rosario Jackseario Antonio Dionisio Power quality of service optimization for microgrids
CN110086195B (en) * 2019-03-28 2021-04-30 清华大学 Optimization method of alternating current-direct current hybrid power distribution system
CN109978404A (en) * 2019-04-04 2019-07-05 国网经济技术研究院有限公司 The passway for transmitting electricity Expansion Planning method that meter and uncertain factor and scene are cut down

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103699805A (en) * 2013-12-31 2014-04-02 国家电网公司 Method of assessing reliability of micro-grid in isolated island operation state
CN104851053A (en) * 2015-05-14 2015-08-19 上海电力学院 Wind-photovoltaic-energy-storage-contained method for power supply reliability evaluation method of distribution network
CN106056305A (en) * 2016-06-14 2016-10-26 中国电力工程顾问集团中南电力设计院有限公司 Power generation system reliability rapid assessment method based on state clustering
CN106875127A (en) * 2017-03-07 2017-06-20 国网江苏省电力公司经济技术研究院 THE UPFC Reliability modeling and its access system adequacy evaluation method
CN107292516A (en) * 2017-06-21 2017-10-24 合肥工业大学 It is a kind of to count and load rating and the load reliability estimation method of energy scheduling

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
主动配电网可靠性评估源荷模型改进及并行处理;陈鹏伟等;《电力系统自动化》;20160925;第40卷(第18期);第68-75页 *
基于伪时序状态转移抽样法评估含储能电力系统可靠性;程林等;《电力系统自动化》;20140410;第38卷(第7期);全文 *
陈鹏伟等.主动配电网可靠性评估源荷模型改进及并行处理.《电力系统自动化》.2016,第40卷(第18期), *

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