CN102904289A - Island new energy system optimal capacity allocation method based on drosophila optimization algorithm - Google Patents

Abstract

The invention provides an island new energy system optimal capacity allocation method based on a drosophila optimization algorithm. A new energy system mainly comprises a photovoltaic generator, a wind power generator, a storage battery and a diesel engine and is characterized in that the capacity allocation of the new energy system is optimized by utilizing the drosophila optimization algorithm. The method comprises the following specific steps of: 1, selecting the types of the photovoltaic generator and the wind power generator according to the natural conditions and climate conditions of an island and determining the parameter values of the photovoltaic generator, the wind power generator, the storage battery and the diesel engine; 2, determining island load conditions which mainly includes a load power utilization time distribution condition, properties of loads in each time period, power values and a value of the load with the maximum peak value; 3, determining an object function of the drosophila optimization algorithm; and 4, obtaining the optimal capacity allocation parameter X={NPV,p,NWT,NBAT,p} of the island new energy system by utilizing the drosophila optimization algorithm. The method provided by the invention has the beneficial effects of greatly lowering the power generation production cost of the island new energy system, giving play to the maximal economic benefit of the electric capacity, reducing the consumption of fossil resources and the emission of environmental pollutants, promoting the island electrical energy to be more environmental-friendly and economical, and providing a sufficient electric energy guarantee for the island.

Description

Based on the optimum capacity collocation method of the island new energy resources system of fruit bat optimized algorithm

Technical field

The present invention relates to a kind of island new energy resources system capacity collocation method, be specially the optimum capacity collocation method of a kind of island new energy resources system based on the fruit bat optimized algorithm.

Background technology

New forms of energy refer to the energy of non-charcoal, such as wind energy, water energy, solar energy, biomass energy etc.Topmost advantage is to tap a new source of energy to be conducive to the sustainable development of society, be conducive to human health, the environment of effectively preserving our planet, the island new forms of energy can improve the utilization ratio of power supply quality and clean energy resource, and the consumption and the environmental contaminants that reduce fossil resource in the island discharge; Strengthen generating admittance ability, satisfy the need for electricity of resident's long-term stability in the island, large area blackout in the island of avoiding causing because of the submarine cable fault; Promote the whole anti-disaster ability of electrical network, for electric network emergency provides support; Formulate the Regulations of the little electrical network in island, for design, construction, the operation and maintenance of this type of engineering are accumulated experience from now on; And can effectively solve the power shortage problem of Island, and reduce consumption and the environmental contaminants discharging of fossil resource, promote that the island electric energy is more green, economy, environmental protection.

Because the independent island that the continent does not have electrical network to connect, the power supply on island mainly comprises photovoltaic generation, wind-powered electricity generation and diesel power generation, but photovoltaic generation, wind-powered electricity generation are subjected to inside even from weather larger.Thereby the island new forms of energy also are provided with storage battery and preserve unnecessary electric weight, how to reduce the generating production cost, improve the utilance of new forms of energy, and the maximum economic benefit of performance capacitance is the current greatest problem that faces.

Summary of the invention

The object of the present invention is to provide the optimum capacity collocation method of a kind of island new energy resources system based on the fruit bat optimized algorithm, guarantee system within useful life, the operating cost of system is minimum, and economic benefit is best.

In order to achieve the above object, the present invention is by the following technical solutions:

The optimum capacity collocation method of a kind of island new energy resources system based on the fruit bat optimized algorithm, new energy resources system mainly comprises: photovoltaic generation, wind-powered electricity generation, storage battery, diesel engine and charge controller, inverter, it is characterized in that, described new energy resources system capacity configuration adopts the fruit bat optimized algorithm to be optimized, and concrete steps are as follows:

1) according to the natural conditions on island, the type that weather conditions are selected photovoltaic generation, wind-powered electricity generation, confirms the parameter value of photovoltaic generation, wind-powered electricity generation, storage battery, diesel engine;

2) determine the load condition on island, mainly comprise character, the performance number of load electricity consumption time distribution situation, each period load, the value of peak-peak load;

3) target function of determining the fruit bat optimized algorithm is the system operation cost function that formula (1) and formula (2) are described,

$\underset{x}{\min }\mathrm{STC}\left(x\right)=\underset{x}{\min }\{C_T\left(x\right)+C_M\left(x\right)+C_I\left(x\right)+C_{T,D}\}---\left(1\right)$

Wherein x is the one-dimensional vector that the system optimization variable forms: x={N _{PV, p}, N _WT, N _{BAT, p}, N _{PV, p}Parallel photovoltaic battery strings number, N _WTBe wind turbine generator number, N _{BAT, p}Be multiple-connected battery string number;

$\mathrm{STC}(N_{\mathrm{PV},p},N_{\mathrm{WT}},N_{\mathrm{BAT},p})=\underset{i=1}{\overset{n_{\mathrm{PV}}}{\mathrm{\Σ}}}{N}_{\mathrm{PV}}^i(C_{\mathrm{PV}}^i+n\·M_{\mathrm{PV}}^i)+\underset{j=1}{\overset{n_{\mathrm{PV}}}{\mathrm{\Σ}}}{N}_{\mathrm{WT}}^j(C_{\mathrm{WT}}^j+n\·M_{\mathrm{WT}}^j+C_h^j+n\·C_{\mathrm{hm}}^j)$

$+\underset{k=1}{\overset{n_{\mathrm{BAT}}}{\mathrm{\Σ}}}{N}_{\mathrm{BAT}}^k\·(C_{\mathrm{BAT}}^k+y_{\mathrm{BAT}}^k\·C_{\mathrm{BAT}}^k+(n-y_{\mathrm{BAT}}^k-1)\·M_{\mathrm{BAT}}^k)+C_I+C_{T,D}$

$+C_{\mathrm{INV}}(y_{\mathrm{INV}}+1)+M_{\mathrm{INV}}(n-y_{\mathrm{INV}}-1)---\left(2\right)$

Wherein, n is system's time limit in useful life, n _PV, n _WT, n _BATBe respectively the type sum of photovoltaic cell, wind turbine generator and storage battery;

C _INVBe respectively the purchase cost of i type of photovoltaic cell, j type wind turbine generator, k type storage battery and inverter, unit is: unit;

M _INVCorresponding to photovoltaic cell, wind turbine generator, storage battery, the maintenance cost in 1 year of inverter, unit is: unit/year;

The purchase cost of tower is installed for wind turbine generator;

Maintenance cost for installation tower every year of correspondence;

y _INVFor storage battery, inverter expect to change number of times in system in useful life; C _IBe the installation cost of system, comprise the installation cost of each part of system, and the purchase cost of charge controller;

Be the sum of type photovoltaic cell among the i, wherein

Be the series connection quantity of i kind photovoltaic cell; And

Be the parallel connection string number of i kind photovoltaic cell, be the variable of optimal design;

It is the storage battery sum of type batteries among the k;

Be the series connection quantity of storage battery,

For storage battery number in parallel, it is the optimal design variable; C _{T, D}Be the total cost of diesel engine within useful life, available following formula calculates:

$C_{T,D}=C_{I,D}+M_D+\frac{C_D}{{\mathrm{Life}}_D}+C_{\mathrm{fuel}}---\left(3\right)$

C wherein _{I, D}Be the installation cost of diesel engine generator, unit is: unit; M _DBe diesel engine generator maintenance cost hourly, unit is: unit/hour; C _DBe the purchase cost of diesel engine, unit is: unit; Life _DBe the useful life of diesel engine, unit is: hour; C _FuelMove the fuel cost that consumed in a hour for diesel engine;

Set up the constraints of power system capacity configuration optimization design, the constraints of described system mainly comprises following content:

1) power-balance: the power that system provides equates with the load power demand

P _p(t)＝P _L(t) (4)

P wherein _p(t) power that provides for system, available following formula calculates:

P _p(t)＝P _RE(t)+P _D(t)-P _B(t) (5)

Wherein $P_{\mathrm{RE}}\left(t\right)=\underset{i=1}{\overset{n_{\mathrm{PV}}}{\mathrm{\Σ}}}{N}_{\mathrm{PV}}^i\·P_{\mathrm{PV}}^i\left(t\right)+\underset{j=1}{\overset{n_{\mathrm{WT}}}{\mathrm{\Σ}}}{N}_{\mathrm{WT}}^j\·P_{\mathrm{WT}}^j\left(t\right)$ The power that provides for regenerative resource.P _B(t) be the I/O power of batteries: P _B(t)＞0 an o'clock storage battery is in charged state, works as P _B(t)＜0 an o'clock storage battery is in discharge condition.

2) charged state of storage battery can not surpass the maximum carrying capacity of storage battery and minimum charged quantitative limitation.

SOC _min≤SOC(t)≤SOC _max(6)

3) P _D: diesel engine year energy output account for electric weight that system provides 10% in, i.e. P _D/ (P _RE+ P _D)≤0.1

4) other constraintss:

$\left\{\begin{array}{c}1\&le;N_{\mathrm{PV},p}^i\&le;N_{\mathrm{PV},p\max }^i\\ 1\&le;N_{\mathrm{WT}}^j\&le;N_{\mathrm{WT}\mathrm{<figure-callout\; id="1"\; label="max\; j"\; filenames="HSA00000790253000021.png"\; state="\{\{state\}\}">max</figure-callout>}}^j\\ 1\&le;N_{\mathrm{BAT},p}^k\&le;N_{\mathrm{BAT},p\max }^k\end{array}\right.---\left(7\right)$

Wherein

To calculate according to photovoltaic cell, wind turbine generator, storage battery and peak load respectively.

(4) adopt the fruit bat optimized algorithm, constantly search, the cost of computing system, and so forth, until the algorithm end of run, the output optimal solution obtains the optimum capacity configuration parameter x of island new energy resources system={ N _{PV, p}, N _WT, N _{BAT, p}.

Further, described fruit bat optimized algorithm step is:

1) position of first random initializtion fruit bat colony;

2) then be assigned to each fruit bat sense of smell, the i.e. random direction of search of food and random distance;

3) owing to can't learn the particular location of food, therefore when single fruit bat single flight arrives a position (xi, yi), calculate the distance D i with initial point, with the inverse of distance as flavor concentration decision content Si, shown in (8):

$\left\{\begin{array}{c}\mathrm{Di}=\sqrt{{\mathrm{xi}}^2+{\mathrm{yi}}^2}\\ \mathrm{Si}=\frac{1}{\mathrm{Di}}\end{array}\right.---\left(8\right)$

4) with flavor concentration decision content Si substitution flavor concentration decision function, obtain the flavor concentration of single fruit bat position, wherein the flavor concentration decision function is set according to the problem of reality;

5) find out the fruit bat of flavor concentration maximum in the whole fruit bat colony, the coordinate position at this fruit bat place be set as the best flavors concentration value, and in the fruit bat group toward this direction flight;

Utilize the method for iteration optimizing, repeated execution of steps 2) to step 5) until find the food position.

Further, described is that the system's time limit in useful life n span is 5-20.

The invention has the beneficial effects as follows:

1, greatly reduces island new energy resources system generating production cost, the maximum economic benefit of performance capacitance;

2, reduce consumption and the environmental contaminants discharging of fossil resource, promote that the island electric energy is more green, economy, environmental protection;

3, provide the sufficient electrical energy guarantee for the island.

Description of drawings

Fig. 1 fruit bat optimized algorithm flow chart

The optimum capacity collocation method flow chart of Fig. 2 island new energy resources system

Fig. 3 is load characteristic figure per month

Fig. 4 load power demand situation

Ambient temperature value per hour in Fig. 5 A island 1 year

Fig. 6 holds the hybrid power system total cost based on fruit bat optimized algorithm wind-light-diesel

Fig. 7 HOMER software light radiation data inputting interface

Wind speed inputting interface in Fig. 8 HOMER software

Embodiment

The present invention mainly for the independent island that does not have electrical network to be connected with the continent, the power supply on island mainly is comprised of photovoltaic generation, wind-powered electricity generation, but considers that photovoltaic generation, wind-powered electricity generation are subjected to inside even from weather larger, thereby has adopted storage battery.When the power of photovoltaic generation, wind-powered electricity generation exceeds power load, charge in batteries; When the power of photovoltaic generation, wind-powered electricity generation is lower than power load, battery discharging.The effect of diesel engine mainly is as stand-by power supply, when photovoltaic generation, wind-powered electricity generation and storage battery power supply are not enough, perhaps when system equipment overhaul or fault, adopts the diesel engine power supply.Thereby the island new energy resources system comprises: photovoltaic generation, wind-powered electricity generation, storage battery, 4 major parts of diesel engine form.

The optimum capacity configuration of island new energy resources system is will guarantee system within useful life, and the operating cost of system is minimum.Therefore, the target function of the cost function of system being regarded as optimal design.

The cost function of island new energy resources system comprises following components:

A. photovoltaic cell, wind turbine generator, wind turbine generator are installed purchase cost and the installation cost of tower, storage battery, charge controller, inverter and diesel engine generator.

B. at the replacement cost of system's storage battery, wind turbine generator, charge controller, inverter, diesel engine in useful life.

C. photovoltaic cell, wind turbine generator, installation tower, the maintenance cost of storage battery within its useful life.

D. the operation and maintenance expense of diesel engine generator in the life-span is benefited from by system.

E. the fuel cost that consumes in useful life in system of diesel engine generator.

Adopt following math equation to describe:

$\underset{x}{\min }\mathrm{STC}\left(x\right)=\underset{x}{\min }\{C_T\left(x\right)+C_M\left(x\right)+C_I\left(x\right)+C_{T,D}\}---\left(1\right)$

Wherein x is the one-dimensional vector that the system optimization variable forms: x={N _{PV, p}, N _WT, N _{BAT, p}, N _{PV, p}Parallel photovoltaic battery strings number, N _WTBe wind turbine generator number, N _{BAT, p}Be multiple-connected battery string number.

The year in useful life of supposing system is limited to 20 years, so:

$\mathrm{STC}(N_{\mathrm{PV},p},N_{\mathrm{WT}},N_{\mathrm{BAT},p})=\underset{i=1}{\overset{n_{\mathrm{PV}}}{\mathrm{\&Sigma;}}}{N}_{\mathrm{PV}}^i(C_{\mathrm{PV}}^i+20\&CenterDot;M_{\mathrm{PV}}^i)+\underset{j=1}{\overset{n_{\mathrm{PV}}}{\mathrm{\&Sigma;}}}{N}_{\mathrm{WT}}^j(C_{\mathrm{WT}}^j+20\&CenterDot;M_{\mathrm{WT}}^j+C_h^j+20\&CenterDot;C_{\mathrm{hm}}^j)$

$+\underset{k=1}{\overset{n_{\mathrm{BAT}}}{\mathrm{\&Sigma;}}}{N}_{\mathrm{BAT}}^k\&CenterDot;(C_{\mathrm{BAT}}^k+y_{\mathrm{BAT}}^k\&CenterDot;C_{\mathrm{BAT}}^k+(20-y_{\mathrm{BAT}}^k-1)\&CenterDot;M_{\mathrm{BAT}}^k)+C_I+C_{T,D}$

+C _INV(y _INV+1)+M _INV(20-y _INV-1)(2)

Wherein, n _PV, n _WT, n _BATBe respectively the type sum of photovoltaic cell, wind turbine generator and storage battery;

C _INVBe respectively the purchase cost (unit) of i type of photovoltaic cell, j type wind turbine generator, k type storage battery and inverter;

MINV is corresponding to photovoltaic cell, wind turbine generator, storage battery, the maintenance cost in 1 year of inverter (unit/year);

The purchase cost of tower is installed for wind turbine generator; Maintenance cost for installation tower every year of correspondence;

YINV is that storage battery, inverter expect to change number of times in system in useful life; C _IBe the installation cost of system, comprise the installation cost of each part of system, and the purchase cost of charge controller. Be the sum of type photovoltaic cell among the i, wherein

Be the series connection quantity of i kind photovoltaic cell; And

Be the parallel connection string number of i kind photovoltaic cell, be the variable of optimal design.

It is the storage battery sum of type batteries among the k.

Be the series connection quantity of storage battery,

For storage battery number in parallel, it is the optimal design variable.C _{T, D}Be the total cost of diesel engine within useful life, available following formula calculates:

$C_{T,D}=C_{I,D}+M_D+\frac{C_D}{{\mathrm{Life}}_D}+C_{\mathrm{fuel}}---\left(3\right)$

C wherein _{I, D}Installation cost (unit) for diesel engine generator; M _DBe diesel engine generator maintenance cost hourly (unit/hour); C _DPurchase cost (unit) for diesel engine; Life _DFor useful life of diesel engine (hour); C _FuelMove the fuel cost that consumed in a hour for diesel engine.

The constraints of power system capacity configuration optimization design:

The constraints of island new energy resources system aims of systems function is to set up according to user's load request and element characteristic, being used for the power that the assurance system provides satisfies loading demand, the power that is provided by diesel engine simultaneously is in given range, with the pollution of minimizing system to environment.The constraints of native system mainly comprises following content:

(1) power-balance: the power that system provides equates with the load power demand

P _p(t)＝P _L(t) (4)

P wherein _p(t) power that provides for system, available following formula calculates:

P _p(t)＝P _RE(t)+P _D(t)-P _B(t) (5)

Wherein $P_{\mathrm{RE}}\left(t\right)=\underset{i=1}{\overset{n_{\mathrm{PV}}}{\mathrm{\&Sigma;}}}{N}_{\mathrm{PV}}^i\&CenterDot;P_{\mathrm{PV}}^i\left(t\right)+\underset{j=1}{\overset{n_{\mathrm{WT}}}{\mathrm{\&Sigma;}}}{N}_{\mathrm{WT}}^j\&CenterDot;P_{\mathrm{WT}}^j\left(t\right)$ The power that provides for regenerative resource.P _B(t) be the I/O power of batteries: P _B(t)＞0 an o'clock storage battery is in charged state, works as P _B(t)＜0 an o'clock storage battery is in discharge condition.

(2) charged state of storage battery can not surpass the maximum carrying capacity of storage battery and minimum charged quantitative limitation.

SOC _min≤SOC(t)≤SOC _max (6)

(3) P _D: diesel engine year energy output account for electric weight that system provides 10% in, i.e. P _D/ (P _RE+ P _D)≤0.1

(4) other constraintss:

$\left\{\begin{array}{c}1\&le;N_{\mathrm{PV},p}^i\&le;N_{\mathrm{PV},\mathrm{<figure-callout\; id="1"\; label="p\; max\; i"\; filenames="HSA00000790253000021.png"\; state="\{\{state\}\}">p</figure-callout>}\max }^i\\ 1\&le;N_{\mathrm{WT}}^j\&le;N_{\mathrm{<figure-callout\; id="1"\; label="WT\; max\; j"\; filenames="HSA00000790253000021.png"\; state="\{\{state\}\}">WT</figure-callout>}\max }^j\\ 1\&le;N_{\mathrm{BAT},p}^k\&le;N_{\mathrm{BAT},p\max }^k\end{array}\right.---\left(7\right)$

Wherein

To calculate according to photovoltaic cell, wind turbine generator, storage battery and peak load respectively.

The fruit bat optimized algorithm:

The fruit bat optimized algorithm is a kind of new method of deducing out the searching global optimization based on the fruit bat foraging behavior, and specific algorithm is realized as follows:

1) position of first random initializtion fruit bat colony;

2) then be assigned to each fruit bat sense of smell, the i.e. random direction of search of food and random distance;

3) owing to can't learn the particular location of food, therefore when single fruit bat single flight arrives a position (xi, yi), calculate the distance D i with initial point, with the inverse of distance as flavor concentration decision content Si, suc as formula (8);

4) with flavor concentration decision content Si substitution flavor concentration decision function, obtain the flavor concentration of single fruit bat position, wherein the flavor concentration decision function is set according to the problem of reality;

5) find out the fruit bat of flavor concentration maximum in the whole fruit bat colony, the coordinate position at this fruit bat place be set as the best flavors concentration value, and in the fruit bat group toward this direction flight.

Utilize the method for iteration optimizing, repeated execution of steps 2) to step 5) until find the food position.

$\left\{\begin{array}{c}\mathrm{Di}=\sqrt{{\mathrm{xi}}^2+{\mathrm{yi}}^2}\\ \mathrm{Si}=\frac{1}{\mathrm{Di}}\end{array}\right.---\left(8\right)$

The realization of island new energy resources system capacity configuration optimal design:

Utilize the fruit bat optimized algorithm as follows to the key step that the island new energy resources system is optimized design:

(1) select the type of photovoltaic generation, wind-powered electricity generation according to the natural conditions on island, weather conditions, obtain the parameter value of relevant photovoltaic generation, wind-powered electricity generation etc., and the related parameter values of storage battery, diesel engine.

(2) understand the load condition on island, mainly comprise the load electricity consumption time distribute, the size of the character of each period load, watt level, peak-peak load etc.

(3) target function of determining the fruit bat optimized algorithm is the system operation cost function that formula (1) and (2) are described, and sets up the constraints of power system capacity configuration optimization design;

(4) adopt the fruit bat optimized algorithm, constantly search, the cost of computing system, and so forth, until the algorithm end of run, the output optimal solution obtains the optimum capacity configuration parameter x of island new energy resources system={ N _{PV, p}, N _WT, N _{BAT, p}.

New energy resources system optimum capacity collocation method in island carries out following enforcement:

The A island is divided into several sections equal time (being assumed to 1 hour) with the total simulation time of system (a year), namely to the assessment of wind energy resources, solar energy resources and load prediction all take hour as unit.

Electricity generation system is for the electricity consumption of satisfying the user requires to design, and provide reliable electric power for the user, just necessary serious analysis user's power load feature.Mainly be maximum power load and the average daily power consumption of understanding the user.The concrete electricity consumption situation on A island is added up the peak period that can get electricity consumption be distributed between 5 annual～October, island 2008, maximum daily power consumption in 2009 are 7800 degree, are distributed in summer.

Its concrete load electricity consumption situation is as shown in table 1: the load condition on A island can be divided into residential electricity consumption load, commercial power load and high-power power load.Wherein residential electricity consumption is to be determined by the household electrical appliance situation of inhabitant on the island, and its power consumption is smaller comparatively speaking, generally only takies 8%～9% of electric total amount; Because the A island is tourism type island, as shown in Figure 3 and Figure 4, is its tourist season in the 5～October in every year, the commercial power load on the island can significantly increase during this period, and according to statistics, commercial power consumption accounts for 80% of its total electricity consumption on the island; High-power power load is mainly fish production electricity consumption on the island, and comparatively speaking, high-power electricity consumption is more stable, generally can open in the set time.Its power consumption is also less.

The load electricity consumption information slip on table 1 project implementation ground

The data of light radiation and wind speed are seen Fig. 7 and shown in Figure 8 in the A island 1 year.

Statistics A island temperature Change for many years adopts the Sinusoidal function calculation to go out temperature data hourly in one year.

$T\left(t\right)=0.5[(T_{\max }+T_{\min })+(T_{\max }-T_{\min })\sin \left(\frac{2\mathrm{\&pi;}(t-t_p)}{24}\right)]---\left(9\right)$

Wherein, T _MaxAnd T _MinBe respectively maximum and the minimum value of this degree/day; T (t) is the temperature value of any time this day; t _pBe the mean temperature moment.

The data of collecting for many years according to weather station, A island, by above-mentioned formula discrete obtain 1 year by the time temperature data shown in Figure 5, at the relevant parameter that adopts wind turbine generator, photovoltaic cell and storage battery among the design shown in table 2～4.The rated power of diesel engine is 350KW, and its purchasing price is 298000 yuan, and be 7000h useful life, and the price of diesel oil is 7 yuan/L at present; Suppose that diesel engine maintenance cost hourly is 1.5 yuan, the rated power of two-way inverter is 350Kw, and its maintenance cost is 4000 yuan/year, and the conversion efficiency of inverter is 95%.Generally be 20 years the useful life of photovoltaic cell and wind turbine generator, and be 3 years the useful life of storage battery, supposes that system is 20 years useful life, then at the replacing number of times y of system's storage battery in useful life _BAT=6.Because the series connection number of batteries is to be determined by system's dc bus voltage in the number of photovoltaic array series-connected cell and the system, the dc bus voltage that wind-light-diesel holds hybrid power system is standard value 480V, and the serial number wind that can get photovoltaic cell and storage battery is not

Table 2 wind turbine generator parameter

Table 3 photovoltaic cell parameter

Table 4 accumulator parameter

After determining each component parameters of new forms of energy hybrid power system, adopt the MATLAB programming to realize with the fruit bat optimized algorithm hybrid system being optimized design, according to shown in Figure 2, working procedure under the MATLAB environment can get the analogous diagram of hybrid system cost as shown in Figure 6.Ordinate is the hybrid system cost of electricity-generating among the figure, and abscissa is the flavor concentration decision content, as seen from Figure 6, can satisfy the requirement of algorithmic statement.The minimum operating cost of independent new forms of energy hybrid power system is 2,605 ten thousand yuan.The individual solution of the allocation optimum of the minimum operating cost of correspondence system is as shown in table 5.Be that to hold the hybrid power system allocation optimum be to be 10KW and 58 wind turbine generator that power is 5KW by 37 power to wind-light-diesel; 82 * 20 capacity are 180W and 135 * 30 photovoltaic cell and 2 * 240 storage battery compositions that rated capacity is 800Ah that capacity is 110W.

Table 5 Optimum Design Results

Claims (3)

1. optimum capacity collocation method of the island new energy resources system based on the fruit bat optimized algorithm, new energy resources system mainly comprises: photovoltaic generation, wind-powered electricity generation, storage battery, diesel engine, it is characterized in that, described new energy resources system capacity configuration adopts the fruit bat optimized algorithm to be optimized, and concrete steps are as follows:

1) according to the natural conditions on island, the type that weather conditions are selected photovoltaic generation, wind-powered electricity generation, confirms the parameter value of photovoltaic generation, wind-powered electricity generation, storage battery, diesel engine;

2) determine the load condition on island, mainly comprise character, the performance number of load electricity consumption time distribution situation, each period load, the value of peak-peak load;

3) target function of determining the fruit bat optimized algorithm is the system operation cost function that formula (1) and formula (2) are described,

$\underset{x}{\min }\mathrm{STC}\left(x\right)=\underset{x}{\min }\{C_T\left(x\right)+C_M\left(x\right)+C_I\left(x\right)+C_{T,D}\}---\left(1\right)$

Wherein x is the one-dimensional vector that the system optimization variable forms: x={N _{PV, p}, N _WT, N _{BAT, p}, N _{PV, p}Parallel photovoltaic battery strings number, N _WTBe wind turbine generator number, N _{BAT, p}Be multiple-connected battery string number;

$\mathrm{STC}(N_{\mathrm{PV},p},N_{\mathrm{WT}},N_{\mathrm{BAT},p})=\underset{i=1}{\overset{n_{\mathrm{PV}}}{\mathrm{\&Sigma;}}}{N}_{\mathrm{PV}}^i(C_{\mathrm{PV}}^i+n\&CenterDot;M_{\mathrm{PV}}^i)+\underset{j=1}{\overset{n_{\mathrm{PV}}}{\mathrm{\&Sigma;}}}{N}_{\mathrm{WT}}^j(C_{\mathrm{WT}}^j+n\&CenterDot;M_{\mathrm{WT}}^j+C_h^j+n\&CenterDot;C_{\mathrm{hm}}^j)$

$+\underset{k=1}{\overset{n_{\mathrm{BAT}}}{\mathrm{\&Sigma;}}}{N}_{\mathrm{BAT}}^k\&CenterDot;(C_{\mathrm{BAT}}^k+y_{\mathrm{BAT}}^k\&CenterDot;C_{\mathrm{BAT}}^k+(n-y_{\mathrm{BAT}}^k-1)\&CenterDot;M_{\mathrm{BAT}}^k)+C_I+C_{T,D}$

$+C_{\mathrm{INV}}(y_{\mathrm{INV}}+1)+M_{\mathrm{INV}}(n-y_{\mathrm{INV}}-1)---\left(2\right)$

Wherein, n is system's time limit in useful life, n _PV, n _WT, n _BATBe respectively the type sum of photovoltaic cell, wind turbine generator and storage battery;

C _INVBe respectively the purchase cost of i type of photovoltaic cell, j type wind turbine generator, k type storage battery and inverter, unit is: unit;

M _INVCorresponding to photovoltaic cell, wind turbine generator, storage battery, the maintenance cost in 1 year of inverter, unit is: unit/year;

The purchase cost of tower is installed for wind turbine generator;

Maintenance cost for installation tower every year of correspondence;

y _INVFor storage battery, inverter expect to change number of times in system in useful life; C _IBe the installation cost of system, comprise the installation cost of each part of system, and the purchase cost of charge controller;

Be the sum of type photovoltaic cell among the i, wherein

Be the series connection quantity of i kind photovoltaic cell; And

Be the parallel connection string number of i kind photovoltaic cell, be the variable of optimal design;

It is the storage battery sum of type batteries among the k;

Be the series connection quantity of storage battery,

For storage battery number in parallel, it is the optimal design variable; CT, D are the total cost of diesel engine within useful life, and available following formula calculates:

$C_{T,D}=C_{I,D}+M_D+\frac{C_D}{{\mathrm{Life}}_D}+C_{\mathrm{fuel}}---\left(3\right)$

C wherein _{I, D}Installation cost (unit) for diesel engine generator; M _DBe diesel engine generator maintenance cost hourly, unit is: unit/hour; C _DBe the purchase cost of diesel engine, unit is: unit; Life _DBe the useful life of diesel engine, unit is: hour; C _FuelMove the fuel cost that consumed in a hour for diesel engine;

Set up the constraints of power system capacity configuration optimization design, the constraints of described system mainly comprises following content:

One) power-balance: the power that system provides equates with the load power demand

P _p(t)＝P _L(t) (4)

P wherein _p(t) power that provides for system, available following formula calculates:

P _p(t)＝P _RE(t)+P _D(t)-P _B(t) (5)

Wherein $P_{\mathrm{RE}}\left(t\right)=\underset{i=1}{\overset{n_{\mathrm{PV}}}{\mathrm{\&Sigma;}}}{N}_{\mathrm{PV}}^i\&CenterDot;P_{\mathrm{PV}}^i\left(t\right)+\underset{j=1}{\overset{n_{\mathrm{WT}}}{\mathrm{\&Sigma;}}}{N}_{\mathrm{WT}}^j\&CenterDot;P_{\mathrm{WT}}^j\left(t\right)$ Be the power that regenerative resource provides, P _B(t) be the I/O power of batteries: P _B(t)＞0 an o'clock storage battery is in charged state, works as P _B(t)＜0 an o'clock storage battery is in discharge condition;

Two) charged state of storage battery can not surpass the maximum carrying capacity of storage battery and minimum charged quantitative limitation;

SOC _min≤SOC(t)≤SOC _max (6)

Three) P _D: diesel engine year energy output account for electric weight that system provides 10% in, i.e. P _D/ (P _RE+ P _D)≤0.1

Four) other constraintss:

$\left\{\begin{array}{c}1\&le;N_{\mathrm{PV},p}^i\&le;N_{\mathrm{PV},p\max }^i\\ 1\&le;N_{\mathrm{WT}}^j\&le;N_{\mathrm{WT}\max }^j\\ 1\&le;N_{\mathrm{BAT},p}^k\&le;N_{\mathrm{BAT},p\max }^k\end{array}\right.---\left(7\right)$

Wherein

To calculate according to photovoltaic cell, wind turbine generator, storage battery and peak load respectively;

Five) adopt the fruit bat optimized algorithm, constantly search, the cost of computing system, and so forth, until the algorithm end of run, the output optimal solution obtains the optimum capacity configuration parameter x of island new energy resources system={ N _{PV, p}, N _WT, N _{BAT, p}.

2. the optimum capacity collocation method of a kind of island new energy resources system based on the fruit bat optimized algorithm according to claim 1, it is characterized in that: described fruit bat optimized algorithm step is:

1) position of first random initializtion fruit bat colony;

2) then be assigned to each fruit bat sense of smell, the i.e. random direction of search of food and random distance;

3) owing to can't learn the particular location of food, therefore when single fruit bat single flight arrives a position (xi, yi), calculate the distance D i with initial point, with the inverse of distance as flavor concentration decision content Si, shown in (8):

$\left\{\begin{array}{c}\mathrm{Di}=\sqrt{{\mathrm{xi}}^2+{\mathrm{yi}}^2}\\ \mathrm{Si}=\frac{1}{\mathrm{Di}}\end{array}\right.---\left(8\right)$

4) with flavor concentration decision content Si substitution flavor concentration decision function, obtain the flavor concentration of single fruit bat position, wherein the flavor concentration decision function is set according to the problem of reality;

5) find out the fruit bat of flavor concentration maximum in the whole fruit bat colony, the coordinate position at this fruit bat place be set as the best flavors concentration value, and in the fruit bat group toward this direction flight;

Utilize the method for iteration optimizing, repeated execution of steps 2) to step 5) until find the food position.

3. the optimum capacity collocation method of a kind of island new energy resources system based on the fruit bat optimized algorithm according to claim 2 is characterized in that: described for the system's time limit in useful life n span be 5-20.

Images