CN105976063A - Multi-target area multi-microgrid structure and capacity optimization planning method - Google Patents

Abstract

The invention relates to a multi-target area multi-microgrid structure and capacity optimization planning method. The method includes steps of obtaining the capacity and type of a load, the position, capacity, and type of a distributed power supply, a multi-microgrid network structure, and initialized data of energy storage position, and capacity, and type; setting the requirement values of networking flexibility, distributed energy consumption, and multi-energy comprehensive utilization target; obtaining a series of antibody populations that meet the value requirements of networking flexibility, distributed energy consumption and multi-energy utilization target; operating the antibody populations by means of an immune genetic algorithm; and outputting an economic and optimal area multi-microgrid structure and capacity planning method meeting the networking flexibility, distributed energy consumption, and multi-energy comprehensive utilization target. On the premise of guaranteeing the economy, the networking flexibility, distributed energy consumption capability, and multi-energy comprehensive utilization efficiency can be improved.

Description

A kind of multiobject region many microgrids structure and capacity Method for optimized planning

Technical field

The invention belongs to microgrid field, relate to a kind of region many microgrids structure and capacity Method for optimized planning.

Background technology

Renewable energy power generation with wind-powered electricity generation, photovoltaic as representative has bigger uncertainty owing to exerting oneself, and direct grid-connected is the most right The safe operation of electrical network and the reliable supply of electric power produce impact.The renewable energy power generation such as wind-powered electricity generation, photovoltaic and energy storage, load etc. The form coordinating composition microgrid accesses electrical network, then contribute to eliminating the probabilistic impact of renewable energy power generation, improve electrical network pair The digestion capability of regenerative resource.Meanwhile, microgrid can be incorporated into the power networks, again can when outside grid collapses islet operation, Thus continuous powerup issue to critical load under the conditions of bulk power grid has a power failure can be solved, improve power supply reliability.Microgrid above-mentioned Advantage makes it rapidly become study hotspot.Multiple microgrid, joining of each microgrid is had owing to may build in the most neighbouring region Put different with workload demand, by reasonably planning, microgrid interconnection is become the many micro-grid systems in region and runs that to will assist in raising whole The performance of individual system.

Summary of the invention

It is an object of the invention to as region many piconet networkings motility, distributed energy is dissolved and multipotency comprehensively utilizes multiobject rule Draw the structure and method for planning capacity providing a kind of economy optimum.Technical scheme is as follows:

A kind of multiobject region many microgrids structure and capacity Method for optimized planning, comprise the following steps:

1) collect local conventional illumination and wind data, it was predicted that local load condition, obtain and include that gas turbine parameter exists In related data, set up and comprise the distributed electrical source model of photovoltaic and wind-force and gas turbine, load forecasting model and Energy storage model.

2) according to capacity and the type of the load predicted, it was predicted that the position of distributed power source and capacity and type, further according to negative Lotus and distributed power source predict the network architecture of many microgrids, predict the position of energy storage according to load, distributed power source and the network architecture With capacity and type, obtain capacity and the type of load, the position of distributed power source and capacity and type, the net of many microgrids Network framework, the position of energy storage and capacity and the initialization data of type.

3) set networking flexibility, distributed energy is dissolved, the required value of multipotency comprehensive utilization target, and above-mentioned three kinds of targets are all It is that the index under respective target is obtained with the combination of certain weight ratio, wherein,

Networking flexibility target is the convenient, flexible networking for realizing many microgrids, embodies the optimization of microgrid structure and the target that proposes, bag Containing following two index:

(1) power of contact between each microgrid of many microgrid contact degree MCD: these index characterization, the contact degree of many microgrids is more Greatly, the contact between each microgrid is the strongest:

MCD=2n₁/n₂(n₂-1)

Wherein, n₁、n₂Represent the circuit number being joined directly together between microgrid and the number of microgrid respectively, between any two microgrid all When being joined directly together, the contact degree index of many microgrids is maximum and be 1, represents the contact between the most microgrids the most by force, any one Microgrid directly to the offer of other microgrids or can accept energy by a circuit；

(2) region many microgrids configuration flexibility index MSF: this index characterization degree of flexibility of region many microgrids structure, score value The highest, the structure representing the many microgrids in region is the most flexible:

MSF=(100*n₁+90*n₂+80*n₃)/(n₁+n₂+n₃+n₄)

Wherein, n₁、n₂、n₃、n₄Represent the number of the many microgrids of block form, nested type, tandem, distributing respectively, 100, 90,80,0 is block form, nested type, tandem, the scoring of the many microgrids of distributing respectively, and 100 points is full marks.

Both indexs are combined, obtain networking flexibility target.

4) consider that the cost of the distributed energy of environmental benefit and energy storage device and switch includes distributed energy, energy storage, quiet The investment of state switch and operation expense, realize above-mentioned 3 groups of targets with minimum investment, i.e. realize the economic optimum of many microgrids；

5) networking flexibility of calculating antibody population, distributed energy dissolve, multipotency comprehensive utilization target and distributed energy With energy storage device and the economy of switch.

6) be met networking flexibility, distributed energy is dissolved, a series of antibody population of multipotency comprehensive utilization desired value； If be unsatisfactory for networking flexibility, distributed energy is dissolved, multipotency comprehensive utilization desired value, then reselect antibody population, then Return to step 4.

7) judge whether to meet stop condition, as being unsatisfactory for, then use immune genetic algorithm antagonist population to operate, so After return to step 4.

8) meeting stop condition, output meets networking flexibility, distributed energy is dissolved and multipotency comprehensive utilization mesh target area The economy optimum programming method of many microgrids structure and capacity.

The present invention proposes using networking flexibility, distributed energy is dissolved and multipotency comprehensive utilization is as optimizing sub-goal, with economy As optimizing major heading, use structure and the capacity multi-objection optimization planning method of the many microgrids in region of immune genetic algorithm, by region The optimization planning problem of many microgrids is regarded structure optimization and capacity as and is optimized two sub-optimization problems, and with networking flexibility, distributed Energy consumption and multipotency comprehensive utilization are optimized planning as the multiple objective function optimized, structure and capacity to many microgrids, To the planing method that economy is optimum, the method on the premise of ensureing economy, can improve the many microgrids in region networking flexibility, Distributed energy digestion capability and multipotency comprehensive utilization ratio.

Accompanying drawing explanation

Fig. 1 many microgrids based on immune genetic algorithm structure and capacity planning Optimizing Flow.

Detailed description of the invention

Below in conjunction with accompanying drawing 1 and detailed description of the invention to the present invention dissolving with networking flexibility, distributed energy and multipotency is comprehensive The economy optimum programming method being utilized as mesh target area many microgrids structure and capacity carries out detailed narration.

The technical solution used in the present invention includes many microgrids open space planning, the object of planning, specific as follows:

1. the open space planning of microgrid more than includes that structure optimization and capacity optimize 2 parts, is respectively described below:

1) structure optimization

Structure optimization mainly includes topological structure optimization and many microgrids topological structure optimization two parts in microgrid.Topological structure in microgrid Optimize the immune genetic algorithm proposed mainly by the present invention and the position of distributed energy in microgrid and energy storage carried out plan optimization, Its target be in microgrid distributed energy dissolve, multipotency comprehensive utilization and the multiobjective optimization of economy composition；Many microgrids topology Structure optimization mainly by the reasonable disposition of switch and energy storage etc., promotes the raising of the networking flexibility of many microgrids, on this Realize the overall economy of many microgrids optimum.

2) capacity optimization

Capacity optimization provides the capacity of the gas turbine of cold, heat and electricity triple supply to distribute rationally in mainly including many microgrids, photovoltaic, wind-force Distribute rationally Deng the capacity providing the distributed power source capacity of electric energy to distribute rationally with energy storage.In microgrid and two aspects of many microgrids, The object of planning of the distributed energy capacity comprising gas turbine and photovoltaic, wind-force is all in distributed energy permeability and many Can comprehensive utilization ratio the highest under conditions of improve in microgrid or economy that many microgrids are overall, and the mesh of the capacity planning of energy storage Mark then mainly reduces the uncertainty of distributed energy so that the smooth output of distributed energy.

2. the planning of microgrid more than be considered as one comprise networking flexibility, distributed energy dissolve and multipotency comprehensive utilization multiple-objection optimization Planning problem.It mainly includes following target:

1) networking flexibility target

Networking flexibility target is the convenient, flexible networking in order to realize many microgrids, embodies the optimization of microgrid structure and the target that proposes. Many microgrids are the most flexible, then its alternative method of operation is the most, more can meet the differentiated demand of different user.Main bag Containing following two index:

(1) many microgrid contact degree (Multi-microgrid Connection Degree；MCD): this index characterization is each micro- The power of contact between net, the contact degree of many microgrids is the biggest, and the contact between each microgrid is the strongest.

MCD=2n₁/n₂(n₂-1) (1)

Wherein, n₁、n₂Represent the circuit number being joined directly together between microgrid and the number of microgrid respectively.Between any two microgrid all When being joined directly together, the contact degree index of many microgrids is maximum and be 1, represents the contact between the most microgrids the most by force, any one Microgrid directly to the offer of other microgrids or can accept energy by a circuit.

(2) region many microgrids configuration flexibility index (Multi-microgrid Structure Flexibility；MSF): this index Characterize the degree of flexibility of region many microgrids structure.Score value is the highest, and the structure representing the many microgrids in region is the most flexible.

MSF=(100*n₁+90*n₂+80*n₃)/(n₁+n₂+n₃+n₄) (2)

Wherein, n₁、n₂、n₃、n₄Represent the number of the many microgrids of block form, nested type, tandem, distributing respectively, 100, 90,80,0 is block form, nested type, tandem, the scoring of the many microgrids of distributing respectively, and 100 points is full marks.According to above-mentioned The result obtained by many microgrid contact degree metrics evaluation, the structure of the many microgrids of block form is the most flexible, therefore gives and divide 100,；Nested type is many The motility of microgrid structure is taken second place, therefore gives and divide 90；Third the motility of tandem many microgrids structure, therefore is given and is divided 80；And disperse The motility of formula many microgrids structure is worst, almost without, therefore give and divide 0.

2) distributed energy is dissolved target

Distributed energy target of dissolving is divided into microgrid and many microgrids two class target, comprises following six index altogether:

(1) microgrid distributed energy is used by oneself rate (Microgrid Distributed Energy Microgrid-load Consumption Rate；MDEMCR), this index describes the energy that microgrid autophage distributed power source sends and accounts in microgrid The ratio of the energy that distributed power source sends.

$MDEMCR=({\∫}_{t=0}^{t=8760}{P}_g\left(t\right)dt-{\∫}_{t=0}^{t=8760}{P}_i(t\left)dt\right)/{\∫}_{t=0}^{t=8760}{P}_g\left(t\right)dt---\left(3\right)$

Wherein, P_iT () is the output of microgrid, P_gT () is generated output total in microgrid, this index is obtained by prediction, if its Be worth the biggest, illustrate that the degree that microgrid is generated power for their own use is the highest, can be or need other microgrids provide energy requirement the lowest.

(2) micro-grid distributed generation and load capacity ratio (Microgrid Distributed Generation and Load Capacity Rate；MDGLCR), the rated capacity of distributed power source and the ratio of rated load in this index describes microgrid.

$MDGLCR=\underset{i=1}{\overset{n}{\Σ}}{P}_{Gi}/\underset{j=1}{\overset{m}{\Σ}}{P}_{Lj}---\left(4\right)$

Wherein, P_GiAnd P_LjRepresent i-th distributed power source and the rated power of jth load in microgrid respectively.

(3) microgrid energy storage and distributed power source Capacity Ratio (Microgrid Energy Storage and Distributed Generation Capacity Rate；MESDGCR), in this index describes microgrid, the rated capacity of energy storage accounts for distributed power source The ratio of rated capacity.

$MESDGCR=\underset{i=1}{\overset{n}{\Σ}}{P}_{Si}/\underset{j=1}{\overset{m}{\Σ}}{P}_{Gj}---\left(5\right)$

Wherein, P_SiAnd P_GjRepresent i-th energy storage and the rated power of jth distributed power source in microgrid respectively.This index is the biggest, Then in microgrid energy storage rated capacity to account for the value of distributed power source rated capacity the biggest, more can make the smooth output of distributed power source, but phase The economy answered is the poorest.

(4) many microgrids overall distribution formula energy is used by oneself rate (Multi-microgrid Whole Distributed Energy Microgrid-load Consumption Rate；MWDEMCR), this index describes many microgrids autophage distributed power source and sends out The energy gone out accounts for the ratio of the energy that distributed power source in many microgrids sends.

$MWDEMCR=({\∫}_{t=0}^{t=8760}\underset{i=1}{\overset{i=n}{\Σ}}{P}_{ig}\left(t\right)dt-{\∫}_{t=0}^{t=8760}P(t\left)dt\right)/{\∫}_{t=0}^{t=8760}\underset{i=1}{\overset{i=n}{\Σ}}{P}_{ig}\left(t\right)dt---\left(6\right)$

P_igT () and P (t) represent total generated output and the output of many microgrids in i-th microgrid respectively.This index is by recording in advance Arrive, if its value is the biggest, illustrate that the degree that many microgrids are generated power for their own use is the highest.

(5) many microgrids overall distribution formula power supply and load capacity ratio (Multi-microgrid Whole Distributed Generation and Load Capacity Rate；MWDGLCR), the specified appearance of distributed power source in this index describes many microgrids Amount and the ratio of rated load.

$MWDGLCR=\frac{\mathrm{\Σ}\left({\mathrm{\ΣP}}_{Gij}\right)}{\mathrm{\Σ}\left({\mathrm{\ΣP}}_{Lmn}\right)}---\left(7\right)$

Wherein, P_GijAnd P_LmnRepresent in i-th microgrid the n-th load in jth distributed power source and m-th microgrid respectively Rated power.

(6) energy storage of many microgrids entirety and distributed power source Capacity Ratio (Multi-microgrid Whole Energy Storage and Distributed Generation Capacity Rate；MWESDGCR), in this index describes many microgrids, the rated capacity of energy storage accounts for The ratio of the rated capacity of distributed power source.

$MWESDGCR=\frac{\mathrm{\Σ}\left({\mathrm{\ΣP}}_{Sij}\right)}{\mathrm{\Σ}\left({\mathrm{\ΣP}}_{Gmn}\right)}---\left(8\right)$

Wherein, P_SijAnd P_GmnRepresent in i-th microgrid the n-th distributed power source in jth energy storage and m-th microgrid respectively Rated power.This index is the biggest, and in the most microgrids, to account for the value of distributed power source rated capacity the biggest for energy storage rated capacity, more can make The smooth output of distributed power source, but corresponding economy is the poorest, can improve the economy of many microgrids by sharing energy storage between microgrid.

3) multipotency comprehensive utilization target

Multipotency comprehensive utilization target mainly comprises three kinds of indexs, as follows:

(1) renewable energy power generation permeability (Renewable Energy Penetration；REP).This index is in microgrid The average generated energy of regenerative resource accounts for the percentage ratio of average load total demand.

In formula: P_RΣT () is to consider that DG fault and microgrid run under constraints, certain class or all can be again in t microgrid The output sum (kW) of raw energy DG, PL (t) is t microgrid load total amount (kW).This index reflects energy In the utilization of source, regenerative resource accounts for the ratio of total energy.

(2) many microgrids electricity/hot charging machine capacity ratio (Multi-microgrid Electrical/Thermal Capacity Ratio； METCR), the ratio of electricity/hot installed capacity in the many microgrids of assessment area.

$METCR=\frac{{\mathrm{\ΣP}}_{ec}}{{\mathrm{\ΣP}}_{tc}}---\left(10\right)$

In formula: P_ecPower for all microgrids total rated power of unit；P_tcRated power for all thermal power plant unit；This index is anti- Reflect the relative size relation of different types of energy in utilization of energy, describe the level of electric heating comprehensive utilization.

(3) region many microgrids comprehensive energy efficiency index (Regional Multi-microgrid Comprehensive Energy Efficiency Index；RMCEEI), this index describes the efficiency of energy utilization that the many microgrids in region comprise cool and thermal power.

$RMCEEI=\frac{{\mathrm{\ΣE}}_L}{{\mathrm{\ΣE}}_G}---\left(11\right)$

In formula: E_LAnd E_GIt is illustrated respectively in energy that all of load in a certain many microgrids of typical period of time inner region consumes and all of The energy (comprising three kinds of energy of cool and thermal power) that unit sends.This index reflects the efficiency of multipotency comprehensive utilization.

The present invention needs to realize on the premise of meeting certain constraints, realizes above-mentioned 3 groups of targets with minimum investment, i.e. Realize the economic optimum of many microgrids.Consider that the distributed energy of environmental benefit and the cost of energy storage device and switch include distributed The energy, energy storage, the investment of static switch and operation expense.It is expressed as follows:

$G\left(X\right)=\underset{i=1}{\overset{N_T}{\Σ}}{N}_i\·(C_{AI,i}+C_{M,i})---\left(12\right)$

In formula: N_TFor device type sum, N_iIt is the quantity of the i-th kind equipment, C_{AI, i}With C_{M, i}The investment being respectively equipment i becomes It is worth this year and year operation and maintenance cost.

The cost of investment year value of equipment is relevant with the initial outlay cost of equipment and service life, is represented by

$C_{AI,i}=C_i\·\frac{{(1+\mathrm{\γ})}^{T_i}\·\mathrm{\γ}}{{(1+\mathrm{\γ})}^{T_i}-1}---\left(13\right)$

In formula: C_i、T_iBeing unit cost and the service life of the i-th kind equipment, γ is discount rate.

It is considered herein that the annual operation expense of equipment is directly proportional to cost of investment year value, be represented by

C_M,i=C_AI,i·η_i (14)

In formula: η_iBe i-th kind equipment year operation and maintenance cost with cost of investment year value proportionality coefficient.

Technical scheme may be summarized to be:

1) collecting local conventional illumination and wind data, it was predicted that local load condition, the parameter etc. obtaining gas turbine is correlated with Data.Set up the model of the distributed power source comprising photovoltaic and wind-force and gas turbine, set up the forecast model of load, Set up the model of energy storage.

2) according to capacity and the type of the load predicted, it was predicted that the position of distributed power source and capacity and type, further according to load With the network architecture that distributed power source predicts many microgrids, predict the position of energy storage finally according to load, distributed power source and the network architecture Put and capacity and type, obtain capacity and the type of load, the position of distributed power source and capacity and type, many microgrids The network architecture, the position of energy storage and capacity and the initialization data of type.

3) set networking flexibility, distributed energy is dissolved, the required value of multipotency comprehensive utilization target, and above-mentioned three kinds of targets are all Index under respective target is obtained with the combination of certain weight ratio.

4) networking flexibility of calculating antibody population, distributed energy dissolve, multipotency comprehensive utilization target and distributed energy and Energy storage device and the economy of switch.

5) be met networking flexibility, distributed energy is dissolved, a series of antibody population of multipotency comprehensive utilization desired value；If Be unsatisfactory for networking flexibility, distributed energy is dissolved, multipotency comprehensive utilization desired value, then reselect antibody population, then return To step 4.

6) judge whether to meet stop condition, as being unsatisfactory for, then use immune genetic algorithm antagonist population to operate, then Return to step 4.

7) meeting stop condition, output meets networking flexibility, distributed energy is dissolved and multipotency comprehensive utilization mesh target area is many The economy optimum programming method of microgrid structure and capacity.

As a example by the demonstration system of animation garden, Tianjin, animation garden is respectively built and carries out load prediction, wherein electric load prediction case For main building 3963kW, 02-01 building 1645kW, 02-02 building 2259kW, 02-03 building 2314kW, wherein bear for two grades Lotus capacity is about 3978kW, and three stage load capacity are about 136.5kW, and pure fire fighting burthen installed capacity is about 16.5kW；Heat is negative Lotus prediction case is main building 3509kW, 02-01 building 1886kW, 02-02 building 2006kW, 02-03 building 2342kW； Cooling load prediction situation is main building 5055kW, 02-01 building 2717kW, 02-02 building 2889kW, 02-03 building 3374kW. Obtain programme as shown in table 1 below:

Animation garden, table 1 Tianjin demonstration system programme

Illustrate: the 400kWh of animation garden main building shares with animation garden energy source station.

Claims (1)

1. multiobject region many microgrids structure and a capacity Method for optimized planning, comprise the following steps:

1) collect local conventional illumination and wind data, it was predicted that local load condition, obtain the related data including gas turbine parameter, Set up the distributed electrical source model comprising photovoltaic and wind-force and gas turbine, load forecasting model and energy storage model.

2) according to capacity and the type of the load predicted, it was predicted that the position of distributed power source and capacity and type, further according to load and distributed electrical The network architecture of many microgrids is predicted in source, according to load, distributed power source and the position of network architecture prediction energy storage and capacity and type, obtains load Capacity and type, the position of distributed power source and capacity and type, the network architecture of many microgrids, the position of energy storage and capacity and type at the beginning of Beginningization data；

3) set networking flexibility, distributed energy is dissolved, the required value of multipotency comprehensive utilization target, and above-mentioned three kinds of targets are all by respective target Under index with certain weight ratio combination obtain, wherein,

Networking flexibility target is the convenient, flexible networking for realizing many microgrids, embodies the optimization of microgrid structure and the target that proposes, comprises following two and refer to Mark:

(1) power of contact between each microgrid of many microgrid contact degree MCD: these index characterization, the contact degree of many microgrids is the biggest, each microgrid Between contact the strongest:

MCD=2n₁/n₂(n₂-1)

Wherein, n₁、n₂Represent the circuit number being joined directly together between microgrid and the number of microgrid respectively, when being all joined directly together between any two microgrid, The contact degree index of many microgrids is maximum and be 1, represents that the contact between the most microgrids is the strongest, and any one microgrid directly can pass through one Circuit provides to other microgrids or accepts energy；

(2) region many microgrids configuration flexibility index MSF: this index characterization degree of flexibility of region many microgrids structure, score value is the highest, represents The structure of the many microgrids in region is the most flexible:

MSF=(100*n₁+90*n₂+80*n₃)/(n₁+n₂+n₃+n₄)

Wherein, n₁、n₂、n₃、n₄Represent the number of the many microgrids of block form, nested type, tandem, distributing respectively, 100,90,80,0 point Not being block form, nested type, tandem, the scoring of the many microgrids of distributing, 100 points is full marks；

Both indexs are combined, obtain networking flexibility target；

4) consider that the distributed energy of environmental benefit and the cost of energy storage device and switch include the investment of distributed energy, energy storage, static switch And operation expense, realize above-mentioned 3 groups of targets with minimum investment, i.e. realize the economic optimum of many microgrids；

5) networking flexibility of calculating antibody population, distributed energy dissolve, multipotency comprehensive utilization target and distributed energy and energy storage device with And the economy of switch；

6) be met networking flexibility, distributed energy is dissolved, a series of antibody population of multipotency comprehensive utilization desired value；If being unsatisfactory for networking Motility, distributed energy are dissolved, multipotency comprehensive utilization desired value, then reselect antibody population, be then return to step 4；

7) judge whether to meet stop condition, as being unsatisfactory for, then use immune genetic algorithm antagonist population to operate, be then return to step 4；

8) meet stop condition, output meet networking flexibility, distributed energy dissolve and multipotency comprehensive utilization mesh target area many microgrids structure and The economy optimum programming method of capacity.