CN105005872A - Capacity configuration method for peak-load-shifting energy storage system - Google Patents

Abstract

The invention discloses a capacity configuration method for a peak-load-shifting energy storage system, belonging to the technical field of energy storage for suppressing the load fluctuation of a power grid. Capacity configuration comprises output setting, capacity calculation, cost calculation, constraint condition setting and algorithm writing. Capacity configuration mainly relates to optimized configuration of renewable power generation devices and energy storage systems, and the energy storage systems mainly refer to energy storage battery devices. For energy storage system capacity configuration, in consideration of the limited service life of energy storage systems, device replacement must be performed, and the appropriate cost price is chosen according to different energy storage sizes. By considering the energy storage battery constraints, charge and discharge balance constraints, converter efficiency and benefits from electricity price difference, a micro network system including wind-photovoltaic equipment is integrally configured in an economical manner so as to obtain an energy storage capacity configuration scheme maximizing the benefit.

Description

A kind of capacity collocation method of accumulator system of peak load shifting

Technical field

The invention belongs to the technical field of energy storage suppressing network load fluctuation, in particular to a kind of capacity collocation method of accumulator system of peak load shifting, be specifically related to balance based on the biogeography optimized algorithm improved and discharge and recharge the method be configured stored energy capacitance.

Background technology

The increase of power load; renewable energy power generation device participates in grid-connected; the undulatory property of electrical network, randomness is all made to become large; load peak-valley difference also progressively increases; extensive battery energy storage system can be played a great role in peak load shifting with the advantage of its uniqueness, and the high cost of accumulator system limits the scale application of energy storage technology.

Network load is irregular, uninterruptedly change, and its peak directly affects the construction of the equipment such as transmission of electricity, distribution.But shorter owing to holding time peak period, therefore cause the consumer utilization factor under conventional sense lower.In order to avoid, network load peak period is short, the shortcoming of equipment waste, and large-scale energy-storage battery, with its excellent feature, obtains more wide application space.Its energy-storage property, ensure that the release of its electric energy at load boom period and the energy storage capacity of load valley phase, reduces load fluctuation, enhance the regulating power of system.It can change planning construction present situation, reduces the input of Resources for construction, increases power network resources utilization factor, improves the whole efficiency of system.

Research about peak load shifting control strategy has had roughly ripe system, considerable research has been had to carry out peak load shifting for how using energy storage device, this patent focuses in the Economic and Efficiency Analysis that the constant volume of energy storage and configuration bring, use the optimized algorithm improved, reliable allocation plan under obtaining limited conditions.

The present invention is mainly for economy optimal objective, and the load large to peak-valley difference carries out peak load shifting, by carrying out optimizing to the allocation plan satisfied condition, thus obtains rational capacity configuration scheme.

Summary of the invention

The object of the invention is the capacity collocation method of the accumulator system proposing a kind of peak load shifting, it is characterized in that, described capacity collocation method comprises setting of exerting oneself, calculation of capacity, pricing, constraint condition arranges and algorithm is write;

Described setting of exerting oneself relates generally to renewable Blast Furnace Top Gas Recovery Turbine Unit (TRT), typical case's generated output curve on the one of setting blower fan and photovoltaic generation, photovoltaic considers the factor such as deviation efficiency, line loss, dust impact, and the factors such as practical efficiency, atmospheric density, wake effect, the mistake of field network loss, weather effect considered by blower fan;

Described calculation of capacity and pricing, relate generally to the cost calculation model of computing method to stored energy capacitance and each several part device, calculation of capacity is premised on discharge and recharge every day balance, accumulation calculates the discharge and recharge of each sampling interval, and consider the interval impact on battery life of battery charging and discharging, every construction cost, O&M cost, basic charge as per installed capacity and alternative costs are partly considered in pricing;

Described constraint condition is arranged, and the optimization aim and constraint condition related generally to comprising honourable accumulator system configuration is arranged; The optimization aim of accumulator system configuration is considered from income optimization, comprising the income that the construction cost of each several part device, O&M cost, government subsidy, equipment basic charge as per installed capacity and electricity price difference band come; For the setting of constraint condition, main consider energy-storage battery discharge and recharge the constraint of dump energy, the discharge and recharge Constraints of Equilibrium of accumulator system and current transformer loss constraint;

Described algorithm writes the discharge and recharge statistics during the biogeography optimized algorithm (need to set parameters, and mutation operation is replaced with the iteratively faster mode of particle cluster algorithm) and peak load shifting relating generally to improvement; Discharge and recharge statistics is then the independent variable by setting, and cumulative discharge and recharge is expressed as the formula of band independent variable, discharge and recharge is represented by sign, and absolute value error within the specific limits, namely thinks that discharge and recharge reaches equilibrium state.

Described setting of exerting oneself relates generally to renewable Blast Furnace Top Gas Recovery Turbine Unit (TRT) and comprises:

1) close photovoltaic to exert oneself setting, the impact of size by geographic position of exerting oneself of photovoltaic, the parameter such as intensity of solar radiation, temperature all can be different, simultaneously, size of exerting oneself and consumer institute subfam. Spiraeoideae also closely bound up, need according to the size of power consumption to adjust the photovoltaic pond plate size come into operation at any time, therefore, theory at any time exerts oneself size such as formula shown in (1):

P _PV(t)＝η _PV×W _PV×S _PV(1)

In formula, η _pV---the conversion efficiency of photovoltaic battery panel;

W _pV---average solar radiation total amount;

S _pV---the area that comes into operation of photovoltaic battery panel;

2) blower fan is exerted oneself setting, and the power that Wind turbines sends was determined originally jointly by the assembly of on-the-spot machine set condition, blower fan quantity, real-time wind speed and wind power generating set;

Described pricing, each several part installation cost arranges as follows:

1) photovoltaic devices

The total cost of photovoltaic (PV) unit is made up of construction cost and O&M cost two parts, is represented by formula (3):

C _PV＝B _PVP _PV+OM _PVP _PV(3)

Wherein, C _pV---photovoltaic unit cost;

B _pV---the construction price under photovoltaic unit specific power;

OM _pV---the O&M price under photovoltaic unit specific power;

P _pV---the photovoltaic unit rated power used;

2) blower fan apparatus

The total cost of wind power generating set is made up of construction cost and O&M cost two parts, is represented by formula (4):

C _wind＝B _windP _wind+OM _windP _wind(4)

Wherein, C _wind---Wind turbines cost;

B _wind---the construction price under Wind turbines specific power;

OM _wind---the O&M price under Wind turbines specific power;

P _wind---the Wind turbines rated power used.

3) energy storage battery device

Consider the life-span restriction of accumulator system, must carry out the replacement of device, choose cost price according to different energy storage scales, then the cost of battery energy storage system is such as formula shown in (5):

$\left\{\begin{array}{c}{C}_{ES}=\left(\frac{L_{PV}}{L_{ES}}\right)B_{ES}R\\ B_{ES}=B_{Storage}+B_{Conversion}+B_{Balance}\end{array}\right.---\left(5\right)$

Wherein, C _eS---energy-storage battery (ES) system cost;

L _pV---the life-span of photovoltaic unit;

L _eS---the life-span of energy-storage battery;

B _eS---the construction price under energy-storage battery unit capacity;

R---join the capacity of energy-storage battery;

B _storage---the stored energy price of energy-storage battery;

B _conversion---the energy conversion price of energy-storage battery;

B _balance---the balancing energy price of energy-storage battery;

4) optimization aim of accumulator system configuration comprises the calculating of the income that unit cost, operation maintenance expense, government subsidy, equipment basic charge as per installed capacity and electricity price difference band come: the cost-operation maintenance cost-basic charge as per installed capacity of the income+government subsidy-original unit of total revenue=segmentation electricity price, basic charge as per installed capacity (transformer capacity expense)=maximum demand * 38 yuan/kW, maximum demand refers to electric power during electricity consumption top, namely power when device all goes into operation, then total revenue is such as formula shown in (6).

C＝max(C _S+C _Z-C _PV-C _wind-C _ES-C _B) (6)

C _B＝38(P _PV+P _wind) (7)

C _Z＝kR (8)

Wherein, C _b---equipment basic charge as per installed capacity, shown in (7);

C _s---electricity price difference band carrys out income;

C _z---government subsidy expense, shown in (8);

K---unit capacity government subsidy expense;

R---join the capacity of energy-storage battery.

The described setting for constraint condition, main consider energy-storage battery discharge and recharge the constraint of dump energy, the discharge and recharge Constraints of Equilibrium of accumulator system and current transformer loss constraint; Wherein,

(1) battery charging and discharging constraint, energy-storage battery discharge and recharge needs the situation considering its efficiency for charge-discharge and dump energy, otherwise has considerable influence to battery life loss, and dump energy constraint is such as formula shown in (9).

0.1R≤SOC(t)≤0.9R (9)

(2) current transformer loss constraint, considers the conversion efficiency of energy accumulation current converter in the calculation, and every section of time load rate is different, and conversion efficiency is also in change; Pass through, the error rate through 4 matchings is less than 5%, and the polynomial function of the conversion efficiency discrete points data matching conversion efficiency curve of corresponding energy accumulation current converter manufacturer is such as formula shown in (10):

$\left\{\begin{array}{c}y=-0.0031x^4+0.0603x^3-0.4543x^2+2.1589x+92.483\\ x=SOC\left(t\right)/R\end{array}\right.---\left(10\right)$

Wherein, x---load factor;

Y---conversion efficiency;

SOC (t)---t energy storage dump energy.

(3) energy-storage battery life-span constraint, data are provided to show according to energy-storage lithium battery manufacturer, when proper use of energy-storage battery, the cycle index of cell is 4500 times, suppose energy storage device complete discharge and recharge every day once, then its life-span is 12.3, and when many Battery packs form system jointly, the life-span of whole system also can be affected, reduce to 60% of cell, therefore, the energy storage battery system life-span that many Battery packs are formed is designated as 7.4 years, so when computing equipment cost and operation maintenance expense, consider that equipment substitutes expense;

The invention has the beneficial effects as follows and use energy-storage battery to regulate the load that peak-valley difference is large, the income that the constraint of consideration energy-storage battery, discharge and recharge Constraints of Equilibrium, current transformer efficiency and electricity price difference band come, macroeconomic configuration is carried out to the micro-grid system comprising honourable equipment, obtains the stored energy capacitance allocation plan of income the best.

Accompanying drawing explanation

Fig. 1 is that Qinghai typical daylight is according to radiation intensity histogram;

Fig. 2 to exert oneself histogram for typical case's day blower fan;

Fig. 3 is the biogeography optimized algorithm process flow diagram after improving;

Fig. 4 is energy-storage battery charging and discharging curve figure in example;

Fig. 5 is load variations and peak interval of time correlation curve figure before and after peak load shifting;

Fig. 6 is partial data yield curve figure;

Fig. 7 is peak-valley ratio change curve;

Embodiment

The present invention proposes a kind of capacity collocation method of accumulator system of peak load shifting, be mainly used to solve the stored energy capacitance allocation problem realizing peak load shifting in micro-grid system, accumulator system is utilized to reduce the peak-valley difference of load, reduce line loss, improve resource utilization, adopt actual electric network load data to verify, obtain accumulator system charge-discharge electric power curve, finally calculate the amount of capacity of energy storage under Income Maximum situation.Be explained below in conjunction with accompanying drawing.

The capacity collocation method of the accumulator system of described peak load shifting mainly adopts following steps:

Step one: setting of exerting oneself

(1) relevant photovoltaic is exerted oneself setting, the impact of size by geographic position of exerting oneself of photovoltaic, the parameter such as intensity of solar radiation, temperature all can be different, simultaneously, size of exerting oneself and consumer institute subfam. Spiraeoideae also closely bound up, need according to the size of power consumption to adjust the photovoltaic pond plate size come into operation at any time, therefore, theory at any time exerts oneself size such as formula shown in (1):

P _PV(t)＝η _PV×W _PV×S _PV(1)

In formula, η _pV---the conversion efficiency of photovoltaic battery panel;

W _pV---average solar radiation total amount;

S _pV---the area that comes into operation of photovoltaic battery panel.

Shine radiation intensity data according to measured light one day that Jiangsu photovoltaic manufacturer adopts in Qinghai, consider deviation efficiency 95%, line loss 95%, dust affects 93%, and above efficiency is multiplied by the conversion efficiency of photovoltaic battery panel, finally calculates according to 83.9%.Light radiation intensity as shown in Figure 1.

(2) have Blowing stopper to exert oneself setting, the power that Wind turbines sends is determined jointly by conditions such as on-the-spot machine set condition, blower fan quantity, real-time wind speed.

According to the wind speed measured data that Jiangsu enterprise provides, consider that practical efficiency 95%, atmospheric density 90%, wake effect 94%, field network loss lose 98%, the reduction factor of weather effect 98% and other influences 98%, getting every 10 minutes is a sampled point, then intraday blower fan is exerted oneself as shown in Figure 2.

Step 2: calculation of capacity

Stored energy capacitance size calculates such as formula shown in (2).

$\left\{\begin{array}{c}{N}_1=\max \left(\left|{\mathrm{\ΔP}}_1\mathrm{\Δ}T\right|,\left|{\mathrm{\ΔP}}_1\mathrm{\Δ}T+{\mathrm{\ΔP}}_2\mathrm{\Δ}T\right|,\mathrm{...},\left|{\mathrm{\ΔP}}_1\mathrm{\Δ}T+{\mathrm{\ΔP}}_2\mathrm{\Δ}T+\mathrm{...}{\mathrm{\ΔP}}_N\mathrm{\Δ}T\right|\right)\\ N_2=\max \left(\left|\underset{i=1}{\overset{m_1}{\Σ}}{\mathrm{\ΔP}}_i\mathrm{\Δ}T\right|,\left|\underset{i=m_2}{\overset{m_3}{\Σ}}{\mathrm{\ΔP}}_i\mathrm{\Δ}T\right|,\mathrm{...},\left|\underset{i=m_j}{\overset{m_n}{\Σ}}{\mathrm{\ΔP}}_i\mathrm{\Δ}T\right|\right)\\ R_0=\max \left(N_1,N_2\right)\end{array}\right\}---\left(2\right)$

Wherein, Δ P _i---each moment accumulator system is exerted oneself demand, and i is positive integer;

10 minutes Δ T---sampling times;

1 ~ m ₁, m ₂~ m ₃, m _j~ m _n---need the period of trickle charge or continuous discharge in sample data.

R ₀---do not consider stored energy capacitance size when efficiency for charge-discharge and energy-storage battery working range.

N ₁for during to each time-sampling point, the maximal value in the discharge and recharge absolute value of accumulation, N ₂for the maximal value of discharge and recharge in each discharge and recharge period.

Charging and discharging state is determined according to sign, each period calculates its charging accumulated or discharge capacity, and the charge volume that computing time, section accumulation was got up or generated energy, then the maximal value of its absolute value is just the amount of capacity of energy storage needs, again according to the constraint condition of efficiency for charge-discharge and energy-storage battery surplus, show that actual energy storage needs the size of configuration.

Step 3: pricing

Each several part installation cost arranges as follows:

1) photovoltaic devices

The total cost of photovoltaic unit is made up of construction cost and O&M cost two parts, is represented by formula (3):

C _PV＝B _PVP _PV+OM _PVP _PV(3)

Wherein, C _pV---photovoltaic unit cost;

B _pV---the construction price under photovoltaic unit specific power;

OM _pV---the O&M price under photovoltaic unit specific power;

P _pV---the photovoltaic unit rated power used.

2) blower fan apparatus

The total cost of wind power generating set is made up of construction cost and O&M cost two parts, is represented by formula (4):

C _wind＝B _windP _wind+OM _windP _wind(4)

Wherein, C _wind---Wind turbines cost;

B _wind---the construction price under Wind turbines specific power;

OM _wind---the O&M price under Wind turbines specific power;

P _wind---the Wind turbines rated power used.

3) energy storage battery device

Consider the life-span restriction of accumulator system, must carry out the replacement of device in this article, choose cost price according to different energy storage scales, then the cost of battery energy storage system is such as formula shown in (5):

$\left\{\begin{array}{c}{C}_{ES}=\left(\frac{L_{PV}}{L_{ES}}\right)B_{ES}R\\ B_{ES}=B_{Storage}+B_{Conversion}+B_{Balance}\end{array}\right.---\left(5\right)$

Wherein, C _eS---battery energy storage system cost;

L _pV---the life-span of photovoltaic unit;

L _eS---the life-span of energy-storage battery;

B _eS---the construction price under energy-storage battery unit capacity;

R---join the capacity of energy-storage battery;

B _storage---the stored energy price of energy-storage battery;

B _conversion---the energy conversion price of energy-storage battery;

B _balance---the balancing energy price of energy-storage battery.

4) optimization aim of accumulator system configuration comprises the calculating of the income that unit cost, operation maintenance expense, government subsidy, equipment basic charge as per installed capacity and electricity price difference band come: the cost-operation maintenance cost-basic charge as per installed capacity of the income+government subsidy-original unit of total revenue=segmentation electricity price, basic charge as per installed capacity (transformer capacity expense)=maximum demand * 38 yuan/kW, maximum demand refers to electric power during electricity consumption top, namely power when device all goes into operation, then total revenue is such as formula shown in (6).

C＝max(C _S+C _Z-C _PV-C _wind-C _ES-C _B) (6)

C _B＝38(P _PV+P _wind) (7)

C _Z＝kR (8)

Wherein, C _b---equipment basic charge as per installed capacity, shown in (7);

C _s---electricity price difference band carrys out income;

C _z---government subsidy expense, shown in (8);

K---unit capacity government subsidy expense;

R---join the capacity of energy-storage battery.

Step 4: constraint condition

According to the constraint in battery specific works and burden requirement, set up following constraint condition:

(1) battery charging and discharging constraint

Energy-storage battery discharge and recharge needs the situation considering its efficiency for charge-discharge and dump energy, otherwise there is considerable influence to battery life loss, through the experimental data explanation of active distribution network Technology R & D Center of Beijing Jiaotong University, efficiency for charge-discharge is 90%, discharge and recharge interval selection 10% to 90%, its depth of discharge is 80%.

Dump energy constraint is such as formula shown in (9).

0.1R≤SOC(t)≤0.9R (9)

(2) current transformer loss constraint

Consider the conversion efficiency of energy accumulation current converter in the calculation, every section of time load rate is different, and conversion efficiency is also in change.By the conversion efficiency discrete points data matching conversion efficiency curve of energy accumulation current converter manufacturer, the error rate through 4 matchings is less than 5%, and corresponding polynomial function is such as formula shown in (10):

$\{\begin{array}{c}y=-0.0031x^4+0.0603x^3-0.4543x^2+2.1589x+92.483\\ x=SOC\left(t\right)/R\end{array}---\left(10\right)$

Wherein, x---load factor;

Y---conversion efficiency;

SOC (t)---t energy storage dump energy.

(3) energy-storage battery life-span constraint

Data are provided to show according to energy-storage lithium battery manufacturer, when proper use of energy-storage battery, the cycle index of cell is approximately 4500 times, suppose energy storage device complete discharge and recharge every day once, then its life-span is approximately 12.3, and when many Battery packs form system jointly, the life-span of whole system also can be affected, approximately reduce to 60% of cell, therefore, the energy storage battery system life-span that many Battery packs are formed is designated as 7.4 years, so when computing equipment cost and operation maintenance expense, consider that equipment substitutes expense.

Step 5: algorithm is write

In particle cluster algorithm, the process of optimizing is finding particle best in individuality always, and the individuality of suboptimum has all been left in the basket, in biogeography optimized algorithm, each individuality has shares the possibility that characteristic sum accepts other individual good feature, can overcome the local convergence situation that particle cluster algorithm may occur like this, can utilize the iteratively faster mode of particle cluster algorithm simultaneously, biogeography optimized algorithm is simplified more, reaches the effect of Fast Convergent.

Particle cluster algorithm hypothesis flock of birds is looked for food in a D dimension space, D represents the number of the unknown amount of solving, so every bird is exactly a particle, the colony that flock of birds is namely formed by m particle, each particle is represented by self position and velocity vector, the position vector of i-th particle represents such as formula (11), and the velocity vector of i-th particle represents such as formula (12).

$\stackrel{\→}{x_i}=(x_{i1},x_{i2},x_{i3},...,x_{iD})(i=1,2,3,...,m)---\left(11\right)$

$\stackrel{\→}{v_i}=(v_{i1},v_{i2},v_{i3},...,v_{iD}),(i=1,2,3,...,m)---\left(12\right)$

Every bird all can a lot of target of approach in flight course, and will produce self-optimal correction, the desired positions of process in flight course is defined as p by us _i, and whole ethnic group the desired positions of process be defined as p _g, shown in (13) and (14).

$\stackrel{\→}{p_i}=(p_{i1},p_{i2},p_{i3},...,p_{iD}),(i=1,2,3,...,m)---\left(13\right)$

$\stackrel{\→}{p_g}=(p_{g1},p_{g2},p_{g3},...,p_{gD}),(g=1,2,3,...,m)---\left(14\right)$

Each particle constantly adjusts velocity vector and the position of oneself by self inertia and colony's history optimal location, and its change represents such as formula (15).

$\begin{array}{c}\left\{\begin{array}{c}{v}_{id}^{t+1}=v_{id}^t+c_1{r}_1(p_{id}^t-x_{id}^t)+c_2{r}_2(p_{gd}^t-x_{id}^t)\\ x_{id}^{t+1}=x_{id}^t+v_{id}^{t+1}\end{array}\right.\\ \left(i=1,2,\mathrm{...},m;d=1,2,\mathrm{...},D\right)\end{array}---\left(15\right)$

Wherein, c ₁, c ₂---Studying factors, nonnegative constant, plays the effect summed up to team learning and oneself;

R ₁, r ₂---the random number in interval [0,1];

V _id---absolute value range is no more than maximal rate v _max;

T---the algebraically of current calculating.

Here it is initial particle cluster algorithm, in order to improve the applicability of this algorithm, introduces inertial coefficient ω, formula (15) is changed an accepted way of doing sth (16), namely now common standard particle colony optimization algorithm.

$\begin{array}{c}\left\{\begin{array}{c}{v}_{id}^{t+1}={\mathrm{\ωv}}_{id}^t+c_1{r}_1(p_{id}^t-x_{id}^t)+c_2{r}_2(p_{gd}^t-x_{id}^t)\\ x_{id}^{t+1}=x_{id}^t+v_{id}^{t+1}\end{array}\right.\\ \left(i=1,2,\mathrm{...},m;d=1,2,\mathrm{...},D\right)\end{array}---\left(16\right)$

The present invention adopts the biogeography optimized algorithm of improvement, the advantage of two kinds of algorithms combines by innovatory algorithm, in particle cluster algorithm, each particle constantly adjusts velocity vector and the position of oneself by self inertia and colony's history optimal location, the iterative manner of particle cluster algorithm and formula (16) is used to substitute the mutation operation of biogeography algorithm, after can making particle evolution like this, there is better feature, it also avoid the drawback of particle cluster algorithm Premature Convergence, convergence is good, and computing velocity is fast.Concrete operation step is as follows: (algorithm flow as shown in Figure 3)

Step 1: habitat initialization, namely sets initial habitat matrix, and setting evolutionary generation t is 1, maximum evolutionary generation t _max, and the suitability degree of each habitat of initialization is vectorial, and each vector represents a solution;

Step 2: the ideal adaptation degree of each habitat is calculated, evaluate the fitness index of habitat current state, and calculate entry/leave rate and the species quantity of this habitat, suitability degree represents in electric system the capital and operation cost that meet electricity needs;

Step 3: judge whether to enter Transfer free energy, upgrades the habitat parameter after migrating;

Step 4: the renewal parameter of non-for a part outstanding habitat being carried out particle cluster algorithm, enters next iteration using the habitat not having secondary to upgrade after the habitat after renewal and Transfer free energy as new habitat sample;

Step 5: judge whether to reach iterations, does not then return step 2 and calculates, otherwise export current optimum solution.

Example explanation

Example is arranged

1) algorithm is arranged, and habitat number is set to 100, i.e. stochastic generation 100 groups of feasible solutions, iteration maximum times is set to 100, and dimension is set to 2, i.e. independent variable number, secondary upgrades number and is set to 30, and 30 groups of feasible solutions that namely suitability degree is the poorest need secondary to upgrade habitat parameter, and sampling interval is set to 10 minutes.

2) load data illustrates, Beijing one daily load data that patent example adopts one group of Utilities Electric Co. to provide, this group data peak load 16495.31kW, minimum load 8627.056kW, then peak-valley ratio is about 47.7%, considers government subsidy 500 yuan/kWh.

Simulation Example result

First need to import load data in algorithm, calculate blower fan photovoltaic exert oneself and the algebraic sum of load as initial curve, the valley load number after setting peak load shifting is unknown independent variable P _min, namely payload is less than this standard value, and the unnecessary electricity of blower fan and photovoltaic just charges to energy storage device, and the peak load number after setting peak load shifting is unknown independent variable P _max, when load exceedes peak value standard, blower fan and photovoltaic provide not enough electric energy just to be provided by energy storage device.In computation process, constantly statistics discharge and recharge total amount, when discharge and recharge reaches equilibrium state, namely total charging equal or exceed only discharge capacity 1% time, then can calculate the capacity of energy storage.Referred fragment electricity price is as table 1.

Table 1 peak interval of time electricity price

With reference to honourable cost as table 2.

The each installation cost parameter of table 2

Table 3 is selected from reference to energy-storage battery cost.

The project cost of table 3 battery energy storage system

By algorithm simulating, choose wherein 10 groups of data and carry out interpretation of result.

Choose 10 groups low valley P _minbe respectively 9800kW, 10100kW, 10400kW, 10700kW, 11000kW, 11300kW, 11600kW, 11900kW, 12200kW and 12500kW to compare.Obtain energy-storage battery charging and discharging curve as shown in Figure 4.Before and after peak load shifting, load variations and peak interval of time correlation curve are as shown in Figure 5; Obtain the yield curve in 10 groups of situations, as shown in Figure 6.

Selected low valley is different, then the degree of peak load shifting is also different, chooses larger, then the degree of peak load shifting is darker, this group peak-valley ratio with capacity variation tendency as shown in Figure 7.

Algorithm draws when capacity configuration is 19.87MWh, and its income is best; Concrete data are as shown in table 4.

Table 4 example tables of data

Claims (4)

1. a capacity collocation method for the accumulator system of peak load shifting, is characterized in that, described capacity collocation method comprises setting of exerting oneself, calculation of capacity, pricing, constraint condition arranges and algorithm is write;

Described setting of exerting oneself relates generally to renewable Blast Furnace Top Gas Recovery Turbine Unit (TRT), typical case's generated output curve on the one of setting blower fan and photovoltaic generation, photovoltaic considers the factor such as deviation efficiency, line loss, dust impact, and the factors such as practical efficiency, atmospheric density, wake effect, the mistake of field network loss, weather effect considered by blower fan;

Described calculation of capacity and pricing, relate generally to the cost calculation model of computing method to stored energy capacitance and each several part device, calculation of capacity is premised on discharge and recharge every day balance, accumulation calculates the discharge and recharge of each sampling interval, and consider the interval impact on battery life of battery charging and discharging, every construction cost, O&M cost, basic charge as per installed capacity and alternative costs are partly considered in pricing;

Described constraint condition is arranged, and the optimization aim and constraint condition related generally to comprising honourable accumulator system configuration is arranged; The optimization aim of accumulator system configuration is considered from income optimization, comprising the income that the construction cost of each several part device, O&M cost, government subsidy, equipment basic charge as per installed capacity and electricity price difference band come; For the setting of constraint condition, main consider energy-storage battery discharge and recharge the constraint of dump energy, the discharge and recharge Constraints of Equilibrium of accumulator system and current transformer loss constraint;

Described algorithm writes the discharge and recharge statistics during the biogeography optimized algorithm (need to set parameters, and mutation operation is replaced with the iteratively faster mode of particle cluster algorithm) and peak load shifting relating generally to improvement; Discharge and recharge statistics is then the independent variable by setting, and cumulative discharge and recharge is expressed as the formula of band independent variable, discharge and recharge is represented by sign, and absolute value error within the specific limits, namely thinks that discharge and recharge reaches equilibrium state.

2. the capacity collocation method of a kind of accumulator system of peak load shifting according to claim 1, is characterized in that, described in setting of exerting oneself relate generally to renewable Blast Furnace Top Gas Recovery Turbine Unit (TRT) and comprise:

1) photovoltaic is exerted oneself setting, the impact of size by geographic position of exerting oneself of photovoltaic, the parameter such as intensity of solar radiation, temperature all can be different, simultaneously, size of exerting oneself and consumer institute subfam. Spiraeoideae also closely bound up, need according to the size of power consumption to adjust the photovoltaic pond plate size come into operation at any time, therefore, theory at any time exerts oneself size such as formula shown in (1):

P _PV(t)＝η _PV×W _PV×S _PV(1)

In formula, η _pV---the conversion efficiency of photovoltaic battery panel;

W _pV---average solar radiation total amount;

S _pV---the area that comes into operation of photovoltaic battery panel;

2) blower fan is exerted oneself setting, and the power that Wind turbines sends was determined originally jointly by the assembly of on-the-spot machine set condition, blower fan quantity, real-time wind speed and wind power generating set.

3. the capacity collocation method of a kind of accumulator system of peak load shifting according to claim 1, it is characterized in that, described pricing, each several part installation cost arranges as follows:

1) photovoltaic devices

The total cost of photovoltaic (PV) unit is made up of construction cost and O&M cost two parts, is represented by formula (3):

C _PV＝B _PVP _PV+OM _PVP _PV(3)

Wherein, C _pV---photovoltaic unit cost;

B _pV---the construction price under photovoltaic unit specific power;

OM _pV---the O&M price under photovoltaic unit specific power;

P _pV---the photovoltaic unit rated power used;

2) blower fan apparatus

The total cost of wind power generating set is made up of construction cost and O&M cost two parts, is represented by formula (4):

C _wind＝B _windP _wind+OM _windP _wind(4)

Wherein, C _wind---Wind turbines cost;

B _wind---the construction price under Wind turbines specific power;

OM _wind---the O&M price under Wind turbines specific power;

P _wind---the Wind turbines rated power used,

3) energy storage battery device

Consider the life-span restriction of accumulator system, must carry out the replacement of device, choose cost price according to different energy storage scales, then the cost of battery energy storage system is such as formula shown in (5):

$\left\{\begin{array}{c}{C}_{ES}=\left(\frac{L_{PV}}{L_{ES}}\right)B_{ES}R\\ B_{ES}=B_{Storage}+B_{Conversion}+B_{Balance}\end{array}\right.---\left(5\right)$

Wherein, C _eS---energy-storage battery (ES) system cost;

L _pV---the life-span of photovoltaic unit;

L _eS---the life-span of energy-storage battery;

B _eS---the construction price under energy-storage battery unit capacity;

R---join the capacity of energy-storage battery;

B _storage---the stored energy price of energy-storage battery;

B _conversion---the energy conversion price of energy-storage battery;

B _balance---the balancing energy price of energy-storage battery;

4) optimization aim of accumulator system configuration comprises the calculating of the income that unit cost, operation maintenance expense, government subsidy, equipment basic charge as per installed capacity and electricity price difference band come: the cost-operation maintenance cost-basic charge as per installed capacity of the income+government subsidy-original unit of total revenue=segmentation electricity price, basic charge as per installed capacity (transformer capacity expense)=maximum demand * 38 yuan/kW, maximum demand refers to electric power during electricity consumption top, namely power when device all goes into operation, then total revenue is such as formula shown in (6)

C＝max(C _S+C _Z-C _PV-C _wind-C _ES-C _B) (6)

C _B＝38(P _PV+P _wind) (7)

C _Z＝kR (8)

Wherein, C _b---equipment basic charge as per installed capacity, shown in (7);

C _s---electricity price difference band carrys out income;

C _z---government subsidy expense, shown in (8);

K---unit capacity government subsidy expense;

R---join the capacity of energy-storage battery.

4. the capacity collocation method of a kind of accumulator system of peak load shifting according to claim 1, it is characterized in that, the described setting for constraint condition, main consider energy-storage battery discharge and recharge the constraint of dump energy, the discharge and recharge Constraints of Equilibrium of accumulator system and current transformer loss constraint; Wherein,

(1) battery charging and discharging constraint, energy-storage battery discharge and recharge needs the situation considering its efficiency for charge-discharge and dump energy, otherwise has considerable influence to battery life loss, and dump energy retrains such as formula shown in (9),

0.1R≤SOC(t)≤0.9R (9)

(2) current transformer loss constraint, considers the conversion efficiency of energy accumulation current converter in the calculation, and every section of time load rate is different, and conversion efficiency is also in change; Pass through, the error rate through 4 matchings is less than 5%, and the polynomial function of the conversion efficiency discrete points data matching conversion efficiency curve of corresponding energy accumulation current converter manufacturer is such as formula shown in (10):

$\left\{\begin{array}{c}y=-0.0031x^4+0.0603x^3-0.4543x^2+2.1589x+92.483\\ x=SOC\left(t\right)/R\end{array}\right.---\left(10\right)$

Wherein, x---load factor;

Y---conversion efficiency;

SOC (t)---t energy storage dump energy;

(3) energy-storage battery life-span constraint, data are provided to show according to energy-storage lithium battery manufacturer, when proper use of energy-storage battery, the cycle index of cell is 4500 times, suppose energy storage device complete discharge and recharge every day once, then its life-span is 12.3, and when many Battery packs form system jointly, the life-span of whole system also can be affected, reduce to 60% of cell, therefore, the energy storage battery system life-span that many Battery packs are formed is designated as 7.4 years, so when computing equipment cost and operation maintenance expense, consider that equipment substitutes expense.