CN104935004A - Multi-micro-grid polymerization coordination optimization operation method based on panorama theory - Google Patents

Abstract

The invention provides a multi-micro-grid polymerization coordination optimization operation method based on a panorama theory. The multi-micro-grid polymerization coordination optimization operation method comprises steps of 1) analyzing the structure of the micro-grid, collecting power supply parameters and generating information of each micro-grid and the electricity usage information of a load, 2) defining a panorama theory scale and a matching degree parameter through different distribution type power supply complementarity, and constructing a panorama energy function, 3) calculating and determining multi-micro-grid polymerization mode through the panorama polymerization mode, 4) constructing a multi-micro-grid coordination operation scheduling model, and 5) substituting the power supply information, the load information and the multi-micro-grid polymerization mode which are obtained through the step 1) and the step 3) into the multi-micro-grid coordination operation scheduling model which is constructed through the step 4) and adopting an optimized algorithm to solve, and 6) performing safety verification and coordination operation according to the obtained scheduling plan by the all micro-grids. Compared with the prior art, the multi-micro-grid polymerization coordination optimization operation method based on the panorama theory can effectively optimize and manage the operation of the multi-micro-grid and improves the system stability while guaranteeing the economy of the micro-grid.

Description

Based on many microgrid polymerization coordination optimization operation methods of panorama theory

Technical field

The present invention relates to polymerization coordinated operation method and technology field, particularly, relate to a kind of many microgrid polymerization coordination optimization operation methods based on panorama theory.

Background technology

Along with global energy environmental problem highlights day by day, make the cry of clean energy resource and renewable energy utilization day by day surging, microgrid provides effective means for solution renewable energy utilization, comprise the clean reproducible energy such as wind-powered electricity generation, photovoltaic cell, add power supply flexibility, enriched traditional power system operating mode, access operation of power networks can realize energy-saving and emission-reduction, reduces system losses and improves power supply reliability and flexibility.Its tactic pattern can connect and compose by multiple microgrid, final formation many micro-capacitance sensor intelligent grid.Future is popularized gradually at many microgrids, and when occupying grid generation and power supply significant proportion, the coordinated operation pattern between the energy-optimised management of microgrid self, multiple microgrid will become the theory and practical problem that must study.

It is target with economy that traditional Economic Dispatch runs general, or comprehensive as target function using economy and loss minimization etc.And in microgrid, dispatcher also needs environment of interest benefit, and ensure that actual power meets higher level's dispatching of power netwoks instruction as far as possible, reduce to exert oneself fluctuation.Therefore, consider from the angle of scheduling and more meet the dispatching requirement of microgrid in conjunction with multiple optimizing operation target.

The microgrid modality for co-operation determined generally is considered in many microgrids coordinated operation in past, does not consider which kind of microgrid aggregation scheme is best from basic.And when many microgrids have some, dispatcher also needs the polymerization coordinated operation pattern being concerned about microgrid.Therefore, consider that coordinated operation pattern more meets many microgrids and optimizes demand from many microgrids concrete aggregation scheme angle.

Summary of the invention

For the above-mentioned defect existed in prior art, the object of this invention is to provide a kind of many microgrid polymerization coordination optimization operation methods based on panorama theory.

For achieving the above object, the present invention is achieved by the following technical solutions.

Based on many microgrid polymerization coordination optimization operation methods of panorama theory, comprise the following steps:

Step 1: analyze microgrid structure, gather power parameter and the generating information of distributed power source in each microgrid, and the power information of load;

Step 2: complementary by different distributions formula power supply, the theoretical scale of definition panorama and matching degree parameter, structure panorama energy function;

Step 3: determine many microgrids aggregation scheme by panorama energy balane;

Step 4: construct many microgrids coordinated operation scheduling model;

Step 5: the power information of the power parameter of the power supply obtained in step 1 and step 3 and generating information, load and many microgrids aggregation scheme are substituting in many microgrids coordinated operation scheduling model that step 4 constructs, adopt optimized algorithm to solve, obtain operation plan;

Step 6: each microgrid carries out security verification according to gained operation plan, if met the demands, then carries out coordinated operation according to operation plan; If do not met the demands, then re-execute step 3 to step 5, redefine many microgrids aggregation scheme and be optimized, until meet the demands.

Preferably, in described step 2, by panorama theoretical origin in many micro-grid systems, define the theoretical scale of panorama and matching degree parameter by different distributions formula power supply complementarity, structure panorama energy function, expression formula E _i(X) be:

$E_i\left(X\right)=\underset{i,j}{\mathrm{\Σ}}{s}_i{s}_j{p}_{\mathrm{ij}}{d}_{\mathrm{ij}}\left(X\right)$

In formula, s _ithe large small-scale of i-th microgrid, s _jthe large small-scale of a jth microgrid, p _ijbe i-th microgrid to the matching degree of a jth microgrid, d _ij(X) be i-th microgrid and the distance of a jth microgrid in grouping model X.

Preferably, in described step 3, be the best aggregation scheme of many microgrids by the panorama energy balane grouping model of trying to achieve corresponding to panorama minimum energy point, concrete steps are as follows:

Step 3.1, stochastic generation grouping model X, calculates ENERGY E (X);

Step 3.2, generates all the other grouping models that grouping model X can reach, and calculates energy, selects the grouping model with least energy to be designated as Y;

Step 3.3, if the ENERGY E of grouping model X (X) is greater than the ENERGY E (Y) of grouping model Y, then another X=Y, returns step 3.2; Otherwise, grouping model X is added least energy list;

Step 3.4, repeats step 3.2 to step 3.3, until all grouping models are all analyzed complete.

Preferably, in described step 4, many microgrids coordinated operation scheduling model concrete steps of structure are:

Step 4.1, builds optimization aim: the target function setting up fail safe and economy, is embodied in target function using major network tie point power fluctuation as punishment cost;

Step 4.2, builds constraints, comprising: the constraint of system power Constraints of Equilibrium, distributed power source power output, miniature gas turbine Climing constant and tie-line power transmission constraint.

Preferably, in described step 5, the optimized algorithm of use is Sequential Quadratic Programming method or genetic algorithm.

Compared with prior art, the present invention has following beneficial effect:

1, panorama theory is applied in the operation of many microgrids polymerization coordination optimization by the present invention, many microgrids polymerization operational mode is determined by panorama energy function, set up the microgrid energy Optimized model considering major network tie point power fluctuation on this basis, determine many microgrids optimal scheduling plan.

2, the present invention can determine the polymerization operational mode of many microgrids the best; Major network tie point power fluctuation can be reduced; Elevator system fail safe while can realizing the economical operation of many microgrids.

3, the present invention effectively optimizes and manages the operation of many microgrids, while guarantee microgrid economy, improve the stability of a system.

Accompanying drawing explanation

By reading the detailed description done non-limiting example with reference to the following drawings, other features, objects and advantages of the present invention will become more obvious:

Fig. 1 is the process principle figure of the many microgrid polymerization coordination optimization operation methods that the present invention is based on panorama theory.

Embodiment

Below embodiments of the invention are elaborated: the present embodiment is implemented under premised on technical solution of the present invention, give detailed execution mode and concrete operating process.It should be pointed out that to those skilled in the art, without departing from the inventive concept of the premise, can also make some distortion and improvement, these all belong to protection scope of the present invention.

Embodiment

Present embodiments provide a kind of many microgrid polymerization coordination optimization operation methods based on panorama theory, comprise the following steps:

Step 1: analyze microgrid structure, gather power parameter and the generating information of distributed power source in each microgrid, and the power information of load;

Step 2: complementary by different distributions formula power supply, the theoretical scale of definition panorama and matching degree parameter, structure panorama energy function;

Step 3: determine many microgrids aggregation scheme by panorama energy balane;

Step 4: construct many microgrids coordinated operation scheduling model;

Step 5: the power information of the power parameter of the power supply obtained in step 1 and step 3 and generating information, load and many microgrids aggregation scheme are substituting in many microgrids coordinated operation scheduling model that step 4 constructs, adopt optimized algorithm to solve, obtain operation plan;

Step 6: each microgrid carries out security verification according to gained operation plan, if met the demands, then carries out coordinated operation according to operation plan; If do not met the demands, then re-execute step 3 to step 5, redefine many microgrids aggregation scheme and be optimized, until meet the demands.

Further, in described step 2, by panorama theoretical origin in many micro-grid systems, define the theoretical scale of panorama and matching degree parameter by different distributions formula power supply complementarity, structure panorama energy function, expression formula E _i(X) be:

$E_i\left(X\right)=\underset{i,j}{\mathrm{\Σ}}{s}_i{s}_j{p}_{\mathrm{ij}}{d}_{\mathrm{ij}}\left(X\right)$

In formula, s _ithe large small-scale of i-th microgrid, s _jthe large small-scale of a jth microgrid, p _ijbe i-th microgrid to the matching degree of a jth microgrid, d _ij(X) be i-th microgrid and the distance of a jth microgrid in grouping model X.

Further, in described step 3, be the best aggregation scheme of many microgrids by the panorama energy balane grouping model of trying to achieve corresponding to panorama minimum energy point, concrete steps are as follows:

Step 3.1, stochastic generation grouping model X, calculates ENERGY E (X);

Step 3.2, generates all the other grouping models that grouping model X can reach, and calculates energy, selects the grouping model with least energy to be designated as Y;

Step 3.3, if the ENERGY E of grouping model X (X) is greater than the ENERGY E (Y) of grouping model Y, then another X=Y, returns step 3.2; Otherwise, grouping model X is added least energy list;

Step 3.4, repeats step 3.3, until all grouping models are all analyzed complete.

Further, in described step 4, many microgrids coordinated operation scheduling model concrete steps of structure are:

Step 4.1, builds optimization aim: the target function setting up fail safe and economy, is embodied in target function using major network tie point power fluctuation as punishment cost;

Step 4.2, builds constraints, comprising: the constraint of system power Constraints of Equilibrium, distributed power source power output, miniature gas turbine Climing constant and tie-line power transmission constraint.

Further, in described step 5, the optimized algorithm of use is Sequential Quadratic Programming method or genetic algorithm.

Below in conjunction with accompanying drawing, the present embodiment is further described.

As shown in Figure 1, it is the process principle figure of the many microgrid polymerization coordination optimization operation methods that the present invention is based on panorama theory, and concrete steps are as follows:

1, data acquisition

Analyze microgrid structure, gather power parameter and the generating information of distributed power source in each microgrid, and the power information of load.

2, panorama energy function is set up

Complementary by different distributions formula power supply, the theoretical scale of definition panorama and matching degree parameter, structure panorama energy function, concrete grammar is:

Suppose F _i=1,2 ..., q ..., m _iand F _j=1,2 ..., r ..., m _jrepresent the DGs kind of two microgrids and number situation.To r ∈ F _j, definition s _ir (), for r is to the attraction of i, computational methods are as follows:

$s_i\left(r\right)=\underset{q=1}{\overset{m_i}{\mathrm{\Σ}}}{s}_q\left(r\right)$

Wherein

$s_q\left(r\right)=\left\{\begin{array}{c}-1,r=q\\ +1,r\≠q\end{array}\right.$

The meaning of above formula is: embody DG complementarity when DG is different, have s _qr there is randomness and expand further and cause microgrid to exert oneself the possibility of more great fluctuation process in () > 0, DG, makes s time identical _q(r) < 0.In concrete condition, according to the attribute of each DGs of microgrid, the randomness impact of such as PV, WT is comparatively large, s _qr the definition of () can be more more complex than above formula.

Microgrid as member, s _ifor the scale of microgrid i, determined by DGs capacity summation in microgrid.Microgrid i, the matching degree p between j _ijbe defined as follows:

$p_{\mathrm{ij}}=\underset{r=1}{\overset{m_j}{\mathrm{\&Sigma;}}}{s}_i\left(r\right)/m_i$

By above-mentioned parameter, structure panorama energy function, expression formula is:

$E_i\left(X\right)=\underset{i,j}{\mathrm{\&Sigma;}}{s}_i{s}_j{p}_{\mathrm{ij}}{d}_{\mathrm{ij}}\left(X\right)$

In formula, d _ij(X) be the distance of i and j in grouping model X.

3, many microgrids aggregation scheme is determined

Be the best aggregation scheme of many microgrids by calculating the grouping model of trying to achieve corresponding to panorama minimum energy point, concrete steps are as follows:

(1) stochastic generation grouping model X, calculates ENERGY E (X).

(2) generate all the other grouping models that all X can reach, calculate energy, select the model with least energy to be designated as Y.

(3) if E (X) > E (Y), then another X=Y, returns (2); Otherwise, X is added least energy list.

(4) above-mentioned steps is repeated until all grouping models are all analyzed complete.

4, many microgrids coordinated operation scheduling model is set up

(1) target function is set up

min F＝C _fuel+C _OM+C _DEP-I _SE+C _PCC

Wherein:

$C_{\mathrm{fuel}}={\&Integral;}_0^T\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{K}_{\mathrm{fueli}}{P}_{\mathrm{it}}\mathrm{dt}$

$C_{\mathrm{OM}}={\&Integral;}_0^T\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{K}_{\mathrm{OMi}}{P}_{\mathrm{it}}\mathrm{dt}$

$C_{\mathrm{DEP}}={\&Integral;}_0^T\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}\left(\frac{r{(1+r)}^n}{{(1+r)}^n}\right)\left(\frac{C_{\mathrm{inv},i}}{8760k}\right)P_{\mathrm{it}}\mathrm{dt}$

$I_{\mathrm{SE}}={\&Integral;}_0^T{c}_{\mathrm{st}}{P}_{\mathrm{pcct}}\mathrm{dt}$

$C_{\mathrm{pcc}}={\&Integral;}_0^T{c}_{\mathrm{vio}}{(P_{\mathrm{pcct}}-P_{\mathrm{pcc}})}^2\mathrm{dt}$

In formula: C _fuelfor micro-grid system fuel cost; C _oMfor the operation expense of micro-grid system; C _dEPfor each DG of micro-grid system installs depreciable cost; I _sEfor microgrid is to major network sale of electricity income; C _pccfor PCC place penalty cost; P _itfor DG _iactive power when t exports, K _fuelifor DG _iunit of fuel cost, K _oMifor DG _iunit operation expense, C _{inv, i}for DG _iinstallation cost Average Annual Cost; R is allowance for depreciation; K is average size coefficient, k=annual energy output/(8760* system nominal power); N is DG useful life; P _pcctfor the mutual power of reality of microgrid and major network; c _stfor microgrid is to major network sale of electricity electricity price; P _pccfor the optimizing power of dispatching of power netwoks microgrid, c _viofor the unit penalty cost at PCC place.

(2) constraints is set

Power-balance retrains:

P _loadt＝∑P _it-P _pcct

In formula: P _loadtfor the burden with power that t microgrid is total; ∑ P _itfor DG all in t microgrid exert oneself sum.

DG units limits:

P _imin≤P _i≤P _imax

In formula: P _imin, P _imaxbe respectively minimum, the maximum of i-th DG active power.

Miniature gas turbine climbing rate retrains:

When increasing load, have

P _MT(t)-P _MT(t-1)≤R _up，MT

During load shedding, have

P _MT(t-1)-P _MT(t)≤R _down，MT

In formula, R _{up, MT}, R _{down, MT}be respectively the limit value that MT increases and reduces active power.

5, many microgrids coordinative dispatching model solves

The best aggregation scheme of many microgrids that the power information of the power information obtained (power parameter and generating information), load and calculating are tried to achieve is substituting in many microgrids coordinated operation scheduling model, adopt Sequential Quadratic Programming method or genetic algorithm to solve, draw Optimized Operation plan.

6, many microgrids coordinated operation

Each microgrid carries out security verification according to gained operation plan, if met the demands, then carries out coordinated operation according to operation plan; If do not met the demands, then redefine many microgrids aggregation scheme, then be optimized, until meet the demands.

Above specific embodiments of the invention are described.It is to be appreciated that the present invention is not limited to above-mentioned particular implementation, those skilled in the art can make various distortion or amendment within the scope of the claims, and this does not affect flesh and blood of the present invention.

Claims (5)

1., based on many microgrid polymerization coordination optimization operation methods of panorama theory, it is characterized in that, comprise the following steps:

Step 1: analyze microgrid structure, gather power parameter and the generating information of distributed power source in each microgrid, and the power information of load;

Step 2: complementary by different distributions formula power supply, the theoretical scale of definition panorama and matching degree parameter, structure panorama energy function;

Step 3: determine many microgrids aggregation scheme by panorama energy balane;

Step 4: construct many microgrids coordinated operation scheduling model;

Step 5: the power information of the power parameter of the power supply obtained in step 1 and step 3 and generating information, load and many microgrids aggregation scheme are substituting in many microgrids coordinated operation scheduling model that step 4 constructs, adopt optimized algorithm to solve, obtain operation plan;

Step 6: each microgrid carries out security verification according to gained operation plan, if met the demands, then carries out coordinated operation according to operation plan; If do not met the demands, then repeated execution of steps 3 to step 5, redefines many microgrids aggregation scheme and is optimized.

2. the many microgrid polymerization coordination optimization operation methods based on panorama theory according to claim 1, it is characterized in that, in step 2, by panorama theoretical origin in many micro-grid systems, the theoretical scale of panorama and matching degree parameter is defined by different distributions formula power supply complementarity, structure panorama energy function, expression formula E _i(X) be:

$E_i\left(X\right)=\underset{i,j}{\mathrm{\&Sigma;}}{s}_i{s}_j{p}_{\mathrm{ij}}{d}_{\mathrm{ij}}\left(X\right)$

In formula, s _ithe large small-scale of i-th microgrid, s _jthe large small-scale of a jth microgrid, p _ijbe i-th microgrid to the matching degree of a jth microgrid, d _ij(X) be i-th microgrid and the distance of a jth microgrid in grouping model X.

3. the many microgrid polymerization coordination optimization operation methods based on panorama theory according to claim 1, it is characterized in that, in step 3, be the best aggregation scheme of many microgrids by the panorama energy balane grouping model of trying to achieve corresponding to panorama minimum energy point, concrete steps are as follows:

Step 3.1, stochastic generation grouping model X, calculates ENERGY E (X);

Step 3.2, generates all the other grouping models that grouping model X can reach, and calculates energy, selects the grouping model with least energy to be designated as Y;

Step 3.3, if the ENERGY E of grouping model X (X) is greater than the ENERGY E (Y) of grouping model Y, then another X=Y, returns step 3.2; Otherwise, grouping model X is added least energy list;

Step 3.4, repeats step 3.2 to step 3.3, until all grouping models are all analyzed complete.

4. the many microgrid polymerization coordination optimization operation methods based on panorama theory according to claim 1, it is characterized in that, in step 4, many microgrids coordinated operation scheduling model concrete steps of structure are:

Step 4.1, builds optimization aim: the target function setting up fail safe and economy, is embodied in target function using major network tie point power fluctuation as punishment cost;

Step 4.2, builds constraints, comprising: the constraint of system power Constraints of Equilibrium, distributed power source power output, miniature gas turbine Climing constant and tie-line power transmission constraint.

5. the many microgrid polymerization coordination optimization operation methods based on panorama theory according to claim 1, it is characterized in that, in step 5, the optimized algorithm of use is Sequential Quadratic Programming method or genetic algorithm.