CN110880793A - Daily flow-based power capacity configuration method for small hydropower station micro-grid - Google Patents
Daily flow-based power capacity configuration method for small hydropower station micro-grid Download PDFInfo
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Abstract
The invention discloses a daily flow-based power supply capacity configuration method for a small hydropower station and a microgrid, which comprises the steps of firstly obtaining historical data of 1-360 days of warehousing flow of a hydropower station in the microgrid in one year from a related database, determining 1-360 days of warehousing flow of the small hydropower station in one year, and constructing a daily warehousing flow data set; then calculating and determining the mean value and the variance of the warehousing flow of the small hydropower stations in the micro-grid within 1-360 days in one year according to the normal distribution rule; then aiming at the characteristic of reservoir warehousing flow change of the small hydropower stations in 1-360 days in one year, calculating and determining the probability of reservoir warehousing flow change of the small hydropower stations in the micro-grid according to a normal distribution rule, and calculating the average value of the warehousing flow of the small hydropower stations in the micro-grid; and finally, calculating the capacity of the small hydropower station small hydroelectric generator assembling machine. The method reflects the probability randomness of the flow change of the warehouse entry for many years, provides theoretical guidance for the power capacity configuration of the small hydropower micro-grid, and provides necessary technical support for distributed new energy power generation and intelligent power grid dispatching operation.
Description
Technical Field
The invention relates to the technical field of power grids, in particular to a daily flow-based power supply capacity configuration method for a small hydropower station micro-grid.
Background
The micro-grid is a grid form in which distributed sources (small hydropower, small wind power, photovoltaic power generation) -loads (water, electricity, gas, cold and heat loads) are integrated in a certain way. The micro-grid is connected with a main grid in 380V, 10kV, 35kV and other voltage levels, is in grid-connected operation with the main grid under the normal operation condition, absorbs power from the main grid during heavy load, and can inject power into the main grid during light load; the micro-grid can be operated in isolated network under the condition of local fault of the main grid or under the condition of fault of an adjacent micro-grid, and on the premise of ensuring the quality of electric energy, the electric quantity is provided for a load by a part of distributed power supplies in the micro-grid, so that the normal power supply state of the micro-grid without fault is realized, the power failure time is reduced, and the power supply reliability is improved.
The aim of the construction and operation of the micro-grid is to sustainably and efficiently utilize/consume part of distributed power supply electric quantity in the micro-grid and minimize the electric quantity exchanged with a main grid.
A distributed small hydropower station-based micro-grid is a micro-grid which takes small hydropower stations as a main form for power supply. In a small hydropower station micro-grid, most hydropower stations are of a radial flow type, dams generally have no water storage function, reservoirs have no water storage and water transfer capacity, the utilization of water energy of the small hydropower stations completely depends on the inflow of the reservoirs, and the power generation state and the output scale of small hydropower generating sets also completely depend on the inflow of the reservoirs. Under the condition, in order to realize high-efficiency utilization of water energy to generate electricity, the small hydropower station needs to generate more or less electricity by using more or less water. The water inflow amount of the small hydropower station reservoir is random, the water inflow amount is completely different in different hydrological cycles, the water inflow amount is large in a rich water period, and the water inflow amount is small in a dry water period. Thus, small hydropower farm basin river flows tend to be represented in tabular form as minimum flows, maximum flows, average flows, annual average flows, calculated average flows, weighted average flows, mathematical average flows, and the like. By adopting a meter form with different flow rates, small hydropower stations can obtain different installed capacity levels. The generated power and generated energy of the small hydropower station are different in different hydrologic periods at different installed capacity levels, and the optimal generated power and generated energy result in different hydropower station water energy utilization rates, generating equipment utilization rates and generating equipment annual maximum utilization hours.
Different load levels and the capacity scales of the distributed power supply are integrated in the microgrid, so that the structural form and the tidal current characteristics of the microgrid are changed. Due to the fact that various distributed power sources such as small hydropower, small wind power and photovoltaic power generation are connected, voltages of various levels can be adopted due to different connected power source capacity scales. Due to the randomness of electricity utilization, the load power can always change on different time-space scales, and the time-interval performance is obvious; meanwhile, the output of distributed power supplies such as wind power generation and photovoltaic power generation is intermittent, random and time-interval, and the output of small hydroelectric generating sets is seasonal. Therefore, the balance relation between the load power and the power supply power of the micro-grid is difficult to maintain, when the load power is greater than the power supply power, the micro-grid needs to obtain supplementary power from the main power grid, and when the load power is less than the power supply power, the residual power of the micro-grid needs to be injected into the main power grid, so that a random bidirectional power flow characteristic is formed. The random bidirectional power flow characteristic can cause the voltage of the node in the local area in the microgrid to be higher when the distributed power supply is large in output and light in load and cause the voltage of the node in the local area in the microgrid to be lower when the distributed power supply is small in output and heavy in load. Therefore, the limitation conditions and requirements of the node voltage inside the microgrid have influence and restriction on the capacity configuration, the operation mode and the voltage control strategy of the distributed power supply in the microgrid, and the limitation conditions and requirements of the node voltage inside the microgrid need to be considered. When a micro-grid is connected to nodes of power distribution networks with different voltage grades, the node voltage of the power distribution network is changed to be higher or lower due to different absorption or injection power of the micro-grid from or into the power distribution network, and the limit conditions and requirements of the node voltage of the power distribution network need to be considered in the capacity configuration, the operation mode and the voltage control strategy of a distributed power supply in the micro-grid.
A microgrid distributed power system is a system with both complex and interactive stochastic and fuzzy uncertainty events or parameters. Under the influence of various uncertain random and fuzzy events or parameters, the power generation power and the power generation amount of the micro-grid distributed power supply become more random and fuzzy, and the capacity configuration of the micro-grid distributed power supply is greatly influenced by the characteristics. In the past, the generated power and the generated energy of a micro-grid distributed power system usually adopt a deterministic calculation method, and some of the generated power and the generated energy also adopt an uncertain calculation method of probability analysis. The deterministic calculation method is generally used for calculating the generated power, the generated energy and the installed capacity of the micro-grid distributed power supply system under the condition that the water inflow and the flow of a small hydropower station, the sunlight intensity in an area and the wind speed are all determined, the influences of factors such as the voltage regulation requirements of the micro-grid and a power distribution network and a flexible control mode are not considered, the calculation result is unique and deterministic, and the actual conditions of the generated power, the generated energy and the installed capacity of the micro-grid distributed power supply system cannot be reflected. The calculation method of probability analysis is generally to calculate the generated power, the generated energy and the installed capacity of the microgrid distributed power supply system under the condition that only single factors such as the water inflow and the flow of a small hydropower station, the sunlight intensity in an area, the wind speed and the like are assumed as uncertainty factors, and the calculation result is a probability value with a certain confidence level. In fact, the generated power, the generated energy and the installed capacity of the microgrid distributed power supply system are influenced by various uncertainty factors. Moreover, these influencing factors are typically random uncertainties or fuzzy uncertainties, or they are random and fuzzy uncertainties, often present as random and fuzzy uncertainty events or quantities. Therefore, the uncertainty and randomness of the influence factors are not considered comprehensively in the prior art of calculating the generated power, the generated energy and the installed capacity of the microgrid distributed power supply system, and the applicability, the practicability and the applicability of the calculation method are difficult to meet.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a method for configuring the power supply capacity of a small hydropower station micro-grid based on daily flow by considering the uncertainty and randomness of the above influence factors.
In order to achieve the purpose, the technical scheme provided by the invention is as follows:
a method for configuring the power capacity of a small hydropower station micro-grid based on daily flow comprises the following steps:
s1, acquiring historical data of 1-360-day-one-year warehousing flow of a hydropower station in a microgrid from a related database, determining 1-360-day-one-year warehousing flow of a small hydropower station through calculation and analysis, and constructing a daily warehousing flow data set;
s2, calculating and determining warehousing flow of small and medium hydropower stations in the micro-grid for 1-360 days in one year according to normal scores by adopting a probability analysis methodMean and variance of the cloth law variation: mu.sQD1And σQD1、μQD2And σQD2、...、μQD365And σQD365；
S3, calculating and determining the probability of the reservoir warehousing flow of the small hydropower stations in the micro-grid changing according to a normal distribution rule by adopting a probability analysis method aiming at the warehousing flow change characteristics of 1-360 days in one year;
s4, calculating the average value of warehousing flow of the small and medium hydropower stations in the micro-grid;
and S5, calculating the capacity of the small hydropower station generator assembling machine.
Further, the step S3 is to calculate and determine the probability that the reservoir warehousing flow of the small hydropower station in the microgrid changes according to the normal distribution rule by using a probability analysis method aiming at the warehousing flow change characteristics of 1-360 days in one year:
...
in the above formula, QMAVIs the average flow of a small hydropower station basin for many years, QQD1、QQD2、...、QQD365Respectively the warehousing flow of the small hydropower stations of 1-365 days;
further, the formula for calculating the average value of the warehousing flow of the small hydropower stations in the microgrid in the step S4 is as follows:
QI＝pQID1QQD1+pQID2QQD2+...+pQID365QQD365)/365；
wherein Q isQD1、QQD2、...、QQD365The flow rates of the small hydropower stations in storage are respectively 1-365 days.
Further, the formula for calculating the capacity of the small hydropower station small hydroelectric generator assembling machine in the step S5 is as follows:
PS＝0.0098(kD1+kD2+...+kD365)HQI/365；
wherein k isD1、kD2、...、kD365The generating efficiency of the small hydropower station small hydropower unit is 1-360 days in one year, and H is a small hydropower station water head.
Compared with the prior art, the principle and the advantages of the scheme are as follows:
according to the scheme, historical data of 1-360-day-one-year warehousing flow of the hydropower station in the micro-grid are obtained from a related database, 1-360-day-one-year warehousing flow of the small hydropower station is determined through calculation and analysis, and a daily warehousing flow data set is constructed; then, calculating and determining the mean value and the variance of the warehousing flow of the small hydropower stations in the micro-grid 1-360 days a year according to the normal distribution rule by adopting a probability analysis method; secondly, calculating and determining the probability of reservoir warehousing flow of the small and medium hydropower stations in the micro-grid changing according to a normal distribution rule aiming at the warehousing flow change characteristics of 1-360 days in one year by adopting a probability analysis method, and calculating the average value of the warehousing flow of the small and medium hydropower stations in the micro-grid; and finally, calculating the capacity of the small hydropower station small hydroelectric generator assembling machine. The scheme reflects probability randomness of warehousing flow change for many years, provides theoretical guidance for power capacity configuration, power generation output prediction and operation scheduling of the small hydropower micro-grid, and provides necessary technical support for distributed new energy power generation and intelligent power grid scheduling operation.
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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 services required for the embodiments or the technical solutions in the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for configuring the capacity of a small hydropower station micro-grid power supply based on daily flow.
Detailed Description
The invention will be further illustrated with reference to specific examples:
as shown in fig. 1, a method for configuring the power capacity of a small hydropower station micro-grid based on daily flow comprises the following steps:
s1, acquiring historical data of 1-360-day-one-year warehousing flow of a hydropower station in a microgrid from a related database, determining 1-360-day-one-year warehousing flow of a small hydropower station through calculation and analysis, and constructing a daily warehousing flow data set;
s2, calculating and determining the mean value and the variance of the warehousing flow of the small hydropower stations in the micro-grid 1-360 days a year according to a normal distribution rule by adopting a probability analysis method: mu.sQD1And σQD1、μQD2And σQD2、...、μQD365And σQD365；
S3, calculating and determining the probability that the reservoir warehousing flow of the small hydropower stations in the micro-grid changes according to a normal distribution rule by adopting a probability analysis method aiming at the warehousing flow change characteristics of 1-360 days in one year:
...
in the above formula, QMAVIs the average flow of a small hydropower station basin for many years, QQD1、QQD2、...、QQD365Respectively the warehousing flow of the small hydropower stations of 1-365 days;
s4, calculating the average value of warehousing flow of the small hydropower stations in the microgrid:
QI＝pQID1QQD1+pQID2QQD2+...+pQID365QQD365)/365；
wherein Q isQD1、QQD2、...、QQD365The flow rates of the small hydropower stations in storage are respectively 1-365 days.
S5, calculating the capacity of the small hydropower station generator assembling machine:
PS＝0.0098(kD1+kD2+...+kD365)HQI/365；
wherein k isD1、kD2、...、kD365The generating efficiency of the small hydropower station small hydropower unit is 1-360 days in one year, and H is a small hydropower station water head.
The above-mentioned embodiments are merely preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, so that variations based on the shape and principle of the present invention should be covered within the scope of the present invention.
Claims (4)
1. A method for configuring the power capacity of a small hydropower station micro-grid based on daily flow is characterized by comprising the following steps:
s1, acquiring historical data of 1-360-day-one-year warehousing flow of a hydropower station in a microgrid from a related database, determining 1-360-day-one-year warehousing flow of a small hydropower station through calculation and analysis, and constructing a daily warehousing flow data set;
s2, calculating and determining the mean value and the variance of the warehousing flow of the small hydropower stations in the micro-grid 1-360 days a year according to a normal distribution rule by adopting a probability analysis method: mu.sQD1And σQD1、μQD2And σQD2、...、μQD365And σQD365；
S3, calculating and determining the probability of the reservoir warehousing flow of the small hydropower stations in the micro-grid changing according to a normal distribution rule by adopting a probability analysis method aiming at the warehousing flow change characteristics of 1-360 days in one year;
s4, calculating the average value of warehousing flow of the small and medium hydropower stations in the micro-grid;
and S5, calculating the capacity of the small hydropower station generator assembling machine.
2. The method for configuring the power supply capacity of the small hydropower station micro-grid based on the daily flow as claimed in claim 1, wherein the step S3 is implemented by adopting a probability analysis method, and aiming at the warehousing flow change characteristics of 1-360 days in one year, the probability that the warehousing flow of the small hydropower station reservoir in the micro-grid changes according to a normal distribution rule is calculated and determined:
...
in the above formula, QMAVIs the average flow of a small hydropower station basin for many years, QQD1、QQD2、...、QQD365Respectively the warehousing flow of the small hydropower stations of 1-365 days;
3. the method for configuring the power supply capacity of the small hydropower station micro-grid based on daily flow according to claim 2, wherein the formula for calculating the average value of the warehousing flow of the small hydropower stations in the micro-grid in the step S4 is as follows:
QI＝pQID1QQD1+pQID2QQD2+...+pQID365QQD365)/365；
wherein Q isQD1、QQD2、...、QQD365The flow rates of the small hydropower stations in storage are respectively 1-365 days.
4. The method for configuring the power supply capacity of the small hydropower station micro-grid based on daily flow according to claim 3, wherein the formula for calculating the capacity of the small hydropower station generator assembling machine in the step S5 is as follows:
PS＝0.0098(kD1+kD2+...+kD365)HQI/365；
wherein k isD1、kD2、...、kD365The generating efficiency of the small hydropower station small hydropower unit is 1-360 days in one year, and H is a small hydropower station water head.
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| CN103580061A (en) * | 2013-10-28 | 2014-02-12 | 贵州电网公司电网规划研究中心 | Microgrid operating method |
| CN103903073A (en) * | 2014-04-23 | 2014-07-02 | 河海大学 | Planning method and system for optimizing micro-grid containing distributed power sources and stored energy |
| CN109063901A (en) * | 2018-07-17 | 2018-12-21 | 昆明电力交易中心有限责任公司 | Long-term generating capacity analysis method in a kind of provincial power network hydroelectric system |
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| CN103580061A (en) * | 2013-10-28 | 2014-02-12 | 贵州电网公司电网规划研究中心 | Microgrid operating method |
| CN103903073A (en) * | 2014-04-23 | 2014-07-02 | 河海大学 | Planning method and system for optimizing micro-grid containing distributed power sources and stored energy |
| CN109063901A (en) * | 2018-07-17 | 2018-12-21 | 昆明电力交易中心有限责任公司 | Long-term generating capacity analysis method in a kind of provincial power network hydroelectric system |
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