WO2013120347A1

WO2013120347A1 - Control method for unifying self-balancing and self-smoothing of micro-grid

Info

Publication number: WO2013120347A1
Application number: PCT/CN2012/081832
Authority: WO
Inventors: 李洋; 刘海涛; 季宇; 吴鸣; 梁惠施; 苏剑
Original assignee: 中国电力科学研究院; 国家电网公司
Priority date: 2012-02-17
Filing date: 2012-09-24
Publication date: 2013-08-22
Also published as: CN102611127A; CN102611127B

Abstract

A control method for unifying self-balancing and self-smoothing of micro-grid is provided. The method comprises the following steps: formulating a local load demand power prediction curve, a self-balancing degree plan curve and a self-smoothing degree limit value by a micro-grid energy managing system; judging whether the micro-grid energy managing system accept schedule of a regional distribution network scheduling system; reporting the self-balancing degree plan curve and the self-smoothing degree limit value to the regional distribution network scheduling system; formulating a self-balancing degree boundary curve and a self-smoothing degree boundary limit value by the regional distribution network scheduling system; receiving the self-balancing degree boundary curve and the self-smoothing degree boundary limit value by the micro-grid energy managing system; and processing coordination control to distributed power supply, an energy storage device and controllable load in the micro-grid by a micro-grid central controller. The method can reduce disturbance influence of intermittent renewable energy resource power fluctuation to accessed regional distribution network at high permeability; and high energy utilization ratio is acquired.

Description

Method for controlling self-balancing and self-smoothing of microgrid

The invention belongs to the field of power systems, and particularly relates to a control method for self-balancing and self-smoothing of a micro-grid. Background technique

In recent years, with the deteriorating environment and the scarcity of non-renewable energy, distributed power (DG) and micro-grid technologies have gradually received attention from various countries. The distributed power supply is integrated into the distribution network in the form of a microgrid, which can effectively control the distributed power supply, improve energy utilization, improve power supply reliability, and improve power quality. Therefore, a number of microgrid project projects have been built in recent years in China. However, in many microgrid projects, the distributed power supply, energy storage and load capacity ratio are chaotic, and the control is uncoordinated. After large-scale access, large power fluctuations will have a serious impact on the regional distribution network, and even cause regional distribution. The grid is oscillating. In addition, the research methods of domestic microgrid control are mainly concentrated in the microgrid, such as active/frequency control, reactive power/voltage control of microgrid, etc.; and no effective control based on coordination and interaction between microgrid and distribution network has been proposed. The method cannot effectively solve the series of problems brought about by the above-mentioned microgrid grid connection, which hinders the rapid development and efficient utilization of renewable clean energy in China. Summary of the invention

Aiming at the problems existing in the existing microgrid interconnection, the object of the present invention is to provide a control method for self-balancing and self-smoothing of the microgrid. The control method cooperates with and supports each other through the self-balancing control and the regional distribution network; the self-smoothing control effectively reduces the impact of the power fluctuation on the distribution network, and at the same time reduces the frequent adjustment of the energy storage device and prolongs the service life of the device; Renewable clean energy provides a solution for "gross access" on the distribution grid side.

The object of the present invention is achieved by the following technical solutions:

A control method for self-balancing and self-smoothing of a microgrid is improved in that the method comprises the following steps:

1 The microgrid energy management system formulates a local load demand power prediction curve, a self-balancing plan curve, and a self-leveling slip limit;

2 judging whether the microgrid energy management system accepts the dispatching of the regional distribution network dispatching system;

3 reporting the self-balancing plan curve and the self-smoothing plan limit to the regional distribution network dispatching system;

4 The regional distribution network dispatching system formulates a self-balancing boundary curve and a self-smoothing boundary limit;

5 the microgrid energy management system receives the self-balancing boundary curve and the self-smoothing boundary limit;

6 The micro-grid central controller performs coordinated control of the distributed power source, the energy storage device and the controllable load in the micro-grid. A preferred technical solution provided by the present invention is: in the step 1: the microgrid energy management system formulates a local load demand power prediction curve (0, self-balance plan curve ^{k (t)} and self-smoothity plan limit Value S.

A second preferred technical solution provided by the present invention is: The step 2 includes: determining whether the microgrid energy management system is associated with the regional distribution network scheduling system:

i. If there is no correlation, proceed from step 2 to step 6. According to the self-balance plan curve and self-smoothing plan limit set by the micro-grid energy management system, the distributed power source in the micro-grid (refers to wind power generation, photovoltaic power generation, Micro gas turbines, fuel cells, etc., not limited to wind power generation, photovoltaic power generation), energy storage devices (referred to as supercapacitors, lithium batteries, lead-acid batteries and other energy storage devices; can also be more than two types of composite energy storage devices; not limited Coordinated control with an energy storage device) and a controllable load;

If it is already associated, further determine whether the microgrid energy management system accepts the regional distribution network dispatching system scheduling:

a. If the regional distribution network scheduling system scheduling is not accepted, proceed from step 2 to step 6; b. If the scheduling is accepted, the local load demand power prediction curve ^W , the self-balancing plan curve ^3⁄4 "() and self-smoothing The degree plan limit ^{a is} uploaded to the regional distribution network dispatching system, that is, from step 2 to step 3.

The third preferred technical solution provided by the present invention is: in the step 4, the regional distribution network dispatching system according to the local load demand power prediction curve P _L W and the self-balanced plan curve reported by the micro-grid energy management system^ ^„(0 and self-smoothing plan limit _Spkm , formulate the microgrid self-equilibrium boundary curve ^„ (0 - k (0 and self-smoothing boundary limit and s _max , and return the microgrid energy) Management system.

The fourth preferred technical solution provided by the present invention is: in the step 5, the microgrid energy management system receives the microgrid self-equilibrium boundary curve U) - k (0 and the self-smoothing boundary limit s _mn And, and passed to the microgrid central controller.

A fifth preferred technical solution provided by the present invention is: in the step 6, the micro-grid central controller is based on a self-equilibrium boundary curve ^(0 - k (0 and self-smoothing boundary limit s _mn and pair The distributed power supply, energy storage device and controllable load in the microgrid are coordinated.

The sixth preferred technical solution provided by the present invention is: the ^ is the lower limit of the self-balancing boundary curve; the ax (0 is the upper limit of the self-balancing boundary curve; the ^ is the self-smoothing boundary limit The lower limit; the ^_ is an upper limit of the self-smoothing boundary limit; the controllable load is a load in which the third-stage load is switched according to the degree of power surplus.

The seventh preferred technical solution provided by the present invention is: the micro power grid central controller is distributed power to the micro grid, The contents of the energy storage device and the controllable load for coordinated control are as follows:

1) Comparing the real-time self-equilibrium of the microgrid with ^ and ^; when u≤wo≤, the output power of the microgrid meets the load demand (the load includes local or remote load, which includes the first, second and third loads, The controllable load is part of the three-stage load); When ^0<^ (0, the output power of the microgrid cannot meet the load demand, increase the output power of the microgrid or reduce the controllable load that has been input; when wo>^ _max (o), the output power of the microgrid is greater than the load demand, reducing the output power of the microgrid or investing in the controlled load that has been removed;

2) Compare the absolute value of the real-time self-smoothness of the microgrid with ^„ and ^ _; when ^„≤^«|≤^_, it means that the microgrid grid-connected line exchange power output is stable, and the micro-grid is connected to the grid. The line exchange power curve is smooth; when μομ^^, it means that the microgrid grid-connected line exchange power fluctuation is small, the power output is relatively stable, but the frequent adjustment and excessive damage to the service life of the energy storage device can reduce the adjustment of the energy storage device. Strength; When μ(ί)|>^_, it indicates that the microgrid grid-connected line exchange power fluctuates greatly, and it is necessary to increase the regulation of the energy storage device to reduce the disturbance to the regional distribution network.

The eighth preferred technical solution provided by the present invention is:

I. The expression of the output power of the microgrid is as follows:

P _c ( t ) = ∑ P, ( t ) + X Ρ , { ί ) + χ P _k ( t )

(1); Its towel:

ρ. ^(ί) a total output power of a microgrid;

ρ' ^(ί) — intermittent distributed power output power;

W a controllable distributed power output power;

A ^w — charge and discharge power of the energy storage device;

II. The expression of the power demand of the microgrid is as follows:

(2

P _L ( t ) = ∑ , ( + ∑ P _{2 j} ( t + ∑ ( );

p ', a total load demand power in a microgrid;

- the primary load demand power in the microgrid;

P^ ^(t) a secondary load demand power in a microgrid;

p, a three-stage load demand power in a microgrid;

III. The expression of the power exchange of the microgrid grid-connected line is as follows:

P _TL (t) = P _L (t) - P _G (t) = P _L (t) - k(t)P _L (t) Its towel:

- microgrid grid-connected line exchange power;

( ^ί ) a microgrid local load demand power;

Microgrid total output power;

feW-microgrid self-balancing;

IV. The self-equilibrium of the micro-grid fc (0 refers to the ratio of the output power of the distributed power source and the energy storage device to the load demand power in the micro-grid, fc (0 expression is as follows: k(t) = M∑ (4) ; P _L it)

V, the self-smoothness of the micro-grid 0 refers to the rate of change of the exchange power of the grid-connected line of the micro-grid, and the expression of 0 is as follows: (5).

Dt Compared with the prior art, the beneficial effects achieved by the invention are:

1. The control method provided by the invention can effectively coordinate and interact with the regional distribution network through self-balancing control, and support each other, and improve peak-to-valley characteristics of power consumption;

2. The control method provided by the present invention effectively reduces the impact of power fluctuations on the distribution network through self-smoothing control, and at the same time reduces the frequent adjustment of the energy storage device and prolongs the service life of the energy storage device;

3. The control method provided by the invention helps the distribution network containing the micro grid to predict the load demand and power output in the area, and uniformly manages the dispatch;

4. The control method provided by the present invention helps to improve the power supply reliability and power quality of users in the microgrid;

5. The control method provided by the present invention provides a solution for realizing "clean access" of renewable clean energy in the distribution network side;

6. The control method provided by the present invention provides an effective defining method for the current chaotic distributed power supply and microgrid interconnection mode in China.

DRAWINGS

1 is a structural diagram of a regional distribution network dispatching system of the present invention;

2 is a flow chart of a control method for self-balancing and self-smoothing of the microgrid according to the present invention;

Figure 3 is a diagram showing the contents of the main control of the microgrid of the present invention;

4 is a structural diagram of a microgrid system containing wind and light storage according to an embodiment of the present invention;

Figure 5 is a schematic diagram of the microgrid self-equilibrium curve Wt) of the present invention. detailed description

The specific embodiments of the present invention are further described in detail below with reference to the drawings and specific embodiments.

First, two new definitions proposed in the present invention are described: microgrid self-equilibrium and self-smoothness.

(1) Self-balancing and self-smoothing of the microgrid:

1. Output power in the microgrid:

^ _G ( ί ) = ∑ ρ, ( ί ) + ∑ Pj (t) + ∑ p _t (t) ( ^{ί) The} total output power of a microgrid system;

ρ' ^(ί) — intermittent distributed power output power;

A controllable distributed power output power;

A W—The energy storage and discharge power of the energy storage device.

2. Load demand power in the microgrid:

P _L ( ) = ∑ P ( ) + ∑ f _{2 J} (o + ∑ ⁽² ) pt, total load demand power in a microgrid;

The power demand of the primary load in a microgrid;

P^ ^(t) a secondary load demand power in a microgrid;

Three-stage load demand power in a microgrid.

3. Microgrid tie line exchange power:

P _TL (t) = P _L (t) - P _G (t) = P _L (t) - k(t)P _L (t) (3)

W-microgrid grid-connected line exchange power;

«—Microgrid local load demand power;

ρ. ^{(ί) the} total output power of a microgrid system;

feW-micro-grid self-balancing.

4. Microgrid self-balancing:

The self-equilibrium of the micro-grid refers to the ratio of the output power of the distributed power source and the energy storage device to the load demand power in the micro-grid; it is a characteristic value reflecting whether the output power of the micro-grid can meet the local load demand;

k _{it) =} o 0∑ (4)

P _L (t)

When fc(i)<l, it means that the output power of the microgrid cannot meet the local load demand, and the distribution network transmits the work to the microgrid. Rate, that is, purchase electricity from the distribution network; when fc(i) > l, indicating that the output power of the microgrid exceeds the local load demand, the microgrid delivers power to the distribution network, that is, sells electricity to the distribution network; fc(o = i, It means that the microgrid just meets the local load demand, and the microgrid grid-connected line exchange power is zero.

5. Microgrid self-smoothness:

The self-smoothness of the micro-grid 0 refers to the rate of change of the exchange power of the grid-connected line of the micro-grid; it is a characteristic value reflecting the exchange power fluctuation between the micro-grid and the distribution network;

,, dPj (0 , _c , sit) = ^^ (5)

Dt

When s(i) < 0, the exchange power of the grid connection of the micro grid is reduced, and the power time curve is downward; when s(i) > 0, the exchange power of the grid connection of the micro grid is increased, and the power time is The curve is tilted upwards; ί)=0, which is the power exchange of the microgrid grid-connected line, and the power curve is smooth.

(2) A control method for self-balancing and self-smoothing of the microgrid:

The core of the microgrid self-balancing and self-smoothing control method is the micro-grid self-balancing plan curve, _a „(o and self-smoothing plan limit. „Identification, and according to the self-equilibrium boundary curve ^^-^^ And the constraints of the self-smoothing boundary limits ^„>, s _max coordinate the distributed power supply, the energy storage device and the controllable load. The structure of the regional distribution network dispatching system is shown in Figure 1, where the network involved There is a regional distribution network and a microgrid, and the regional distribution network includes a regional distribution network dispatching system, a substation monitoring system, a power plant monitoring system, and a distributed power monitoring system; the microgrid includes a microgrid energy management system a microgrid central controller and a local controller; the substation monitoring system, the power plant monitoring system, the distributed power monitoring system, and the microgrid energy management system are respectively connected to the regional distribution network dispatching system; The energy management system, the microgrid central controller and the local controller are connected in sequence. The regional distribution network B receives a large number of distributed power sources and microgrids. The permeability is relatively high. The regional distribution network dispatching system is a superior system, responsible for the dispatching of substation monitoring systems, power plant monitoring systems, distributed power monitoring systems and microgrid energy management systems, substation monitoring systems, power plant monitoring systems, The distributed power monitoring system is responsible for monitoring and controlling the respective areas and reporting to the higher-level dispatching system; the micro-grid energy management system is responsible for the energy management and scheduling of the micro-grid, and the micro-grid central controller is responsible for executing the pre-programmed control method procedures. The local controller is responsible for the control of the local equipment.

The flow of the control method for the self-balancing and self-smoothing of the microgrid according to the present invention is as shown in FIG. 2, and the method includes the following steps:

Step 1: The microgrid energy management system develops a local load demand power forecast curve, a self-balancing plan curve, and a self-smoothing plan limit:

The microgrid energy management system combines peak and valley power regulation based on historical and real-time data to make local load short Forecasting, forming a local load demand power forecast curve (0; at the same time according to meteorological resource information, combined with intermittent distributed power supply characteristics, the output of intermittent distributed power supply is predicted; and according to factors such as power generation cost, market electricity price, etc. The power generation plan of the distributed power source and the charge and discharge plan of the energy storage device finally form a self-balancing plan _ta (o curve and self-smoothing plan limit ^ _a „, aiming at meeting the local load demand and power supply reliability while achieving economy Maximize benefits; Step 2: Determine whether the microgrid energy management system accepts regional distribution network dispatching system scheduling:

Determine whether the microgrid energy management system is associated with the regional distribution network dispatching system. If there is no association, proceed from step 2 to step 4, directly according to ^ _a „ (o and ^. „ coordinate control; if already, further judgment Whether it is necessary to coordinate interaction with the distribution network and accept the regional distribution network scheduling system scheduling; if it is not necessary to accept the scheduling, go from step 2 to step 4; if it is necessary to accept the scheduling, from step 2 to step 3;

Step 3: Report the self-balancing plan curve and the self-smoothing plan limit to the regional distribution network dispatching system: The micro-grid energy management system will calculate the local load demand power curve (0, micro-grid self-balancing plan curve k _plan ( And the self-smoothing plan limit _Spla „ ± passed to the regional ffi grid dispatching system;

Step 4: The regional distribution network dispatching system sets the self-equilibrium boundary curve and the self-smoothing boundary limit:

The regional distribution network dispatching system is based on the reported by the microgrid (0 ^^„ (0 and ^.„, combined with the substation monitoring system, power plant monitoring system, distributed power monitoring system, microgrid and load in the entire regional distribution network. Comprehensive information, considering the influence of power disturbance after distributed power supply and microgrid interconnection, develop self-equilibrium boundary curve ^„(0-^^(0 and self-smoothing boundary limit ^„ and ^ _, and return each Microgrid energy management system;

Step 5: The microgrid energy management system receives the self-equilibrium boundary curve and the self-smoothing boundary limit:

The microgrid energy management system receives the self-equilibrium boundary curve fc _mn (0 - k _max (0 and self-smoothing boundary limit)

^^ and ^ are passed to the central controller of the microgrid;

Step 6: The micro-grid central controller coordinates the distributed power supply, energy storage device and controllable load in the micro-grid: According to the logic control program and the self-equilibrium boundary curve of the micro-grid central controller ^(0 -^_ (0 and self-smoothing boundary limits ^ and ^, to perform coordinated control of distributed power, energy storage devices and controllable loads in the microgrid.

The coordinated control content of the distributed power source, the energy storage device and the controllable load in the microgrid is described in conjunction with FIG. 3, and the microgrid central controller divides the control of the microgrid into several cases according to the constraints of self-balancing and self-smoothing, and Perform the corresponding control operations for each case, as follows:

1) Comparing the real-time self-balancing of the microgrid with U) and when; when ≤ 0≤), it means that the output power of the microgrid is within the specified range (the specified range refers to ^^^), which can satisfy local or Remote load demand; when ^0 <^^ (0, it means that the microgrid output power can not meet the local or remote load demand, Need to increase the microgrid output power output or reduce the input controllable load; when wo > ^ _max (o, it means that the microgrid output power is greater than the local or remote load demand, it is necessary to reduce the microgrid output power or the input can be cut off Control load

2) Compare the absolute value of the real-time self-smoothness of the microgrid with ^„ and ^ _; when ^„≤^«|≤^_, it is considered that the microgrid grid-connected line exchange power fluctuation is small, and the exchange power curve is relatively smooth. When μ(ί)| < ^ _η , it is considered that the microgrid grid-connected line exchange power fluctuation is small, and the exchange curve is quite smooth, but the frequent adjustment damages the service life of the energy storage device, and the adjustment strength of the energy storage device can be reduced; When |^«| > ^_, it is considered that the microgrid grid-connected line exchange power fluctuates greatly, and the exchange power curve is not smooth enough. It is necessary to increase the regulation of the energy storage device to reduce the disturbance to the regional distribution network.

1. When one of the following conditions is met, it shall be the primary load:

1. Interruption of power supply will result in personal injury or death.

2. Interruption of power supply will cause significant political and economic losses. For example: Major equipment damage, major product scrapping, and the production of products made from important raw materials are largely scrapped. The continuous production process of key enterprises in the national economy is disrupted and it takes a long time to recover.

3. Interruption of power supply will affect the normal operation of power units with significant political and economic significance. For example: important transportation hubs, important communication hubs, important hotels, large stadiums, public places where large numbers of people are often used for international activities, and other important electrical loads in power units. In the primary load, the load that will be poisoned, exploded, and fired when the power supply is interrupted, and the load that is not allowed to interrupt the power supply in a particularly important place should be considered as a particularly important load.

2. When one of the following conditions is met, it shall be the secondary load:

1. Interruption of power supply will cause significant political and economic losses. For example: major equipment damage, a large number of products are scrapped, the continuous production process is disrupted, it takes a long time to recover, and a large number of key enterprises reduce production.

2. Interruption of power supply will affect the normal operation of important power units. For example, important power loads in power units such as transportation hubs and communication hubs, as well as power outages, will cause confusion in important public places where large theaters, large shopping malls, and other people are concentrated.

3. Those who do not belong to the primary and secondary loads shall be the tertiary load:

The primary load should be powered by two independent power sources.

Secondary load: The interruption of power supply to this type of load by the more important power load will result in a large number of industrial and agricultural production cuts, suspension of industrial and mining transportation, productivity decline, and significant impact on the normal life and business activities of the city. Generally, large-scale factory enterprises, research institutes, etc. are all secondary loads.

Tertiary load: Other electrical loads that do not fall into the first and second levels mentioned above, such as auxiliary enterprises, affiliated workshops, and unimportant electrical loads in certain non-productive locations.

Example 1 In order to make the technical solution of the present invention clearer, the embodiment of the present invention provides a structure diagram of a microgrid system containing wind and light storage as shown in FIG. 4, and the microgrid A mainly includes wind power generation, photovoltaic power generation, lithium battery pack, and micro Gas turbine, primary load, secondary load, tertiary load and reactive power compensation device. The microgrid A access area distribution network B is taken as an example, and the present invention is further described in detail with reference to the accompanying drawings and specific implementation procedures.

First, the energy management system of the microgrid A performs short-term prediction based on load historical data and real-time measurement data, and formulates a local load demand prediction curve (0; based on meteorological information, combined with wind power and photovoltaic power generation characteristics, makes short-term predictions for wind power and photovoltaic power generation; According to the market time-of-use electricity price and power generation cost, the micro-gas turbine power generation plan and the lithium battery pack charge and discharge plan are formulated; finally, the micro-grid self-balancing plan curve fc O and the self-smoothing plan limit are set to be planned at the electricity wave valley time 22:00 - At 8:00 the next day, purchase low-cost electricity from the regional distribution network B; sell high-priced electricity to the regional distribution network B during the peak hours of electricity consumption from 9:00-10:00 am and 17:00-22:00 pm .

The dispatching system of the regional distribution network B is based on the distributed power generation plan, the micro-grid self-balance plan curve and the self-smoothing plan limit reported in the region, after the accepted capacity calculation and system stability analysis, The microgrid as a controllable unit formulates its self-balancing boundary curve and self-smoothing plan limit, and then returns it to each microgrid energy management system in the form of dispatch instructions. The specification for microgrid A is to allow the range of self-equilibrium to fluctuate between ^ and (between 0 and ^, and the range of absolute values of self-smoothing fluctuates between ^ and ^ _.

The energy management system of the microgrid A receives the returned vessel (-k (and, s _max and passes it to the microgrid central controller. The microgrid central controller pairs the real-time self-equalization fc (0 and the absolute value of the self-smoothness) 0 is compared with the boundary range value, and the coordinated control of wind power, photovoltaic, micro gas turbine, lithium battery pack and controllable load is automatically performed according to the pre-programmed logic program. The real-time curve of self-equilibrium of micro-grid is shown in Fig. 5. Show.

Through the above steps, the self-balancing and self-smoothing control of the micro-grid is realized, and the disturbance of the intermittent renewable energy power fluctuation on the access area distribution network under high permeability is reduced, and the use of related equipment in the micro-grid is prolonged. The service life improves the power supply reliability of the local load of the microgrid, and obtains higher energy utilization rate and greater economic benefits.

Example 2

The invention has high applicability and can perform relatively flexible change adjustment. In order to make the technical solution of the present invention more flexible, the following description will be made by taking the above-mentioned micro grid A and regional distribution network B as an example:

First, the energy management system of the microgrid A performs short-term prediction based on load historical data and real-time measurement data, and formulates a local load demand prediction curve (0; based on meteorological information, combined with wind power and photovoltaic power generation characteristics, makes short-term predictions for wind power and photovoltaic power generation; According to the market time-of-use electricity price and power generation cost, the micro-gas turbine power generation plan and the lithium battery pack charge and discharge plan are formulated; finally, the self-equilibrium boundary curve of the micro-grid plan is formed ^^ ^W - ^^ ^W and the self-smoothing boundary limit ^S , , and reported to the regional distribution network B's dispatch management system, that is, it is planned to purchase low-cost electricity from the regional distribution network B from 22:00 to 8:00 on the electricity wave valley; 9:00-10:00, 17:00-22:00, sell high-priced electricity to the regional distribution network B.

The dispatching system of the regional distribution network B is based on the various distributed power generation plans, micro-grid self-equilibrium boundary curves and self-smoothing boundary limits reported in the region, after the accepted capacity calculation and system stability analysis, The microgrid as a controllable unit develops its own boundary limits and scheduling plans and then returns them to each microgrid energy management system. In the peak hours of electricity consumption from 17:00 to 22:00, the microgrid A is required to deliver electricity to the regional distribution network B according to the scheduling curve, and the self-smoothing scheduling limit for this period is ^^, . _maxl ; other time periods are in accordance with the boundary. Curve ^„(0 -^^(0 delivers or receives power, the self-smoothing scheduling limit is ^„ ₂ , s _max2 .

The energy management system of the microgrid A receives the returned scheduling instructions and passes them to the microgrid central controller. The microgrid central controller compares the real-time self-balancing wo and the absolute value of the self-smoothing with the given limits of the scheduling command, and automatically executes the wind, photovoltaic, micro gas turbine, lithium battery pack and according to the pre-programmed logic program. Coordinated control of controllable loads, etc.

It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the scope of the present invention. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand A person skilled in the art can still make various changes, modifications, or equivalents to the specific embodiments of the invention after reading the present invention. These modifications, modifications, and equivalents are all within the scope of the appended claims.

Claims

Rights request

A control method for self-balancing and self-smoothing of a microgrid, characterized in that the method comprises the following steps:

1 The microgrid energy management system formulates a local load demand power prediction curve, a self-balancing plan curve, and a self-leveling plan limit;

6 The micro-grid central controller performs coordinated control of the distributed power source, the energy storage device and the controllable load in the micro-grid.

2. The control method according to claim 1, wherein in the step 1: the microgrid energy management system formulates a local load demand power prediction curve (0, self-balance plan curve '.) ⁽ ° and Self-smoothing plan limit s _plan

3. The control method according to claim 1, wherein the step 2 comprises: determining whether the microgrid energy management system is associated with the regional distribution network scheduling system:

i. If there is no correlation, proceed from step 2 to step 6. According to the self-balance plan curve ^{k (t)} and the self-smoothing plan limit ^S developed by the micro-grid energy management system, the distributed power supply and energy storage in the micro-grid Coordinated control of the device and the controllable load;

Ii. If it is already associated, further determine whether the microgrid energy management system accepts the regional distribution network scheduling system scheduling:

a, if the regional distribution network scheduling system scheduling is not accepted, then proceed from step 2 to step 6;

b. If the schedule is accepted, the local load demand power prediction curve (0, self-balance plan curve ^ ^ (0 and self-smoothing plan limit ^. „ is uploaded to the regional distribution network dispatching system, ie from step 2 Go to step 3.

The control method according to claim 1, wherein in the step 4, the regional distribution network dispatching system predicts a curve according to a local load demand power reported by the microgrid energy management system (0, self-balance degree) Plan the curve k _≠an it) and the self-smoothing plan limit _s≠m , formulate the micro-grid self-equilibrium boundary curve ^ (0 - k (and the self-smoothing boundary value and return to the micro-grid) Energy management system.

The control method according to claim 1, wherein in the step 5, the microgrid energy management system receives the microgrid self-equilibrium boundary curve U) - k (0 and self-smoothness boundary Limit s _mn and pass to the _station The microgrid central controller.

The control method according to claim 1, wherein in the step 6, the micro-grid central controller is based on a self-balancing boundary curve (0 - k (0 and self-smoothing boundary limit) s _mn and coordinated control of distributed power supplies, energy storage devices and controllable loads in the microgrid.

The control method according to any one of claims 3 to 6, wherein the ^ is a lower limit of the self-equilibrium boundary curve; the ^ is an upper limit of the self-balancing boundary curve; It is the lower limit of the self-smoothing boundary limit; the ^_ is the upper limit of the self-smoothing boundary limit; the controllable load is the load of the tertiary load according to the degree of power surplus.

8. The control method according to claim 7, wherein the central controller of the microgrid performs coordinated control of the distributed power source, the energy storage device and the controllable load in the micro grid as follows:

1) Comparing the real-time self-equilibrium of the microgrid with ^ and ^; when u≤wo≤, the output power of the microgrid meets the load demand; when ^0<^^(0, the output power of the microgrid cannot meet the load Demand, increase microgrid output power output or reduce the input controllable load; when fc(0>^ _max (0, microgrid output power is greater than load demand, reduce microgrid output power or input cut controllable load) ;

2) Compare the absolute value of the real-time self-smoothness of the microgrid with ^„ and ^ _; when ^„≤^«|≤^_, it means that the microgrid grid-connected line exchange power output is stable, and the micro-grid is connected to the grid. The line switching power curve is smooth; when μωμ^^, the microgrid grid-connected line exchange power output is stable; when | 0|>^_, the regulation of the energy storage device is increased, and the disturbance to the regional distribution network is reduced. .

The control method according to any one of claims 1 to 8, wherein

I. The expression of the output power of the microgrid is as follows:

P _G (t) = ∑ P, (t) + X Ρ , {ί) + χ P _k (t)

(1); Its towel:

ρ. ( ^ί) a total output power of a microgrid;

ρ' ^(ί) — intermittent distributed power output power;

A controllable distributed power output power;

A ^w — charge and discharge power of the energy storage device;

II. The expression of the power demand of the microgrid is as follows:

P _L (0 = ∑ Pu (t + ∑ P _{2 )} (t + ∑ P, _k (( ^2); Its towel:

^P t, the total load demand power in a microgrid;

The power demand of the primary load in a microgrid;

P^ ^(t) a secondary load demand power in a microgrid;

p, a three-stage load demand power in a microgrid;

P _TL (t) = P _L (t) - P _G (t) = P _L (t) - k(t)P _L (t) ₍₃₎ .

- microgrid grid-connected line exchange power;

( ^ί ) a microgrid local load demand power;

Microgrid total output power;

feW-microgrid self-balancing;

IV. The self-equilibrium of the micro-grid fc (0 refers to the ratio of the output power of the distributed power source and the energy storage device to the load demand power in the micro-grid, fc (0 expression is as follows: k(t) = ^- (4) ; P _L it)

V. The self-smoothness of the micro-grid 0 refers to the rate of change of the exchange power of the grid connection of the micro-grid, and the expression is as follows: s(t) = ~ (5).

Dt