CN105958519A - Power distribution network energy storage system configuration method based on active management and cost-benefit analysis - Google Patents

Abstract

The invention relates to a power distribution network energy storage system configuration method based on active management and cost-benefit analysis, and the method comprises the following steps: S1, an active management system is established for actively managing a power distribution network, and a cost-benefit analysis system is also established and comprises an energy storage configuration model; S2, a power distribution system module reads time series data of annual load and photovoltaic power generation output, records a real-time SVR/OLTC running state and transmits to the cost-benefit analysis system and an EMS control module; S3, the EMS module compares the present voltage level data with a set voltage index and transmits charge-discharge power information to an energy storage system module to control the present voltage level in a normal range; and S4, the cost-benefit analysis system performs cost-benefit calculation on the energy storage system and optimizes the energy storage capacity configuration. According to the invention, the power distribution network active management system is established to perform the active management of the power distribution network; and the energy storage cost-benefit analysis system can accurately describe the energy storage configuration model.

Description

A kind of power distribution network energy-storage system configuration based on active management with cost effectiveness analysis Method

Technical field

The present invention relates to energy-storage system planning field in active distribution network, particularly relate to a kind of based on active management with become The power distribution network energy-storage system collocation method of this performance analysis.

Background technology

It is considered as one of the important research direction of 21 century power industry that distributed power source (DG) generates electricity by way of merging two or more grid systems.DG future Power distribution network will be accessed on a large scale.But the increase of DG permeability also will bring one to distribution network voltage, the quality of power supply, management and running The impact of series.Energy-storage system is by the regulation of its fast power and has the feature for accumulation of energy power concurrently, in smooth intermittent energy Power swing, peak load shifting, improve quality of voltage and provide stand-by power supply aspect all to give play to huge effect, being actively Power distribution network realizes the key point running the distributed energy flexible extensively accessed and the network optimization, and its configuration will be straight Connect and have influence on the active distribution network ability for distributed energy active management and the economy of the network operation.

At present, the configuration of energy storage be based on energy storage realize a certain or several functions (such as: reduce network loss, stabilize distributed Power fluctuation, power-supply fluctuation, peak load shifting etc.) optimize energy storage capacity.Due to power distribution network, distributed power source, energy storage, bear Lotus has collectively constituted actively distribution system, and actively distribution system is a unified entirety, so advising in active distribution network energy storage Only consider the effect of energy storage self in Huaing, ignore the systematicness of active distribution network, ignore the active management merit of active distribution network The traditional planning method of energy, the adaptedness making model is poor, and result of calculation is inaccurate, and the systems organization allocation plan of gained is not Rationally.

Summary of the invention

In view of this, it is an object of the invention to provide a kind of power distribution network energy storage based on active management Yu cost effectiveness analysis ' In System Reconfiguration Method, plays the active management effect of power distribution network by setting up power distribution network active management system of automotive；By energy storage cost Performance analysis system energy accurate description energy-storage system allocation models, provides the reasonable plan of energy-storage system configuration.

The present invention uses below scheme to realize: a kind of power distribution network energy-storage system based on active management Yu cost effectiveness analysis Collocation method, specifically includes following steps:

Step S1: setting up one in order to the active management system of automotive of active management power distribution network, described active management system of automotive includes joining Electricity system module, energy-storage system module and EMS module, set up one simultaneously and divide in order to configure the cost benefit of energy-storage system model Analysis system；

Step S2: described distribution system module reads year load and photovoltaic is exerted oneself the time series data under each scene, Record real-time SVR/OLTC running status, and the running status of SVR/OLTC, peak load shifting information are communicated to cost benefit Real-time busbar voltage assessment data are also flowed to EMS control module by analysis system；

Step S3:EMS module is by the voltage indexes of relatively current voltage levvl data with setting, to energy-storage system module The voltage levvl that transmission charge-discharge electric power information controls now is positioned at normal range, if now busbar voltage is out-of-limit, then leads to Cross SVR and OLTC control voltage and be positioned at normal range；Energy-storage system module estimation energy storage charge-discharge electric power now and filling Depth of discharge, and dynamically adjust energy storage charge-discharge electric power；

Step S4: described cost effectiveness analysis system obtain energy storage life cycle, SVR OLTC running status, peak load shifting After information, the cost-benefit carrying out energy-storage system calculates, and continues to optimize the capacity configuration of energy storage, to optimal allocation capacity.

Further, described distribution system module includes distributed photovoltaic power, BESS, load, SVR/OLTC；

Described energy-storage system module is in order to assess SOC and the SOH index of aging of BESS；Feed back to after SOC index evaluation EMS module, EMS module sends charge-discharge power demand instruction according to SOC state to BESS；SOH index instruction energy-storage system module The residual life cycle；

Described EMS module reaches peak load shifting in order to adjust the trend in energy storage, photovoltaic, load and network and adjusts electricity Pressure；When the uncertainty that PV exerts oneself causes overtension, EMS module sends charge requirement instruction to energy-storage system module；Electricity When pressing through low, EMS module sends electric discharge requirement command to energy-storage system module.

Further, the stored energy capacitance allocation models of described cost effectiveness analysis system is bilayer model:

The object function of described stored energy capacitance allocation models is as follows:

Internal layer optimizes:

In formula: Ω_BESSFor energy storage, node set is installed；N_sFor scene sum；

Owing to energy-storage system overall cost of ownership includes Technics of Power Electronic Conversion PSC cost, energy storage installed capacity cost and energy storage Plant running maintenance cost, energy-storage system overall cost of ownership is:

$C_{{\mathrm{BESS}}_k}=\left(\right(C_{PSC}{P}_{BESS}+\frac{C_W{W}_{BESS}}{\mathrm{\η}}\left)n_k\right)(1+{\mathrm{Cf}}_{install})\left(\frac{r{(1+r)}^y}{{(1+r)}^y-1}\right)+C_{{\mathrm{OM}}_k}+C_{{\mathrm{life}}_k}$

In formula: C_BESSAnnual energy storage overall cost of ownership is converted for kth node energy storage；C_PSCFor energy storage power electronics Changer unit cost；P_BESSFor single energy storage device rated power；C_WFor energy storage unit capacity cost of investment；W_BESSFor single Energy storage device rated capacity；Cf_installFor installation cost coefficient；R is discount rate；N is planning horizon, with year unit；η is energy storage Device conversion efficiency；Y is planning year number；Annual operating and maintenance cost for kth node energy storage；For kth node energy storage Life cycle cost；

If energy storage device belongs to grid company, it is not that third party is all then

$C_{{\mathrm{OM}}_k}=m\underset{t=1}{\overset{T}{\Σ}}\left(c_{om}{P}_k\right(t\left)\right)$

In formula: m is year natural law.T is the planning period, is divided into 24 periods；

If energy storage device belongs to the third party energy storage investor, owing to distributed energy storage filling apparatus discharging efficiency is different, and During discharge and recharge, price is different with the flow direction of fund, so:

$C_{OM}=m\underset{t=1}{\overset{T}{\Σ}}\left(c_{om}^{dc}{P}_k^{dc}\right(t)-c_{om}^{ch}{P}_k^{ch}(t\left)\right)$

In formula:It is respectively electric discharge and the charging expense of energy storage；It is respectively discharge power and charging Power；For energy storage device life cycle cost；

Via net loss cost is:

$C_{LOSS}=c_{loss}m\underset{t=1}{\overset{T}{\Σ}}\mathrm{\Δ}P\left(t\right)\mathrm{\Δ}t$

In formula: Δ P (t), Δ t be respectively Power loss and time scale；c_lossFor unit Web-based exercise；

Low-carbon (LC) annual earnings are that energy-storage system discharges when load peak, thus decrease regulating units and exert oneself, for:

$B_{{\mathrm{LC}}_k}=C_{LC}m\underset{t=1}{\overset{T}{\Σ}}{P}_k^{PG}\left(t\right)$

In formula:Exerting oneself when being used for peak regulation for energy storage；C_LCThe homogenizing year cost of electricity-generating of peak regulation it is used for for fired power generating unit；

Energy storage for low storage year occurred frequently income is:

$B_{{\mathrm{PL}}_k}=E_k^{pl}(C_{peak}-C_{offpeak})$

In formula: C_peak, C_offpeakElectricity price for load peak moment Yu non-peak moment；For energy storage for load peak The year discharge capacity in moment；

Reducing OLTC/SVR O&M income is:

In formula:The saving annual earnings of OLTC/SVR number of run are reduced for kth node；C_OLTC&SVRFor OLTC Operation and maintenance cost with SVR；cf_omOLTC/SVR O&M cost factor；T_saved, T_cycleIt is respectively the saving fortune of OLTC/SVR Places number and total cycle times, T_cycle=150,000；Energy storage year number of run for kth node；

The constraints of described stored energy capacitance allocation models is as follows:

The constraints of power-balance is:

$P_{is}=U_i\underset{j\∈i}{\Σ}{U}_j(G_{ij}{\mathrm{cos\θ}}_{ij}+B_{ij}{\mathrm{sin\θ}}_{ij})$

$Q_{is}=U_i\underset{j\∈i}{\Σ}{U}_j(G_{ij}{\mathrm{sin\θ}}_{ij}-B_{ij}{\mathrm{cos\θ}}_{ij})$

In formula: P_isAnd Q_isIt is respectively the meritorious injection of node i and idle injection；U_iVoltage magnitude for node i；

J ∈ i represents that node j is connected with node i；G_ijAnd B_ijIt is respectively real part and the imaginary part of bus admittance matrix；θ_ijFor joint Point i, the phase angle difference between j.

Voltage constraints is:

U_min≤U_i≤U_max

In formula: U_minAnd U_maxIt is respectively the voltage magnitude bound of node i；

Number constraints is installed in energy storage:

$N_{BESS}^{\min }\≤N_{BESS}\≤N_{BESS}^{\max }$

Energy storage charge-discharge electric power constraints is:

-P_kmax≤P_k(t)≤P_kmax

-Q_kmax≤Q_k(t)≤Q_kmax

$\sqrt{{\left(P_k\right(t\left)\right)}^2+{\left(Q_k\right(t\left)\right)}^2}\≤S_{kmax}$

In formula: P_k(t) and Q_kT () is respectively the meritorious and idle of t kth inverter output；S_kmaxAnd Q_kmaxRespectively Rated capacity and the reactive power upper limit for kth inverter；

Energy storage charging and discharging state constraints is:

The charging and discharging state of energy storage has seriality in sequential, and the energy storage energy of each time point should meet SOC The upper limit requirement of state, should make initial SOC keep consistent, then with final SOC state within a fixed cycle simultaneously:

$S_k^{soc}\left(t\right)-S_k^{soc}(t+\mathrm{\Δ}t)=\frac{P_k\left(t\right)\mathrm{\Δ}t}{C_k}$

$S_{kmin}^{soc}\≤S_k^{soc}\left(t\right)\≤S_{kmax}^{soc}$

$S_k^{soc}\left(0\right)=S_k^{soc}\left(T\right)$

In formula: k=1,2 ... .N_st；SOC value for t kth energy storage；

Further, described step S4 uses genetic algorithm to solve bilayer model with sequential quadratic programming algorithm: Determined the stored energy capacitance of outer layer by genetic algorithm, internal layer optimizes the charge-discharge electric power of energy storage by sequential quadratic programming algorithm, Optimization aim is peak load shifting and voltage pulsation.

Compared with prior art, the present invention plays the active management work of power distribution network by setting up power distribution network active management system of automotive With；By energy storage cost effectiveness analysis system energy accurate description energy-storage system allocation models.

Accompanying drawing explanation

Fig. 1 is the overall system architecture schematic diagram of the present invention.

Fig. 2 is that in the present invention, EMS controls part energy storage charging control strategy figure.

Fig. 3 is that in the present invention, EMS controls part energy storage control of discharge policy map.

Fig. 4 is the algorithm flow chart of the cost effectiveness analysis system of the present invention.

Detailed description of the invention

Below in conjunction with the accompanying drawings and embodiment the present invention will be further described.

The present embodiment provides a kind of power distribution network energy-storage system collocation method based on active management Yu cost effectiveness analysis, as Shown in Fig. 1, specifically include following steps:

Step S1: setting up one in order to the active management system of automotive of active management power distribution network, described active management system of automotive includes joining Electricity system module, energy-storage system module and EMS module, set up one simultaneously and divide in order to configure the cost benefit of energy-storage system model Analysis system；

Step S2: described distribution system module reads year load and photovoltaic is exerted oneself the time series data under each scene, Record real-time SVR/OLTC running status, and the running status of SVR/OLTC, peak load shifting information are communicated to cost benefit Real-time busbar voltage assessment data are also flowed to EMS control module by analysis system；

Step S3:EMS module is by the voltage indexes of relatively current voltage levvl data with setting, to energy-storage system module The voltage levvl that transmission charge-discharge electric power information controls now is positioned at normal range, if now busbar voltage is out-of-limit, then leads to Cross SVR and OLTC control voltage and be positioned at normal range；Energy-storage system module estimation energy storage charge-discharge electric power now and filling Depth of discharge, and dynamically adjust energy storage charge-discharge electric power；

Step S4: described cost effectiveness analysis system obtain energy storage life cycle, SVR OLTC running status, peak load shifting After information, the cost-benefit carrying out energy-storage system calculates, and continues to optimize the capacity configuration of energy storage, to optimal allocation capacity.

In the present embodiment, persistently carrying out according to above step, described energy-storage system module will update SOC state and fortune Row service life state (SOH), until the service life state of energy storage reaches operational limit.

In the present embodiment, described distribution system module includes distributed photovoltaic power, BESS, load, SVR/OLTC；Its Middle distributed power source is exerted oneself and is had uncertainty, is divided into multiple scene of exerting oneself.SVR/OLTC device is used for voltage-regulation；

Described energy-storage system module is in order to assess SOC and the SOH index of aging of BESS, by the active of SOC and SOH Management can be with parameters such as the charge-discharge electric power of active accommodation energy storage device and discharge and recharge number of times so that energy storage can operate in normally Duty；Feeding back to EMS module after SOC index evaluation, EMS module sends charge-discharge power demand according to SOC state to BESS and refers to Order；The residual life cycle of SOH index instruction energy-storage system module.

The control centre of described EMS module whole active distribution system, in order to adjust energy storage, photovoltaic, load and network In trend reach peak load shifting and adjust voltage, by voltage condition and the charge power of energy-storage system of distribution system, fill Discharge condition contrasts with the control parameter of input, by the discharge and recharge initial time of comparing result real time coordination energy-storage system And charge-discharge electric power, it is achieved that energy storage is to voltage and the active management of peak load shifting；The uncertainty exerted oneself as PV causes During overtension, EMS module sends charge requirement instruction to energy-storage system module；During brownout, EMS module is to energy-storage system Module sends electric discharge requirement command.

In the present embodiment, the stored energy capacitance allocation models of described cost effectiveness analysis system is bilayer model, at model In relate to the investment operating cost of energy storage, life cycle cost, Web-based exercise, low-carbon (LC) income, peak load shifting arbitrage income, subtract The operation income of other voltage adjusting devices in few electrical network:

The object function of described stored energy capacitance allocation models is as follows:

Internal layer optimizes:

In formula: Ω_BESSFor energy storage, node set is installed；N_sFor scene sum；

Owing to energy-storage system overall cost of ownership includes Technics of Power Electronic Conversion PSC cost, energy storage installed capacity cost and energy storage Plant running maintenance cost, energy-storage system overall cost of ownership is:

$C_{{\mathrm{BESS}}_k}=\left(\right(C_{PSC}{P}_{BESS}+\frac{C_W{W}_{BESS}}{\mathrm{\η}}\left)n_k\right)(1+{\mathrm{Cf}}_{install})\left(\frac{r{(1+r)}^y}{{(1+r)}^y-1}\right)+C_{{\mathrm{OM}}_k}+C_{{\mathrm{life}}_k}$

In formula: C_BESSAnnual energy storage overall cost of ownership is converted for kth node energy storage；C_PSCFor energy storage power electronics Changer unit cost；P_BESSFor single energy storage device rated power；C_WFor energy storage unit capacity cost of investment；W_BESSFor single Energy storage device rated capacity；Cf_installFor installation cost coefficient；R is discount rate；N is planning horizon, with year unit；η is energy storage Device conversion efficiency；Y is planning year number；Annual operating and maintenance cost for kth node energy storage；For kth node energy storage Life cycle cost；

If energy storage device belongs to grid company, it is not that third party is all then

$C_{{\mathrm{OM}}_k}=m\underset{t=1}{\overset{T}{\Σ}}\left(c_{om}{P}_k\right(t\left)\right)$

In formula: m is year natural law.T is the planning period, is divided into 24 periods；

If energy storage device belongs to the third party energy storage investor, owing to distributed energy storage filling apparatus discharging efficiency is different, and During discharge and recharge, price is different with the flow direction of fund, so:

$C_{OM}=m\underset{t=1}{\overset{T}{\Σ}}\left(c_{om}^{dc}{P}_k^{dc}\right(t)-c_{om}^{ch}{P}_k^{ch}(t\left)\right)$

In formula:It is respectively electric discharge and the charging expense of energy storage；It is respectively discharge power and charging Power；For energy storage device life cycle cost；

Via net loss cost is:

$C_{LOSS}=c_{loss}m\underset{t=1}{\overset{T}{\Σ}}\mathrm{\Δ}P\left(t\right)\mathrm{\Δ}t$

In formula: Δ P (t), Δ t be respectively Power loss and time scale；c_lossFor unit Web-based exercise；

Low-carbon (LC) annual earnings are that energy-storage system discharges when load peak, thus decrease regulating units and exert oneself, for:

$B_{{\mathrm{LC}}_k}=C_{LC}m\underset{t=1}{\overset{T}{\Σ}}{P}_k^{PG}\left(t\right)$

In formula:Exerting oneself when being used for peak regulation for energy storage；C_LCThe homogenizing year cost of electricity-generating of peak regulation it is used for for fired power generating unit；

Energy storage for low storage year occurred frequently income is:

$B_{{\mathrm{PL}}_k}=E_k^{pl}(C_{peak}-C_{offpeak})$

In formula: C_peak, C_offpeakElectricity price for load peak moment Yu non-peak moment；For energy storage for load peak The year discharge capacity in moment；

Reducing OLTC/SVR O&M income is:

In formula:The saving annual earnings of OLTC/SVR number of run are reduced for kth node；C_OLTC&SVRFor OLTC Operation and maintenance cost with SVR；cf_omOLTC/SVR O&M cost factor；T_saved, T_cycleIt is respectively the saving fortune of OLTC/SVR Places number and total cycle times, T_cycle=150,000；Energy storage year number of run for kth node；

The constraints of described stored energy capacitance allocation models is as follows:

The constraints of power-balance is:

$P_{is}=U_i\underset{j\∈i}{\Σ}{U}_j(G_{ij}{\mathrm{cos\θ}}_{ij}+B_{ij}{\mathrm{sin\θ}}_{ij})$

$Q_{is}=U_i\underset{j\∈i}{\Σ}{U}_j(G_{ij}{\mathrm{sin\θ}}_{ij}-B_{ij}{\mathrm{cos\θ}}_{ij})$

In formula: P_isAnd Q_isIt is respectively the meritorious injection of node i and idle injection；U_iVoltage magnitude for node i；

J ∈ i represents that node j is connected with node i；G_ijAnd B_ijIt is respectively real part and the imaginary part of bus admittance matrix；θ_ijFor joint Point i, the phase angle difference between j.

Voltage constraints is:

U_min≤U_i≤U_max

In formula: U_minAnd U_maxIt is respectively the voltage magnitude bound of node i；

Number constraints is installed in energy storage:

$N_{BESS}^{\min }\≤N_{BESS}\≤N_{BESS}^{\max }$

Energy storage charge-discharge electric power constraints is:

-P_kmax≤P_k(t)≤P_kmax

-Q_kmax≤Q_k(t)≤Q_kmax

$\sqrt{{\left(P_k\right(t\left)\right)}^2+{\left(Q_k\right(t\left)\right)}^2}\≤S_{kmax}$

In formula: P_k(t) and Q_kT () is respectively the meritorious and idle of t kth inverter output；S_kmaxAnd Q_kmaxRespectively Rated capacity and the reactive power upper limit for kth inverter；

Energy storage charging and discharging state constraints is:

The charging and discharging state of energy storage has seriality in sequential, and the energy storage energy of each time point should meet SOC The upper limit requirement of state, should make initial SOC keep consistent, then with final SOC state within a fixed cycle simultaneously:

$S_k^{soc}\left(t\right)-S_k^{soc}(t+\mathrm{\Δ}t)=\frac{P_k\left(t\right)\mathrm{\Δ}t}{C_k}$

$S_{kmin}^{soc}\≤S_k^{soc}\left(t\right)\≤S_{kmax}^{soc}$

$S_k^{soc}\left(0\right)=S_k^{soc}\left(T\right)$

In formula: k=1,2 ... .N_st；SOC value for t kth energy storage.

In the present embodiment, as in figure 2 it is shown, the energy storage charging control strategy of described EMS module is particularly as follows: work as voltage and more go up In limited time, charging signals is passed to energy-storage system by EMS module, if now charge power is less than or equal to maximum charge power, then It is charged with power now；If more than maximum charge power, OLTC/SVR adjusting voltage, and record OLTC/SVR's Number of run.

In the present embodiment, as it is shown on figure 3, the energy storage control of discharge strategy of described EMS module particularly as follows: when voltage more under When limit or peak load (peak load) reach preset value, discharge signal is passed to energy-storage system by EMS, if now discharging Power less than or equal to maximum discharge power, then discharges with power now；If more than maximum discharge power, by OLTC/ SVR adjusts voltage, and records the number of run of OLTC/SVR.

In the present embodiment, as shown in Figure 4, described step S4 uses genetic algorithm and sequential quadratic programming algorithm to bilayer Model solves: determined the stored energy capacitance of outer layer by genetic algorithm, produces the initial population of energy storage installed capacity, fitness Function is that cost effectiveness analysis result is optimum；Internal layer optimizes the charge-discharge electric power of energy storage by sequential quadratic programming algorithm, optimizes Target is peak load shifting and voltage pulsation.Wherein, the function of active management system of automotive is realized by internal layer optimization.

The foregoing is only presently preferred embodiments of the present invention, all impartial changes done according to scope of the present invention patent with Modify, all should belong to the covering scope of the present invention.

Claims (4)

1. a power distribution network energy-storage system collocation method based on active management Yu cost effectiveness analysis, it is characterised in that: concrete Comprise the following steps:

Step S1: setting up one in order to the active management system of automotive of active management power distribution network, described active management system of automotive includes power distribution system System module, energy-storage system module and EMS module, set up a cost effectiveness analysis system including stored energy capacitance allocation models simultaneously System；

Step S2: described distribution system module reads year load and photovoltaic is exerted oneself the time series data under each scene, record Real-time SVR/OLTC running status, and the running status of SVR/OLTC, peak load shifting information are communicated to cost effectiveness analysis Real-time busbar voltage assessment data are also flowed to EMS control module by system；

Step S3:EMS module, by the voltage indexes of relatively current voltage levvl data with setting, sends to energy-storage system module The voltage levvl that charge-discharge electric power information controls now is positioned at normal range, if now busbar voltage is out-of-limit, then passes through SVR And OLTC controls voltage and is positioned at normal range；Energy-storage system module estimation energy storage charge-discharge electric power now and discharge and recharge are deep Degree, and dynamically adjust energy storage charge-discharge electric power；

Step S4: described cost effectiveness analysis system obtain energy storage life cycle, SVR OLTC running status, peak load shifting information After, the cost-benefit carrying out energy-storage system calculates, and continues to optimize the capacity configuration of energy storage, to optimal allocation capacity.

A kind of power distribution network energy-storage system configuration side based on active management Yu cost effectiveness analysis the most according to claim 1 Method, it is characterised in that: described distribution system module includes distributed photovoltaic power, BESS, load, SVR/OLTC；

Described energy-storage system module is in order to assess SOC and the SOH index of aging of BESS；EMS mould is fed back to after SOC index evaluation Block, EMS module sends charge-discharge power demand instruction according to SOC state to BESS；The residue longevity of SOH index instruction energy-storage system module The life cycle；

Described EMS module reaches peak load shifting in order to adjust the trend in energy storage, photovoltaic, load and network and adjusts voltage； When the uncertainty that PV exerts oneself causes overtension, EMS module sends charge requirement instruction to energy-storage system module；Voltage mistake Time low, EMS module sends electric discharge requirement command to energy-storage system module.

A kind of power distribution network energy-storage system configuration side based on active management Yu cost effectiveness analysis the most according to claim 1 Method, it is characterised in that:

The stored energy capacitance allocation models of described cost effectiveness analysis system is bilayer model:

The object function of described stored energy capacitance allocation models is as follows:

Internal layer optimizes:

In formula: Ω_BESSFor energy storage, node set is installed；N_sFor scene sum；

Owing to energy-storage system overall cost of ownership includes Technics of Power Electronic Conversion PSC cost, energy storage installed capacity cost and energy storage device Operation expense, energy-storage system overall cost of ownership is:

$C_{{\mathrm{BESS}}_k}=\left(\right(C_{PSC}{P}_{BESS}+\frac{C_W{W}_{BESS}}{\mathrm{\η}}\left)n_k\right)(1+{\mathrm{Cf}}_{install})\left(\frac{r{(1+r)}^y}{{(1+r)}^y-1}\right)+C_{{\mathrm{OM}}_k}+C_{{\mathrm{life}}_k}$

In formula: C_BESSAnnual energy storage overall cost of ownership is converted for kth node energy storage；C_PSCFor energy storage converters Unit cost；P_BESSFor single energy storage device rated power；C_WFor energy storage unit capacity cost of investment；W_BESSFill for single energy storage Put rated capacity；Cf_installFor installation cost coefficient；R is discount rate；N is planning horizon, with year unit；η is that energy storage device turns Change efficiency；Y is planning year number；Annual operating and maintenance cost for kth node energy storage；Week in life-span for kth node energy storage Current cost；

If energy storage device belongs to grid company, it is not that third party is all then

$C_{{\mathrm{OM}}_k}=m\underset{t=1}{\overset{T}{\Σ}}\left(c_{om}{P}_k\right(t\left)\right)$

In formula: m is year natural law.T is the planning period, is divided into 24 periods；

If energy storage device belongs to the third party energy storage investor, owing to distributed energy storage filling apparatus discharging efficiency is different, and charge and discharge During electricity, price is different with the flow direction of fund, so:

$C_{OM}=m\underset{t=1}{\overset{T}{\Σ}}\left(c_{om}^{dc}{P}_k^{dc}\right(t)-c_{om}^{ch}{P}_k^{dc}(t\left)\right)$

In formula:It is respectively electric discharge and the charging expense of energy storage；It is respectively discharge power and charge power；For energy storage device life cycle cost；

Via net loss cost is:

$C_{LOSS}=c_{loss}m\underset{t=1}{\overset{T}{\Σ}}\mathrm{\Δ}P\left(t\right)\mathrm{\Δ}t$

In formula: Δ P (t), Δ t be respectively Power loss and time scale；c_lossFor unit Web-based exercise；

Low-carbon (LC) annual earnings are that energy-storage system discharges when load peak, thus decrease regulating units and exert oneself, for:

$B_{{\mathrm{LC}}_k}=C_{LC}m\underset{t=1}{\overset{T}{\Σ}}{P}_k^{PG}\left(t\right)$

In formula:Exerting oneself when being used for peak regulation for energy storage；C_LCThe homogenizing year cost of electricity-generating of peak regulation it is used for for fired power generating unit；

Energy storage for low storage year occurred frequently income is:

$B_{{\mathrm{PL}}_k}=E_k^{pl}(C_{peak}-C_{offpeak})$

In formula: C_peak, C_offpeakElectricity price for load peak moment Yu non-peak moment；For energy storage for the load peak moment Year discharge capacity；

Reducing OLTC/SVR O&M income is:

In formula:The saving annual earnings of OLTC/SVR number of run are reduced for kth node；C_OLTC&SVRFor OLTC with The operation and maintenance cost of SVR；cf_omOLTC/SVR O&M cost factor；T_saved, T_cycleThe saving being respectively OLTC/SVR runs Number of times and total cycle times, T_cycle=150,000；Energy storage year number of run for kth node；

The constraints of described stored energy capacitance allocation models is as follows:

The constraints of power-balance is:

$P_{is}=U_i\underset{j\∈i}{\Σ}{U}_j(G_{ij}{\mathrm{cos\θ}}_{ij}+B_{ij}{\mathrm{sin\θ}}_{ij})$

$Q_{is}=U_i\underset{j\∈i}{\Σ}{U}_j(G_{ij}{\mathrm{sin\θ}}_{ij}-B_{ij}{\mathrm{cos\θ}}_{ij})$

In formula: P_isAnd Q_isIt is respectively the meritorious injection of node i and idle injection；U_iVoltage magnitude for node i；

J ∈ i represents that node j is connected with node i；G_ijAnd B_ijIt is respectively real part and the imaginary part of bus admittance matrix；θ_ijFor node i, Phase angle difference between j；

Voltage constraints is:

U_min≤U_i≤U_max

In formula: U_minAnd U_maxIt is respectively the voltage magnitude bound of node i；

Number constraints is installed in energy storage:

$N_{BESS}^{\min }\≤N_{BESS}\≤N_{BESS}^{\max }$

Energy storage charge-discharge electric power constraints is:

-P_kmax≤P_k(t)≤P_kmax

-Q_kmax≤Q_k(t)≤Q_kmax

$\sqrt{{\left(P_k\right(t\left)\right)}^2+{\left(Q_k\right(t\left)\right)}^2}\≤S_{kmax}$

In formula: P_k(t) and Q_kT () is respectively the meritorious and idle of t kth inverter output；S_kmaxAnd Q_kmaxIt is respectively kth The rated capacity of individual inverter and the reactive power upper limit；

Energy storage charging and discharging state constraints is:

The charging and discharging state of energy storage has seriality in sequential, and the energy storage energy of each time point should meet SOC state Upper limit requirement, initial SOC should be made within a fixed cycle to keep consistent, then with final SOC state simultaneously:

$S_k^{soc}\left(t\right)-S_k^{soc}(t+\mathrm{\Δ}t)=\frac{P_k\left(t\right)\mathrm{\Δ}t}{C_k}$

$S_{kmin}^{soc}\≤S_k^{soc}\left(t\right)\≤S_{kmax}^{soc}$

$S_k^{soc}\left(0\right)=S_k^{soc}\left(T\right)$

In formula: k=1,2 ... .N_st；SOC value for t kth energy storage.

A kind of power distribution network energy-storage system configuration side based on active management Yu cost effectiveness analysis the most according to claim 1 Method, it is characterised in that: described step S4 uses genetic algorithm to solve bilayer model with sequential quadratic programming algorithm: pass through Genetic algorithm determines the stored energy capacitance of outer layer, and internal layer optimizes the charge-discharge electric power of energy storage by sequential quadratic programming algorithm, optimizes Target is peak load shifting and voltage pulsation.