CN110555620A - new energy reliability evaluation method in energy internet power distribution system - Google Patents
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Abstract
The invention discloses a new energy reliability evaluation method in an energy internet power distribution system, which comprises the following steps of 1, calculating reliability parameters of a wind driven generator; step 2, calculating reliability parameters of the photovoltaic power generation system; step 3, calculating the reliability parameters of the standby minimum path; the prior art continuously adopts the traditional power distribution network reliability evaluation method which can not be suitable for a power distribution network system containing new energy, and adopts the technical problems that the traditional power distribution system reliability evaluation index can not effectively and accurately evaluate the power supply reliability of the power distribution system, and the like.
Description
Technical Field
The invention belongs to a power distribution network planning technology, and particularly relates to a new energy reliability evaluation method in an energy internet power distribution system.
Background
the reliability of the power distribution system is the measurement of the capability of the whole power distribution system and equipment from a power supply point to a user, including a power distribution substation, a high-low voltage distribution line and a service line, to meet the power and electric energy demands of the user according to an acceptable standard and an expected quantity; the reliability evaluation of the power distribution system generally adopts a power distribution network system average power failure frequency index (SAIFI), a power distribution network system average power failure time index (SAIDI), an urban/rural power network user power supply reliability index (ASAI) and the like; with the development of energy internet, power distribution systems containing new energy are gradually increased, and the power supply reliability of the power distribution systems cannot be effectively and accurately evaluated by adopting the traditional reliability evaluation indexes of the power distribution systems.
Disclosure of Invention
the technical problem to be solved by the invention is as follows: the method for evaluating the reliability of the new energy in the energy Internet power distribution system is provided, and the technical problems that the traditional power distribution network reliability evaluation method cannot be applied to the power distribution network system containing the new energy, the traditional power distribution system reliability evaluation index cannot effectively and accurately evaluate the power supply reliability of the power distribution system and the like in the prior art are solved.
the technical scheme of the invention is as follows:
a method for evaluating reliability of new energy in an energy Internet power distribution system comprises the following steps:
Step 1, calculating reliability parameters of the wind driven generator;
step 2, calculating reliability parameters of the photovoltaic power generation system;
and 3, calculating the reliability parameters of the standby minimum path.
the method for calculating the reliability parameters of the wind driven generator comprises the following steps:
in the formula: pt is the output of the wind turbine at the time t, Vt is the wind speed at the time t, Vci, Vr and Vco respectively represent the cut-in wind speed, the rated wind speed and the cut-off wind speed of the wind turbine, Pr is the rated power of the wind turbine, A, B and C are parameters, and the following formula is given:
the method for calculating the reliability parameters of the photovoltaic power generation system comprises the following steps:
first, energy conversion was calculated:
And then calculating the output power of the battery panel:
In the formula: kc is a threshold value; eta is the energy conversion rate; i is the incident light intensity; the area of the solar cell panel is S, and the light intensity which can be received by the solar cell panel at a certain moment is It.
The method for calculating the reliability parameters of the standby minimum path comprises the following steps:
The standby minimum path is a special minimum path, and the criterion is that the standby minimum path comprises a disconnected interconnection switch or a distributed power supply; the reliability parameters of the standby minimum path include the switching time t in addition to all devices on the pathpsAnd handover success rate pps(ii) a If the standby minimum path contains a tie switch, then there is tps＝ts，pps＝ps(ii) a When more than one tie switch exists, the switching time of the standby minimum path is the maximum switching time of all tie switches, the switching success rate is the product of the switching success rates of all tie switches, and the formula is shown as follows:
In the formula:andRespectively the switching time and the switching success rate of the ith interconnection switch in the standby minimum path;
If the end of the standby minimum path is the distributed power supply, the switching time of the standby minimum path is firstly determined, and t is providedps＝tds0; obtaining a distributed power source multi-state model accumulation probability table carried by switching success rate query; the method specifically comprises the steps of counting the sum of load active power of all load points passed by the load points and the standby minimum path, and then obtaining the effective probability of the standby minimum path by inquiring the accumulation probability table.
If the standby minimum path has both the interconnection switch and the distributed power supply, the reliability parameter calculation method of the standby minimum path comprises the following steps:
The invention has the beneficial effects that:
According to the method, on the basis of the reliability indexes of the traditional power distribution network, various reliability indexes of new energy are calculated, and the technical problems that the reliability evaluation method of the traditional power distribution network cannot be suitable for a power distribution network system containing new energy, the reliability evaluation indexes of the traditional power distribution system cannot effectively and accurately evaluate the power supply reliability of the power distribution system and the like in the prior art are solved.
Detailed Description
The reliability evaluation index of the power distribution system is an index facing users, and the average power failure frequency and time of the users are used as measurement standards, and the reliability evaluation index comprises the following steps: average power failure times index (SAIFI) of a power distribution network system, average power failure time index (SAIDI) of the power distribution network system, power supply reliability index (ASAI) of urban/rural power network users and the like. The reliability evaluation algorithm of the power distribution system calculates the indexes; on the basis of the indexes, the reliability of the new energy accessed to the power distribution system is calculated, so that the accuracy of reliability analysis of the whole system is improved. The invention adopts a multi-state model when evaluating the reliability of distributed power systems such as wind driven generators, photovoltaic power generation systems and the like. The power output of the distributed power supply is related to natural environments such as wind speed, illumination intensity and the like, and presents certain random characteristics, so that the power output is a continuous random variable. Probability density functions or probability distribution functions are usually used for mathematically researching continuous random variables, however, the probability density functions and the distribution functions for describing the power output of the distributed power supply are very complex and are inconvenient to apply to the reliability evaluation of the power system; the probability distribution table for discrete random variables is researched, the method is simple and intuitive, and parameters such as expectation, variance and the like are easy to calculate.
under a certain precision requirement, the power output of the distributed power supply is dispersed into a plurality of states, and the power output and the probability of each state are described in a form similar to a probability distribution table (shown in the following table).
distributed power supply power output state table
| power output level/kW | Probability of |
| 0 | 0.2059 |
| 50 | 0.0661 |
| 150 | 0.1123 |
| 250 | 0.1036 |
| 350 | 0.1122 |
| 450 | 0.0912 |
| 550 | 0.0773 |
| 650 | 0.0501 |
| 750 | 0.0451 |
| 850 | 0.0326 |
| 950 | 0.025 |
| 1000 | 0.0786 |
for the sake of calculation convenience, the distributed power supply power output state table is sometimes converted into a state table expressed by an accumulated probability as shown in the following table.
Distributed power supply power output state table expressed by accumulated probability
| power output level/kW | Probability of |
| >＝0 | 1.0000 |
| >0 | 0.7941 |
| >50 | 0.7280 |
| >150 | 0.6157 |
| >250 | 0.5121 |
| >350 | 0.3999 |
| >450 | 0.3087 |
| >550 | 0.2314 |
| >650 | 0.1813 |
| >750 | 0.1362 |
| >850 | 0.1036 |
| >950 | 0.0786 |
| >1000 | 0 |
(1) Wind turbine reliability parameter calculation
The output of the wind turbine generator changes with the change of wind speed, and whether the wind turbine generator is in a power generation state or not and the output magnitude depend on the condition of the wind speed. The relation curve of the output power of the wind turbine generator and the wind speed is called as the power characteristic curve of the wind turbine generator,
Wherein Pt is the wind turbine generator output at time t, Vt is the wind speed at time t, Vci, Vr, Vco respectively represent the cut-in wind speed, the rated wind speed, and the cut-off wind speed of the wind turbine generator, Pr is the rated power of the wind turbine generator, A, B and C are parameters, and can be given by the following formula:
Wind has the characteristics of randomness and fluctuation, but the wind speed distribution of most areas still has a certain rule. The invention adopts Weibull distribution, which is probability distribution with a simpler form and can be well fitted with the actual wind speed distribution. The weibull distribution is a unimodal, two-parameter cluster of distribution functions. The distribution function and the probability density function are respectively expressed as:
Where v is the wind speed, k and c are two parameters of the Weibull distribution, k being called the shape parameter and c being called the scale parameter. These two parameters can be approximated by the mean wind speed μ and the standard deviation σ:
Γ is a Gamma function, and its expression is:
According to a partial integral formula, Γ (1) ═ 1; when x > 1, Γ (x) ═ x-1 Γ (x-1).
In the formula, Γ is the Gamma function Γ (k). Since k > 1, for computational convenience, Γ (k) is considered approximately:
Γ(k)≈(k-1)(k-2)…(k-[k])
Wherein [ k ] is the largest integer not exceeding k.
photovoltaic power generation system reliability parameter calculation
Solar cells are the basis and core of photovoltaic power generation systems, and their output power depends on a number of factors, the two most important of which are the intensity of the solar radiation that can be received on the panel and its own energy conversion efficiency. The energy conversion efficiency of a photovoltaic power generation system is defined as the ratio of the amount of electricity generated by a solar panel per square meter to the intensity of sunlight received by the solar panel. The energy conversion rate is a variable quantity, which is closely related to the light intensity received by the panel, and increases with the increase of the light intensity. Typical energy conversion efficiency eta is in a curve relation with the incident light intensity I. A threshold value Kc exists in the relation, and when the light intensity is less than Kc, the energy conversion rate eta can be obviously increased along with the increase of the incident light intensity I; when the light intensity is greater than Kc, the energy conversion rate η becomes very slow with the increase of the light intensity I. To simplify the analysis and calculation, we can approximate this curve as a broken line, whose mathematical expressions and relationship are as follows:
An approximate relation curve of the energy conversion rate and the light intensity of the photovoltaic power generation system; knowing the relationship between the energy conversion rate and the light intensity, the output power of the photovoltaic power generation system can be determined by the incident light intensity. Assuming that the area of the solar panel is S, the light intensity that the solar panel can receive at a certain time is It, then the output power of the solar panel is:
the output power of the solar cell is varied with the intensity of the solar radiation. The radiation intensity of sunlight mainly depends on the solar altitude and the attenuation effect of cloud shielding on sunlight. The variation of the solar altitude over time during the day can be determined by a deterministic function; the attenuation effect of the cloud layer on the intensity of solar radiation is random when the weather changes. It can therefore be considered that the intensity of radiation of the sunlight id (t) at a certain moment is equal to a determined base intensity id (t) superimposed by a random attenuation Δ i (t).
We define the base intensity id (t) as the average of the solar radiation intensity at time t of day for a statistical period of time, typically one year. Id (t) can be approximated as a quadratic function with the following mathematical expression and time dependence:
Wherein t is the time of day in hours; imax is an average value of the solar radiation intensity at 12 pm, i.e., Imax is I (12).
The amount of attenuation Δ i (t) depends mainly on the state of the cloud layer in the sky. Since transition probabilities between different cloud layer states are difficult to obtain, we simplify Δ i (t), and we can consider Δ i (t) to follow normal distribution. The probability density function of a normal distribution is expressed as:
and (3) calculating the reliability of the standby minimum path:
by definition, a standby minimum is a particular minimum that is determined to include an open tie switch or distributed power source. The reliability parameters of the standby minimum path include the switching time t in addition to all devices on the pathpsAnd handover success rate pps。
If the standby minimum path contains a tie switch, then there is tps＝ts，pps＝ps(ii) a When there are multiple interconnection switches, it is standbythe switching time of the minimum path is the maximum switching time of all tie switches, and the switching success rate is the product of the switching success rates of all tie switches, as shown in the following formula.
Andrespectively the switching time and the switching success rate of the ith interconnection switch in the standby minimum path.
if the end of the standby minimum path is a distributed power supply, the switching time of the standby minimum path can be determined firstly, and t is providedps＝tds0; and the switching success rate needs to be obtained by inquiring the accumulated probability table of the multi-state model of the carried distributed power supply. The method specifically comprises the steps of counting the sum of load active power of all load points passed by the load points and the standby minimum path, and then obtaining the effective probability of the standby minimum path by inquiring the accumulation probability table. Assuming that the total load along a certain standby minimum path is 680kW, the switching success rate p of the standby minimum path ispsis 0.1813; if the total load along the way is 1050kW, then the switching success rate p of this standby minimum pathpsIs simply 0.
if the standby minimum path has both the interconnection switch and the distributed power supply, the reliability parameter calculation method of the standby minimum path is the same as that of the plurality of interconnection switches.
Claims (5)
1. A method for evaluating reliability of new energy in an energy Internet power distribution system comprises the following steps:
step 1, calculating reliability parameters of the wind driven generator;
step 2, calculating reliability parameters of the photovoltaic power generation system;
and 3, calculating the reliability parameters of the standby minimum path.
2. The method for evaluating the reliability of the new energy in the energy internet power distribution system according to claim 1, wherein the method comprises the following steps: the method for calculating the reliability parameters of the wind driven generator comprises the following steps:
in the formula: pt is the output of the wind turbine at the time t, Vt is the wind speed at the time t, Vci, Vr and Vco respectively represent the cut-in wind speed, the rated wind speed and the cut-off wind speed of the wind turbine, Pr is the rated power of the wind turbine, A, B and C are parameters, and the following formula is given:
3. The method for evaluating the reliability of the new energy in the energy internet power distribution system according to claim 1, wherein the method comprises the following steps: the method for calculating the reliability parameters of the photovoltaic power generation system comprises the following steps: first, energy conversion was calculated:
And then calculating the output power of the battery panel:
In the formula: kc is a threshold value; eta is the energy conversion rate; i is the incident light intensity; the area of the solar cell panel is S, and the light intensity which can be received by the solar cell panel at a certain moment is It.
4. the method for evaluating the reliability of the new energy in the energy internet power distribution system according to claim 1, wherein the method comprises the following steps: the method for calculating the reliability parameters of the standby minimum path comprises the following steps: the standby minimum path is a special minimum path, and the criterion is that the standby minimum path comprises a disconnected interconnection switch or a distributed power supply; the reliability parameters of the standby minimum path include the switching time t in addition to all devices on the pathpsand handover success rate pps(ii) a If the standby minimum path contains a tie switch, then there is tps＝ts，pps＝ps(ii) a When more than one tie switch exists, the switching time of the standby minimum path is the maximum switching time of all tie switches, the switching success rate is the product of the switching success rates of all tie switches, and the formula is shown as follows:
In the formula:andrespectively the switching time and the switching success rate of the ith interconnection switch in the standby minimum path;
if the end of the standby minimum path is the distributed power supply, the switching time of the standby minimum path is firstly determined, and t is providedps＝tds0; obtaining a distributed power source multi-state model accumulation probability table carried by switching success rate query; the concrete methodThe method is to count the load active power sum of all load points passed by the load point and the standby minimum path, and then obtain the effective probability of the standby minimum path by inquiring the accumulated probability table.
5. The method for evaluating the reliability of the new energy in the energy internet power distribution system according to claim 1, wherein the method comprises the following steps: if the standby minimum path has both the interconnection switch and the distributed power supply, the reliability parameter calculation method of the standby minimum path comprises the following steps:
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| CN113364050A (en) * | 2021-06-22 | 2021-09-07 | 山东交通职业学院 | New energy reliability evaluation method in energy internet power distribution system |
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