CN112865146A - Method for generating coordinated operation strategy of user-side energy storage system - Google Patents

Method for generating coordinated operation strategy of user-side energy storage system Download PDF

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CN112865146A
CN112865146A CN202110136891.3A CN202110136891A CN112865146A CN 112865146 A CN112865146 A CN 112865146A CN 202110136891 A CN202110136891 A CN 202110136891A CN 112865146 A CN112865146 A CN 112865146A
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刘文霞
杨梦瑶
张舒婷
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North China Electric Power University
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    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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Abstract

The invention provides a generation method of a coordinated operation strategy of a user-side energy storage system, which is based on an energy storage system equipment cost model and an energy storage system equipment operation profit model, under the existing market price mechanism, based on the principle of obtaining high profit by priority selection, the economy of different profits obtained by the energy storage system in participation is compared, the energy storage operation power and the duration time at t are determined according to the sequence of delaying the power grid upgrading and transformation profits, improving the power supply reliability profit, participating in the electric energy market profit and participating in the auxiliary service market profit of the energy storage system, and finally the energy storage system operation condition at each hour every day is determined.

Description

Method for generating coordinated operation strategy of user-side energy storage system
Technical Field
The invention belongs to the technical field of energy storage system operation, and particularly relates to a generation method of a coordinated operation strategy of a user-side energy storage system.
Background
In order to deal with the dual pressure of energy crisis and environmental pollution, a large number of clean power supplies such as wind power and photovoltaic power supplies and reelectrification equipment such as electric automobiles and electric heating are connected into a power grid, so that the standby demand, peak-valley difference and peak regulation pressure of the power grid are obviously increased. Energy storage systems (ES) are receiving increasing attention as a new technology to participate in system peak shaving due to their excellent regulation performance. At present, the energy storage system may be centrally configured on the power supply side or in the high voltage grid, or may be connected to the distribution network in a distributed manner. The distributed access of the energy storage system can stabilize the load nearby, the investment of a power supply and a power grid can be effectively reduced, the operation performance of the system is improved, and the operation economy is improved.
For the energy storage at the user side, if the energy storage system is optimized to operate under a market mechanism, the energy storage configuration benefit is maximized, the healthy development of the user side can be promoted, and the application of the ES at the user side can be promoted.
At present, scholars at home and abroad have conducted intensive research on the optimized operation of an energy storage system and the obtainable benefits thereof. The research shows that: the energy storage system is configured to obtain benefits, and the benefits are closely related to investment subjects, equipment capacity, market mechanisms and operation strategies. Because the power grid enterprises can not participate in peak shaving, the main purpose of configuring the energy storage system is to stabilize source load fluctuation so as to reduce network loss, reduce load peak-valley difference and delay upgrading and reconstruction. The method is characterized in that an energy storage system is configured on a medium-voltage feeder line to cope with the influence of a large number of user self-built distributed photovoltaic devices, the method comprehensively considers the benefits of reliability, loss reduction, delay of upgrading and reconstruction, environment and the like, and an ES optimization configuration model considering the operation strategy is established with the aim of optimal economy. The results show that: based on the variable operating strategy, the energy storage system can obtain the maximum profit in the reliability and economy game. In order to deal with fluctuating risks brought by distributed grid connection, the operation of an energy storage system is optimized by taking the minimum risk cost due to insufficient system flexibility as a target, and energy storage investment, energy storage charging and discharging cost, switch operation cost, gear adjustment cost of an on-load tap-changing transformer, insufficient flexibility risk and other multiple costs are calculated, and the capacity and the position of energy storage are configured. The research takes a power grid company as an energy storage investment main body, and various negative effects caused by grid connection of distributed power supplies are solved by optimizing energy storage operation, so that the performance of the power distribution network is further improved.
And the user side energy storage investment focuses more on obtaining income from the market. The light-storage combined system investor obtains reduction of power generation loss and low-storage high-transmission profit through coordinated operation of photovoltaic and energy storage, and the profit is related to photovoltaic internet access, time-of-use electricity price of a power distribution network, energy storage charging and discharging cost, government subsidy and local load. Although the configuration of the optical storage may reduce the network loss at this time, the third party cannot obtain the portion of the benefit. Based on the electricity price in the two-part system, the rated power and the capacity of the energy storage at the user side are configured by taking the net income in the whole life cycle of the energy storage system as a target, and the reduction value of the electricity fee, the price arbitrage of low storage and high emission, the cost of the transformer and the recovery value of the energy storage are comprehensively considered. Therefore, most energy storage systems taking a third party as an investment subject pay more attention to the comprehensive benefit condition of energy storage operation.
In summary, both the power distribution network and the user side invest energy storage, the importance of the operation strategy on the energy storage realization efficiency is emphasized, double-layer optimization is adopted, and the operation optimization of the lower layer realizes the operation benefit maximization. Because various gains are acquired related to loads and electricity prices of different time scales of year, day and time, and different gains are required to have strategy priorities, the lower-layer operation optimization in the existing research only aims at the optimal daily operation benefit, and the global coordination optimization of different time scales cannot be realized.
Disclosure of Invention
Therefore, the invention provides a generation method of a coordinated operation strategy of a user side energy storage system aiming at the user side energy storage system, and solves the problem that the overall coordinated optimization of different time scales cannot be realized in the existing research aiming at the operation strategy. The method comprises the following steps: establishing an energy storage system equipment cost model and an energy storage system equipment operation income model, wherein the energy storage system equipment cost model comprises an energy storage system investment construction cost model and a charge and discharge loss cost model considering the cycle life of an energy storage system, and the energy storage system equipment operation income model comprises a power grid upgrading and transformation income delaying model, a power supply reliability promotion income model, an electric energy market income model and an auxiliary service market income model; for a specific power grid, under certain conditions of self load characteristics, abundance and external price mechanism, the optimized operation strategy is clear, and based on the clear operation strategy, the ES capacity A for delaying the upgrading and reconstruction of the power grid is obtained through optimized configuration1ES capacity A for improving power supply reliability2And ES capacity A participating in market revenue configuration3And can reversely derive from1And A2Corresponding load characteristic P1And P2Based on the energy storage system equipment cost model and the energy storage system equipment operation profit model, under the existing market price mechanism, based on the principle of obtaining high profit by priority selection, the economy of different profits obtained by the energy storage system in participation is compared, according to the sequence of delaying the power grid upgrading and transformation profits, improving the power supply reliability profits, participating in the electric energy market profits and participating in the auxiliary service market profits in the energy storage system, the energy storage operation power and the duration time at t are determined, and finally the energy storage system operation condition of each hour of each day is determined.
Further, the energy storage system investment construction cost model is represented by the formulas (1) and (2)
Cinv＝-(A·ccons+ESP·ccyber) (1)
A＝A1+A2+A3 (2)
Wherein A is the total capacity of the energy storage system (ES) configuration, A1、A2And A3The ESP is the rated total power of the ES, and C is the ES capacity configured for delaying the upgrading and the reconstruction of the power grid, improving the power supply reliability and participating in the market incomeinvFor the investment and construction costs of the energy storage system, cconsFor the unit construction cost of the energy storage system, ccyberConfiguring cost for unit software of the energy storage system;
further, a charge-discharge loss cost model considering the cycle life of the energy storage system is represented by equation (3),
Figure BDA0002927306670000031
in the formula, CmFor charge-discharge loss cost, NanuTotal days of the year, NtIs the number of time segments of a day, k is the power loss coefficient, Δ t is the time interval, PES(N, j) is the scheduling power of the ES in the jth time period on the nth day, theta is the aging coefficient, ndc is the number of charging and discharging times of the ES, and N isdcmIs the cycle life of the ES.
Further, the height Δ P is reduced according to the peak loadpeakEstablishing an ES delay power grid upgrading and transforming income model expressed as:
Figure BDA0002927306670000032
Figure BDA0002927306670000033
Figure BDA0002927306670000034
Figure BDA0002927306670000041
in the formula, RupdTo delay the gains of upgrading and transforming the power grid, csubIs the construction cost, Delta T, of unit power transformer stations and linesdelayFor the number of years of slow construction of the power grid, lambda is the peak clipping rate realized by configuring ES, tau is the annual growth rate of peak load, PmFor configuring the maximum peak load, P, before the energy storage systemmax(N) is the load spike at day N, NanuThe total days of the year.
Further, to obtain the benefit of delaying the upgrading and reconstruction of the power grid, the following constraints are also required to be met:
capacity constraint: discharge initiation time t on the nth day1SWhen (n) is A1The residual capacity of the capacity ES is more than or equal to the ES capacity required by the peak clipping of the nth day;
discharge restraint: daily load higher than P1When A is1The capacity ES needs to be loaded with P at the time1The differential force of (A) is shown in equation (14) at other times1The capacity ES is 0 for delaying the upgrade and reconstruction of the power grid,
P1ES(n,t)＝max(0，Pload(n,t)-P1) (8)
in the formula, P1ES(n, t) is A at t on the nth day1The output of the capacity ES;
and (3) charging restraint: the load of the nth day is reduced to P according to the total rated power ESP charging in the valley period ES after discharging1The required charging time is as shown in equation (15);
tch1(n)＝A1(n)/(ESP·η) (9)
wherein tch1(n) is A1And the capacity ES participates in the nth day to delay the charging time required by the upgrading and reconstruction of the power grid, the ESP is the total rated power of the stored energy, and the eta is the charging and discharging efficiency.
Further, A2The mathematical model for acquiring the benefit of improving the power supply reliability within one year by the capacity ES is as follows:
Figure BDA0002927306670000042
pd(n)＝t2(n)/24 (11)
t2(n)＝min(tfault(d),td(n)) (12)
Figure BDA0002927306670000043
Prel,d(n,t)＝min(ESP2,max(0,Pload(n,t)-Pcap,d)) (14)
Figure BDA0002927306670000044
in the formula, RrelFor increasing the reliability gain of power supply, pd(n) is the probability of the actual system influence on the failure of the device d on the nth day, fdAs fault probability of the d-th device, Δ Srel(n, d) ES capacity for recovery of lost load at nth equipment failure, clossAs loss of power per unit user, t2(n) duration of fault effect on day n, tfault(d) Time of failure, t, of device dd(n) is the nth dayLoad higher than Pcap,dDuration of (P)rel,d(n, t) is the outputtable power of ES at the time of the d-th equipment failure on the nth day t, Pcap,dFor the power supply capacity of the system in case of failure of the d-th transformer, PT,jFor the power supply capacity of the jth transformer, NsNumber of substations in contact, alphakIs the load factor, P, of the kth substationS,kThe total power supply capacity of the kth substation.
Further, the constraint conditions for obtaining the reliability gain are as follows: maximum load greater than P on the same day2And in time, once the system fails, the energy storage system outputs power according to the current size of the power shortage load.
Further, the energy storage system participating in the electric energy market can obtain benefits including low storage, high emission, arbitrage and reduced capacity electricity fee, and the mathematical model of the benefits in one year is as follows:
Figure BDA0002927306670000051
in the formula, RpmFor energy storage systems to participate in electric energy market revenue, R1Low reserve high hair arbitrage for ES, R2Reduced capacity electricity charges for the ES;
low reserve high hair arbitrage R on day n1Can be calculated according to equation (30):
Figure BDA0002927306670000052
in the formula, R1(n) low-storage high-development profit-making, SP is electricity price at peak electricity selling time, BV is electricity price at valley electricity purchasing time, and eta is charge-discharge efficiency;
monthly capacity electricity rate R with reduced ES in one year2Comprises the following steps:
Figure BDA0002927306670000053
Figure BDA0002927306670000054
Figure BDA0002927306670000055
Figure BDA0002927306670000061
P'load(n,:)＝Pload(n,:)-M'(n) (22)
wherein a is the basic electricity charge to be paid per 1kW of maximum load, MjAnd M'jThe maximum demand load (the maximum value of the average load every 30 minutes per month) t of the user before and after the jth month low-storage and high-emission of the energy storage system is respectivelystartAnd tendRespectively, the start and end times of the peak time, Eespm(n) is the energy storage system capacity available to participate in the electric energy market on the nth day, PloadAnd M ' (n) is the load level, P ', before and after ES low-storage high-emission 'load(n, t) is the peak load value which decreases on the nth day after the low-storage and high-rise of ES.
Further, obtaining electric energy market revenue requires satisfying the following constraints:
electric energy market price constraint: on the premise of the peak hour period, if the sum of monthly electricity selling yield and the unit price of the capacity electricity fee is more than the sum of monthly charging cost and charging and discharging loss cost, the ES can discharge electricity, the discharging power is as shown in the following,
Figure BDA0002927306670000062
in the formula, P3ES(n, t) is the output of the ES participating in the electric energy market on the nth day t, t3S(n) and t3E(n) are each Eespm(n) the capacity ES participates in the start-stop time of discharge in the electric energy market;
and (3) charging restraint: the valley period ES after the peak period is over can be charged according to the rated power ESP, the charging time required by the ES participating in the electric energy market on the nth day is shown as a formula (37),
tch3(n)＝Eespm(n)·DOD/(ESP·η) (24)
wherein tch3(n) is Eespm(n) the capacity ES participates in the charging time required after the electric energy market on the nth day.
Further, the energy storage system participates in auxiliary service market income, preferably carries out bilateral transaction, then market bidding and finally unified scheduling, assuming that the transaction mode is bilateral negotiation, and agrees the output power and duration of the energy storage system in a form of contract, the calculation of the income which can be obtained by the energy storage system participating in the auxiliary service market within one year is as follows:
Figure BDA0002927306670000063
P3ES(n,t)＝min(Pdemand(n,t),ESPaux(n,t)) (26)
Figure BDA0002927306670000071
in the formula, RauxFor participating in ancillary services market benefits, NanuTotal days of the year, NtNumber of time periods of one day, P3ES(n, t) is the discharge power of ES participating in the auxiliary service market at the nth day t, delta t is the time interval, rauxPeak shaving price per unit power, Rch(n) charging cost, ESP, required for participating in the auxiliary service market on the nth dayaux(n, t) is the power that can be output when the ES participates in the auxiliary service market at the nth day t, ESP1、ESP2And ESP3Are respectively A1、A2And A3Rated power, t, of a volumetric energy storage system1S(n) and t1E(n) are each A1The capacity ES participates in delaying the starting and stopping time of the electric discharge of the upgrading and reconstruction of the power grid.
Further, obtaining the auxiliary service market revenue requires satisfying the following constraints:
auxiliary service market price constraints: if the unit price of the auxiliary service market is more than the sum of the charging cost and the charging and discharging loss cost (formula (3)), the ES can discharge, and the discharging power is shown as a formula (39);
Figure BDA0002927306670000072
and (3) charging restraint: the ES can be charged according to the rated power ESP in the off-peak period;
and (3) discharge time constraint: the secondary service market admits only ESs ES that can sustain discharge times greater than 4 hours.
Further, if P2≥P1The ES also guarantees the improvement of the power supply reliability while participating in delaying the upgrading of the power grid; if P2<P1And configuring A because the benefit of delaying the upgrading and reconstruction of the power grid is the best1Capacity ES, load reduction to P1First, the gain is guaranteed to be obtained; simultaneous configuration A2Capacity ES guarantee P1And P2Reliability of power supply within the load interval; additional configuration A3The capacity ES gains market revenue.
Further, suppose P2<P1Maximum payload P on the daymax(n) is higher than P1When, A1The capacity ES obtains delay power grid upgrading and transformation benefits UPD and electric energy market benefits PM under the discharge constraint and the electric energy market price constraint, obtains auxiliary peak shaving benefits AM under the capacity constraint and the auxiliary service market price constraint, and obtains enhanced reliability benefits REL; a. the2The capacity ES obtains a gain REL for improving the power supply reliability; a. the3And A1And the surplus capacity ES obtains market income, the surplus capacity ES selectively participates in the electric energy market at peak time according to the income priority, the electric energy market income PM is obtained under the constraint of the electric price of the electric energy market, and the auxiliary service market income AM can be obtained under the constraint of the electric price of the auxiliary service market at non-peak time.
Further, suppose P2<P1Maximum payload P on the daymax(n) is higher than P2But not higher than P1When, A2The capacity ES obtains the benefit of improving the power supply reliability; a. the1+A3Capacity ES is based on charge under the constraint of electricity price of electric energy marketAnd the size priority is increased to obtain market income.
Further, suppose P2<P1Maximum payload P on the daymax(n) is not higher than P2When, A1+A2+A3The capacity ES obtains market revenue according to the revenue size priority under the constraint of market electricity prices.
Drawings
FIG. 1 is a unimodal load year-on-year load curve;
FIG. 2 is a schematic diagram of ES participation in delaying the improvement and the transformation of a power grid;
FIG. 3 is a schematic illustration of the participation of A1+ A2+ A3 capacity ES in electric energy market revenue;
FIG. 4 is a schematic diagram of the constraint on the suspension day and ES operation (Pmax (n) > P1);
FIG. 5 is a graph of an operating strategy based on a load curve;
fig. 6 is a block diagram of an energy storage system equipment area distribution network configuration in accordance with an example of the present invention.
Detailed Description
The embodiments are described in detail below with reference to the accompanying drawings.
The income obtained by configuring the energy storage system at the user side mainly comprises the steps of delaying the upgrading and the reconstruction of a power grid, and improving the power supply reliability and the market income, wherein the market income consists of the electric energy market income and the auxiliary service market income. But various gains are often not available, and the optimal operation strategies applicable to different load scenes are different.
Taking the industrial park of the incremental power distribution system as an example, a large user usually has the characteristics of large load, irregular peak-valley distribution and large influence by the industrial type, and the following typical load curves are common: trimodal, bimodal, unimodal, stationary and peak avoidance. The annual continuous load curve is shown in fig. 1, taking the unimodal load as an example. When the load is higher than P1When the load peak is large, the electric quantity is small, the equipment utilization rate of the power grid investment is low, and if the ES is used for reducing the load, the benefit of upgrading and transforming the power grid can be well delayed; when the load is greater than P2In time, the operation margin of the power grid is small, and once equipment failure and maintenance occur, load reduction is possibly caused, and if the equipment failure and maintenance occur, the load is storedThe method can replace part of power grid equipment and network investment, and can generate better power supply reliability improvement benefits in areas with slow load increase, short land resources and high land price; in addition, energy storage can be configured to participate in market trading, and electric energy market benefits and auxiliary service market benefits are obtained.
Establishing cost model of energy storage system and profit model for various purposes
Since the different gains involved in the operation of the energy storage system are sometimes obtained simultaneously and in some cases not, this is strongly related to the load characteristics and the external market price mechanism. Respectively configuring A for delaying upgrading and reconstruction of a power grid, improving power supply reliability and participating in market income1、A2And A3And (4) a capacity energy storage system, and analyzing related cost and benefits.
1. Energy storage system equipment cost model considering charge and discharge loss
The method takes the energy storage of lithium iron phosphate as an example, establishes profit models of ES cost and various purposes, obtains different profit economical efficiency by comparing and analyzing ES with unit capacity, and supports the formulation of subsequent operation strategies.
(1) Investment and construction cost model
The energy storage system investment construction cost comprises hardware cost and software cost. The hardware cost is the cost required for preparing a certain capacity of battery, and the software cost refers to the cost of Power Conversion System (PCS), Battery Management System (BMS), and other equipment for monitoring and controlling the system. The investment cost is shown as follows:
Cinv＝-(A·ccons+ESP·ccyber) (29)
A＝A1+A2+A3 (30)
wherein A is the total capacity of ES configuration, A1、A2And A3The ESP is the rated total power of the ES, and C is the ES capacity configured for delaying the upgrading and the reconstruction of the power grid, improving the power supply reliability and participating in the market incomeinvFor the investment and construction costs of the energy storage system, cconsFor the unit construction cost of the energy storage system, ccyberFor energy storage systemsPer unit software configuration cost.
(2) Charge-discharge loss cost model considering cycle life of energy storage system
From the electrochemical point of view, during the recycling process of lithium ions, the battery performance is slowly degraded due to the loss of active lithium ions, side reactions on the surface of an electrode and the like. Therefore, the operation of the energy storage system generates the charge and discharge loss cost, and the mathematical model of the charge and discharge loss cost is shown as the formula (3). It can be seen that the charging and discharging loss cost of the ES increases with the increase of the charging and discharging times, and the initial charging and discharging loss cost is consistent with the electric energy loss coefficient.
Figure BDA0002927306670000101
In the formula, CmFor charge-discharge loss cost, NanuTotal days of the year, NtIs the number of time segments of a day, k is the power loss coefficient, Δ t is the time interval, PES(N, j) is the scheduling power of the ES in the jth time period on the nth day, theta is the aging coefficient, ndc is the number of charging and discharging times of the ES, and N isdcmIs the cycle life of the ES.
The ES cycle life varies at different depths of Discharge (DOD). And fitting the relation between the cycle life of the lithium battery, the DOD and the battery capacity, wherein the larger the DOD is, the faster the capacity attenuation of the energy storage system is. And when the battery capacity is reduced to 80%, the cycle life is the maximum charge-discharge cycle life of the energy storage system.
2. Operating strategy and revenue analysis of energy storage system devices
(1) Model for delaying upgrading and improving income of power grid
To obtain the benefit of deferred upgrade reconstruction, it is necessary to ensure that the ES has sufficient capacity A1Can bear more than P every day all year1Is continuously discharged in the period of time to reduce the annual maximum load to P1. Capacity of energy storage system A1And rated power ESP1Can be obtained by the following formulae (4) to (7).
Figure BDA0002927306670000102
Figure BDA0002927306670000103
Figure BDA0002927306670000104
Figure BDA0002927306670000105
In the formula, A1(n) load reduction to P on day n1Required energy storage system capacity, Pload(N, t) is the load at t on the nth day, NanuFor total days of the year, DOD is ES depth of discharge, ESP1Is A1Rated discharge power, Δ P, of capacity ESpeak(n) is the maximum load on day n and P1Difference of (A), Pmax(n) is the load spike on day n.
t1S(n) and t1E(n) is the daily load curve and P1The abscissa of the point of intersection, i.e. A1The capacity ES participates in the discharge start-stop time of the nth day, which delays the upgrading and reconstruction of the power grid, as shown in fig. 2. If the daily load of the nth day shows a bimodal characteristic, i.e. the daily load curve and P1The intersection point of the two lines has m pairs (m)>1) Then there are m pairs of start and stop times of ES discharge, which are t1S1(n) and t1E1(n)，…，t1Sm(n) and t1Em(n) of (a). The capacity of the corresponding energy storage system under the constraint of each discharge start-stop time is A1,1，…，A1,m. At this time, it needs to be verified at A1,kAnd A1,k+1In the valley period in between, i.e. at A1,kAfter the discharge time of (A) is over1,k+1Whether the energy storage system is chargeable to A or not in the valley period before the start of the discharge time1,k+1The required capacity. If the check is satisfied, then A1(n) is as shown in formula (8), otherwise P should be adjusted up1To re-determine the ES dischargeStart-stop time and corresponding required energy storage system capacity until the check is satisfied.
Figure BDA0002927306670000111
The delaying of the size of the benefit of the upgrading and reconstruction of the power grid is related to the actual reduction of the height of the peak load. In FIG. 2,. DELTA.Ppeak(n) is the nth day A1The load height reduced by the capacity ES is as shown in equation (7). Then A is1Peak load reduction height delta P capable of being realized by delaying power grid upgrading and transformation with capacity energy storage systempeakIs delta P in all days of the yearpeakThe maximum value of (n) is shown in formula (9).
Figure BDA0002927306670000112
Height Δ P reduction based on peak loadpeakEstablishing an ES delay power grid upgrading and transforming income model which can be expressed as:
Figure BDA0002927306670000113
Figure BDA0002927306670000114
Figure BDA0002927306670000115
Figure BDA0002927306670000116
in the formula, RupdTo delay the gains of upgrading and transforming the power grid, csubIs the construction cost, Delta T, of unit power transformer stations and linesdelayThe number of years of slow construction of the power grid, lambda is the peak clipping rate realized by configuring the ES, and tau is the annual increase of the peak loadRate, PmThe maximum peak load before the energy storage system is configured.
The following constraints are also required to be met to obtain the benefit of delaying the upgrading and reconstruction of the power grid:
capacity constraint: discharge initiation time t on the nth day1SWhen (n) is A1The residual capacity of the capacity ES is more than or equal to the ES capacity required by peak clipping on the nth day.
Discharge restraint: daily load higher than P1When A is1The capacity ES needs to be loaded with P at the time1The differential force of (A) is shown in equation (14) at other times1The capacity ES is 0 for delaying the upgrade and reconstruction of the power grid.
P1ES(n,t)＝max(0,Pload(n,t)-P1) (42)
In the formula, P1ES(n, t) is A at t on the nth day1The output of the capacity ES.
And (3) charging restraint: during the valley period ES after discharge, the charging can be based on the total rated power ESP. Load on the nth day is reduced to P1The required charging time is shown in equation (15).
tch1(n)＝A1(n)/(ESP·η) (43)
Wherein tch1(n) is A1And the capacity ES participates in the nth day to delay the charging time required by the upgrading and reconstruction of the power grid, the ESP is the total rated power of the stored energy, and the eta is the charging and discharging efficiency.
(2) Revenue model for improving power supply reliability
Configuration A2The capacity energy storage system is used when the load is more than P2When the system is insufficient in abundance, the energy storage system is used for discharging to reduce load reduction, and power supply reliability is obtained and the income is improved. The income can be measured according to the reduction of annual power supply shortage and the power failure loss of a user unit. To ensure the load supply in the event of a fault, the ESP has an ES rated power, taking into account the duration of the fault effect2、A2And P2The relationship of (a) is as follows:
Figure BDA0002927306670000121
Figure BDA0002927306670000122
Figure BDA0002927306670000123
and calculating the faults of the transformer in the station and the inter-station transfer power supply in the station, and calculating and improving the power supply reliability and income based on the equipment fault probability, the probability of actually influencing the system, the reduced power shortage amount and the power failure loss of a user. Then A is2The mathematical model for obtaining the benefit of improving the power supply reliability within one year of the capacity ES is as follows:
Figure BDA0002927306670000124
pd(n)＝t2(n)/24 (48)
t2(n)＝min(tfault(d),td(n)) (49)
Figure BDA0002927306670000125
Prel,d(n,t)＝min(ESP2,max(0,Pload(n,t)-Pcap,d)) (51)
Figure BDA0002927306670000131
in the formula, RrelFor increasing the reliability gain of power supply, pd(n) is the probability of the actual system influence on the failure of the device d on the nth day, fdAs fault probability of the d-th device, Δ Srel(n, d) ES capacity for recovery of lost load at nth equipment failure, clossAs loss of power per unit user, t2(n) duration of fault effect on day n, tfault(d) Time of failure, t, of device dd(n) is the nth dayLoad higher than Pcap,dDuration of (P)rel,d(n, t) is the outputtable power of ES at the time of the d-th equipment failure on the nth day t, Pcap,dFor the power supply capacity of the system in case of failure of the d-th transformer, PT,jFor the power supply capacity of the jth transformer, NsNumber of substations in contact, alphakIs the load factor, P, of the kth substationS,kThe total power supply capacity of the kth substation.
The constraint conditions for obtaining the reliability gain are as follows: maximum load greater than P on the same day2And in time, once the system fails, the energy storage system outputs power according to the current size of the power shortage load.
(3) Electric energy market income model
The participation of the ES in the electric energy market benefits includes in particular the trading of the consumer side with the consumer (discharge benefits) and the grid (charging costs). According to the regulation, the maximum price limit management is carried out on the actually charged distribution price of the incremental distribution network, namely the sum of the distribution price of the distribution network borne by a user and the transmission and distribution price of the previous-level power grid is not higher than the transmission and distribution price of the current provincial power grid corresponding to the same voltage level of the power distribution network directly accessed by the user. And the settlement between the system and the power grid, the invention selects two electricity price making modes commonly used by industrial users, including electric quantity and electric capacity charges, wherein the electric capacity charges are collected according to monthly maximum load. Supposing that the power supply of the power distribution network is preferentially scheduled to store the energy, when A is available3Rated power ESP when capacity ES participates in electric energy market3As follows:
Figure BDA0002927306670000132
ΔPdpeak(n)＝Pmax(n)-P3(n) (54)
Figure BDA0002927306670000133
in the formula,. DELTA.Pdpeak(n) is the nth day A3Height of peak clipping, P, of volume ESmax(n) is the load peak value on the nth day,P3(n) is the achievable peak reduction load level on day n, Δ t is the time interval.
Because the electricity consumption is not changed after the energy storage system is configured, the electricity quantity and the electricity fee are not changed. Therefore, the gains available from the energy storage system participating in the electric energy market include low-storage high-emission arbitrage and reduced capacity electricity charges, and the mathematical model of the gains in one year is as follows:
Figure BDA0002927306670000141
in the formula, RpmFor energy storage systems to participate in electric energy market revenue, R1Low reserve high hair arbitrage for ES, R2Reduced capacity electricity charges for the ES.
From the viewpoint of economy of operation, with P1>P2The description is given for the sake of example: maximum load higher than P on the same day1Participation of ES in the electric energy market is considered A1The remaining capacity of (d); maximum load on the same day is lower than P1Then the capacity of the energy storage system of the ES participating in the electric energy market is considered A1Full capacity; maximum load on the same day is lower than P2Then ES participates in the electric energy market to consider A1And A2Is schematically shown in FIG. 3, where t is the total capacity of3S(n) and t3E(n) is the daily load curve and P3(n) the abscissa of the intersection, i.e. the start and end discharge time of the ES participating in the nth day's electric energy market. As can be seen from FIG. 3, the maximum load on the day is lower than P1When, A1、A2And A3All can participate in the electric energy market, discharge at peak to obtain low-storage high-emission arbitrage, simultaneously realize the reduction of peak load and obtain the income of reduced capacity charges of electricity. Three shaded parts are respectively A1、A2And A3The capacity of the energy storage system participates in the electric energy market, and M (n) and M' (n) are the load levels of the energy storage system before and after the energy storage system participates in the electric energy market and discharges. And for A3In other words, the peak reduction height P achievable at day ndpeak(n) is A3The power value required by the capacity storage system on the nth day.
Figure BDA0002927306670000142
In the formula EespmAnd (n) is the capacity of the ES which can participate in the electric energy market on the nth day.
Maximum load P of the daymax(n) is greater than P1，A1And (n) capacity energy storage is used for delaying the upgrading and reconstruction of the power grid. Considering that peak loads generally occur at peak, therefore A1(n) the ES with capacity can also obtain low-storage high-emission arbitrage. Low reserve high hair arbitrage R on day n1Can be calculated according to equation (30):
Figure BDA0002927306670000143
in the formula, R1(n) represents low storage and high generation profit, SP represents peak electricity selling price, BV represents valley electricity purchasing price, and eta represents charge-discharge efficiency.
In addition, the energy storage system can also reduce the daily load peak-valley difference of the system by participating in low-storage high-generation of the electric energy market, thereby reducing monthly capacity electricity charge. Monthly capacity electricity rate R with reduced ES in one year2As follows:
Figure BDA0002927306670000151
Figure BDA0002927306670000152
Figure BDA0002927306670000153
Figure BDA0002927306670000154
P'load(n,:)＝Pload(n,:)-M'(n) (63)
wherein a is the basic electricity charge to be paid per 1kW of maximum load, MjAnd M'jThe maximum demand load (the maximum value of the average load every 30 minutes per month) t of the user before and after the jth month low-storage and high-emission of the energy storage system is respectivelystartAnd tendRespectively, the start and end times of the peak time, Eespm(n) is the energy storage system capacity available to participate in the electric energy market on the nth day, PloadAnd M ' (n) is the load level, P ', before and after ES low-storage high-emission 'load(n, t) is the peak load value which decreases on the nth day after the low-storage and high-rise of ES.
Obtaining electric energy market revenue requires satisfying the following constraints:
electric energy market price constraint: on the premise of the peak hour period, if the sum of monthly electricity selling yield and the unit price of the capacity electricity fee is greater than the sum of monthly charging cost and charging and discharging loss cost, the ES can discharge electricity, and the discharging power is as follows.
Figure BDA0002927306670000155
In the formula, P3ES(n, t) is the output of the ES participating in the electric energy market on the nth day t, t3S(n) and t3E(n) are each Eespm(n) the capacity ES participates in the start-stop time of discharge in the electric energy market.
And (3) charging restraint: the valley period ES after the end of the peak period may be charged in accordance with the rated power ESP. The charging time required for the ES participating in the electric energy market on the nth day is as shown in equation (37).
tch3(n)＝Eespm(n)·DOD/(ESP·η) (65)
Wherein tch3(n) is Eespm(n) the capacity ES participates in the charging time required after the electric energy market on the nth day.
(4) Auxiliary service market revenue model
The income obtained by the ES participating in the auxiliary service market is related to the peak regulation demand of the market, the output and clear electricity quantity and the output and clear price of the ES participating in the peak regulation, and the income is calculated according to the contribution of the stored energy actually participating in the auxiliary service. System peak shaving demand PdemandFor the net load in the market area and the best of the daySmall difference in net load. According to the regulations, the energy storage system participates in an auxiliary service market, preferably carries out bilateral transaction, then market bidding and finally unified scheduling. Assuming that the transaction mode is bilateral negotiation, the power and duration of the energy storage system output are agreed in a form of contract, and assuming that the smaller value is selected between the output available size of the energy storage system and the auxiliary service requirement, the calculation of the income available in the energy storage system participating in the auxiliary service market within one year is as follows:
Figure BDA0002927306670000161
P3ES(n,t)＝min(Pdemand(n,t),ESPaux(n,t)) (67)
Figure BDA0002927306670000162
in the formula, RauxFor participating in ancillary services market benefits, NanuTotal days of the year, NtNumber of time periods of one day, P3ES(n, t) is the discharge power of ES participating in the auxiliary service market at the nth day t, delta t is the time interval, rauxPeak shaving price per unit power, Rch(n) charging cost, ESP, required for participating in the auxiliary service market on the nth dayaux(n, t) is the power that can be output when the ES participates in the auxiliary service market at the nth day t, ESP1、ESP2And ESP3Are respectively A1、A2And A3Rated power, t, of the energy storage capacity1S(n) and t1E(n) are each A1The capacity ES participates in delaying the starting and stopping time of the electric discharge of the upgrading and reconstruction of the power grid.
Obtaining ancillary services market revenue requires satisfying the following constraints:
auxiliary service market price constraints: if the unit price of the auxiliary service market is larger than the sum of the charging cost and the charging and discharging loss cost (equation (3)), the ES can discharge, and the discharging power is shown as equation (39).
Figure BDA0002927306670000163
And (3) charging restraint: charging during the system peak load period is not allowed due to the auxiliary service market, so charging at rated power ESP is only possible during off-peak periods ES.
And (3) discharge time constraint: the secondary service market admits only ESs ES that can sustain discharge times greater than 4 hours.
Intelligent operation strategy generation method based on load characteristics
The economics of comparing ES participation to obtain different revenue under existing market price mechanisms are compared according to the ES operational revenue model mentioned above. Since the relationship between the size of the obtained profit and the ES capacity is not completely linear (such as delaying the benefit of upgrading and transforming the power grid), the size of the obtained profit can be considered to be directly proportional to the ES capacity in general. Considering the discharging benefit, the charging cost and the charging and discharging loss cost, the economic efficiency of each income participated by the unit capacity ES obtained by calculation is ranked from high to low as: obtaining the yield of delaying the upgrading and reconstruction of the power grid of 631 yuan/kilowatt hour, improving the reliability of power supply of 32 yuan/kilowatt hour, the market yield of electric energy of 9 yuan/kilowatt hour and the auxiliary peak regulation yield of-0.3 yuan/kilowatt hour.
The ES operation should be prioritized to ensure higher revenue. Due to differences in the abundance of the grid, P1And P2There is uncertainty about the magnitude relationship of (a). If P2≥P1And the ES also guarantees the improvement of the power supply reliability while participating in delaying the upgrading of the power grid. If P2<P1And configuring A because the benefit of delaying the upgrading and reconstruction of the power grid is the best1Capacity ES, load reduction to P1First, the gain is guaranteed to be obtained; simultaneous configuration A2Capacity ES guarantee P1And P2Reliability of power supply within the load interval; additional configuration A3The capacity ES gains market revenue. Total ES capacity A of A1、A2And A3The total rated power ESP is ESP1、ESP2And ESP3And (4) summing. For a specific power grid, under certain conditions of self-load characteristics, abundance and external price mechanism, the optimal operation strategy of the power grid is toSpecifically, based on this, A can be obtained by optimizing the configuration1、A2And A3And can reversely derive from1And A2Corresponding load characteristic P1And P2。
Multiple benefits may be obtained simultaneously or separately, in P, upon consideration of ES runtime, according to benefit size order2<P1For example, considering the access of the distributed power supply, based on the net load curve, the matching condition of the source load characteristic and the operation strategy is formed as follows:
(1) maximum payload P of the daymax(n) is higher than P1Time of flight
At this time, the delay day, A1The capacity ES can obtain the yield UPD of the delayed power grid upgrading and transformation and the yield PM of the electric energy market under the discharge constraint and the electric energy market price constraint; obtaining auxiliary peak shaving income AM under the capacity constraint and the auxiliary service market price constraint; an enhanced reliability benefit REL may also be obtained. A. the2The capacity ES obtains a benefit REL for improving the reliability of power supply. A. the3And A1The surplus capacity ES obtains market income, the surplus capacity ES selectively participates in the electric energy market at peak time according to the income priority, and the electric energy market income PM is obtained under the power price constraint of the electric energy market; the ancillary service market revenue AM may be obtained off peak under the constraints of the ancillary service market electricity prices. Operating power P of ES at nth day tES(n, t) is represented by the formula (42). The charge time required after the end of the peak discharge is tch (n), i.e. A1Capacities ES and A3The sum of the discharge times of the capacity ES is shown in the following equation.
PES(n,t)＝P1ES(n,t)+P3ES(n,t) (70)
tch(n)＝tch1(n)+tch3(n) (71)
The operation strategy of the ES on the nth day is as shown in fig. 4. In FIG. 4, tstartAnd tendRespectively, the start and end times of the peak time, t1S(n) and t1E(n) are each A1The capacity ES participates in delaying the starting and stopping time t of the discharge of the upgrading and reconstruction of the power grid3S(n) and t3E(n) are each Eespm(n) Capacity ES participating in the Start and stop time of discharge, t, of the electric energy marketC(n-1) is the nth dayThe time when the charging is completed in the (n-1) th day, tch (n) is the charging time required after the end of the peak time discharging, M' (n) is the maximum load value of the (n) th day after the low-reserve and high-rise of ES, and A1(n) on the nth day, the load is reduced to P1The required energy storage system capacity.
Analyzing the situation of ES participating in the auxiliary service market at each time period on the nth day: if the formula (44) is satisfied, the discharge capacity generated by the ES participating in the auxiliary service market at t can be charged before the charging is completed from the nth-1 day to the nth day peak or from the nth day to the nth day, namely the capacity constraint of delaying the upgrading and transformation of the power grid and the electric energy market is satisfied, the ES can output power according to the formula (39), otherwise, the P3ES(n, t) is 0;
Figure BDA0002927306670000181
taux(n,t)＝ΔEaux(n,t)/(η·ESP) (73)
Figure BDA0002927306670000182
ΔEaux(n,t)≤Eespm(n) (75)
in the formula, tstartAnd tendRespectively, the start and stop time of the peak time, delta t is the time interval, taux(n, t) is the charge time required after participation in the auxiliary service market on day n, t, Δ Eaux(n, t) is the cumulative discharge capacity of ES participating in the auxiliary service at the nth day t, tC(n-1) is the time when charging is completed on the n-1 th day within the n-1 th day, and if charging is completed on the n-1 th day, t isC(n-1) is 0.
Initialization assisted service discharge number flag Δ nauxIs 0. If equation (47) is not satisfied, indicating that ES has reached the maximum depth of discharge DOD, then ES needs to be charged with ESP for tch3(n) (as shown in equation (37)), resulting in a charging cost. At this time, let Δ naux＝Δnaux+1, modifying the left boundary of k in equation (74) based on the new full charge time and clearing Δ Eaux(n, t) continued analysis of ES participation in the auxiliary service marketplaceAnd obtaining the benefits. The time when the constraint represented by the formula (44) is not satisfied is toverAccordingly, the discharging cost of the nth day participating in the auxiliary service market is calculated, as shown in the formula (48).
Rch(n)＝(Δnaux·Eespm(n)+ΔEaux(n,tover-1))·BV/η (76)
In the formula,. DELTA.nauxFor auxiliary service discharge number marking, Δ Eaux(n, t) is the accumulated discharge capacity of the ES participating in the auxiliary service at the nth day t, BV is the electricity price at the electricity purchasing valley, and eta is the charge-discharge efficiency.
The charge constraint specifically means that the energy storage discharge capacity in the nth day can be finished t at the peak of the nth dayendAnd charging to full power within the period of time from the later time to the valley time before the discharge of the (n + 1) th day. Let T be the set of the time periods from the end time of the discharge on the nth day to the start of the discharge on the (n + 1) th daydThe time interval set of the electricity price of the electricity purchased at the valley hour is TBVThen the charging constraint may be expressed as equation (49).
Figure BDA0002927306670000191
(2) Maximum payload P of the daymax(n) is higher than P2But not higher than P1Time of flight
At this time, the day of reliability, A2The capacity ES obtains the benefit of improving the power supply reliability; a. the1+A3And the capacity ES obtains market benefits according to the benefit size priority under the constraint of the electricity price of the electric energy market. The capacity constraint and the charging constraint at this time are similar to those of the suspension day.
(3) Maximum payload P of the daymax(n) is not higher than P2Time of flight
At this time, market date, A1+A2+A3The capacity ES obtains market revenue according to the revenue size priority under the constraint of market electricity prices. The capacity constraint and the charging constraint at this time are still similar to those of the suspension day.
According to the analysis of the three types of daily operation strategies, giving out the original load, the market electricity price mechanism and A1、A2And A3Under the conditions of the capacity and the DOD of the energy storage system, an ES charge-discharge strategy can be formulated, and an operation strategy based on load characteristics is shown in figure 5. As can be seen from fig. 5, by determining whether the energy storage system is in peak time, before peak time starts, after peak time starts, whether the energy storage system is in discharge time (i.e., whether the load is higher than M' (n)) for obtaining the electric energy market profit, whether the energy storage system participates in the auxiliary service market and meets the capacity constraint, whether the energy storage system participates in the electric energy market/the auxiliary service market is economical, and the like, based on the principle of preferentially selecting and obtaining high profit, the energy storage system is preferentially ensured to participate in delaying the upgrading and transformation of the power grid, then improving the power supply reliability, re-establishing the electric energy market, and finally determining the operating power and the duration of the energy storage system at t, and finally determining the operating.
The method of the present invention is described below by way of a specific example. Setting 3 interconnected transformer substations in incremental distribution system area, and predicting at transformer substation S1The energy storage system device is arranged in the device, see fig. 6. Transformer substation S2And substation S3The load ratios of (A) and (B) were 65% and 70%, respectively. The power supply to the upper-level power grid electricity purchasing and the increment power distribution system adopts a peak-valley electricity price mechanism, and the peak-valley time period is as follows: the peak is 08: 00-20: 00, and the valley is 20: 00-08: 00. The peak-valley electricity prices for purchasing electricity from the upper-level power grid are 1.1372 yuan/kilowatt hour and 0.3639 yuan/kilowatt hour respectively, the peak-valley electricity prices corresponding to power supply in the system are 0.9176 yuan/kilowatt hour and 0.2443 yuan/kilowatt hour respectively, and the reference yield i0And 8 percent of the total weight is taken.
Control group
Because the highest load occurrence proportion which can not be supplied is only 2%, considering the economical efficiency of configuration, the energy storage is not separately configured for improving the power supply reliability, A2Is 0. And because the current ES operation does not satisfy the formula (47), auxiliary peak regulation income cannot be obtained, and the investment cost cannot be recovered only by obtaining electric energy market income, the method is provided with A3Is 0.
TABLE 1 ES optimized configuration scheme
Figure BDA0002927306670000201
Figure BDA0002927306670000211
Based on the energy storage configuration scheme shown in table 1, on the premise of adopting the coordinated operation strategy for the user-side energy storage system proposed by the present invention, the costs and benefits of the energy storage system are shown in table 2.
TABLE 2 ES cost and revenue situation
Figure BDA0002927306670000212
It can be seen that A1By reducing annual peak load, 2.17 ten thousand yuan of delayed power grid upgrading and transformation benefits can be obtained in the annual load peak period, the electric energy market can also participate, and the net income value of the electric energy market reaches 36.46 ten thousand yuan. Meanwhile, if the system fails, A1The system can also participate in fault recovery in non-peak clipping periods to obtain the benefit of improving reliability, but because the energy supply for transfer between the stations of the system reaches 2.85MVA, the energy storage does not need to be scheduled when the system fails, and the fault recovery can be realized by the transfer between the stations, so that A1The benefit is not obtained.
Therefore, the method for generating the coordinated operation strategy aiming at the user side energy storage system can realize good economy. Along with the reduction of the construction cost of the energy storage system and the improvement of the economy of the energy storage system participating in the auxiliary service market in the future, the energy storage bear capacity A configured for improving the power supply reliability2And energy storage system capacity A configured for market participation3Will no longer be 0 and the economy of the energy storage system in adopting this operating strategy will be even more pronounced.
The present invention is not limited to the above embodiments, and any changes or substitutions that can be easily made by those skilled in the art within the technical scope of the present invention are also within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (14)

1. A generation method of a coordinated operation strategy of a user side energy storage system is characterized by comprising the following steps:
establishing an energy storage system equipment cost model and an energy storage system equipment operation income model, wherein the energy storage system equipment cost model comprises an energy storage system investment construction cost model and a charge and discharge loss cost model considering the cycle life of an energy storage system, and the energy storage system equipment operation income model comprises a power grid upgrading and transformation income delaying model, a power supply reliability promotion income model, an electric energy market income model and an auxiliary service market income model; for a specific power grid, under certain conditions of self load characteristics, abundance and external price mechanism, the optimized operation strategy is clear, and based on the clear operation strategy, the ES capacity A for delaying the upgrading and reconstruction of the power grid is obtained through optimized configuration1ES capacity A for improving power supply reliability2And ES capacity A participating in market revenue configuration3And can reversely derive from1And A2Corresponding load characteristic P1And P2Based on the energy storage system equipment cost model and the energy storage system equipment operation profit model, under the existing market price mechanism, based on the principle of obtaining high profit by priority selection, the economy of different profits obtained by the energy storage system in participation is compared, according to the sequence of delaying the power grid upgrading and transformation profits, improving the power supply reliability profits, participating in the electric energy market profits and participating in the auxiliary service market profits in the energy storage system, the energy storage operation power and the duration time at t are determined, and finally the energy storage system operation condition of each hour of each day is determined.
2. The method for generating the coordinated operation strategy of the user-side energy storage system according to claim 1, wherein: the energy storage system investment construction cost model is represented by the formulas (1) and (2)
Cinv＝-(A·ccons+ESP·ccyber) (1)
A＝A1+A2+A3 (2)
Wherein A is the total capacity of the energy storage system (ES) configuration, A1、A2And A3The ESP is the rated total power of the ES, and C is the ES capacity configured for delaying the upgrading and the reconstruction of the power grid, improving the power supply reliability and participating in the market incomeinvFor the investment and construction costs of the energy storage system, cconsFor the unit construction cost of the energy storage system, ccyberConfiguring cost for unit software of the energy storage system;
the charge-discharge loss cost model considering the cycle life of the energy storage system is represented by formula (3),
Figure FDA0002927306660000021
in the formula, CmFor charge-discharge loss cost, NanuTotal days of the year, NtIs the number of time segments of a day, k is the power loss coefficient, Δ t is the time interval, PES(N, j) is the scheduling power of the ES in the jth time period on the nth day, theta is the aging coefficient, ndc is the number of charging and discharging times of the ES, and N isdcmIs the cycle life of the ES.
3. The method for generating the coordinated operation strategy of the user-side energy storage system according to claim 2, wherein: height Δ P reduction based on peak loadpeakEstablishing an ES delay power grid upgrading and transforming income model expressed as:
Figure FDA0002927306660000022
Figure FDA0002927306660000023
Figure FDA0002927306660000024
Figure FDA0002927306660000025
in the formula, RupdTo delay the gains of upgrading and transforming the power grid, csubIs the construction cost, Delta T, of unit power transformer stations and linesdelayFor the number of years of slow construction of the power grid, lambda is the peak clipping rate realized by configuring ES, tau is the annual growth rate of peak load, PmFor configuring the maximum peak load, P, before the energy storage systemmax(N) is the load spike at day N, NanuThe total days of the year.
4. The method for generating the coordinated operation strategy of the user-side energy storage system according to claim 3, wherein: the following constraints are also required to be met to obtain the benefit of delaying the upgrading and reconstruction of the power grid:
capacity constraint: discharge initiation time t on the nth day1SWhen (n) is A1The residual capacity of the capacity ES is more than or equal to the ES capacity required by the peak clipping of the nth day;
discharge restraint: daily load higher than P1When A is1The capacity ES needs to be loaded with P at the time1The differential force of (A) is shown in equation (14) at other times1The capacity ES is 0 for delaying the upgrade and reconstruction of the power grid,
P1ES(n,t)＝max(0,Pload(n,t)-P1) (8)
in the formula, P1ES(n, t) is A at t on the nth day1The output of the capacity ES;
and (3) charging restraint: the load of the nth day is reduced to P according to the total rated power ESP charging in the valley period ES after discharging1The required charging time is as shown in equation (15);
tch1(n)＝A1(n)/(ESP·η) (9)
wherein tch1(n) is A1And the capacity ES participates in the nth day to delay the charging time required by the upgrading and reconstruction of the power grid, the ESP is the total rated power of the stored energy, and the eta is the charging and discharging efficiency.
5. The method for generating the coordinated operation strategy of the user-side energy storage system according to claim 2, wherein: a. the2The mathematical model for acquiring the benefit of improving the power supply reliability within one year by the capacity ES is as follows:
Figure FDA0002927306660000031
pd(n)＝t2(n)/24 (11)
t2(n)＝min(tfault(d),td(n)) (12)
Figure FDA0002927306660000032
Prel,d(n,t)＝min(ESP2,max(0,Pload(n,t)-Pcap,d)) (14)
Figure FDA0002927306660000033
in the formula, RrelFor increasing the reliability gain of power supply, pd(n) is the probability of the actual system influence on the failure of the device d on the nth day, fdAs fault probability of the d-th device, Δ Srel(n, d) ES capacity for recovery of lost load at nth equipment failure, clossAs loss of power per unit user, t2(n) duration of fault effect on day n, tfault(d) Time of failure, t, of device dd(n) is that the load on the nth day is higher than Pcap,dDuration of (P)rel,d(n, t) is the outputtable power of ES at the time of the d-th equipment failure on the nth day t, Pcap,dFor the power supply capacity of the system in case of failure of the d-th transformer, PT,jFor the power supply capacity of the jth transformer, NsNumber of substations in contact, alphakIs the load factor, P, of the kth substationS,kFor the kth transformationTotal power supply capacity of the station.
6. The method for generating the coordinated operation strategy of the user-side energy storage system according to claim 5, wherein: the constraint conditions for obtaining the reliability gain are as follows: maximum load greater than P on the same day2And in time, once the system fails, the energy storage system outputs power according to the current size of the power shortage load.
7. The method for generating the coordinated operation strategy of the user-side energy storage system according to claim 2, wherein: the energy storage system participates in the electric energy market to obtain benefits including low storage, high emission, arbitrage and reduced capacity electric charge, and the mathematical model of the benefits in one year is as follows:
Figure FDA0002927306660000041
in the formula, RpmFor energy storage systems to participate in electric energy market revenue, R1Low reserve high hair arbitrage for ES, R2Reduced capacity electricity charges for the ES;
low reserve high hair arbitrage R on day n1Can be calculated according to equation (30):
Figure FDA0002927306660000042
in the formula, R1(n) low-storage high-development profit-making, SP is electricity price at peak electricity selling time, BV is electricity price at valley electricity purchasing time, and eta is charge-discharge efficiency;
monthly capacity electricity rate R with reduced ES in one year2Comprises the following steps:
Figure FDA0002927306660000043
Figure FDA0002927306660000044
Figure FDA0002927306660000045
Figure FDA0002927306660000046
P′load(n,:)＝Pload(n,:)-M'(n) (22)
wherein a is the basic electricity charge to be paid per 1kW of maximum load, MjAnd M'jThe maximum demand load (the maximum value of the average load every 30 minutes per month) t of the user before and after the jth month low-storage and high-emission of the energy storage system is respectivelystartAnd tendRespectively, the start and end times of the peak time, Eespm(n) is the energy storage system capacity available to participate in the electric energy market on the nth day, PloadAnd M ' (n) is the load level, P ', before and after ES low-storage high-emission 'load(n, t) is the peak load value which decreases on the nth day after the low-storage and high-rise of ES.
8. The method for generating the coordinated operation strategy of the user-side energy storage system according to claim 7, wherein: obtaining electric energy market revenue requires satisfying the following constraints:
electric energy market price constraint: on the premise of the peak hour period, if the sum of monthly electricity selling yield and the unit price of the capacity electricity fee is more than the sum of monthly charging cost and charging and discharging loss cost, the ES can discharge electricity, the discharging power is as shown in the following,
Figure FDA0002927306660000051
in the formula, P3ES(n, t) is the output of the ES participating in the electric energy market on the nth day t, t3S(n) and t3E(n) are each Eespm(n) Capacity ES participating in discharge start of electric energy marketStopping time;
and (3) charging restraint: the valley period ES after the peak period is over can be charged according to the rated power ESP, the charging time required by the ES participating in the electric energy market on the nth day is shown as a formula (37),
tch3(n)＝Eespm(n)·DOD/(ESP·η) (24)
wherein tch3(n) is Eespm(n) the capacity ES participates in the charging time required after the electric energy market on the nth day.
9. The method for generating the coordinated operation strategy of the user-side energy storage system according to claim 2, wherein: the energy storage system participates in auxiliary service market income, preferably carries out bilateral transaction, then market bidding and finally unified scheduling, assuming that the transaction mode is bilateral negotiation, and agrees the output power and duration of the energy storage system in a form of contract, the calculation of the income which can be obtained by the energy storage system participating in the auxiliary service market within one year is as follows:
Figure FDA0002927306660000061
P3ES(n,t)＝min(Pdemand(n,t),ESPaux(n,t)) (26)
Figure FDA0002927306660000062
in the formula, RauxFor participating in ancillary services market benefits, NanuTotal days of the year, NtNumber of time periods of one day, P3ES(n, t) is the discharge power of ES participating in the auxiliary service market at the nth day t, delta t is the time interval, rauxPeak shaving price per unit power, Rch(n) charging cost, ESP, required for participating in the auxiliary service market on the nth dayaux(n, t) is the power that can be output when the ES participates in the auxiliary service market at the nth day t, ESP1、ESP2And ESP3Are respectively A1、A2And A3Rated power, t, of a volumetric energy storage system1S(n) and t1E(n) are each A1The capacity ES participates in delaying the starting and stopping time of the electric discharge of the upgrading and reconstruction of the power grid.
10. The method for generating the coordinated operation strategy of the user-side energy storage system according to claim 9, wherein: obtaining ancillary services market revenue requires satisfying the following constraints:
auxiliary service market price constraints: if the unit price of the auxiliary service market is more than the sum of the charging cost and the charging and discharging loss cost (formula (3)), the ES can discharge, and the discharging power is shown as a formula (39);
Figure FDA0002927306660000063
and (3) charging restraint: the ES can be charged according to the rated power ESP in the off-peak period;
and (3) discharge time constraint: the secondary service market admits only ESs ES that can sustain discharge times greater than 4 hours.
11. The method for generating the coordinated operation strategy of the user-side energy storage system according to claim 1, wherein: if P2≥P1The ES also guarantees the improvement of the power supply reliability while participating in delaying the upgrading of the power grid; if P2<P1And configuring A because the benefit of delaying the upgrading and reconstruction of the power grid is the best1Capacity ES, load reduction to P1First, the gain is guaranteed to be obtained; simultaneous configuration A2Capacity ES guarantee P1And P2Reliability of power supply within the load interval; additional configuration A3The capacity ES gains market revenue.
12. The method for generating the coordinated operation strategy of the user-side energy storage system according to claim 1, wherein: suppose P2<P1Maximum payload P on the daymax(n) is higher than P1When, A1Capacity ES in discharge confinement and electrical energyObtaining the upgrade and reconstruction yield UPD of the delayed power grid and the electric energy market yield PM under the constraint of market price, obtaining the auxiliary peak shaving yield AM under the constraint of capacity and the market price of the auxiliary service, and obtaining the reliability improvement yield REL; a. the2The capacity ES obtains a gain REL for improving the power supply reliability; a. the3And A1And the surplus capacity ES obtains market income, the surplus capacity ES selectively participates in the electric energy market at peak time according to the income priority, the electric energy market income PM is obtained under the constraint of the electric price of the electric energy market, and the auxiliary service market income AM can be obtained under the constraint of the electric price of the auxiliary service market at non-peak time.
13. The method for generating the coordinated operation strategy of the user-side energy storage system according to claim 1, wherein: suppose P2<P1Maximum payload P on the daymax(n) is higher than P2But not higher than P1When, A2The capacity ES obtains the benefit of improving the power supply reliability; a. the1+A3And the capacity ES obtains market benefits according to the benefit size priority under the constraint of the electricity price of the electric energy market.
14. The method for generating the coordinated operation strategy of the user-side energy storage system according to claim 1, wherein: suppose P2<P1Maximum payload P on the daymax(n) is not higher than P2When, A1+A2+A3The capacity ES obtains market revenue according to the revenue size priority under the constraint of market electricity prices.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115842345A (en) * 2023-02-07 2023-03-24 长园飞轮物联网技术(杭州)有限公司 Energy router control method and energy router
CN116826816A (en) * 2023-08-30 2023-09-29 湖南大学 Energy storage active-reactive coordination multiplexing method considering electric energy quality grading management
CN114069669B (en) * 2021-11-09 2023-10-13 国网冀北电力有限公司经济技术研究院 Shared energy storage operation mode control method

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114069669B (en) * 2021-11-09 2023-10-13 国网冀北电力有限公司经济技术研究院 Shared energy storage operation mode control method
CN115842345A (en) * 2023-02-07 2023-03-24 长园飞轮物联网技术(杭州)有限公司 Energy router control method and energy router
CN116826816A (en) * 2023-08-30 2023-09-29 湖南大学 Energy storage active-reactive coordination multiplexing method considering electric energy quality grading management
CN116826816B (en) * 2023-08-30 2023-11-10 湖南大学 Energy storage active-reactive coordination multiplexing method considering electric energy quality grading management

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