CN103887825B - Micro-grid operational control method - Google Patents

Abstract

The present invention proposes a kind of micro-grid operational control method.The method comprises the following steps: the data message obtaining multiple wind-powered electricity generation and photovoltaic generating system in micro-capacitance sensor, and calculates the power output of each wind-powered electricity generation and photovoltaic generating system respectively according to data message; Generate the particle of predetermined number in water power electricity generation system according to the default qualifications of the power output of water power electricity generation system multiple in micro-capacitance sensor, and generate population according to the particle of predetermined number; Calculate the fitness value of each particle in population, and determine the individual optimal particle of global optimum's particle in population and each particle; When meeting default end condition, according to the power output of global optimum's particle adjustment water power electricity generation system.The method of the embodiment of the present invention, by effectively controlling the power output in water power electricity generation system, can form good complementation with wind-powered electricity generation and photovoltaic generating system, can ensure the safe and reliable of electric power system and reservoir, micro-capacitance sensor power selling income can be made again maximum.

Description

Micro-grid operation control method

Technical Field

The invention relates to the technical field of power grids, in particular to a micro-grid operation control method.

Background

In recent years, the renewable distributed energy power generation technology is rapidly developed by virtue of the advantages of environmental friendliness, investment saving, flexible power generation and the like, wherein the renewable distributed energy power generation technology mainly comprises power generation technologies such as hydropower, wind power, photovoltaic and the like. However, in the process of generating power by using renewable energy, due to the influence of adverse factors such as randomness, intermittency and back-peak-shaving characteristics of wind energy, the output power of wind power is likely to have great fluctuation, so that the wind power integration brings great pressure to the safe and stable operation of a power system, and the wide application of distributed renewable energy is seriously influenced.

At present, contradictions between a large power grid and a renewable distributed power source can be adjusted through a micro-grid, however, the existing micro-grid cannot effectively control a distributed power generation system integrating technologies such as hydropower, wind power and photovoltaic, so that the value and benefit of distributed renewable energy power generation cannot be fully exploited, and the reliability and economy of the micro-grid are low.

Disclosure of Invention

The present invention is directed to solving at least one of the above problems.

Therefore, the invention aims to provide a micro-grid operation control method. The method can form better complementation with a wind power generation system and a photovoltaic power generation system in the microgrid by controlling the output power in the hydroelectric power generation system, namely by utilizing the regulating capacity of small and medium hydropower stations in the hydroelectric power generation system in the microgrid, thereby ensuring the safety and reliability of the power system and the reservoir and simultaneously ensuring the maximum power selling income of the microgrid to the large power grid. In addition, the situation that small and medium-sized hydropower stations in a micro-grid are often located on a river is considered, and a more practical step small hydropower model is established.

In order to achieve the above object, a microgrid operation control method according to an embodiment of the present invention includes the steps of: acquiring data information of a plurality of wind power generation systems and photovoltaic power generation systems in a microgrid, and respectively calculating the output power of each wind power generation system and each photovoltaic power generation system according to the data information; generating a preset number of particles in each hydroelectric power generation system according to preset limiting conditions of output power of a plurality of hydroelectric power generation systems in the microgrid, and generating particle swarms according to the preset number of particles; calculating a fitness value of each particle in the particle swarm, and determining a global optimal particle and an individual optimal particle of each particle in the particle swarm; and when the preset termination condition is met, adjusting the output power of the hydroelectric power generation system according to the global optimal particles.

According to the micro-grid operation control method, the output power in the hydroelectric power generation system is controlled, namely the adjusting capacity of small and medium hydropower stations in the hydroelectric power generation system in the micro-grid is utilized, so that good complementation can be formed between the micro-grid and a wind power generation system and a photovoltaic power generation system, the safety and the reliability of the power system and a reservoir are guaranteed, and the electricity selling income of the micro-grid to a large power grid is maximized. In addition, the situation that small and medium-sized hydropower stations in a micro-grid are often located on a river is considered, and a more practical step small hydropower model is established.

Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.

Drawings

The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which,

fig. 1 is a flowchart of a microgrid operation control method according to an embodiment of the present invention;

Detailed Description

Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention. On the contrary, the embodiments of the invention include all changes, modifications and equivalents coming within the spirit and terms of the claims appended hereto.

In the description of the present invention, it is to be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In the description of the present invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "connected" and "connected" are to be interpreted broadly, e.g., as being fixed or detachable or integrally connected; can be mechanically or electrically connected; may be directly connected or indirectly connected through an intermediate. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art. In addition, in the description of the present invention, "a plurality" means two or more unless otherwise specified.

Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.

A microgrid operation control method according to an embodiment of the present invention is described below with reference to the accompanying drawings.

Fig. 1 is a flowchart of a microgrid operation control method according to an embodiment of the present invention.

As shown in fig. 1, the microgrid operation control method comprises the following steps.

S101, acquiring data information of a plurality of wind power generation systems and photovoltaic power generation systems in the microgrid, and calculating output power of each wind power generation system and each photovoltaic power generation system according to the data information.

Specifically, the data information mainly comprises data curves of wind speed and solar irradiation intensity in each time period in one day.

It should be understood that besides data information of a plurality of wind power generation systems and photovoltaic power generation systems in the microgrid, a microgrid model, a load data curve of each node, and a price curve of the microgrid for selling and buying electricity to and from the large power grid should also be obtained.

In the embodiment of the invention, after the data information is obtained, the wind speed value v of the position of the wind power generation system can be obtained, and the active power P of the wind power generation system is calculated according to the wind speed value v_wt(v) And calculating the output power of the wind power generation system according to the active power. The wind power generation system can comprise one or more wind motors.

Specifically, the active power P of the wind power generation system can be calculated according to the following formula_wt(v)，

$P_{wt}\left(v\right)=\left\{\begin{array}{cc}0,& 0\≤v\≤v_{ci}\\ P_{wtR}(v-v_{ci})/(v_r-v_{ci}),& v_{ci}\≤v\≤v_r\\ P_{wtR},& v_r\≤v\≤v_{co}\\ 0,& v_{co}\≤v\end{array}\right.---\left(1\right)$

Wherein, P_wt(v) Is the active power of the wind power generation system at the wind speed value v, i.e. P_wt(v) When the wind speed is v, the accumulated sum of the active power of the wind turbine generator in the wind power generation system is v_ciFor cut-in wind speed, i.e. the minimum wind speed limit, v, at which the wind power generation system can operate to generate electricity_rRated wind speed, v_coFor cutting out the wind speed, i.e. the maximum wind speed limit value, P, at which the wind power generation system can operate to generate power_wtRThe rated active power in the wind power generation system.

Obtaining active power P of wind power generation system_wt(v) Then, the active power P of the wind power generation system can be obtained_wt(v) And calculating the output power of the wind power generation system by using the reactive power. In the embodiment of the present invention, the reactive power of the wind power generation system is 0, that is, the active power P of the wind power generation system of the present invention_wt(v) And the output power is equal.

In the embodiment of the invention, after the data information of the microgrid is obtained, the irradiance intensity of the position where the photovoltaic power generation system is located can be obtained, and the active power P of the photovoltaic power generation system is calculated according to the following formula_PV，

$P_{PV}=N_{PV}{p}_{PV}{f}_{PV}\left(\frac{G_T}{G_{T,STC}}\right)\[1+{\mathrm{\α}}_P(T_c-T_{c,STC})\]---\left(2\right)$

Wherein, P_PVThe active power of the photovoltaic power generation system; n is a radical of_PVNumber of photovoltaic arrays; p is a radical of_PVRated output power of the photovoltaic power generation system under standard test conditions; f. of_PVFor derating photovoltaic outputThe default value of the coefficient is 0.9, and the coefficient is mainly used for describing the reduction of the actual output of the photovoltaic array caused by dust accumulation, snow accumulation, shading and the like on the surface of the photovoltaic array; g_TIrradiance intensity; g_T,STCThe value of the irradiance intensity of the light source under the standard test condition is 1000w/m²；α_PIs the power temperature coefficient of the photovoltaic cell, wherein the power temperature coefficient of the photovoltaic cell α_PDepending on the type and material of the photovoltaic cell, for example, the power temperature coefficient α of the polysilicon photovoltaic cell currently on the market_PIs-0.5; t is_c,STCThe working temperature of the photovoltaic cell under the standard test condition is 25 ℃; t is_cIs the operating temperature of the photovoltaic cells in the photovoltaic power generation system.

Specifically, the operating temperature T of the photovoltaic cells in the photovoltaic power generation system can be calculated according to the following formula_c，

$T_c=T_a+\frac{G_T}{G_{T,NOCT}}(T_{c,NOCT}-T_{a,NOCT})---\left(3\right)$

Wherein, T_aIs ambient temperature; g_T,NOCTThe irradiance intensity at the nominal working temperature of the photovoltaic cell is 800w/m²；T_c,NOCTThe temperature is the temperature of the photovoltaic cell at the nominal working temperature, which is mainly provided by a photovoltaic cell manufacturer, and under the normal condition, the temperature of the photovoltaic cell at the nominal working temperature is about 47 ℃; t is_a,NOCTThe ambient temperature, which is defined as the nominal operating temperature, has a value of 20 ℃.

Obtaining active power P of photovoltaic power generation system_PVThen, the active power P of the photovoltaic power generation system can be determined_PVAnd calculating the output power of the photovoltaic power generation system by using the reactive power. In an embodiment of the invention, the reactive power of the photovoltaic power generation system is 0, that is, the active power P of the photovoltaic power generation system of the invention_PVAnd the output power is equal.

S102, generating a preset number of particles in each hydroelectric power generation system according to preset limiting conditions of output power of a plurality of hydroelectric power generation systems in the microgrid, and generating particle swarms according to the preset number of particles.

In an embodiment of the invention, the output power of the hydroelectric power generation system comprises: active power of hydroelectric power generation systemAnd reactive powerIn particular, the active power of multiple hydroelectric power generation systems in a microgrid is determinedAnd reactive powerRandomly generating a preset number of particles, wherein the particles are represented in the following form,

$\begin{array}{c}{X}_1=(P_{HT1}^{t=1},P_{HT2}^{t=1},...,P_{HTn}^{t=1}{P}_{HT1}^{t=2},P_{HT2}^{t=2},...,P_{HTn}^{t=2},......,P_{HT1}^{t=T},P_{HT2}^{t=T},...,P_{HTn}^{t=T},\\ Q_{HT1}^{t=1},Q_{HT2}^{t=1},...,Q_{HTn}^{t=1},...,Q_{HTn}^{t=1},Q_{HT1}^{t=2},Q_{HT2}^{t=2},...,Q_{HTn}^{t=2},......,Q_{HT1}^{t=T},Q_{HT2}^{t=T},...,Q_{HTn}^{t=T})\end{array}$

wherein n is the number of small hydropower stations in the hydropower generation system, and T is the total time period number divided in one day. Active power of hydroelectric power generation systemAnd reactive powerThe preset limiting condition refers to the active power of the hydroelectric power generation systemAnd reactive powerShould satisfy the systemBetween the upper and lower limits of the active and reactive power in normal operation, the upper and lower limits of the active and reactive power will be described in detail in the following embodiments.

S103, calculating the fitness value of each particle in the particle swarm, and determining the global optimal particle and the individual optimal particle of each particle in the particle swarm.

In the embodiment of the invention, the flow value of the hydroelectric power generation system is calculated, the objective function with the constraint condition is obtained according to the flow value of the hydroelectric power generation system, the objective function with the constraint condition is converted into the fitness function without the constraint condition, and the fitness value of each particle in the particle swarm is calculated according to the fitness function without the constraint condition.

Firstly, a small hydropower station model of a hydroelectric power generation system in a microgrid is determined, specifically, in the microgrid, small hydropower stations in the hydroelectric power generation system are often located on a river to form a stepped small hydropower station group, from the viewpoint of economy, a reservoir is often built only in an upstream first-stage small hydropower station and has a certain adjusting capacity, while the downstream small hydropower stations are radial small hydropower stations without adjusting capacity, and the power generation amount is influenced by the scheduling of the upstream small hydropower station reservoir.

For convenience of description, a two-step small hydropower station is taken as an example for explanation.

The output of the ith hydropower station in the hydroelectric power generation system is as follows:

$P_{HTi}^t=A_i{Q}_i^t{H}_i^t---\left(4\right)$

wherein,the active power of the ith hydropower station in the hydropower generation system at the time period t; a. the_iThe comprehensive output coefficient of the ith hydropower station is obtained;generating a flow rate for the ith hydropower station during the t-th period,and averaging the generated water heads for the ith hydropower station in the t-th time period.

Water balance limiting conditions:

$\left\{\begin{array}{c}{\mathrm{VR}}^{t-1}-{\mathrm{VR}}^t+(q_1^t-Q_1^t-y_1^t)\mathrm{\Δ}t=0\\ (q_2^t-Q_1^{t-\mathrm{\τ}}-y_1^{t-\mathrm{\τ}}-Q_2^t-y_2^t)\mathrm{\Δ}t=0\end{array}\right.---\left(5\right)$

hydropower station output limiting conditions:

$\underset{\‾}{P_i}\≤P_{HTi}^t\≤\stackrel{\‾}{P_i}---\left(6\right)$

$\underset{\‾}{Q_{HTi}}\≤Q_{HTi}^t\≤\stackrel{\‾}{Q_{HTi}}---\left(7\right)$

the limiting conditions of the generating flow and the storage capacity of the reservoir are as follows:

$\underset{\‾}{Q_1}\≤Q_1^t\≤\stackrel{\‾}{Q_1}---\left(8\right)$

$\underset{\‾}{VR}\≤{\mathrm{VR}}^t\≤\stackrel{\‾}{VR}---\left(9\right)$

in the formulas (5), (6), (7), (8) and (9), the initial water storage amount VR of the upstream reservoir of the river⁰Is known;P _i 、the active power of the ith hydropower station is the upper limit and the lower limit;for the active and reactive power generated by the ith hydropower station at time t,Q _HTi 、generating an upper limit and a lower limit of reactive power for the ith hydropower station; VR (virtual reality)^tThe amount of water stored in the upstream reservoir at the time t;VR、the upper and lower limits of the water storage capacity of the upstream reservoir;the natural water inflow, the average power generation flow and the water abandoning flow of an upstream hydropower station in the period of t;the water flow rate of the upstream hydropower station and the downstream hydropower station in the interval of the t time period, the average power generation flow rate of the downstream hydropower station and the water discharge rate;Q ₁ 、the upper and lower limits of the power generation flow of the upstream reservoir; tau is upstream reservoir of water flowFlow to a downstream reservoir for a time; Δ t is the period length.

Then, under the condition that the load requirement of the micro-grid is met and the line voltage does not exceed the limit, the maximum income from the micro-grid to the large grid in one day is the target, and the income can be expressed as:

$\max F=max\underset{t=1}{\overset{T}{\Σ}}\left(E_{sell}\right(t\left)P_{sell}\right(t)-E_{buy}(t\left)P_{buy}\right(t\left)\right)---\left(10\right)$

f is income of the micro-grid for selling electricity to the large power grid; t is the total time period divided in one day; t is a time period; e_sell(t) the price of electricity sold to the large power grid by the micro power grid at the moment t; p_sell(t) the power sold by the microgrid to the large power grid at the moment t, wherein the power is the power of a wind power generation system, a photovoltaic power generation system and water in the microgridThe sum of the output powers of the electrical power generation systems; e_buy(t) the price of electricity bought from the large power grid by the micro power grid at the moment t; p_buyAnd (t) the power bought by the micro-grid to the large-grid at the moment t. After the particle swarm is initialized, calculating the power flow of the micro-grid by a Newton-Raphson method, and obtaining the injection power P from the large grid to the micro-grid at the connecting point of the micro-grid and the large grid_PCC(t) wherein the injection power P_PCC(t) and P_sell(t) and P_buy(t) has a certain relationship, which is expressed as: if P_PCC(t) is greater than or equal to 0, then P_buy(t)＝P_PCC(t)，P_sell(t) ═ 0; if P_PCC(t)<0, then P_sell(t)＝P_PCC(t)，P_buy(t)＝0。

Writing the electricity selling income of the micro-grid to the large-grid into a minimum value form and using the minimum value as an objective function to be optimized can be expressed as follows:

$\min F^{\&prime;}=min(-\underset{t=1}{\overset{T}{\&Sigma;}}(E_{sell}\left(t\right)P_{sell}\left(t\right)-E_{buy}\left(t\right)P_{buy}\left(t\right)\left)\right)---\left(11\right)$

in an embodiment of the invention, after the step small hydropower station model is established, a power flow constraint equation is utilized

$\left\{\begin{array}{c}{P}_i=U_i\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}{U}_j(G_{ij}{\mathrm{cos\&delta;}}_{ij}+B_{ij}{\mathrm{sin\&delta;}}_{ij})\\ Q_i=U_i\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}{U}_j(G_{ij}{\mathrm{cos\&delta;}}_{ij}-B_{ij}{\mathrm{sin\&delta;}}_{ij})\end{array}\right.---\left(12\right)$

Wherein, P_i、Q_iRespectively injecting active power and reactive power into the node i; u shape_i、U_jThe voltages at nodes i and j, respectively; n is the number of nodes in the microgrid; g_ij、B_ijIs the real and imaginary parts of the admittance between nodes i and j;_ijthe phase difference of the voltages between nodes i and j.

Wherein, the voltage constraint conditions are as follows:

U_i,min≤U_i≤U_i,max，i＝1,2,…,N_N(13)

wherein, U_iIs the voltage at the ith node; u shape_i,maxAnd U_i,minRespectively, the upper limit and the lower limit of the voltage allowed at the ith node.

Then, according to each constraint condition of small and medium hydropower stations in a hydropower generation system in the microgrid, establishing an objective function with the constraint condition, which can be expressed as:

minF'(x)

s.t.g_i(x)≥0i＝1,…,m

h_j(x)＝0j＝1,…,n

(14)

wherein minF' (x) is an objective function, namely the negative number of the total electricity selling income of the micro-grid, x is a particle position vector in the particle swarm, namely a particle position vector consisting of active power and reactive power in each hydroelectric power generation system, and g_i(x) Is an inequality constraint, namely equations (6), (7), (8), (9) and (13); h is_i(x) Is an equality constraint, i.e., equation (5); and m and n are the number of corresponding constraints.

Finally, the constraint problem can be converted into an unconstrained problem according to, for example, an external point penalty function method, that is, the external point penalty function method can convert the objective function with the constraint condition into the form of the unconstrained fitness function we need. Specifically, the constraint condition may be included in the objective function in the form of a penalty function term, so as to obtain a fitness function without constraint condition, which may be expressed as:

$\min F^{\&prime;\&prime;}\left(x\right)=F^{\&prime;}\left(x\right)+\mathrm{\&sigma;}\{\mathrm{\&Sigma;}{\left(max\right\{0,-g_i\left\}\right)}^2+\mathrm{\&Sigma;}|h_j{|}^2\}---\left(15\right)$

wherein F "(x) is an unconstrained fitness function, that is, after the population of particles is obtained, a fitness value corresponding to each particle can be calculated from F" (x); sigma is a preset penalty factor, specifically, the selection of the preset penalty factor sigma in the fitness function of the unconstrained condition is very important, and if the preset penalty factor sigma is too large, the difficulty in calculation is increased for minimization of a penalty function item; if the preset penalty factor sigma is too small, the minimum point of the penalty function item is far away from the optimal solution of the constraint problem, and the calculation efficiency is poor. The predetermined penalty factor σ can be accurately calculated by the existing method, and is not described herein for simplicity.

And S104, when the preset termination condition is met, adjusting the output power of the hydroelectric power generation system according to the global optimal particles.

In an embodiment of the present invention, the preset termination condition may be that the maximum iteration number is reached and/or a difference value of particle fitness values corresponding to the preset iteration number is smaller than a preset threshold. Wherein the maximum iteration number is greater than or equal to 50, the preset iteration number is greater than or equal to 10, and the preset threshold is 10^-5. For example, after a plurality of iterations on the particle swarm, if the difference between the fitness value of the global particle calculated at the 2 nd time and the fitness value of the global particle calculated at the 12 th time is less than the preset threshold 10^-5And judging that the preset termination condition is met, stopping iteration, and obtaining the global optimal particles according to calculation, wherein the corresponding global optimal particles are the optimal active and reactive output power of each small hydropower station at each moment. And after the global optimal particles are obtained, generating control signals of all small hydropower stations according to the global optimal particles, and adjusting the actual active and reactive output power of the small hydropower stations to the optimal active and reactive output power of all small hydropower stations by all small hydropower stations according to the control signals. Therefore, the purpose of controlling the operation of the micro-grid comprising the step small hydropower station is achieved. In addition, after the output power of the hydroelectric power generation system is adjusted, the total electricity selling income of the micro-grid can be calculated according to the output power of the hydroelectric power generation system and the output power of each wind power generation system and each photovoltaic power generation system, and the electricity selling income of the micro-grid to the large grid is the maximum at the moment.

In the embodiment of the invention, when the preset termination condition is not met, the individual optimal particles and the corresponding fitness values of the particles are updated, the global optimal particles and the corresponding fitness values of the particle swarm are updated, and the iteration is stopped until the preset termination condition is met, and the global optimal particles are output. The process of updating the particles is the same as the existing standard particle swarm algorithm updating process, and here, for the sake of simplicity, the description is omitted.

According to the micro-grid operation control method, the output power in the hydroelectric power generation system is controlled, namely the adjusting capacity of small and medium hydropower stations in the hydroelectric power generation system in the micro-grid is utilized, so that good complementation can be formed between the micro-grid and a wind power generation system and a photovoltaic power generation system, the safety and the reliability of the power system and a reservoir are guaranteed, and the electricity selling income of the micro-grid to a large power grid is maximized. In addition, the situation that small and medium-sized hydropower stations in a micro-grid are often located on a river is considered, and a more practical step small hydropower model is established.

It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.

In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

While embodiments of the invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims (7)

1. A micro-grid operation control method is characterized by comprising the following steps:

acquiring data information of a plurality of wind power generation systems and photovoltaic power generation systems in a microgrid, and respectively calculating the output power of each wind power generation system and each photovoltaic power generation system according to the data information;

generating a preset number of particles in each hydroelectric power generation system according to preset limiting conditions of output power of a plurality of hydroelectric power generation systems in the microgrid, and generating particle swarms according to the preset number of particles;

calculating a fitness value of each particle in the particle swarm, and determining a global optimal particle and an individual optimal particle of each particle in the particle swarm;

when a preset termination condition is met, adjusting the output power of the hydroelectric power generation system according to the global optimal particles;

wherein said calculating a fitness value for each particle in the population of particles and determining a globally optimal particle in the population of particles and an individual optimal particle for each particle further comprises:

the output of the ith hydropower station in the hydroelectric power generation system is as follows:

wherein,the active power of the ith hydropower station in the hydropower generation system at the time period t; a. the_iThe comprehensive output coefficient of the ith hydropower station is obtained;generating a flow rate for the ith hydropower station during the t-th period,averaging the generating water purification heads for the ith hydropower station in the t-th time period;

water balance limiting conditions:

hydropower station output limiting conditions:

the limiting conditions of the generating flow and the storage capacity of the reservoir are as follows:

P _i 、the active power of the ith hydropower station is the upper limit and the lower limit;for the active and reactive power generated by the ith hydropower station at time t,Q _HTi 、generating an upper limit and a lower limit of reactive power for the ith hydropower station; VR (virtual reality)^tThe amount of water stored in the upstream reservoir at the time t;VR、the upper and lower limits of the water storage capacity of the upstream reservoir;the natural water inflow, the average power generation flow and the water abandoning flow of an upstream hydropower station in the period of t;the water flow rate of the upstream hydropower station and the downstream hydropower station in the interval of the t time period, the average power generation flow rate of the downstream hydropower station and the water discharge rate;Q ₁ 、the upper and lower limits of the power generation flow of the upstream reservoir; τ is the time of flow of the water stream from the upstream reservoir to the downstream reservoir; Δ t is the period length;

under the conditions that the load requirement of the micro-grid is met and the line voltage does not exceed the limit, the maximum income from the micro-grid to the large grid in one day is the target, and the income can be expressed as follows:

f is income of the micro-grid for selling electricity to the large power grid; t is the total time period divided in one day; t is a time period; e_sell(t) the price of electricity sold to the large power grid by the micro power grid at the moment t; p_sell(t) the power sold by the microgrid to the large power grid at the moment t, wherein the power is the sum of the output powers of the wind power generation system, the photovoltaic power generation system and the hydroelectric power generation system in the microgrid; e_buy(t) the price of electricity bought from the large power grid by the micro power grid at the moment t; p_buy(t) power bought from the microgrid to the large power grid at the moment t; after the particle swarm is initialized, calculating the power flow of the micro-grid by a Newton-Raphson method, and obtaining the injection power P from the large grid to the micro-grid at the connecting point of the micro-grid and the large grid_PCC(t) wherein the injection power P_PCC(t) and P_sell(t) and P_buy(t) has a certain relationship, which is expressed as: if P_PCC(t) is greater than or equal to 0, then P_buy(t)＝P_PCC(t)，P_sell(t) ═ 0; if P_PCC(t)<0, then P_sell(t)＝P_PCC(t)，P_buy(t) ═ 0; writing the electricity selling income of the micro-grid to the large-grid into a minimum value form and using the minimum value as an objective function to be optimized can be expressed as follows:

after the cascade small hydropower station model is established, a power flow constraint equation is utilized:

wherein, P_i、Q_iRespectively injecting active power and reactive power into the node i; u shape_i、U_jThe voltages at nodes i and j, respectively; n is the number of nodes in the microgrid; g_ij、B_ijIs the real and imaginary parts of the admittance between nodes i and j;_ijthe phase difference of the voltages between the nodes i and j, wherein the voltage constraint condition is as follows:

U_i,min≤U_i≤U_i,max，i＝1,2,…,N_N

wherein, U_iIs the voltage at the ith node; u shape_i,maxAnd U_i,minThe upper limit and the lower limit of the voltage allowed by the ith node are respectively set;

according to each constraint condition of small and medium hydropower stations in a hydropower generation system in a microgrid, an objective function with the constraint condition is established, and can be expressed as:

minF'(x)

s.t.g_i(x)≥0i＝1,…,m

h_j(x)＝0j＝1,…,n

where minF' (x) is an objective function, x is a particle position vector in the particle population, g_i(x) Is an inequality constraint condition, and m and n are the number of corresponding constraint conditions;

the constraint condition is added into the objective function in the form of a penalty function term, so as to obtain a fitness function without the constraint condition, which can be expressed as:

minF"(x)＝F'(x)+σ{Σ(max{0,-g_i})²+Σ|h_j|²}

wherein F "(x) is an unconstrained fitness function, that is, after the population of particles is obtained, a fitness value corresponding to each particle can be calculated from F" (x); sigma is a preset penalty factor.

2. The method according to claim 1, wherein the calculating the output power of each of the wind power generation system and the photovoltaic power generation system according to the data information specifically comprises:

acquiring a wind speed value v of the position of the wind power generation system, and calculating active power P of the wind power generation system according to the wind speed value v_wt(v) And according to said active power P_wt(v) And calculating the output power of the wind power generation system.

3. The method of claim 2, wherein the active power P of the wind power generation system is calculated according to the following formula_wt(v)，

Wherein, P_wt(v) Is the active power in the wind power generation system at a wind speed value v, v_ciFor cutting into the wind speed, v_rRated wind speed, v_coFor cutting out the wind speed, P_wtRThe rated active power in the wind power generation system.

4. The method according to claim 1, wherein the calculating the output power of each of the wind power generation system and the photovoltaic power generation system according to the data information specifically comprises:

obtaining the irradiance intensity of the position where the photovoltaic power generation system is located, and calculating the active power P of the photovoltaic power generation system according to the following formula_PV，

Wherein, P_PVActive power for photovoltaic power generation systems, N_PVNumber of photovoltaic arrays; p is a radical of_PVRated output power f of the photovoltaic power generation system under standard test conditions_PVDerating factor for photovoltaic output, G_TAs intensity of irradiance, G_T,STCα for the intensity of irradiance of a light source under standard test conditions_PFor photovoltaic cell power temperature coefficient，T_c,STCIs the operating temperature, T, of the photovoltaic cell under standard test conditions_cThe working temperature of a photovoltaic cell in the photovoltaic power generation system; and according to the active power P_PVAnd calculating the output power of the photovoltaic power generation system.

5. The method of claim 4, wherein the operating temperature T of the photovoltaic cells in the photovoltaic power generation system is calculated according to the following formula_c，

Wherein, T_aIs ambient temperature; g_T,NOCTIs irradiance intensity, T, at nominal operating temperature of the photovoltaic cell_c,NOCTIs the photovoltaic cell temperature at the nominal operating temperature, T_a,NOCTThe ambient temperature specified for the nominal operating temperature.

6. The method according to claim 1, wherein the predetermined termination condition is that the maximum number of iterations m is reached and/or a difference between particle fitness values corresponding to the predetermined number of iterations is less than a predetermined threshold.

7. The method of claim 6, wherein the preset number of iterations is greater than or equal to 10, and the preset threshold is 10^-5。